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Forkhead transcription factors control genome wide dynamics of the S. cerevisiae replication timing program

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Forkhead transcription factors control genome wide dynamics of the S. cerevisiae replication timing program

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Content

Forkhead
transcription
factors
control
genome
wide

dynamics
of
the
S.
cerevisiae
replication
timing
program

by

Jared
Michael
Peace

_________________________________________________________________________________________________

A
Dissertation
Presented
to
the

FACULTY
OF
THE
USC
GRADUATE
SCHOOL

UNIVERSITY
OF
SOUTHERN
CALIFORNIA

In
Partial
Fulfillment
of
the

Requirements
for
the
Degree

DOCTOR
OF
PHILOSOPHY

(Molecular
Biology)

December
2014

ii

Table
of
Contents

LIST
OF
FIGURES
VI

LIST
OF
TABLES
VIII

ACKNOWLEDGEMENTS
IX

ABSTRACT
XI

INTRODUCTION
1

REPLICATION
INITIATION
AND
TIMING
1

CHROMATIN
ENVIRONMENT
AFFECTS
REPLICATION
TIMING
3

TRANSCRIPTION
FACTOR
BINDING
AND
LONG-‐RANGE
INTERACTIONS

REGULATE
REPLICATION
INITIATION
4

NUCLEAR
LOCALIZATION
AND
REPLICATION
TIMING
5

FORKHEAD
TRANSCRIPTION
FACTORS
AND
REPLICATION
6

CHAPTER
I:
FORKHEAD
TRANSCRIPTION
FACTORS
ESTABLISH

ORIGIN
TIMING
AND
LONG-‐RANGE
CLUSTERING
IN
S.
CEREVISIAE
8

INTRODUCTION
9

RESULTS
10

FKH1
AND
FKH2
CONTROL
GENOME-‐WIDE
INITIATION
DYNAMICS
OF

REPLICATION
ORIGINS.
10

FKH-‐REGULATION
INVOLVES
ESTABLISHMENT
OF
REPLICATION

TIMING
DOMAINS.
17

FKH1/2
BIND
AND
FUNCTION
IN
CIS
TO
FKH-‐ACTIVATED
ORIGINS.
18

FKH-‐DEPENDENT
ORIGIN
REGULATION
IS
NOT
CORRELATED
WITH

TRANSCRIPTION
LEVELS
OR
CHANGES.
21

iii

CDC45
PREFERENTIALLY
ASSOCIATES
WITH
FKH-‐ACTIVATED

ORIGINS
IN
G1-‐PHASE.
24

FKH1/2
ARE
REQUIRED
FOR
SELECTIVE
CLUSTERING
OF

FKH-‐ACTIVATED
ORIGINS
IN
G1-‐PHASE.
26

FKH1
AND
FKH2
INTERACT
WITH
ORC.
30

DISCUSSION
32

FKH1/2
ESTABLISH
REPLICATION-‐TIMING
DOMAINS
THROUGH

ORIGIN
CLUSTERING.
32

MULTIPLE,
SEPARABLE
ROLES
FOR
FKH1
AND
FKH2
IN
REGULATION

OF
THE
GENOME.
35

MATERIALS
AND
METHODS
39

CHAPTER
II:

FKH1/2
OVER-‐EXPRESSION
ALTERS
GENOME
WIDE
ORIGIN

TIMING
IN
S.
CEREVISIAE
52

INTRODUCTION
53

RESULTS
54

THE
INDUCIBLE
GAL1/10
PROMOTER
EFFECTIVELY

OVER-‐EXPRESSES
FKH1
AND
FKH2
54

OVER-‐EXPRESSION
OF
FKH1
OR
FKH2
ALTERS
REPLICATION
TIMING
56

GLOBAL
ANALYSIS
OF
FKH1
AND
FKH2
OVER-‐EXPRESSION
59

FKH
OE
REGULATED
ORIGIN
CLASSES
HAVE
DIFFERENT
AVERAGE

REPLICATION
TIMES
62

INCREASED
HU-‐EFFICIENCY
OF
FKH
OE
ACTIVATED
ORIGINS
IS
NOT

A
RESULT
OF
INCREASED
NUCLEOTIDE
POOLS
62

ALTERED
REPLICATION
AT
FKH1
AND
FKH2
OE
REGULATED
ORIGINS

IS
NOT
THE
RESULT
OF
A
CHANGE
IN
LOCAL
TRANSCRIPT

ABUNDANCE
OR
REPLICATION
FACTOR
LEVELS
66

TABLE
2.1
DIFFERENTIALLY
EXPRESSED
GENES
OF
BOTH
FKH1

AND
FKH2
OE
CONDITIONS
BY
GENE
ONTOLOGY
CLASS
(GO
CLASS).
68

FKH1
BINDING
IS
ENRICHED
AT
ORIGINS
WITH
OVER-‐EXPRESSION
69

iv

DISCUSSION
72

FKH
OVER-‐EXPRESSION
ALTERS
ORIGIN
TIMING
GENOME
WIDE.
72

CHANGES
IN
TRANSCRIPT
ABUNDANCE
DO
NOT
PROVIDE
AN

OBVIOUS
MECHANISM
FOR
ORIGIN
TIMING
DEREGULATION.
73

FKH1
BINDS
LOCALLY
TO
FKH
OE
ACTIVATED
ORIGINS
WITH
OVER-‐
EXPRESSION.
74

MATERIALS
AND
METHODS
76

CHAPTER
III:
RIF1
REGULATES
INITIATION
TIMING
OF
LATE

REPLICATION
ORIGINS
THROUGHOUT
THE
S.
CEREVISIAE
GENOME
81

INTRODUCTION
82

RESULTS
84

RIF1
REGULATES
ORIGIN
FIRING
INDEPENDENTLY
OF
PFA4
84

RIF1
REGULATES
REPLICATION
ORIGIN
TIMING
87

RIF1
AND
MEC1
REGULATE
REPLICATION
TIMING
THROUGH

DISTINCT
PATHWAYS
90

LANDSCAPE
OF
RIF1
FUNCTION/RIF1
RECRUITMENT
93

DISCUSSION
98

RIF1
IS
A
GLOBAL
REGULATOR
OF
LATE
ORIGINS
98

RIF1
AS
A
CHECKPOINT
REGULATOR
99

HOW
DOES
RIF1
ACT
AT
INTERNAL
CHROMOSOMAL
LOCI?
100

MATERIALS
AND
METHODS
101

CHAPTER
IV:
THE
LEVEL
OF
ORIGIN
FIRING
INVERSELY
AFFECTS

THE
RATE
OF
REPLICATION
FORK
PROGRESSION
105

INTRODUCTION
106

RESULTS
AND
DISCUSSION
107

v

CDC7
ACTIVITY
REGULATES
REPLICATION
FORK
PROGRESSION
107

CDC7
ACTS
UPSTREAM
OF
RAD53
IN
FORK
REGULATION
116

DECREASED
INITIATION
FROM
ORC1-‐DEPLETION
ALSO

DEREGULATES
FORK
PROGRESSION
117

CHECKPOINT
ELIMINATION
IS
NOT
SUFFICIENT
TO
DEREGULATE

FORK
RATE
120

REPLICATION
FORK
AND
CHECKPOINT
LEVELS
REGULATE

REPLICATION
FORK
PROGRESSION
122

MATERIALS
AND
METHODS
126

REFERENCES
132

INTRODUCTION
REFERENCES
132

CHAPTER
I
REFERENCES
135

CHAPTER
II
REFERENCES
139

CHAPTER
III
REFERENCES
142

CHAPTER
IV
REFERENCES
146

APPENDIX
REFERENCES
150

APPENDIX
152

DOES
PHOSPHO-‐REGULATION
OF
FKH1/2
CONTROL
REPLICATION

TIMING?
152

VISUALIZATION
OF
REPLICATION
FOCI
FORMATION
AND
RELATIVE

ORIGIN
POSITIONING
IN
FKH1∆
FKH2∆
CELLS
THROUGH
LIVE
CELL

IMAGING.
157

CARBON
SOURCE
AVAILABILITY
AND
CHANGES
TO
REPLICATION

DYNAMICS
162

vi

LIST
OF
FIGURES

CHAPTER
I

Figure
1.1.
Suppression
of
pseudohyphal
growth
of
fkh1∆
fkh2∆
cells
by

expression
of
Fkh2∆C.

11

Figure
1.2.
Analysis
of
early
S-‐phase
BrdU
incorporation.

13

Figure
1.3.
Miscellaneous
Data.
15

Figure
1.4.
Temporal
analysis
of
DNA
replication
by
BrdU
pulse-‐labeling.
17

Figure
1.5.
Analysis
of
Fkh1
and
Fkh2
binding
sites
near
origins.
19

Figure
1.6.
Transcription
analysis
surrounding
Fkh-‐regulated
origins
in

unsynchronized
and
G1-‐synchronized
cells.
22

Figure
1.7.
Genome-‐wide
binding
of
replication
initiation
factors
to

Fkh-‐regulated
origins.
25

Figure
1.8.
Chromosome-‐conformation
capture
analyses
of
origin
interactions.
28

Figure
1.9.
4C
analysis
of
ARS305
interactions.

29

Figure
1.10.
Co-‐IP
of
Fkh1
with
ORC.
31

CHAPTER
II

Figure
2.1.

Galactose
induction
of
pGal-‐Fkh1/2.
55

Figure
2.2.
Analysis
of
early
S-‐phase
by
BrdU-‐IP-‐Seq.

58

Figure
2.3.
Analysis
of
Fkh
over-‐expression
regulated
origins
by
origin
class.
60

Figure
2.4.
Time
of
Replication
(Trep)
for
Fkh
over-‐expression
origin
classes.
63

Figure
2.5.
Early
S-‐phase
analysis
of
Fkh
over-‐expression
cells
with
increased

nucleotide
pools.
64

Figure
2.6.
Transcriptional
changes
proximal
to
origins
as
a
result
of
Fkh
OE.
69

Figure
2.7.
Enrichment
of
Fkh1
binding
proximal
to
origins
with
OE.
71

vii

CHAPTER
III

Figure
3.1.
Analysis
of
early
S-‐phase
by
BrdU-‐chip.

86

Figure
3.2.
DNA
content
analysis
of
S-‐phase.
87

Figure
3.3.
Temporal
analysis
of
replication
by
BrdU-‐IP-‐chip.
89

Figure
3.4.
Analysis
of
intra-‐S
checkpoint
response.

93

Figure
3.5.
Analysis
of
early
S-‐phase
by
BrdU-‐IP-‐Seq.

94

CHAPTER
IV

Figure
4.1.

Cdc7
function
regulates
replication
fork
progression.
109

Figure
4.2.
Cdc7
function
regulates
replication
fork
progression
(part
2).

110

Figure
4.3.

Cdc7
functions
upstream
of
Rad53
in
fork
regulation.

113

Figure
4.4.

Effective
depletion
of
Cdc7
function
with
the
cdc7-‐1
allele.
115

Figure
4.5.

Orc1
function
regulates
replication
fork
progression.
119

Figure
4.6.

Deregulated
origin
firing
in
mec1-‐100
slows
replication
forks.
121

Figure
4.7.

Deregulated
origin
firing
in
rad53∆
slows
replication
forks.
123

Figure
4.8.

Replication
fork
and
checkpoint
levels
regulate
replication
fork

progression.

125

APPENDIX

Figure
A.1.
Multiple
Sequence
Alignment
of
Forkhead
family
transcription

factor
DNA
binding
domains
in
S.
cerevisiae
and
higher
homologs.
154

Figure
A.2.
Fkh1
Coding
sequence
with
various
highlighted
features.

155

Figure
A.3
Bulk
DNA
content
analysis
of
asynchronously
growing
cultures
by

indicated
strain.
156

viii

Figure
A.4.
Copy
Number
Analysis
(CNA)
of
fluorescently
tagged
strains.
160

Figure
A.5.
Live
Cell
Imaging
of
fkh1∆
fkh2∆
pFkh2∆
cells.
161

Figure
A.6.
DNA
content
analysis
through
S-‐phase
by
FACS
with
indicated
carbon

sources.
164

Figure
A.7.
Analysis
of
early
S-‐phase
by
BrdU-‐IP-‐Seq.
167

SUPPLEMENTAL
FIGURES

Figure
S1.1-‐16.
Analysis
of
early
S-‐phase
by
BrdU-‐IP-‐Seq
for
all

chromosomes
with
Fkh
OE.

168-‐175

Figure
S2.1-‐16.
Analysis
of

early
S-‐phase
by
BrdU-‐IP-‐Seq
for
all

chromosomes
in
rif1Δ.
176-‐183

LIST
OF
TABLES

Table
2.1.
Differentially
expressed
genes
of
both
Fkh1
and
Fkh2
OE
conditions

by
gene
ontology
class
(GO
class).
68

Table
4.1.
Strain
List.
130

Table
A.1.
List
of
base
strains
and
introduced
mutations
analyzed.

155

ix

ACKNOWLEDGEMENTS

First
and
foremost
I
would
like
to
thank
those
individuals
who
were

instrumental
to
my
success
during
my
time
at
USC.
Graduate
school
is
a
long
and

arduous
process
and
wouldn’t
have
been
possible
with
out
the
help
and
support
of

my
mentors,
friends,
and
colleagues.
Dr.
Oscar
Aparicio
has
been
an
incredible

mentor
who
has
taught
me
to
think
critically
and
independently
as
a
scientist.
He

has
helped
me
to
become
a
well-‐rounded
and
complete
scientist
and
I
could
not

have
hoped
to
achieve
the
success
that
I
have
had
without
his
guidance.

He
has

created
an
environment
for
me
to
grow
and
shine
as
a
graduate
student
and
I
am

forever
indebted
to
him
for
his
investment
in
me.
Next,
I
would
like
to
thank
my
lab

mates
for
helpful
discussions,
collaborations,
and
for
helping
to
keep
me
sane
over

the
years.
Zac
Ostrow,
Tittu
Nellimoottil,
Sandra
Villwock,
Simon
Knott,
Yuan
Zhong,

Yan
Gan,
Jeff
Jancuska,
Alexandra
Rex,
Anna
Ter-‐Zakarian,
and
John
Zeytounian
are
a

caliber
of
people
that
I
am
proud
to
have
had
the
opportunity
to
call
my
lab
mates

and
friends.
Additionally,
I
thank
my
committee,
Dr.
Susan
Forsburg,
Dr.
Mathew

Michael,
and
Dr.
Lin
Chen
for
helpful
discussions
and
guidance
throughout
my

graduate
career.
I
would
also
like
to
thank
my
many
friends
and
colleagues
around

Ray
Irani
Hall
for
their
support
both
personally
and
professionally
throughout
the

years.
I
would
like
to
personally
thank
Ana
Carolina
Dantas
Machado,
Michael

Philips,
Daniel
McCoy,
Justin
Dalton,
Ian
Slaymaker,
Aysen
Erdem,
Nimna

Ranatunga,
Tara
Mastro,
Reza
Kahlor,
Melina
Butuci,
Jordan
Eboreime,
Marc
Green,

Frances
Tran,
Brett
Zirkle
and
many
more
who
have
made
my
time
in
graduate

x

school
such
a
rewarding
experience.

Lastly,
I
would
like
to
thank
my
family
for
their

on
going
and
continuing
support
through
the
years.
Mom,
Dad,
and
Chad
thank
you

for
being
there
for
me
and
always
believing
in
me.
Without
you,
none
of
this
would

have
been
possible.

xi

ABSTRACT

Eukaryotic
cells
initiate
DNA
replication
from
hundreds
to
thousands
of

origins
genome
wide.
The
coordinated
firing
of
these
origins
across
a
range
of
times

throughout
S-‐phase
is
a
well-‐conserved
feature
of
replication
initiation
and
is

essential
to
ensure
faithful
duplication
of
the
genome.

Differences
in
replication

timing
can
be
attributed
to
epigenetic
regulation
of
origins
through
chromatin

environment
and
spatial
localization
within
the
nucleus.
Here
we
address
several

important
factors
that
regulate
and
coordinate
the
replication
timing
program
of
the

budding
yeast,
Saccharomyces
cerevisiae.

Our
studies
reveal
the
role
of
Forkhead

transcription
factors
as
modulators
of
DNA
replication
timing.
Here
we
find
that

Forkhead
proteins
regulate
origin
timing
through
binding
proximal
to
certain

origins
and
mediate
clustering
of
these
origins.
This
process
is
tightly
controlled
at

the
protein
level.
Over-‐expression
of
either
Fkh1
or
Fkh2
causes
drastic
changes
in

replication
timing
genome
wide
and
these
changes
are
the
result
of
an
increase
in

protein
binding
proximal
to
regulated
origins.
Many
origins
with
normally
lower

levels
(or
an
absence
of)
Forkhead
binding
show
an
advancement
in
timing
due
to

an
increase
in
Forkhead
binding
with
over-‐expression.
The
advancement
in
timing

at
these
origins
comes
at
the
expense
of
Forkhead
unregulated
origins
and
those

origins
that
already
preferentially
bind
Forkhead
proteins
under
WT
conditions.

This
is
probably
due
to
increased
competition
for
limiting
factors.
While
Fkh1
and

Fkh2
over-‐expression
can
advance
origin
timing
through
proximal
binding,
Rif1

actively
represses
it.

Here
we
show
that
Rif1
regulates
most
late
and
dormant

xii

origins
genome
wide
including
telomere
proximal
origins.
Deletion
of
Rif1
advances

the
timing
of
almost
all
of
these
origins.
Similar
to
the
effect
seen
with
Forkhead

over-‐expression,
the
advanced
timing
of
late
origins
in
rif1∆
cells
appears
to
be
at

the
expense
of
early
robust
firing
origins
probably
because
of
increased
competition

for
limiting
factors.
Lastly,
and
consistent
with
these
results,
we
show
that
cells

lacking
Cdc7
or
Orc1
function
fire
fewer
origins
genome
wide.
This
decrease
in

competition
for
limiting
factors
leads
to
faster
fork
rates
of
origins
that
do
fire
and
a

subsequent
reduction
in
response
to
DNA
damage
as
evidenced
by
a
reduction
in

Rad53
checkpoint
signaling.

This
evidence,
combined
with
analysis
of
checkpoint

defective
cells,
reveals
that
fork
rate
is
sensitive
to
the
level
of
origin
firing.
The

findings
detailed
here
suggest
a
tight
regulation
of
origin
initiation
timing
and

replication
fork
elongation.
Here
we
discuss
these
findings,
the
roles
of
these
factors,

and
their
importance
to
replication
timing
genome
wide.

1

INTRODUCTION

Replication
Initiation
and
Timing

Faithful
replication
of
the
genome
is
required
for
genomic
stability
in
all

organisms.
Each
chromosome
must
be
completely
and
accurately
copied
once
per

cell
cycle
(S-‐phase)
in
order
to
ensure
proper,
error-‐free
propagation
of
genetic

material
to
daughter
cells.
In
order
to
ensure
that
this
process
is
undergone

efficiently,
while
minimizing
potential
errors,
cells
have
developed
a
highly

conserved
mechanism
for
DNA
replication
initiation.
Replication
is
initiated
from

discrete
chromosomal
loci
known
as
origins
of
replication.
Origin
numbers
vary

widely
across
species
with
anywhere
from
roughly
500
active
origins
in

Saccharomyces
cerevisiae
to
tens
of
thousands
in
higher
eukaryotes
(Yoshida
et
al.,

2013).

Origins
were
first
identified
as
ARSs
or
autonomously
replicating
sequences

in
the
budding
yeast,
S.
cerevisiae.
ARS
elements
were
initially
described
as
100-‐
200bp
genomic
fragments
shown
to
confer
extrachromosomal
maintenance
of
a

plasmid
within
the
cell
(Stinchcomb
et
al.,
1979).

S.
cerevisiae
ARSs
contain
several

DNA
sequence
elements
including
a
conserved
11-‐17bp
ACS
or
ARS
consensus

sequence
as
well
as
several
B
elements.
Interestingly,
the
sequence
specificity
of
the

budding
yeast
ACS
is
not
a
common
feature
of
higher
eukaryotes
(Cvetic
and
Walter,

2005).

Origin
firing
is
initiated
through
a
series
of
events
beginning
in
G1
phase
of

2

the
cell
cycle.
In
budding
yeast,
the
ACS
tightly
binds
to
the
Origin
Recognition

Complex
(ORC),
which
during
G1
is
responsible
for
the
recruitment
of
Cdc6
and

Cdt1.
Together,
these
factors
leads
to
loading
of
the
mini-‐chromosomal
maintenance

complex
(MCM),
in
it’s
inactive
form,
to
form
the
pre-‐replicative
complex
or
pre-‐RC

(Bell
and
Dutta,
2002).
A
series
of
additional
recruitment
steps
occur
after
pre-‐RC

formation
before
eventual
DNA
unwinding
and
entry
into
S-‐phase.

A
key
step
to
this

procession
is
the
conversion
of
MCM
to
the
active
helicase
state.
Phosphorylation
of

Mcm4
and
6
by
Dbf4-‐dependent
kinase
(DDK)
leads
to
loading
of
Cdc45
and
Sld3.

Subsequent
phosphorylation
of
Sld2
and
Sld3
by
Cyclin-‐dependent
kinase
(CDK)

leads
to
loading
of
GINS.
These
steps
together,
lead
to
activation
of
the
helicase,

complete
replisome
assembly
and
DNA
unwinding
(Bell
and
Dutta,
2002).

Interestingly,
the
series
of
events
following
pre-‐RC
assembly
do
not
occur

uniformly
across
all
origins
within
a
cell.
This
leads
to
a
temporal
timing
program
in

which
origins
initiate
replication
across
a
range
of
times
with
some
firing
early
and

some
firing
late
(Aparicio,
2013).
Origin
efficiency
is
often
defined
as
the
likelihood

or
probability
of
an
origin
to
fire
within
a
given
S-‐phase.
Timing
and
efficiency,
while

different,
are
highly
correlated;
early
firing
origins
tend
to
have
greater
efficiencies

while
later
firing
origins
tend
to
have
lower
efficiencies.
This,
however,
is
not
a

requirement
as
many
origins
fire
with
high
efficiency
but
with
late
timing
leading
to

passive
replication
of
these
origins
before
they
have
the
ability
to
fire.

These

findings
suggest
the
possibility
that
sequence
environment
plays
a
strong
role
in
the

set
up
of
origin
timing
genome
wide.

3

Chromatin
environment
affects
replication
timing

The
coordination
of
replication
alongside
transcriptional
machinery
is
an

important
topic
that
has
yielded
sometimes-‐conflicting
results.
Early
firing
origins

are
highly
correlated
with
actively
transcribed
regions
of
the
genome
in
metazoans.

Conversely,
late
replicating
origins
tend
to
associate
with
heterochromatic
or

transcriptionally
repressed
domains
(Rhind
and
Gilbert,
2013).

In
contrast
to
the

correlation
of
these
events
in
metazoans,
yeast
origins
fail
to
show
this
relationship

except
in
the
late
replicating,
transcriptionally
repressed
telomeric
regions.
Yeast

origins
are
enriched
at
intergenic
regions
and
transcription
through
origin

sequences
has
been
shown
to
inhibit
origin
firing
by
interfering
with
loading
of
both

ORC
and
MCM
(Aladjem,
2007;
Aparicio,
2013).

Several
factors
including
chromosomal
location,
chromatin
structure,
and

epigenetic
modification
have
been
shown
to
play
important
roles
in
the

determination
of
an
individual
origin’s
timing
during
S-‐phase.
Interestingly,
deletion

of
the
histone
deacetylase,
Rpd3L,
advances
the
timing
of
roughly
one-‐third
of
active

origins
in
the
yeast
genome
while
tethering
of
the
histone
acetylase
GCN5
advanced

the
timing
of
a
proximal
origin
(Aparicio
et
al.,
2004;
Knott
et
al.,
2009;
Vogelauer
et

al.,
2002).

Similarly,
deletion
of
the
gene
encoding
the
silencing
protein
SIR3
leads

to
advanced
timing
of
subtelomeric
origins
(Stevenson
and
Gottschling,
1999).

These
data
reveal
that
removal
of
hallmarks
of
heterochromatin
or
the
inability
to

remove
marks
of
euchromatin
both
yield
advancement
of
origin
timing
in
proximal

regions.

4

Important,
seminal
work
from
Ferguson
and
Fangman,
1992
showed
the

importance
of
chromosomal
location
and
environment
to
origin
timing.

The
early

firing
CEN-‐proximal
origin
ARS1
exhibited
delayed
timing
when
relocated
to
the

heterochromatic,
subtelomeric
region
proximal
to
the
late
firing
origin
ARS501.

Conversely,
when
ARS501
was
relocated
to
a
plasmid
(lacking
its
surrounding

chromatin
environment),
its
timing
was
advanced.
Importantly,
both
origins
were

shown
to
fire
with
high
efficiency
showing
the
importance
of
both
chromosomal

location
and
environment
as
determinants
of
origin
timing.
These
data
highlight
the

importance
of
chromatin
state
and
histone
modification
in
the
assembly
of
the

timing
profile
and
show
the
importance
of
euchromatic
and
heterochromatic

domains
in
the
establishment
of
this
profile.

Transcription
factor
binding
and
long-‐range
interactions
regulate
replication

initiation

Additional
elements
can
also
play
a
role
in
replication
initiation.

Transcription
factor
binding
sites
and
promoter
regions
have
been
shown
to

positively
stimulate
origin
activity

(or
initiation
domains)
sometimes
at
great

distances
in
metazoans
(>
10
kilobases
away)
(Aladjem,
2007).

These
regions
are

often
hypersensitive
to
DNase1
digestion
and
suggest
the
presence
of
open

chromatin.
Additionally,
some
of
these
regions
have
been
implicated
in
formation
of

DNA
loops
or
long-‐range
interactions
potentially
bringing
these
regions
(and
their

chromatin
remodelers)
into
close
proximity
to
the
origins
(initiation
domains)
that

they
regulate
(Smith
and
Aladjem).
In
yeast,
the
transcription
factor
Abf1
is
present

5

at
a
subset
of
origins
and
deletion
of
its
binding
site
resulted
in
reduced
origin
firing

at
the
well
characterized
origin,
ARS1
(Marahrens
and
Stillman,
1992).
Additional

analysis
has
shown
that
Abf1
binding
positively
stimulates
MCM
loading
by

displacing
an
adjacent
nucleosome
(Lipford
and
Bell,
2001).
Positive
stimulation
of

origin
activity
in
cis
by
transcription
factors
has
also
been
observed
in
higher

eukaryotes
(Aladjem,
2007).

Nuclear
localization
and
replication
timing

Particular
interest,
as
of
late,
has
been
placed
on
investigating
the
role
of

nuclear
architecture
in
coordination
of
genomic
processes.
Rather
than
occurring

throughout
the
nucleus,
it
is
plausible
that
replication
might
initiate
from
a
sub-‐
nuclear
region(s)
preferentially
giving
certain
origins
access
to
limiting
replication

machinery.
In
support
of
this
model,
replication
foci
or
replication
factories
form

upon
entry
into
S-‐phase
as
seen
by
Polymerase1/2-‐GFP
fusion
experiments.

(Kitamura
et
al.,
2006).

Additionally,
early,
but
not
late
firing,
origins
exhibit

clustering
as
evidenced
by
three-‐dimensional
genome
reconstruction
experiments

(Duan
et
al.,
2010).
The
formation
of
replication
factories
and
the
preferential

clustering
of
early
origins
suggest
that
certain
sub-‐nuclear
environments
exist

where
replication
factors
may
be
recruited
in
order
to
efficiently
facilitate

replication
initiation
and
elongation.

Localization
of
origins
within
these
sub-‐
nuclear
domains
would
give
them
preferential
access
to
these
factors.
A
likely

candidate
for
such
a
limiting
factor
might
be
Cdc45
and
or
its
loading
factor
Sld3.

This
is
due
to
the
positive
correlation
of
Cdc45-‐Sld3
loading
with
the
timing
of

6

initiation
(early
origins
associate
with
Cdc45
sooner
than
late
origins,
beginning
in

G1)
(Aparicio
et
al.,
1999).

Forkhead
transcription
factors
and
replication

The
roles
of
the
yeast
Forkhead
(Fkh)
transcription
factors,
Fkh1
and
Fkh2

(Fkh1/2),
have
been
well
studied
in
the
context
of
the
G2/M
phase
transition
of
the

cell
cycle
(as
reviewed
in
Murakami
et
al.,
2010).
This
regulatory
control
of
the
CLB2

gene
cluster
is
necessary
for
normal
cell
cycle
progression.
Fkh1/2
play
partially

overlapping
roles
in
this
regulation
as
complete
transcriptional
deregulation
is
only

observed
in
the
double
mutant
(fkh1∆
fkh2∆).
This
may
be
due
to
the
high
level
of

homology
between
Fkh1
and
Fkh2.
Both
Fkh1
and
Fkh2
share
a
conserved

Forkhead
Associated
(FHA)
domain,
a
phosphothreonine-‐binding
motif,
as
well
as
a

winged-‐helix
Forkhead
DNA
binding
domain
(Fkh-‐DBD).
Fkh2
differs
from
Fkh1

with
the
addition
of
a
C-‐terminal
tail
shown
to
be
involved
in
interactions
with
its

binding
partners
MCM1
and
NDD1(Ostrow
et
al.,
2014).

Recently,
we
have
implicated
Fkh1/2
as
global
determinants
of
replication

initiation
timing
in
S.
cerevisiae
(Knott
et
al.,
2012
(Chapter
I)
&
Chapter
II).
In
the

studies
detailed
here,
we
investigate
the
role
of
Forkhead
proteins
as
well
as
several

additional
factors
that
have
been
recently
implicated
in
the
coordination
of

replication
timing.
We
have
shown,
along
with
the
work
of
others,
that
the
telomeric

silencing
protein
Rif1
plays
an
expansive
role
in
replication
timing
outside
of

telomeres
in
S.
cerevisiae
as
well
as
in
other
systems
including
Schizosaccharomyces

pombe
and
higher
metazoans.
(See
Chapter
III)
(Cornacchia
et
al.,
2012;
Hayano
et

7

al.,
2012;
Lian
et
al.,
2011;
Peace
et
al.,
2014;
Yamazaki
et
al.,
2012).
Lastly,
we

investigate
the
consequence
of
decreased
origin
usage
due
to
defective
Cdc7
or
Orc1

function
(Zhong
et
al.,
2013
(Chapter
IV)).

8

Chapter
I

Forkhead
Transcription
Factors
Establish
Origin
Timing
and
Long-‐Range

Clustering
in
S.
cerevisiae

Adapted
from:

Knott,
S.R.V.,
Peace,
J.M.,
Ostrow,
A.Z.,
Gan,
Y.,
Rex,
A.E.,
Viggiani,
C.J.,
Tavaré,
S.,
and

Aparicio,
O.M.
(2012).
Forkhead
Transcription
Factors
Establish
Origin
Timing
and

Long-‐Range
Clustering
in
S.
cerevisiae.
Cell
148,
99–111.

My
primary
contribution
to
the
following
work
included
the
transcriptional

analysis
of
genes
surrounding
Fkh-‐regulated
origin
classes
through
a
combination
of

Rpb3
ChIP-‐Seq
and
ssRNA-‐seq
techniques
(Fig.
1.6).
Additionally,
I
produced

experimental
replicates
for
BrdU-‐IP-‐Seq
experiments
(Fig.
1.1B
&
1.2)
and

contributed
to
discussion
and
analysis
of
data.

9

INTRODUCTION

Similar
to
their
effects
on
transcription,
local
histone
deacetylation
typically

delays
or
suppresses
origin
firing,
whereas
histone
acetylation
advances
or

stimulates
origin
activity
(Aggarwal
and
Calvi,
2004;
Aparicio
et
al.,
2004;
Goren
et

al.,
2008;
Knott
et
al.,
2009c;
Pappas
et
al.,
2004;
Stevenson
and
Gottschling,
1999;

Vogelauer
et
al.,
2002;
Weber
et
al.,
2008).

However,
distinct
aspects
of
chromatin

structure
may
affect
origin
timing
versus
efficiency.
Recent
studies
indicate
that

histone
acetylation
is
required
for
pre-‐RC
assembly
(Miotto
and
Struhl,
2007),
and

multiple,
acetylated
lysines
in
histone
H3
and
H4
N-‐termini
are
required
for
efficient

origin
activity
(Eaton
et
al.,
2011;
Unnikrishnan
et
al.,
2010).

The
mechanism
of

temporal
control
is
less
clear.

Early
firing
is
thought
to
represent
a
default
state,

with
deacetylated
chromatin
imposing
a
delay.

Recently,
we
reported
that
the
Rpd3L
histone
deacetylase
delays
the

activation
of
~100
origins
throughout
the
yeast
genome
(~1/3
of
the
active
origins)

(Knott
et
al.,
2009c).

With
this
dataset
we
used
classification-‐regression
trees
to

identify
annotated
protein
binding-‐sites
(from
(Harbison
et
al.,
2004)
whose

presence
or
absence
near
origins
was
predictive
of
origin
regulation
by
Rpd3L.

This

and
further
analysis
identified
binding
sites
of
Forkhead
transcription
factors,
Fkh1

and
Fkh2,
as
being
depleted
near
Rpd3L-‐regulated
origins
(data
not
shown).

Fkh1

and
Fkh2
have
been
well
characterized
for
their
role
in
regulating
G2/M-‐phase

specific
transcription
of
a
group
of
genes
known
as
the
CLB2
cluster
(reviewed
in

(Murakami
et
al.,
2010)),
but
have
no
known
role
in
DNA
replication.

In
this
study,

10

we
show
that
Fkh1
and
Fkh2
regulate
the
initiation
timing
of
most
of
the
earliest

origins
in
the
yeast
genome
through
a
novel
mechanism
involving
origin
clustering

in
G1-‐phase.

RESULTS

Fkh1
and
Fkh2
control
genome-‐wide
initiation
dynamics
of
replication

origins.

To
test
whether
Fkh1
and
Fkh2
influence
replication
origin
function,
we

examined
genome-‐wide
origin-‐firing
using
BrdU
immunoprecipitation
analyzed
by

DNA
sequencing
(BrdU-‐IP-‐Seq),
in
cells
arrested
in
early
S-‐phase
with
hydroxyurea

(HU).

In
this
analysis,
BrdU
peak
size
is
proportional
to
origin
efficiency
in
HU:

early-‐efficient
origins
produce
large
peaks
while
late
and/or
dormant
origins
yield

smaller
or
no
peaks
(Knott
et
al.,
2009c).

Because
Fkh1
and
Fkh2
play
partially

complementary,
yet
opposing
roles
in
regulation
of
G2/M-‐phase
regulated
genes

(Murakami
et
al.,
2010),
we
analyzed
single
as
well
as
double
deletion
mutants
of

FKH1
and
FKH2.

Furthermore,
because
the
double
mutant
cells
exhibit
slow,

pseudohyphal
growth,
which
complicates
their
analysis,
we
also
examined
these

cells
with
over-‐expression
of
C-‐terminally
truncated
FKH2
(+pfkh2∆C),
which
largely

restores
CLB2
cluster
gene
regulation
(Reynolds
et
al.,
2003).

Consistent
with
this,

we
found
that
expression
of
Fkh2∆C
in
fkh1∆
fkh2∆
cells
suppressed
their

pseudohyphal
growth
and
restored
nearly
normal
growth
rate
(Fig.
1.1A
and
data

not
shown).

11

Figure
1.1.
Suppression
of
pseudohyphal
growth
of
fkh1∆
fkh2∆
cells
by

expression
of
Fkh2∆C.

Phase-‐contrast
images
of
the
indicated
strains
grown
in

liquid
culture
and
sonicated
mildly
to
disrupt
cell
aggregates.

B.
Origins

deregulated
in
fkh1∆,
fkh1∆
fkh2∆,
and
fkh1∆
fkh2∆
+
fkh2∆C
cells.

Venn
diagrams

showing
overlap
of
deregulated
origins
identified
as
Fkh-‐activated
and
Fkh-‐
repressed.

12

In
wild-‐type
(WT)
cells,
295
peaks
of
BrdU
incorporation
were
detected

genome-‐wide
(Fig.
1.2A).

Combined
deletion
of
FKH1
and
FKH2
had
an

unprecedented
effect
on
origin
activity
throughout
the
genome,
with
the
activities
of

the
archetypal
early
origins
ARS305
and
ARS607
being
strongly
reduced
(Fig.
1.2A).

Genome-‐wide,
of
the
352
origins
that
were
detected
to
fire
in
WT
and/or
fkh1∆

fkh2∆
cells,
106
(30%)
origins
were
significantly
decreased
in
activity
(Fkh-‐
activated)
and
82
(23%)
were
significantly
increased
(Fkh-‐repressed).
Deletion
of

FKH1
significantly
(FDR<0.005)
altered
the
activity
of
specific
origins,
with
35
being

Fkh-‐activated
and
16
Fkh-‐repressed,
whereas
deletion
of
FKH2
had
no
significant

effect
on
the
replication
pattern
(Fig.
1.2A,
1.1B).

Fortuitously,
expression
of
fkh2∆C,

while
complementing
the
pseudohyphal
growth
defects
due
to
transcriptional

deregulation,
did
not
complement
the
origin
deregulation
of
fkh1∆
fkh2∆
cells,
with

virtually
all
of
the
same
origins
being
identified
as
Fkh-‐activated
(95)
or
Fkh-‐
repressed
(80)
(Fig.
1A,
S1B,
C,
Table
S1
and
Data
S1).

This
result
demonstrates
that

the
C-‐terminus
of
Fkh2
is
required
for
origin
regulation,
and
suggests
that
the

effects
on
origins
are
independent
of
transcriptional
regulation
by
Fkh1
and
Fkh2.

We
took
advantage
of
the
ability
of
fkh2∆C
expression
to
complement
the

transcriptional
defects,
but
not
the
replication
defects,
and
to
improve
the
growth
of

the
double
mutant
cells
to
facilitate
further
analyses
of
fkh1∆
fkh2∆
cells.

Two-‐dimensional
clustering
of
the
Fkh-‐regulated
origins
based
on
their
peak

sizes
allows
a
global
comparison
of
origin
activities
in
the
WT,
single
and
double

mutant
strains.

This
analysis
reveals
the
extensive
deregulation
of
fkh1∆
fkh2∆
and

13

Figure
1.2.
Analysis
of
early
S-‐phase
BrdU
incorporation.

A.
BrdU
incorporation

plots
of
chromosomes
III
and
VI
are
shown;
plot
colors
and
symbols
correspond
to

the
strain
key
above.

Origins
discussed
in
the
text
are
boxed.

B.
Two-‐dimensional

clustering
of
peak
counts
at
Fkh-‐regulated
origins
is
shown;
columns
(color-‐keyed

above)
correspond
to
strains
and
rows
to
origins.

C.
All
detected
origins
(in
rows)

are
arranged
from
maximum
to
minimum
counts
in
WT,
with
the
positions
of
Fkh-‐
regulated
origins
indicated.

14

fkh1∆
fkh2∆
+pfkh2∆C
cells,
the
strong
similarity
between
replication
patterns
in
the

WT
and
fkh2∆
cells,
and
the
intermediate
phenotype
of
fkh1∆
cells
(Fig.
1B).

These

data
indicate
that
Fkh1
and
Fkh2
play
a
major
and
complementary
role
in
selecting

certain
origins
for
early
activation,
while
repressing
the
activation
of
others.

Fkh1
is

sufficient
to
maintain
normal
(early)
origin
regulation
in
the
absence
of
Fkh2,

whereas
Fkh2
only
partially
compensates
for
the
absence
of
Fkh1.

To
appraise
the
global
relationship
between
origin
activities
and
regulation

by
Fkh1
and/or
Fkh2
(Fkh1/2),
we
arranged
origins
according
to
their
WT
activity

levels
(in
HU)
and
plotted
the
positions
of
Fkh-‐activated
and
-‐repressed
origins
(Fig.

1C).

Fkh-‐activated
origins
were
strongly
enriched
among
earlier-‐firing
origins
while

Fkh-‐repressed
origins
were
strongly
enriched
among
later-‐firing
(or
inefficient)

origins
(p<0.001,
hypergeometric
test).

These
results
show
that
Fkh1
and
Fkh2
are

largely
responsible
for
differential
origin
firing
dynamics
throughout
the
genome.

To
examine
in
more
detail
the
effect
of
Fkh1
and
Fkh2
on
temporal
origin-‐
firing
dynamics,
we
analyzed
replication
throughout
an
unperturbed,
synchronous

S-‐phase.

Total
DNA
content
analysis
showed
similar
overall
replication
kinetics
in

WT
and
fkh1∆
fkh2∆
+pfkh2∆C
cells
(hereon
fkh1∆
fkh2∆C)
(Fig.
1.3A).

We
next
used

BrdU
pulse
labeling
combined
with
BrdU-‐IP
analyzed
by
microarray
(BrdU-‐IP-‐chip)

to
analyze
origin-‐firing
dynamics.

At
Fkh-‐activated
ARS305
in
WT
cells,
substantial

BrdU
incorporation
occurred
during
the
12-‐24min
through
30-‐42min
pulses,
and

ceased
by
the
36-‐48min
pulse,
consistent
with
the
early
and
synchronous

replication
of
this
origin
(Fig.
1.4A).

In
fkh1∆
fkh2∆C
cells,
however,
BrdU

incorporation
at
ARS305
was
delayed
and
reduced
in
comparison,
occurring
mainly

15

after
replication
had
ceased
in
the
WT
(Fig.
1.4A).

ARS607
and
numerous
other

early
origins
showed
similar
delay
of
activity
in
fkh1∆
fkh2∆C
cells.

These
data

confirm
the
results
of
the
analysis
with
HU
and
demonstrate
that
Fkh1/2
are

required
for
the
early
activation
of
many
origins
throughout
the
yeast
genome.

Figure
1.3.
Miscellaneous
Data.
A.
FACScan
analysis
of
DNA
content
of
WT
and

fkh1∆
fkh2∆C
cells
synchronized
in
G1-‐phase
with
α–factor
and
released

synchronously
into
S-‐phase.

B.
Two-‐dimensional
gel
electrophoresis
analysis
of

ARS305
(Fkh-‐activated)
and
ARS1520
(Fkh-‐repressed)
in
unsynchronized
WT
and

fkh1∆
fkh2∆C
cells.

Genomic
DNA
was
digested
with
NcoI
and
SalI.

C.
Non-‐random

distribution
of
Fkh-‐regulated
origins.
Chromosomal
positions
of
Fhk-‐activated
and
–
repressed
origins
are
plotted.

D.
Histogram
displaying
the
frequency
of
“Cut”
counts

observed
in
the
10
5

simulations
as
well
as
the
experimentally
observed
“Cut”
count.

“Cuts”
refers
to
the
number
of
times
a
Fkh-‐activated
origin
is
followed
by
a
Fkh-‐
repressed
origin,
or
vice-‐versa,
given
a
random
distribution
(see
Methods).

16

The
data
also
indicate
that
Fkh1/2
normally
repress
the
earlier
firing
of

many
origins.

For
example,
examination
of
the
late-‐replicating
region
of

chromosome
XV
demonstrates
that
several
later-‐firing
origins,
such
as
ARS1520,

initiated
replication
earlier
in
the
mutant
cells
(Fig.
1.4A).

To
address
the
formal

possibility
that
the
observed
differences
in
origin
activation
timing
derive
from
a

change
in
origin
activation
efficiency,
we
performed
two-‐dimensional
gel

electrophoresis
analysis
of
replication
initiation
structures
of
Fkh-‐activated
origin

ARS305
and
Fkh-‐repressed
origin
ARS1520.

Both
origins
exhibit
high
efficiency
in

both
WT
and
fkh1∆
fkh2∆C
cells
(Fig.
1.3B).

These
data
confirm
that
Fkh1/2

establish
the
temporal
program
of
origin
activation.

For
a
global
view
of
the
impact
of
Fkh1/2
regulation
on
the
temporal

program,
we
clustered
the
Fkh-‐regulated
origins
according
to
their
peak-‐count

differences
in
the
HU
analysis,
and
plotted
the
differences
in
their
levels
of
BrdU-‐
incorporation
between
WT
and
mutant
for
each
interval
in
the
time-‐course
(Fig.

1.4B).

This
analysis
shows
global
correspondence
between
the
change
in
origin

activity
in
HU
and
the
change
in
origin
activity
in
the
time
course
in
the
fkh1∆

fkh2∆C
cells,
with
Fkh-‐activated
origins
firing
earlier
and
Fkh-‐repressed
origins

firing
later
in
WT
cells.

Thus,
Fkh1/2
play
a
major
role
in
determining
the

characteristic
firing
times
of
replication
origins
throughout
much
of
the
yeast

genome.

17

Figure
1.4.
Temporal
analysis
of
DNA
replication
by
BrdU
pulse-‐labeling.

A.

BrdU
incorporation
plots
of
chromosome
III
and
a
region
of
XV
are
shown.

Origins

discussed
in
the
text
are
boxed.

B.
The
matrix
shows
differences
(WT-‐fkh1∆
fkh2∆C)

in
BrdU
incorporation
(Δ
M-‐value)
at
all
Fkh-‐regulated
origins
(columns)
across

time
(rows);
the
origins
are
arranged
from
left
to
right
by
their
differences
(WT-‐
fkh1∆
fkh2∆C)
in
BrdU
incorporation
in
HU
(Δ
HU
Counts).

Specific
origins
are

indicated
below.

Fkh-‐regulation
involves
establishment
of
replication
timing
domains.

Comparison
of
the
WT
and
mutant
chromosomal
replication
profiles
reveals

additional
features
of
interest,
including
even
earlier
replication
of
centromere

(CEN)-‐proximal
sequences,
such
that
these
became
the
earliest
replicating
region
of

18

each
chromosome
(Fig.
1.4A).

Plotting
CEN-‐proximal
origins
(ie,
within
25kb)
in
the

time-‐course
clustergram
shows
that
many
of
these
origins
initiated
earlier
in
the

mutant
cells
and
were
among
the
most
strongly
affected
of
the
Fkh-‐repressed

origins
(Fig.
1.4B).

Another
striking
feature
of
the
mutant
replication
profiles
is
the

delayed
replication
of
most
telomere
(TEL)-‐proximal
sequences,
particularly
those

with
active
origins,
as
evident
on
the
right
arm
of
chromosome
III
(Fig.
1.4A).
These

results
further
demonstrate
the
global
role
of
Fkh1/2
in
determining
genome

replication
timing
and
suggest
a
function
in
chromosomal
organization.

We
wondered
whether
the
distribution
of
Fkh-‐regulated
origins
along

chromosomes
might
provide
additional
clues
about
their
functional
organization.

Chromosomal
plots
of
Fkh-‐regulated
origins
(ignoring
non-‐regulated
origins)
show

frequent,
linearly
contiguous
groups
of
Fkh-‐activated
and
-‐repressed
origins,

suggesting
a
non-‐random
distribution
(Fig.
1.3C).

To
test
this
notion
rigorously,
we

applied
a
permutation
test
that
determines
the
likelihood
that
the
contiguous

groups
are
random.

The
result
shows
that
the
distribution
of
Fkh-‐activated
and
-‐
repressed
origins
is
non-‐random
and
that
origins
of
each
class
frequently
cluster

linearly
along
the
chromosome
with
other
members
of
their
class
(p<0.01,
Fig.

1.3D).

Together
with
the
CEN-‐
and
TEL-‐specific
effects,
these
results
are
consistent

with
Fkh1/2
establishing
domains
of
replication
timing.

19

Figure
1.5.
Analysis
of
Fkh1
and
Fkh2
binding
sites
near
origins.

A
and
B.

Frequencies
of
expected
and
actual
Fkh1
(A)
and
Fkh2
(B)
consensus
binding
sites

near
Fkh-‐activated,
Fkh-‐unregulated,
and
Fkh-‐repressed
origins
are
shown.

C.

Frequency
distribution
plots
of
Fkh1
and
Fkh2
consensus
binding
sites
relative
to

ACS
position
are
shown.

D.
M-‐values
for
BrdU-‐IP-‐chip
and
for
ChIP-‐chip
of
Fkh1
and

ORC
binding
along
the
ARS305
region
in
WT
cells
harboring
ARS305
or
ars305∆2BS.

20

Fkh1/2
bind
and
function
in
cis
to
Fkh-‐activated
origins.

Fkh1
and
Fkh2
exhibit
similar
DNA
sequence
binding
specificities
in
vitro
and
bind

extensively
throughout
the
genome,
with
significant
overlap
of
binding
sites
(data

not
shown
and
(Harbison
et
al.,
2004;
Hollenhorst
et
al.,
2001;
MacIsaac
et
al.,

2006).

To
examine
the
relationship
of
Fkh1
and
Fkh2
binding
with
origin

regulation,
we
analyzed
the
distribution
of
putative
Fkh1
and
Fkh2
binding
sites

within
500bp
of
Fkh-‐activated,
-‐
repressed,
and
-‐unregulated
origins
(see
Methods).

This
analysis
shows
that
Fkh1
and
Fkh2
binding
sites
are
enriched
near
Fkh-‐
activated
origins
and
depleted
near
Fkh-‐repressed
origins
(Fig.
1.5A,
B,

hypergeometric
test,
p<0.01),
as
expected
if
Fkh1/2
act
through
direct
binding
near

Fkh-‐activated
origins.

Fkh1
was
most
enriched,
being
~four-‐fold
enriched
at
Fkh-‐
activated
versus
-‐repressed
origins,
consistent
with
a
predominant
role
for
Fkh1

rather
than
Fkh2
in
origin
regulation
as
indicated
by
the
single
mutant
analysis

above.

The
enrichment
of
Fkh1/2
binding
sites
near
origins
may
explain
the

selection
of
these
origins
for
early
activation,
however,
Fkh1/2
bind
near
some

origins
that
are
not
Fkh-‐activated
suggesting
that
Fkh1/2
binding
in
the
vicinity
is

not
sufficient
for
origin
activation.

To
determine
more
precisely
how
Fkh1
and
Fkh2

localize
in
relation
to
Fkh-‐regulated
origins,
we
calculated
the
distance
from
each

origin’s
ARS-‐consensus
sequence
(ACS),
which
binds
ORC,
to
the
likeliest
Fkh1
and

Fkh2
binding
site
within
500bp
and
plotted
the
results
as
a
frequency
distribution

(see
Methods).

The
distribution
reveals
extraordinary
proximity
of
Fkh1
and
Fkh2

21

consensus
sites
to
ACSs
of
Fkh-‐activated
origins,
with
frequent
overlap
of
the

Fkh1/2
binding
sites
and
ACSs
(Fig.
1.5C).

In
contrast,
Fkh1
and
especially
Fkh2

showed
poorer
alignment
and
binding
density
with
those
few
Fkh-‐repressed
origins

proximal
to
Fkh1/2
binding
sites.

These
results
suggest
that
the
positioning
and/or

number
of
these
sites
may
be
important
for
origin
regulation

To
test
directly
whether
Fkh1/2
regulate
origin
function
through
binding
in

cis
to
the
affected
origin,
we
mutated
two
putative
Fkh1/2
binding
sites
near

ARS305
(ars305∆2BS).

Combined
mutation
of
these
sites
significantly
reduced
BrdU

incorporation
at
ARS305,
but
not
at
more
distal
origins,
indicating
that
Fkh1/2

regulate
ARS305
directly
through
binding
in
cis
(Fig.
1.5D).

Crucially,
mutation
of

these
binding
sites
eliminated
Fkh1
binding
to
the
ARS305
region
without

eliminating
ORC
binding
(Fig.
1.5D).

These
results
also
eliminate
concerns
that

origin
deregulation
results
from
mis-‐expression
of
a
replication
factor(s)
in
fkh1∆

fkh2∆C
cells.

Overall,
these
results
demonstrate
that
Fkh1/2
binding
positively

influences
origin
activity.

Fkh-‐dependent
origin
regulation
is
not
correlated
with
transcription
levels
or

changes.

The
notion
of
a
mechanistic
link
between
replication
origin
timing
and

transcriptional
state,
together
with
the
well-‐characterized
roles
of
Fkh1
and
Fkh2
as

transcriptional
regulators,
suggested
that
altered
transcription,
particularly
of
genes

22

Figure
1.6.
Transcription
analysis
surrounding
Fkh-‐regulated
origins
in

unsynchronized
and
G1-‐synchronized
cells.

RNA-‐Seq
(A)
and
Rpb3
ChIP-‐Seq
(B)

read
counts
of
WT,
fkh1∆
fkh2∆C,
and
WT-‐fkh1∆
fkh2∆C
differences
(Δ),
within
10kb

of
each
Fkh-‐regulated
origin,
are
aligned
by
each
origin’s
predicted
or
verified
ACS.

Origins
are
grouped
according
to
the
orientation
of
the
flanking
genes,
and
arranged

by
differences
(WT-‐fkh1∆
fkh2∆C)
in
BrdU
incorporation
in
HU
(Δ
HU
Counts).

proximal
to
Fkh-‐regulated
origins,
might
explain
the
altered
origin
firing.

Although

expression
of
Fkh2∆C
suppressed
pseudohyphal
growth,
indicating
that
normal

transcriptional
regulation
had
been
at
least
partially
restored,
we
nonetheless

23

wished
to
determine
whether
differences
in
transcription
of
genes
proximal
to
the

affected
origins
could
account
for
the
differences
in
origin
activity.

Accordingly,
we

analyzed
global
RNA
transcript
levels
using
strand-‐specific
RNA
quantification
by

sequencing
(RNA-‐Seq)
and
RNA
Polymerase
II
(Pol
II)
occupancy
using
chromatin

immunoprecipitation
analyzed
by
sequencing
(ChIP-‐Seq)
of
the
Pol
II
core
subunit

Rpb3
in
WT
and
fkh1∆
fkh2∆C
cells,
in
unsynchronized
cells
and
cells
synchronized

in
G1-‐phase,
when
replication
timing
is
established
(Dimitrova
and
Gilbert,
1999;

Raghuraman
et
al.,
1997).

Up-‐regulation
of
CLB2
in
G1-‐phase
fkh1∆
fkh2∆C
cells,

which
is
consistent
with
the
role
of
Fkh1
in
CLB2
repression,
and
significant
overlap

between
genes
identified
by
the
different
methods
validated
both
analyses.

A

permutation
test
indicates
that
genes
deregulated
in
fkh1∆
fkh2∆C
cells
are
not

significantly
co-‐localized
with
or
proximal
to
Fkh-‐regulated
origins
(see
Methods).

We
also
plotted
RNA
transcript
levels
and
Rpb3
occupancy,
as
well
as
their

differences
in
fkh1∆
fkh2∆C
cells,
within
10kb
of
Fkh-‐regulated
origins
(Fig.
1.6).

Visual
inspection
of
these
plots
show
no
obvious
correlation
with
the
effects
on

origin
activities,
regardless
of
the
magnitude
or
directionality
(positive
or
negative)

of
effect,
the
orientation
of
the
immediately
flanking
genes,
or
the
cell
cycle
stage.

Linear
regression
analysis
also
shows
no
consistent
correlation
between
the
effects

on
origin
activity
and
the
expression
levels
of
the
immediately
flanking
genes
(see

Methods).

These
findings
demonstrate
that
origin
regulation
by
Fkh1/2
does
not

involve
proximal
changes
in
transcription.

24

Cdc45
preferentially
associates
with
Fkh-‐activated
origins
in
G1-‐phase.

We
wondered
whether
Fkh1/2
regulate
replication
timing
by
modulating
the

binding
of
replication
factors
to
origins.

To
determine
whether
Fkh1/2
influence

ORC
binding
or
MCM
loading,
we
used
ChIP
analyzed
by
microarray
(ChIP-‐chip)
to

examine
ORC
binding
in
unsynchronized
cells
and
Mcm2+4
binding
in
G1-‐
synchronized
cells.

The
results
show
no
significant,
global
difference
in
ORC
or

Mcm2+4
origin-‐binding
between
WT
and
fkh1∆
fkh2∆C
cells
(Fig.
1.7A),
contrary
to

the
idea
that
Fkh1/2
affect
origin-‐firing
by
modulating
ORC
or
MCM
binding.

Origin
initiation
requires
the
DDK-‐dependent
recruitment
of
Cdc45
to
pre-‐
RCs.

However,
Cdc45
associates
specifically,
albeit
relatively
weakly,
with
several

early
replication
origins
in
G1-‐phase
(prior
to
DDK
activation),
presaging
their

characteristic
early
S-‐phase
activity
(Aparicio
et
al.,
1999).

This
suggests
that
these

origins
gain
an
early
advantage
(by
G1-‐phase)
in
their
ability
to
recruit
Cdc45
to

enable
early
initiation.
Examination
of
Cdc45
binding
by
ChIP-‐chip
shows
Cdc45

association
with
many
early
origins,
including
Fkh-‐activated
origins,
such
as
ARS305

and
ARS607,
and
a
number
of
CEN-‐proximal
origins
(Fig.
1.7A,
B).
Of
28
origins
that

bind
Cdc45
in
WT
G1-‐phase
cells,
15
are
Fkh-‐activated
and
14
are
CEN-‐proximal
(on

11
CENs),
while
only
one
is
Fkh-‐repressed.

Strikingly,
in
the
fkh1∆
fkh2∆C
cells,

Cdc45
binding
is
lost
from
the
Fkh-‐activated
origins,
which
become
significantly

later
firing,
leaving
only
13
origins
binding
Cdc45
(Fig.
1.7B).

Of
these
13,
12
are

CEN-‐proximal,
which
as
shown
above,
remain
early
firing.

Thus,
Cdc45
origin-‐
binding
in
G1-‐phase
is
robustly
associated
with
early
initiation.

These
findings

25

Figure
1.7.
Genome-‐wide
binding
of
replication
initiation
factors
to
Fkh-‐
regulated
origins.

A.
M-‐values
from
ChIP-‐chip
analysis
of
ORC,
Mcm2+4,
and

Cdc45
at
Fkh-‐regulated
origins
(in
rows)
are
arranged
by
differences
(WT-‐fkh1∆

fkh2∆C)
in
BrdU
incorporation
in
HU
(Δ
HU
Counts).

B.
Venn
diagram
of
Cdc45

binding
within
different
origin
classes
is
shown.

26

support
the
idea
that
Fkh1/2
influence
origin
function
by
regulating
access
to
the

pool
of
replication
factors
such
as
Cdc45,
whereas
CEN-‐proximal
origins
have
access

to
Cdc45
independently
of
Fkh1/2.

Fkh1/2
are
required
for
selective
clustering
of
Fkh-‐activated
origins
in
G1-‐
phase.

The
organization
of
selected
origins
into
subnuclear
domains
or
replication

foci
by
Fkh1/2
may
explain
their
preferential
access
to
limiting
or
sequestered

initiation
factors
like
Cdc45.

In
accord
with
this,
a
global
analysis
of
intra-‐
and
inter-‐
chromosomal
interactions
of
the
yeast
genome
using
a
variation
of
4C
(Chromosome

Conformation
Capture-‐on-‐Chip)
suggests
that
early
origins
cluster
in
G1-‐phase

(Duan
et
al.,
2010).

We
analyzed
this
origin
interaction
data
to
determine
whether

origin
clustering
was
associated
with
Fkh-‐regulation
and/or
Cdc45
binding
in
G1-‐
phase.

Two-‐dimensional
clustering
based
on
origin
interaction
frequencies
resulted

in
two
main
clusters
of
interacting
origins,
with
89
and
92
origins,
respectively
(Fig.

1.8A).

One
cluster
contains
most
of
the
Cdc45-‐bound
origins,
the
most
statistically

significant
Fkh-‐activated
origins,
and
CEN-‐proximal
origins.

This
cluster
also

contains
earlier-‐firing
origins
on
average
than
the
other
main
cluster
and
is
depleted

of
non-‐CEN
proximal,
Fkh-‐repressed
origins
(hypergeometric
test,
p<0.005).

These

findings
suggest
that
Fkh-‐regulation
involves
selective
origin
clustering.

To
test
whether
Fkh1/2
have
a
role
in
origin
clustering,
we
used
4C
to

analyze
the
trans
associations
of
Fkh-‐activated
origin
ARS305
with
other
genomic

27

sequences
(for
scheme,
see
Fig.
1.9A).

We
validated
this
analysis
by
comparing

overlap
between
experimental
replicates
of
WT
and
mutant
cells,
with
and
without

crosslinking,
and
by
analyzing
the
number
of
intra-‐
versus
inter-‐chromosomal

interactions
detected
(Fig.
1.9B).

As
expected,
and
consistent
with
the
results
of

(Duan
et
al.,
2010),
intrachromosomal
interactions
were
enriched
versus

interchromosomal
interactions
(p<0.001).

We
detected
48
ARS305-‐interacting
loci

in
both
WT
replicates
(of
71
and
72
in
the
replicates),
and
41
ARS305-‐interacting

loci
in
both
fkh1∆
fkh2∆C
replicates
(of
164
and
189
in
the
replicates)
(Fig.
1.8B).

The
larger
number
of
detected
interactions
with
lower
overlap
between
them
in
the

fkh1∆
fkh2∆C
replicates
is
consistent
with
a
decrease
in
specificity
of
ARS305

interactions
in
the
mutant
cells.

Most
of
the
48
sites
in
WT
cells
were
not
detected

in
the
mutant
cells,
indicating
that
their
interaction
with
ARS305
is
Fkh1/2-‐
dependent.

For
example,
ARS305
interacted
with
ARS607
(as
shown
previously

(Duan
et
al.,
2010))
in
both
WT
replicates
and
in
neither
fkh1∆
fkh2∆C
replicate
(Fig.

1.8C),
indicating
that
Fkh1/2
are
required
for
interaction
in
G1-‐phase
between
these

early-‐firing,
Fkh-‐activated
origins.

These
results
indicate
that
Fkh1/2
play
a
role
in

determining
the
long-‐range
chromatin
contacts
made
by
ARS305,
and
support
the

idea
that
Fkh1/2
function
in
origin
regulation
through
origin
clustering.

28

Figure
1.8.
Chromosome-‐conformation
capture
analyses
of
origin
interactions.

A.
Two-‐dimensional
clustering
of
origin-‐origin
interaction
frequencies
is
shown,

with
origins
in
columns
and
rows
of
the
matrix.

Columns
to
the
right
indicate
Cdc45

ChIP-‐chip
binding,
average
BrdU
∆HU-‐counts,
and
∆BrdU-‐pulse
M-‐values.

The
top

5%
(based
on
p
values)
of
Fkh-‐activated
and
Fkh-‐repressed
origins
are
indicated.

B.

Venn
diagram
of
overlap
between
experimental
replicates
is
shown.

C.
Plots
of
the

ARS607
region
including
relevant
XbaI
sites
are
shown.

See
also
Figure
1.9.

29

Figure
1.9.

4C
analysis
of
ARS305
interactions.

A.
Scheme
of
the
4C
method

showing
relevant
XbaI
(X1-‐X4)
and
MseI
(M1-‐M4)
restriction
sites
surrounding

ARS305
(Bait)
and
a
hypothetical
interacting
locus
(Prey),
and
primers
(P1-‐P4)
used

to
amplify
captured
loci
for
identification
by
microarray.

The
tethering
agent

represents
cross-‐linked
protein(s)
mediating
interaction
between
the
bait
and
prey.

B.
Statistical
analysis
of
ARS305
interacting
sites
by
chromosome
showing
the

expected
preference
for
intrachromosomal
interactions
(i.e.,
with
chromosome
III).

The
p
value
is
based
on
the
number
of
observed
versus
expected
interactions
for

each
chromosome
(the
expected
number
of
interactions
is
directly
proportional
to

the
number
of
XbaI
fragments
per
individual
chromosome).

30

Fkh1
and
Fkh2
interact
with
ORC.

The
binding
of
Fkh1/2
adjacent
to
many
Fkh-‐activated
origins,
including

ARS305
and
ARS607
(data
not
shown
and
(Harbison
et
al.,
2004;
Keich
et
al.,
2008)),

led
us
to
hypothesize
that
Fkh1/2
bound
near
origins
might
stabilize
origin
contacts

in
trans
through
interaction
with
ORC
bound
at
other
Fkh-‐activated
origins.

Immunoprecipitation
(IP)
of
Myc-‐tagged
Fkh1
or
Fkh2
from
soluble
cell
extracts

resulted
in
co-‐precipitation
of
ORC
(Fig.
1.10A,
lanes
1
and
2,
data
not
shown
for

Fkh2);
Orc2
was
robustly
detected,
Orc1
and
Orc3
were
weakly
detected,
and
Orc4-‐
Orc6
were
obscured
by
co-‐migrating
immunoglobulin
heavy
chain
(data
not
shown).

Reciprocal
IP
of
ORC
using
a
polyclonal
antibody
co-‐precipitated
Fkh1
(Fig.
1.10B,

lanes
3
and
4).

Taken
together,
these
results
demonstrate
a
physical
interaction

(direct
or
indirect)
between
ORC
and
Fkh1.

These
interactions
persisted
in
the

presence
of
the
DNA-‐intercalating
agent,
ethidium
bromide,
indicating
that
the

interactions
are
likely
not
DNA-‐mediated
(Fig.
1.10C,
lanes
5-‐8).

Together
with
the

close
proximity
of
Fkh1/2
binding
sites
with
origin
ACSs,
these
results
support
the

idea
that
Fkh1/2
interact
with
ORC
to
bridge
replication
origins
in
trans.

31

Figure
1.10.
Co-‐IP
of
Fkh1
with
ORC.

Soluble
extracts
from
FKH1-‐MYC
(lanes
1,
3,

5-‐8)
and
untagged
(lanes
2,
4)
cells
were
subjected
to
IP
with
anti-‐Myc
antibody
(A)

and
anti-‐ORC
antibody
(B
and
C).

IPs
were
analyzed
by
immunoblotting
with
anti-‐
Myc
and
anti-‐ORC
antibodies.

C.
Ethidium
bromide
(EtBr)
was
included
in
the
IPs
at

10,
40,
and
100
µg/mL
in
lanes
6,
7,
and
8,
respectively.

ORC
protein
was
included

as
standard.

32

DISCUSSION

Fkh1/2
establish
replication-‐timing
domains
through
origin
clustering.

Our
findings
reveal
a
novel,
global
mechanism
for
the
regulation
of
origin

initiation
timing,
involving
the
spatial
organization
of
replication
origins
by
Fkh1/2.

Previous
studies
have
concluded
that
yeast
origins
are
early
by
default,
and
that
late

timing
is
imposed
by
flanking
sequences
of
a
repressive
nature
(Ferguson
and

Fangman,
1992;
Friedman
et
al.,
1996).

However,
our
findings
show
that
Fkh1/2

actively
program
the
timing
of
most
of
the
earliest
origins
throughout
the
genome.

Thus,
we
propose
that
Fkh1/2
establish
early
replication
timing
at
Forkhead-‐
activated
origins
by
recruiting
these
origins
into
clusters
where
Cdc45
is
(and
likely

other
replication
factors
are)
concentrated.

The
enrichment
and
distinct
positioning

relative
to
the
ACS
of
Fkh1/2
binding
sites
likely
explains
the
selective
preference

for
Fkh-‐activated
origins.

Clustering
may
involve
interaction
of
Fkh1/2
bound

adjacent
to
an
origin
with
ORC
bound
to
a
distal,
second
origin.

Likewise,
Fkh1/2

bound
near
the
second
origin
might
interact
with
a
third
origin,
and
so
forth,

providing
a
mechanism
to
cluster
several
origins
together.

This
congregation
of

origins
and
initiation
factors
provides
a
kinetic
advantage
in
assembling
the
factors

needed
for
replication
initiation
upon
S-‐phase
entry,
which
transforms
these
origin

clusters
into
early
replication
factories.

The
ensuing
dynamics
of
the
replication

process,
involving
spooling
of
DNA
through
the
replication
factories
(Kitamura
et
al.,

2006),
eventually
repositions
more
distal,
unfired
origins,
bringing
them
in

33

proximity
of
the
concentration
of
the
replication
factor(ie)s
and
thereby
allowing

them
to
gain
access
as
early
replicons
terminate
and
are
released.

This
is
expected

to
result
in
an
increasingly
stochastic
pattern
of
replication
initiation
as
S-‐phase

proceeds
and
many
unfired
origins
compete
for
limited
access.

However,
later-‐
replicating
regions
also
exhibit
well-‐defined
replication
patterns
indicating

preferred
origin
timing
and
usage.

Indeed,
chromosomes
IV,
XII,
XIV,
and
XV
each

have
distinctly
late-‐replicating
regions
>200kb
in
length,
encompassing
groups
of

contiguous
Fkh-‐repressed
origins,
which
lose
this
unique
character
in
the
absence
of

Fkh1/2
(Fig.
1.4A).

Origin
clusters
may
define
replication-‐timing
domains.

The
organization
of

mammalian
chromosomes
into
spatial
domains
correlates
strongly
with
replication

timing
(Ryba
et
al.,
2010).

Analysis
of
global
4C
in
yeast
shows
clustering
of
early

origins
(in
G1-‐phase),
and
we
have
now
shown
that
the
early
origin
cluster
contains

Fkh-‐activated
and
Cdc45-‐bound
origins
(in
G1-‐phase).

We
have
confirmed
that
Fkh-‐
activated
origins
ARS305
and
ARS607
interact
in
trans,
and
critically,
show
that
this

interaction
depends
on
Fkh1/2.

In
addition,
Fkh-‐activated
and
Fkh-‐repressed

origins
often
occur
in
separate,
linearly
contiguous
groups
along
chromosomes,

suggesting
the
formation
of
distinct
domains.

This
may
involve
the
anchoring
of

intrachromosomal
chromatin
loops
by
Fkh1/2
bound
near
origins,
perhaps
through

interaction
with
ORC,
particularly
in
the
case
of
Fkh-‐activated
origins,
which
are

enriched
for
Fkh1/2
binding.

In
the
case
of
Fkh-‐repressed
origins,
a
dearth
of

Fkh1/2
binding
sites
presumably
reduces
the
likelihood
that
these
origins
join
the

Fkh-‐activated
clusters,
which
may
permit
other
mechanisms,
such
as
deacetylation

34

or
localization
to
the
nuclear
periphery,
to
define
replication
timing
of
these
regions.

Alternatively,
the
later
timing
may
be
a
consequence
of
conformational
or
spatial

constraints
imposed
by
the
chromosomal
architecture
established
by
Fkh1/2

clustering
of
Fkh-‐activated
origins.

In
the
absence
of
Fkh1
and
Fkh2,
CEN-‐proximal
origins
dominate
the
early

replication
landscape,
suggesting
that
CENs
confer
early
replication
intrinsically.

CENs
normally
cluster
and
occupy
a
characteristic
interior
position
in
the
nucleus

(Jin
et
al.,
1998)
that
we
suggest
overlaps
with
the
pool
of
replication
factor(ie)s.

Consequently,
CEN-‐proximal
origins
have
favorable
access
to
this
pool
and
initiate

early,
independently
of
Fkh1/2.

Thus,
CEN-‐proximal
origins
may
act
as
organizing

sites
for
early-‐replicating
origin
clusters
that
include
non-‐CEN-‐proximal
origins.

More
distal
Fkh-‐activated
origins
may
utilize
Fkh1/2
to
cluster
with
CEN-‐proximal

origins,
thereby
drawing
these
more
distal
origins
into
the
pool.

This
is
consistent

with
the
finding
that
CEN-‐proximal
origins
localize
to
the
large,
early-‐replicating

cluster
in
the
global
4C
data
together
with
the
earliest
Fkh-‐activated
origins.

Thus,

the
advanced
replication
timing
of
CEN-‐proximal
origins
(and
perhaps
other
Fkh-‐
repressed
origins)
in
cells
lacking
Fkh1/2
may
result
from
reduced
competition

from
Fkh-‐activated
origins
for
limiting
replication
factor(ie)s,
rather
than
a
direct

repressive
function
of
Fkh1/2.

Incidentally,
CEN-‐proximity
may
explain
the
finding

in
yeast
that
plasmid-‐borne
origins
typically
replicate
early,
as
these
studies
were

performed
with
CEN-‐harboring
plasmids
(Ferguson
and
Fangman,
1992;
Friedman

et
al.,
1996).

35

In
contrast
to
CENs,
TELs
form
several
clusters
that
occupy
the
nuclear

periphery
(Gotta
et
al.,
1996;
Heun
et
al.,
2001).

The
normally
late
replication
of

TEL-‐proximal
regions
is
consistent
with
the
notion
that
the
dynamic
nature
of
the

replication
process
eventually
relocates
these
distal
regions
to
the
interior
of
the

nucleus,
which
ultimately
enables
their
access
to
replication
factor(ie)s.

In
the

absence
of
Fkh1
and
Fkh2,
most
of
the
active
telomeric
origins
are
further
delayed.

We
imagine
that
the
delayed
activation
of
Fkh-‐activated
origins
located
along
distal

chromosomal
arms
results
in
a
corresponding
delay
in
the
relocation
to
TEL-‐
proximal
origins
to
the
vicinity
of
replication
factor(ie)s.

Alternatively,
Fkh1/2
may

act
directly
to
regulate
TEL-‐proximal
origins.

Further
study
will
be
required
to

understand
the
regulation
of
CEN-‐
and
TEL-‐proximal
origin
timing.

Multiple,
separable
roles
for
Fkh1
and
Fkh2
in
regulation
of
the
genome.

A
clear
finding
of
this
study
is
the
mechanistic
independence
of
Fkh-‐origin

regulation
from
transcription.

There
is
no
correlation
between
the
observed

changes
in
replication
timing
and
transcriptional
levels
of
proximal
genes.

Importantly,
expression
of
Fkh2
lacking
its
C-‐terminus
in
fkh1∆
fkh2∆
cells

significantly
restores
transcriptional
regulation
of
CLB2
cluster
genes
(only
CLB2

remained
deregulated
and
only
in
G1-‐phase
cells)
without
restoring
origin

regulation,
directly
demonstrating
a
separation
of
these
Fkh1/2
functions.

Nevertheless,
our
results
do
not
rule
out
the
possibility
that
the
function
of
Fkh1/2

36

in
origin
clustering
may
also
underlie
transcriptional
control
not
elicited
under
our

growth
conditions.

As
transcriptional
regulators,
Fkh1
and
Fkh2
exhibit
opposing,
as
well
as

partially
complementary
functions
(Murakami
et
al.,
2010).

Fkh1
and
Fkh2
also

demonstrate
distinct
abilities
to
regulate
origins,
suggesting
that
the
features
that

distinguish
Fkh1
and
Fkh2
functions
in
transcription
also
impinge
on
their
functions

as
origin
regulators.

Whereas
Fkh2
plays
the
lead
role
in
transcriptional
regulation,

Fkh1
plays
the
lead
role
in
origin
regulation.

Fkh1
differs
from
Fkh2
most

significantly
in
the
presence
of
a
C-‐terminal
extension
in
Fkh2,
which
regulates
its

interaction(s)
with
transcriptional
co-‐activator(s)
(Darieva
et
al.,
2010;
Darieva
et

al.,
2003;
Koranda
et
al.,
2000;
Pic-‐Taylor
et
al.,
2004;
Reynolds
et
al.,
2003).

This

domain
is
also
required
for
Fkh2’s
function
in
origin
regulation,
suggesting
that

proper
regulation
of
co-‐activator
interactions
is
critical,
and
that
factors
interacting

with
Fkh2
but
not
with
Fkh1
may
disrupt
origin
regulation.

Mcm1,
which
binds

cooperatively
with
Fkh2,
but
not
Fkh1
(Boros
et
al.,
2003;
Koranda
et
al.,
2000;

Kumar
et
al.,
2000;
Pic
et
al.,
2000),
is
an
intriguing
candidate,
as
it
has
been

reported
to
modulate
origin
function
(Chang
et
al.,
2004).

We
note
that
Mcm1

binding
sites
are
not
enriched
near
Fkh-‐activated
origins
(data
not
shown).

Thus,

consistent
with
the
lack
of
effect
on
origin
firing
of
FKH2
deletion,
it
is
possible
that

Fkh2
normally
plays
no
role
in
origin
regulation,
and
only
substitutes
(partially)
in

Fkh1’s
absence.

Fkh1,
but
not
Fkh2,
also
regulates
donor
preference
in
yeast
mating-‐type

switching
(Sun
et
al.,
2002).

Mating-‐type
switching
involves
homologous

37

recombination
between
the
MAT
locus
(recipient)
and
one
of
two
silent
mating-‐type

loci
(donor)
distally
located
on
opposite
arms
of
the
same
chromosome,
HMLα
and

HMRa.

This
mechanism
presumably
necessitates
chromosomal
looping
of
either

arm
to
juxtapose
the
donor
and
recipient
loci.

Remarkably,
in
MATa
cells,
HMLα
is

preferentially
selected
as
the
donor
in
over
90%
of
cells,
which
ensures
efficient

mating-‐type
switching.

This
preference
depends
on
Fkh1
binding
to
the

recombination
enhancer
(RE),
which
is
proximal
to
HMLα.

Our
finding
that
Fkh1/2

mediate
long-‐range
origin
interactions
suggest
that
Fkh1
mediates
a
stable,
long-‐
range
interaction
between
MATa
and
the
RE
to
specify
the
recombination
between

MATa
and
HMLα,
which
conspicuously,
like
early
origin
clustering,
occurs
during

G1-‐phase.

The
role
of
Fkh1
in
regulating
recombination
over
long
distances

together
with
Fkh1/2’s
role
in
regulating
replication
initiation
timing
through
long-‐
range
origin
clustering
suggests
that
establishing
long-‐range
chromatin
contacts

may
be
a
common
mechanism
of
Fkh1/2
function,
likely
extending
to

transcriptional
control.

Our
proposed
mechanism
of
origin
clustering
may
also
explain
how
the
long-‐
range
interaction
necessary
for
recombinational
donor
preference
is
established.

Dormant
origins
are
closely
associated
with
the
RE
(ARS304)
and
with
MAT
(ARS313

and
ARS314).

Thus,
interactions
between
Fkh1
bound
to
the
RE
and
ORC
bound
to

the
distal
ARS313
or
ARS314
may
stabilize
long-‐range
contacts
between
these
loci;

similar
interactions
between
ORC
bound
to
ARS304
and
Fkh1
bound
near
MAT
may

also
participate
(though
an
RE-‐like
element
has
not
been
identified
near
MAT).

The

dormancy
of
these
origins
is
consistent
with
the
idea
that
these
loci
form
a
separate

38

chromosomal
domain
dedicated
for
recombination,
which
delays
replication
(by

inhibiting
initiation
and
allowing
passive
replication
from
distal,
flanking
origins).

Exactly
how
such
domains
are
dedicated
to
one
function
over
another
will
require

more
investigation,
but
may
reflect
combinatorial
regulation
by
Fkh1/2
together

with
other
factors,
along
with
defined
sub-‐nuclear
localization
of
these
activities.

The
findings
presented
here
provide
a
clearer
understanding
of
the

epigenetic
basis
for
differential
origin
regulation
and
its
connection
to
the
spatial

organization
of
chromosomes.

Rather
than
a
direct
connection
with
transcription,

the
results
indicate
that
the
organization
of
origins
into
functional
clusters

determines
their
activation
kinetics.

Our
study
identifies
Fkh1
and
Fkh2
as
factors

that
participate
in
the
establishment
of
the
three-‐dimensional
structure
of
the
yeast

genome
and
the
epigenetic
regulation
of
genome
replication.

This
regulation

through
structure
may
be
analogous
to
epigenetic
mechanisms
of
transcriptional

memory
wherein
gene
looping
or
sub-‐nuclear
localization
is
correlated
with
the

maintenance
of
a
transcriptional
state
or
a
potentiated
state
primed
for
rapid

response
(Misteli,
2007).

Furthermore,
this
organization
may
contribute
to
a

coordination
of
replication
and
transcription,
perhaps
with
consequence
for
genome

stability
(Knott
et
al.,
2009a).

Indeed,
this
study’s
findings
provide
a
new
handle
to

investigate
the
consequences
of
deregulating
replication
timing
on
gene
regulation

or
genome
stability.

The
identification
of
yeast
members
of
the
conserved
Fox

transcription
factor
family
as
physical
mediators
of
chromosomal
architecture
and

epigenetic
regulation
suggest
conservation
of
this
function,
which
may
link

replication
timing
control
and
the
role
of
Fox
proteins
in
metazoan
development.

39

MATERIALS
AND
METHODS

Yeast
strain
and
plasmid
constructions.
W303-‐derived,
BrdU-‐incorporating

strains
CVy43
(Mata
ade2-‐1,
bar1::hisG,
can1-‐100,
his3-‐11,15,
leu2-‐3,112,
trp1-‐1,

ura3-‐1::BrdU-‐Inc::URA3)
or
CVy63
(Mata
ade2-‐1,
bar1::hisG,
can1-‐100,
his3-‐11,15,

leu2-‐3,112,
trp1-‐1,
leu2::BrdU-‐Inc::LEU2)
were
the
WT
parents
for
all
strain

constructions
(Viggiani
and
Aparicio,
2006).

FKH1
and
FKH2
were
deleted
in
CVy43

as
described
(Longtine
et
al.,
1998),
yielding
strains:
ZOy1
(fkh1∆::kanMX6),
CVy138

(fkh2∆::His3MX6),
and
CVy139
(fkh1∆::kanMX6
fkh2∆::His3MX6);
only
differences
in

genotype
from
CVy43
are
indicated.

Plasmid
pfkh2∆C
contains
a
C-‐terminally

truncated
NotI-‐KpnI
fragment
of
FKH2
(truncated
at
the
native
KpnI
site
in
FKH2,

deleting
amino
acids
624-‐862;
this
maintains
the
entire
DNA
binding
domain
and
all

homology
with
Fkh1)
into
pRS424
digested
with
the
same
enzymes;
pfkh2∆C
was

transformed
into
CVy139
yielding
strain
SKy1.

CDC45-‐HA3
(LEU2)
was
introduced

into
strains
CVy43
and
CVy139
+
pfkh2∆C
using
p405-‐CDC45-‐HA/C
as
described

(Aparicio
et
al.,
1997),
yielding
strains
CVy46
and
T2y3,
respectively.

FKH1-‐MYC9

replaced
FKH1
in
CVy138
using
plasmid
pTOPO-‐Fkh1-‐Myc9,
yielding
strain
ZOy22.

pTOPO-‐Fkh1-‐Myc9
was
constructed
using
Phusion
High-‐Fidelity
PCR
kit
(New

England
Biolabs,
M0530)
to
amplify
FKH1-‐MYC9-‐TRP1
from
genomic
DNA
of
strain

Z1448
(Harbison
et
al.,
2004),
and
inserting
it
into
pCR2.1-‐TOPO
vector

(Invitrogen).

40

Strain
ARy23
containing
mutations
of
two
Fkh1/2
binding
sites
at
ARS305
was

constructed
by
pop-‐in/pop-‐out
of
plasmid
p306-‐ARS305-‐∆2BS
into
strain
CVy63

and
confirmed
by
sequencing
of
PCR-‐amplified
genomic
DNA.

Plasmid
p306-‐
ARS305∆2BS
was
constructed
as
follows:
Two
~1kb
fragments
covering
ARS305

with
overlapping
ends
were
amplified
from
genomic
DNA
(using
primers:
5´-‐
gtcaagcttggcaatgtcaagagcagagc
with
5´-‐gtcctcgaggaatacataacaaaaatataaaaacc
for
one

fragment
and
5´-‐tgagaattcaggcatcagtttgatgttgg
with
5´-‐
gtcctcgaggtccctttaattttaggatatgaaaac
for
the
second
fragment),
digested
with
EcoRI

+XhoI
and
with
XhoI
+
HindIII,
respectively,
and
three-‐way
ligated
into
pRS306

digested
with
EcoRI
+
HindIII.

The
XhoI
site
changes
the
first
predicted
Fkh1/2

binding
site
(chr
III
coordinates
39,563-‐39,570)
without
deleting
or
inserting

additional
sequence.

The
resulting
plasmid,
p306-‐ARS305∆1BS
was
sequenced
to

confirm
that
only
the
desired
sequence
changes
were
introduced.

This
plasmid
was

mutagenized
using
QuikChange
Lightning
Multi
Site
mutagenesis
kit
(Agilent#

210515-‐5)
using
primer
(5´-‐
caaagaaaaaaatcttagctttaagaactacaaagtcctcgaggaataataaatcacaccggacagtacatg)
to

change
the
second
predicted
Fkh1/2
binding
site
(chr
III
coordinates
39,483-‐
39,490)
to
an
XhoI
site
without
deleting
or
inserting
additional
sequence.

The

resulting
plasmid
p306-‐ARS305∆2BS
was
sequenced
to
confirm
that
only
the

desired
sequence
changes
were
introduced.

Yeast
methods.
W303-‐derived,
BrdU-‐incorporating
strains
were
used
for
all
strain

constructions
(Viggiani
and
Aparicio,
2006).

Cell
cycle
block-‐and-‐release,
DNA

41

content
analysis,
and
two-‐dimensional
gel
analysis
have
been
described
(Aparicio
et

al.,
2004).

Co-‐IP
was
performed
as
described
(Hu
et
al.,
2008),
except
Dynabeads

Protein
G
(Invitrogen)
was
used.

BrdU-‐labeled
DNA
was
isolated
as
described

(Viggiani
et
al.,
2010);
salmon
sperm
DNA
was
omitted
for
sequencing.

80ng
of

BrdU-‐IPed
DNA
was
prepared
for
single-‐end
sequencing
by
Illumina
ChIP-‐Seq

protocol
or
10ng
of
BrdU-‐IPed
DNA
was
prepared
for
hybridization
to
microarrays

as
described
(Viggiani
et
al.,
2010).

ChIP-‐chip
was
performed
and
analyzed
as

described
(Knott
et
al.,
2009b;
Viggiani
et
al.,
2009).

ChIP-‐Seq
was
performed

identically
except
that
culture
was
scaled-‐up
four-‐fold
to
generate
5-‐10ng
of
IP

material
for
single-‐end
sequencing
by
Illumina
ChIP-‐Seq
protocol.

RNA
was
isolated

from
20mL
cultures
using
RiboPure
Yeast
Kit
(Ambion).

rRNA
was
depleted
with

Ribominus
Beads
(Invitrogen),
and
purified
RNA
was
prepared
for
strand-‐specific

RNA-‐Seq
as
described
in
(Parkhomchuk
et
al.,
2009).

We
used
a
custom
microarray

design
(Nimblegen)
that
tiles
one
~60bp
oligonucleotide
for
every
~80bp
of
unique

genomic
sequence.

For
hybridization
and
washing
we
followed
Nimblegen

protocols,
and
for
image
capture
used
an
Axon
4100A
Scanner.

Antibody
methods.
For
BrdU
and
chromatin
IPs
we
used:
anti-‐BrdU
at
1:1000
(GE

Healthcare,
RPN202),
anti-‐Fkh1
at
1:200
(Casey
et
al.,
2008),
anti-‐ORC
at
1:500

(Wyrick
et
al.,
2001),
anti-‐Mcm2
at
1:50
(Santa
Cruz
Biotech.,
SC-‐6680),
anti-‐Mcm4

at
1:50
(Santa
Cruz
Biotech.,
SC-‐33622),
anti-‐Ha
16B12
at
1:200
(Covance,

MMS101R),
and
anti-‐Rpb3
at
1:500
(Neoclone,
W0012).

We
used
anti-‐Myc
9E10
at

42

1:100
and
1:2000
(Covance,
MMS150P),
and
anti-‐ORC
at
1:100
and
1:1000,
for
co-‐IP

and
immunoblotting,
respectively.

Preprocessing
of
sequence
data.
Sequencing
was
carried
out
with
an
Illumina

GAII.

BrdU-‐IP-‐Seq
and
ChIP-‐Seq
were
analyzed
with
36bp
single-‐end
reads,
while

RNA-‐Seq
was
analyzed
with
36bp
paired-‐end
reads.

Reads
were
aligned
to
S.

cerevisiae
genome
release
r.64
with
PerM
(Chen
et
al.,
2009),
allowing
only
unique

matches
with
a
maximum
of
two
mismatches
per
end.

BrdU-‐IP-‐Seq
and
Rpb3
ChIP-‐
Seq
reads
were
binned
into
non-‐overlapping
50bp
bins;
bin-‐counts
were
median-‐
smoothed
(1000bp
and
500bp
windows,
respectively)
and
quantile-‐normalized

across
all
experiments.

This
smoothing
step
was
repeated.

For
all
other
gene

expression
analysis,
each
RNA-‐Seq
read
was
assigned
to
a
gene
only
when
at
least

one
of
its
paired-‐ends
was
fully
contained
within
the
gene’s
ORF
and
when
the

read’s
orientation
corresponded
to
the
gene’s
orientation.

Reads
whose
paired-‐ends

mapped
to
two
or
more
genes
were
discarded.

Gene
read-‐counts
were
quantile-‐
normalized
prior
to
differential
expression
analysis.

BrdU-‐IP-‐Seq
analysis.
To
identify
an
initial
set
of
peaks
in
each
experiment,
a
set
of

apices
(bins
whose
count
was
higher
than
any
neighboring
bin
within
500bp)
were

detected.

We
assigned
a
magnitude
to
these
peaks
equal
to
the
number
of
reads

mapping
to
within
500bp
of
the
apex;
only
peaks
with
a
magnitude
>10
were

considered
further.

For
each
strain
we
aligned
replicate
apex
chromosomal

locations
using
the
dynamic
programming
algorithm
as
described
(Knott
et
al.,

43

2009),
with
a
gap
penalty
of
1000bp.

Apices
that
did
not
align
across
all
replicates

were
removed
from
consideration.

Next,
for
each
strain
we
aligned
peaks
(387)

with
the
set
of
previously
annotated
origins
listed
in
OriDB
(Nieduszynski
et
al.,

2007);
peaks
(35)
that
did
not
align
to
an
annotated
origin
were
not
considered

further.

Origins
that
were
not
detected
to
incorporate
BrdU
within
a
given
strain
were

assigned
a
count
equal
to
the
number
of
reads
that
mapped
to
within
500bp
of
the

average
of
its
corresponding
detected
apices.

To
test
for
differential
BrdU-‐
incorporation
across
strains,
we
employed
DESeq
(Anders
and
Huber,
2010).

Origin

counts
were
normalized
using
DESeq’s
internal
size
and
variance
normalization

strategies
and
were
called
as
different
between
two
strains
with
a
significance
cutoff

of
FDR<0.005.

BrdU-‐IP-‐chip
time-‐course
data
analysis.
Due
to
the
high
proportion
of
enriched

probes
in
BrdU-‐IP-‐chip
experiments,
within-‐array
normalization
methods
designed

for
ChIP-‐chip
are
not
suitable
(Knott
et
al.,
2009).

To
compensate
for
this,
we

developed
a
procedure
and
tested
it
on
BrdU-‐IP-‐chip
experiments
performed
in
the

presence
of
HU.

This
method
requires
that
un-‐enriched
probes
form
a
dense
cluster

in
the
M=log(IP/Total)
vs.
A=(log(IP)+log(Total))/2
plane
(Knott
et
al.,
2009).

However,
in
BrdU
incorporation
experiments
without
HU
(where
the
percentage
of

enriched
probes
can
reach
80%),
this
requirement
is
sometimes
not
met.

To

account
for
this,
we
developed
a
technique
specifically
for
such
experiments.

This

44

method
requires
a
mock
control,
for
which
we
hybridized
BrdU-‐IP
material
obtained

from
a
12min
BrdU
pulse
using
G1-‐arrested
(non-‐replicating)
cells
against
genomic

DNA.

First,
we
identified
the
best
axes
on
which
to
transform
the
experimental
data

by
applying
our
previous
method
on
the
control
data
(Knott
et
al.,
2009).

After

transforming
the
control
and
experimental
data
onto
these
axes,
the
median

absolute
deviations
of
both
datasets
were
normalized
to
1.

Then,
the
M
values
of
the

experimental
data
were
location-‐normalized
such
that
mean
of
the
lowest
20%
of

probes
were
equal
to
mean
of
the
lowest
20%
of
control
probes.

Subsequently,
we

followed
our
previous
method
(Knott
et
al.,
2009).

Analysis
of
linear
clustering
of
Fkh-‐regulated
origins.
We
performed
Monte

Carlo
simulations
to
determine
the
likelihood
of
the
observed
level
of
clustering

between
like-‐regulated
origins
(e.g.
both
Fkh-‐activated)
along
the
chromosome

occurring
by
chance.

In
each
simulation
we
randomly
assigning
(from
352
total

origins)
95
origins
as
Fkh-‐activated
and
80
as
Fkh-‐repressed
(on
each
simulation)

and
determined
the
number
of
occurrences
where
two
Fkh-‐repressed
or
–activated

origins
neighbored
each
other.
We
then
compared
the
observed
level
of
such

instances
to
the
empirical
distribution
obtained
through
simulations
to
calculate
a

p-‐value.

To
test
whether
Fkh-‐activated
and
–repressed
origins
cluster
in
separate
groups

linearly
along
chromosomes,
we
defined
a
clustering
metric
equal
to
the
number
of

“cuts”
required
to
separate
Fkh-‐repressed
and
Fkh-‐activated
origins
(this
is

45

equivalent
to
the
number
of
instances
where
a
Fkh-‐activated
origin
neighbors
a
Fkh-‐
repressed
origin,
ignoring
non-‐Fkh-‐regulated
origins).

A
low
“cut”
count
indicates

higher
clustering
of
like-‐regulated
origins.

We
obtained
a
“cut”
count
of
65
in
the

experimental
data.

To
test
if
this
was
significantly
low,
we
performed
10
6

simulations
on
the
352
origins
that
were
detected
in
WT
or
fkh1∆
fkh2∆C
cells.

In

each
simulation
we
randomly
assigned
95
origins
as
Fkh-‐activated,
80
as
Fkh-‐
repressed,
and
the
remaining
as
Fkh-‐unregulated.

Fewer
than
1%
of
the

simulations
resulted
in
a
“cut”
count
<65
(Fig.
1.3D).

Analysis
of
Fkh1
and
Fkh2
binding
sites.
To
determine
whether
Fkh1
and
Fkh2

are
differentially
bound
at
Fkh-‐regulated
versus
Fkh-‐unregulated
origins
we
used

the
Position
Weight
Matrices
(PWMs)
defined
in
(Morozov
and
Siggia,
2007))
to

identify
all
putative
Fkh1/2
binding
sites
near
origins
(PWM-‐score
cutoff
=5.5).

We

defined
Fkh1/2-‐bound
origins
as
those
with
a
putative
site
within
500bp
of
its

BrdU-‐peak
apex.

To
determine
the
distribution
of
Fkh1/2
binding
sites
relative
to

ACSs,
for
each
Fkh1/2-‐bound
origin
with
a
defined
ACS,
we
calculated
the
distance

from
the
ACS
to
the
highest
scoring
binding
site
(ACS
locations
from
(Eaton
et
al.,

2010));
we
applied
a
kernel
density
function
to
these
distances
to
define
the

probability
curves.

Analysis
of
Fkh-‐regulated
transcription
versus
Fkh-‐regulated
origin
function.

To
determine
whether
proximal
genes
show
co-‐regulation
with
Fkh-‐regulated

origins,
we
performed
a
permutation
test
on
the
distances
between
Fkh-‐regulated

46

origins
and
the
nearest
Fkh-‐regulated
genes.

Fkh-‐regulated
genes
were
identified
as

those
that
showed
differential
expression
(DESeq
FDR<0.01)
between
WT
and
fkh1∆

fkh2∆C
cells
in
the
same
condition
(unsynchronized
or
G1-‐synchronized).

This

analysis
was
performed
using
both
the
RNA-‐Seq
and
Rpb3-‐ChIP-‐Seq
datasets,

(genes
detected
as
differentially
expressed
in
each
of
the
experiments
are
listed
in

Table
S1).

For
each
experiment
we
calculated
the
distance
from
each
Fkh-‐regulated

origin
to
the
nearest
Fkh-‐regulated
gene’s
promoter.

Next,
10
5

simulated
origins

sets
were
identified
by
randomly
selecting
172
origins,
and
randomly
assigning
95

as
Fkh-‐activated
and
82
as
Fkh-‐repressed.

For
each
of
these
sets,
the
minimum

distances
to
the
nearest
Fkh-‐regulated
genes
were
calculated.

With
this
analysis
we

determined
for
all
possible
pair-‐wise
combinations
(e.g.
up-‐regulated
gene
and
Fkh-‐
activated
origin,
down-‐regulated
gene
and
Fkh-‐activated
origin,
etc.)
that
Fkh-‐
regulated
origins
are
not
significantly
clustered
with
Fkh-‐regulated
genes
along
the

chromosome.

To
test
for
correlation
of
Fkh-‐regulated
origins
with
flanking
gene
expression,
we

performed
regression
analysis
separately
on
Fkh-‐regulated
origins
lying
within

intergenic
regions
flanked
by
diverging,
converging,
and
tandemly
oriented
genes.

For
converging
and
diverging
intergenic
regions,
we
used
two
covariates

representing
the
unsynchronized
and
G1-‐phase
fkh1∆
fkh2∆C-‐WT
RNA-‐Seq
read

count
differences
of
the
closest
transcript
(as
measured
in
bp
between
the
origin’s

ARS-‐consensus
sequence
(ACS)
and
the
gene’s
nearest
end)
and
two
covariates

representing
the
same
difference
measure
in
the
farther
of
the
two
transcripts.

For

47

tandem
intergenic
regions,
two
covariates
represented
unsynchronized
and
G1-‐
phase
fkh1∆
fkh2∆C-‐WT
RNA-‐Seq
read
count
differences
for
the
converging
gene

and
another
two
covariates
represented
the
differences
for
the
diverging
gene.

In

this
analysis
the
only
covariate
that
showed
significant
correlation
with
origin

regulation
was
the
gene
farthest
away
from
origins
within
converging
intergenic

regions
in
unsynchronized
cells
(p<0.05).

A
closer
inspection
revealed
that
this

correlation
was
due
to
four
outlying
data
points,
and
when
these
were
removed,
the

same
analysis
found
no
covariate
to
be
significantly
correlated
with
origin

regulation.

Furthermore,
the
application
of
this
same
analysis
to
read
count

differences
in
the
Rpb3
ChIP-‐Seq
data
showed
no
covariate
to
be
significantly

predictive
of
origin
regulation.

Chromosome
conformation
capture
on
chip
(4C).

Chromatin
isolation:
50mL
of
G1-‐sychronized
cells
were
crosslinked
and
harvested

as
described
for
ChIP-‐chip
(Viggiani
et
al.,
2009).

Cells
were
suspended
in
9.5mL

Buffer
Z
(0.7M
Sorbitol,
50mM
Tris
(pH
7.4),
heat
sterilized)
plus
freshly
added
2-‐
mercaptoethanol
(20mM
final)
and
protease
inhibitor
cocktail
(Roche,
Mini

Complete).

0.5mL
Zymolyase
100T
(ICN,
10
mg/mL
freshly
made
in
Buffer
Z)
was

added
and
the
suspension
was
incubated
at
30°C
with
gentle
agitation,
35
min.

The

suspension
was
split
into
six
2mL
microcentrifuge
tubes
and
centrifuged
at
16,000g,

20
min
at
4°C.

The
supernatants
were
discarded,
each
pellet
was
suspended
in

300µL
NP
buffer
(1M
Sorbitol,
100mM
Tris
(pH
7.4),
50mM
NaCl,
5mM
MgCl2,
1mM

CaCl2,
heat
sterilized)
containing
0.5mM
Spermidine
(freshly
added
from
250mM

48

stock)
by
gently
pipetting
with
a
wide-‐bore
pipet
tip,
and
the
samples
were
pooled

in
a
2mL
microcentrifuge
tube.

Digestion
and
ligation
I:
The
suspension
was
centrifuged
as
above
and
the
pellet
was

suspended
in
500µL
ice-‐cold
1X
NEB
(New
England
Biolabs)
digestion
buffer
II,
and

centrifuged
again.

This
wash
step
with
digestion
buffer
was
repeated
and
the
pellet

was
suspended
in
50µL
1X
NEB
digestion
buffer
II.

42µL
1%
SDS
was
added,
mixed

gently,
incubated
at
60°C,
15
min.

328µL
of
ice-‐cold
1X
NEB
digestion
buffer
II
was

added
and
the
resulting
suspension
was
centrifuged
at
600g,
1
min
at
4°C.

400µL
of

the
supernatant
was
transferred
to
a
fresh
microcentrifuge
tube
(the
remainder
was

discarded),
and
44µL
10%
Triton-‐X100
was
added
and
mixed
gently
by
pipetting

with
a
wide-‐bore
pipet
tip.

This
suspension
was
placed
on
ice
for
15
min,
after

which
58.4µL
of
H2O,
16µL
10X
NEB
digestion
buffer
II,
and
1.6µL
BSA
(NEB,

10mg/mL)
were
added.

4µL
XbaI
(NEB,
100
U/µL)
was
added,
mixed
gently,
and
incubated
at
37°C
for
a

minimum
of
8hr
while
shaking
at
275
rpm.

10µL
H2O,
50µL
10%
SDS,
and
9µL
0.5
M

EDTA
was
added,
mixed,
and
incubated
at
65°C
for
10
min,
followed
by
60°C
for
10

min,
and
on
ice
for
5
min.

The
sample
was
transferred
to
a
15mL
conical
screw-‐cap

tube
on
ice
and
3554µL
H2O,
250µL
10X
T4
DNA
ligase
buffer
(NEB),
50µL
BSA

(10mg/mL),
500µL
10%
Triton-‐X100,
and
125µL
1M
Tris
(pH
7.5)
were
added,

mixed
gently,
and
incubated
on
ice,
15
min.

While
on
ice,
2µL
T4
DNA
ligase
(NEB,

49

400U/µL)
was
added,
mixed
gently,
and
incubated
at
16°C
for
4
hr,
after
which
60µL

0.5
M
EDTA
was
added.

To
the
ligated
sample,
50µL
5M
NaCl
and
5µL
RNAase
A
(20mg/mL)
were
added,

mixed,
and
incubated
at
37°C,
1
hr.

25µL
Proteinase
K
(20mg/mL)
was
added,

mixed,
and
incubated
overnight
at
65°C.

The
sample
was
transferred
to
a
15mL

phase-‐lock
tube
(5-‐Prime,
2302850)
and
the
DNA
was
purified
by
extraction
with

6mL
phenol:chloroform:isoamyl
alcohol
(25:24:1)
and
centrifugation
according
to

the
manufacturer’s
instructions.

To
the
4.2mL
of
aqueous
solution
recovered,

225µL
5M
NaCl
and
6µL
glycoblue
were
added
and
mixed,
and
11mL
of
ice-‐cold

ethanol
was
added,
mixed,
and
incubated
at
-‐20°C,
8
hr.

The
sample
was
aliquoted

into
eight
2mL
microcentrifuge
tubes
and
centrifuged
at
~16,000g,
30
min
at
4°C.

After
discarding
the
supernatant,
each
pellet
was
dissolved
in
50µL
1X
TE
and
the

samples
were
pooled.

30µL
3M
NaOAc
(pH
5.2)
and
825µL
of
ice-‐cold
ethanol
were

added,
mixed,
and
incubated
at
-‐80°C,
2
hr.

The
precipitate
was
recovered
by

centrifugation
at
16,000g,
30
min
at
4°C,
and
after
discarding
the
supernatant,
the

pellet
was
dissolved
in
50µL
TE.

Digestion
and
ligation
II:
To
25µL
(~100ng)
of
the
ligated
sample,
64µL
H2O,
10µL

10X
NEB
digestion
buffer
II,
1µL
BSA
(10mg/mL,
NEB)
were
added
and
mixed,
and

2µL
of
MseI
(10
U/µL,
NEB)
was
added,
mixed,
and
incubated
at
37°C,
2
hr.

1µL
20%

SDS
was
added
and
incubated
at
65°C,
20
min;
30µL
10%
Triton-‐X100
was
added

and
incubated
on
ice
for
15
min.

757µL
H2O,
100µL
T4
DNA
ligase
buffer,
and
10µL

50

BSA
(10mg/mL)
were
added
and
incubated
on
ice
for
15
min.

While
still
on
ice,
2µL

T4
DNA
Ligase
(400U/µL)
was
added,
mixed
by
pipetting
gently,
and
incubated

overnight
at
16°C.
The
sample
was
split
into
two
500µL
aliquots
(in
2mL

microcentrifuge
tubes)
and
25µL
5M
NaCl,
2µL
glycoblue,
and
1.2mL
ice-‐cold

ethanol
was
added
to
each,
mixed
and
incubated
at
-‐20°C,
2
hr.

The
precipitate
was

recovered
by
centrifugation
at
16,000g,
30
min
at
4°C;
the
supernatant
was

discarded
and
each
pellet
was
dissolved
in
25µL
TE
and
pooled.

Amplification
and
microarray
analysis:
5µL
was
amplified
by
standard
PCR
(25

cycles)
with
the
following
primers:
5'CTAAGTGTCCTGTTTCGGAAC,
and

5'CAGGCCGCTCTTATAAAATGA.

1µg
amplified
DNA
was
labeled
with
Cy5
and

hybridized
against
Cy3-‐labeled
reference
DNA
(G1-‐synchronized
total
genomic

DNA)
as
described
for
BrdU-‐IP-‐chip
(Viggiani
et
al.,
2010).

Analysis
was
performed

as
described
in
(Knott
et
al.,
2009)
to
identify
enriched
probes,
and
Xba1
fragments

containing

>3
enriched
probes
immediately
adjacent
to
either
cut
site
were
deemed

to
be
interacting

Analysis
of
global
4C.
226
origins
whose
defined
regions
(as
listed
in
OriDB)
were

fully
contained
within
an
EcoRI
and
a
HindIII
restriction
fragment
were
analyzed.

The
restriction
fragment
interaction
map
from
(Duan
et
al.,
2010)
was
used
to
build

two-‐dimensional
interaction
matrices
for
each
restriction
fragment
set
containing

the
226
origins.

The
matrix
value
(0
to
4)
represents
the
interaction
distance

between
two
origin-‐containing
restriction
fragments
defined
in
(Duan
et
al.,
2010).

51

The
two
matrices
were
summed
and
the
two-‐dimensional
clustering
algorithm

defined
in
(Duan
et
al.,
2010)
was
applied.

17
clusters
containing
fewer
than
ten

origins
each
(45
total)
were
not
analyzed
further.

52

CHAPTER
II

Fkh1/2
Over-‐Expression
alters
genome
wide
origin
timing
in
S.
cerevisiae

Adapted
from:

Peace
et
al.,
in
prep

53

INTRODUCTION

Several
studies
have
derived
a
Fkh
consensus
binding
sequence
and
have

shown
that
Fkh1/2
bind
multiple
sites
throughout
the
S.
cerevisiae
genome

(Harbison
et
al.,
2004;
MacIsaac
et
al.,
2006;
Ostrow
et
al.,
2014;
Simon
et
al.,
2001).

The
most
recent
of
these
studies
has
revealed
many
more
binding
sites
genome

wide
than
previous
estimates
(Ostrow
et
al.,
2014).

This
study
has
further
revealed

that
Fkh
binding
is
enriched
at
multiple
genomic
features
genome
wide
and
appears

to
be
under
cell
cycle
regulation.
Importantly,
Fkh
binding
has
been
shown
to
be

enriched
near
origins
(Knott
et
al.,
2012;
Ostrow
et
al.,
2014)
and
strikingly,
Fkh

binding
near
origins
is
largely
confined
to
either
G1
or
S-‐phase.

Fkh1
has
also
been
implicated
in
establishment
of
long-‐range
DNA

interactions
and
origin
clustering.
Deletion
of
the
RE
locus
(Fkh1
binding
site)
in
a

MATa
strain
resulted
in
the
loss
of
preference
for
the
HMLα
arm
during
matching

type
switching.
(Sun
et
al.,
2002).

Enrichment
of
Fkh
binding
near
origins
and
the

involvement
of
Fkh
proteins
in
establishment
of
long-‐range
DNA
interactions

creates
an
attractive
hypothesis
of
origin
clustering
mediating
by
Fkh1/2.
Strong

evidence
provided
by
4C
experiments
showing
the
abolition
of
interaction
between

several
Fkh-‐activated
origins
in
fkh1∆
fkh2∆
cells

(Chapter
I)
(Knott
et
al.,
2012)

lends
support
to
this
model.

Due
to
the
binding
of
Fkh
proteins
genome
wide,
their
cell-‐cycle
controlled

binding
at
origins
and
their
role
in
long-‐range
DNA
interactions,
we
posited
that

cellular
levels
of
Fkh1/2
may
be
in
some
way
limiting
for
origin
firing.
From
this,
we

54

posited
that
over-‐expression
of
Fkh1
or
Fkh2
would
cause
dramatic
effects
on

replication
timing
genome
wide.
Here
we
test
this
effect
through
use
of
an
inducible

over-‐expression
construct.

RESULTS

The
inducible
Gal1/10
promoter
effectively
over-‐expresses
Fkh1
and
Fkh2

A
previous
study
characterizing
Fkh
over-‐expression
focused
on
the
role
of

Fkh1/2
in
response
to
stress
and
lifespan
regulation
but
limited
their
analysis
to

such
topics
and
did
not
characterize
a
replication
related
phenotype
(Postnikoff
et

al.,
2012).

Interestingly,
this
study
showed
that
constitutive
over-‐expression
of

either
Fkh1
or
Fkh2
was
toxic
to
cell
growth.
In
this
study,
to
investigate
the
effect
of

Fkh1/2
over-‐expression
on
replication,
we
first
attempted
to
over-‐express
either

Fkh1
or
Fkh2
under
its
native
promoter
using
a
high
copy
expression
vector.
The

high
copy
vector
resulted
in
only
a
modest
increase
in
overall
protein
levels
(Fig.

2.1C).
We
next
turned
to
the
inducible
Gal1/10
promoter.

To
test
the
effect
of

chronic
over-‐expression
of
Fkh1
or
Fkh2
on
cell
growth
we
constructed
a
CEN-‐
plasmid
harboring
the
Gal1/10
promoter
upstream
of
either
Fkh1
or
Fkh2
and

plated
cells
to
synthetic
media
lacking
uracil
(to
select
for
plasmid
maintenance)

supplemented
with
either
2%
glucose
or
2%
galactose.
Consistent
with
previously

published
data,
chronic
over-‐expression
of
either
Fkh1
or
Fkh2
lead
to
growth

arrest
(Fig.
2.1A)
(Postnikoff
et
al.,
2012).
Visualization
of
cells
plated
with
chronic

Fkh1
or
Fkh2
over-‐expression
revealed
the
formation
of
microcolonies
that
failed
to

55

Figure
2.1.
Galactose
induction
of
pGal-‐Fkh1/2.
(A)
Growth
of
cells
harboring

Gal-‐Fkh1
or
Fkh2
plasmid
under
repressed
or
chronic
over-‐expression
conditions

on
plates
containing
2%
glucose
or
galactose.
(B)
Workflow
for
G1
arrest
and
release

into
S-‐phase
with
induction
of
Gal1/10
promoter.
(C)
Western
blot
of
Fkh1
protein

levels
under
asynchronous
conditions
(pRS426-‐Fkh1:
high
copy
vector
containing

the
native
Fkh1
promoter
and
gene).
(D)
Western
blot
of
Fkh1
protein
levels

following
galactose
induction
using
the
scheme
in
2.1B
in
WT
cells
harboring
either

empty
vector
or
pGal-‐Fkh1
(Time
in
hours
indicates
the
time
post
galactose

induction).

56

continue
cell
division
after
several
generations.

Similar
growth
inhibition
was
seen

with
decreasing
concentrations
of
galactose
as
well
(0.5%,
0.2%,
0.1%,
0.05%

galactose)
(data
not
shown)
leaving
chronic
over-‐expression
as
an
inviable
option

for
characterizing
a
replication
related
phenotype.
Instead
we
took
advantage
of
the

rapid
induction
of
expression
by
the
Gal1/10
promoter
to
induce
over-‐expression

during
a
G1
block
with
α-‐factor
and
release
into
S-‐phase
(workflow
shown
in
Fig.

2.1B).

As
expected,
immunoblot
of
Fkh1
showed
a
robust
increase
in
protein
level

by
two
hours
post
induction
(switch
to
media
containing
2%
galactose)
(Fig.
2.1D).

This
was
in
agreement
with
dramatic
up-‐regulation
of
Fkh1
and
Fkh2
RNA

transcript
abundance
as
seen
by
RNA-‐seq
(detailed
in
more
depth
below).

Over-‐expression
of
Fkh1
or
Fkh2
alters
replication
timing

Previous
studies
have
shown
that
the
amount
of
BrdU
incorporation
in
early
S-‐
phase
accurately
measures
replication
timing
as
it
inversely
correlates
with

replication
origin
timing
(TRep).
This
corresponds
to
a
large
amount
of
BrdU

incorporation
at
the
earliest
firing
origins
and
less
incorporation
at
those
that
fire

later
in
early
S-‐phase.
(Knott
et
al.,
2009a,
2012).
Additionally,
S-‐phase
release
can

be
blocked
early
on
by
the
addition
of
hydroxyurea
(HU)
allowing
only
the
earliest

origins
to
fire
while
inhibiting
late
or
dormant
origins.
As
a
result,
BrdU
peak
size
is

proportional
to
origin
efficiency
in
HU;
hereafter
referred
to
interchangeably
with

timing.
Early
origins
in
WT
cells
fire
efficiently
and
late
origins
are
blocked.

Mutations
or
conditions
that
disrupt
WT
replication
timing
or
are
defective
in

proper
intra-‐S
checkpoint
signaling
result
in
altered
replication
profiles
in
HU

57

(Aparicio
et
al.,
2004;
Knott
et
al.,
2009a;
Santocanale
and
Diffley,
1998).

To
assess

how
over-‐expression
(OE)
of
Fkh1
and
Fkh2
impacts
replication
timing,
we
blocked

cells
in
α-‐factor,
inducing
over-‐expression
2
hours
before
release
into
S-‐phase
with

media
containing
bromodeoxyuridine
(BrdU)
and
HU
(see
Fig.
2.1B).

Samples
were

subjected
to
BrdU-‐IP
and
sequenced
by
next
generation
sequencing
technology
(see

Materials
and
Methods).
Striking
differences
can
be
seen
in
the
timing
profiles
of

cells
over-‐expressing
Fkh1
(Fkh1
OE)
or
Fkh2
(Fkh2
OE)
relative
to
the
empty

vector
control
(Fig.
2.2A,
B,
S1.1-‐16).
Figure
2.2A
shows
a
minor
reduction
in
HU-‐
efficiency
of
the
early,
robust
firing
ARS305
in
both
Fkh1
OE
and
Fkh2
OE
cells
(Fig.

2.2A
and
overlaid
in
Fig.
S1.1.3).
Conversely,
the
later
firing
origin
ARS310
shows
a

significant
increase
in
HU
efficiency
in
Fkh1
OE
cells
and
a
more
modest
increase
in

Fkh2
OE
cells.
This
alteration
of
timing
is
a
genome
wide
phenomenon
with
many

origins
showing
either
an
advancement
or
delay
in
timing
as
a
result
of
Fkh1
or

Fkh2
over-‐expression.
(Fig.
2.2A,
B
and
S1.1-‐16).

Notably,
Fkh1
OE
cells
exhibited

indistinguishable
bulk
DNA
synthesis
relative
to
WT
cells
when
analyzed
by
FACS

under
OE
inducing
conditions.
Fkh2
OE
cells
did
show
a
minor
S-‐phase
delay
but

this
is
most
likely
due
to
a
delay
of
S-‐phase
entry
caused
by
Fkh2
control
over
Clb2

(Fig.
2.2C);
consistent
with
the
observed
delay
in
budding
of
Fkh2
OE
cells
(83%

budded
versus
98%
budded
in
the
WT
control
at
100
minutes
post
release).
Minimal

difference
was
observed
in
budding
of
Fkh1
OE
cells
versus
the
control
(94%

budded
to
98%
budded,
respectively).

58

Figure
2.2.
Analysis
of
early
S-‐phase
by
BrdU-‐IP-‐Seq.

Plot
colors
are
keyed

above.

(A,
B)
Plots
show
average
BrdU
incorporation
from
duplicate
experiments.

(C)
DNA
content
analysis
through
S-‐phase
by
FACS.

59

Global
analysis
of
Fkh1
and
Fkh2
over-‐expression

To
further
characterize
the
changes
in
replication
timing
as
a
result
of
Fkh1

OE
and
Fkh2
OE
we
began
by
calling
significant
peaks
of
BrdU
incorporation

genome
wide
and
assigning
the
called
peaks
to
known
origins
defined
as
either

likely
or
confirmed
by
the
Saccharomyces
Origin
Database
(OriDB)
(see
materials

and
methods)
(Siow
et
al.,
2012;
Zhang
et
al.,
2008).
The
WT/Fkh1
OE
data
set

called
a
total
of
203
origins
(Fig.
2.3A).
Slightly
more
origins
were
called
under
the

WT/Fkh2
OE
data
set
with
223
(Fig.
2.3B).
To
call
origins
with
a
statistical

difference
in
BrdU
incorporation
between
strains
we
took
the
above
lists
and
ran

DEseq
for
differential
analysis
(Anders
and
Huber,
2010).
Of
the
203
total
origins
in

the
WT/
Fkh1
OE
data
set,
86
origins
showed
a
statistically
significant
increase
in

HU
efficiency
(Fkh1OE-‐activated)
while
83
showed
a
decrease
(Fkh1
OE-‐repressed)

(Fig.
2.3A).

Of
223
total
origins
in
the
WT/Fkh2
OE
data
set,
97
showed
an
increase

in
HU
efficiency
(Fkh2
OE-‐activated)
and
92
were
decreased
(Fkh2
OE-‐repressed)

(Fig.
2.3B).
Thus,
~80%
of
origins
identified
showed
a
change
in
HU
efficiency
(or

timing)
as
a
result
of
either
Fkh1
or
Fkh2
over-‐expression.
BrdU
incorporations
was

next
averaged
and
plotted
in
a
5
kilobase
(kb)
window
around
the
origin
summit
for

each
class
(Fig.
2.3A,B).
As
expected,
Fkh1
OE
and
Fkh2
OE
activated
origins
exhibit

more
average
signal
than
the
corresponding
signal
in
WT
cells.
Similarly,
OE

repressed
origins
exhibit
less
average
signal
than
WT
cells.
Interestingly,
Fkh1
OE-‐
activated
origins
show
a
higher
average
signal
than
Fkh2
OE-‐activated
origins
when

their
respective
classes
are
compared.(Fig.
2.3A,B).

60

Figure
2.3.
Analysis
of
Fkh
over-‐expression
regulated
origins
by
origin
class.

(A,B)
Plots
show
average
BrdU
incorporation
signals
centered
on
origins
in
each

class
(5kb
window)
as
described
in
the
text.
(C)
Venn
diagrams
of
overlap
between

Fkh1
and
Fkh2
OE
classes
as
described
in
the
text.

(D)
Fkh
OE
origin
classes
broken

down
by
Fkh
origin
classes
as
identified
under
WT
expression
levels
(see
text,

Chapter
I).

61

To
address
whether
Fkh1
and
Fkh2
over-‐expression
affects
the
same
origins,

the
classes
identified
above
were
intersected
to
find
common
origins.
60
out
of
the

123
origins
identified
as
activated
in
either
Fkh1
OE
or
Fkh2
OE
were
common
to

both
groups
(Fkh1/2
OE
activated).
Similarly,
75
out
of
100
origins
identified
as

repressed
were
common
to
both
groups
(Fkh1/2
OE
repressed)
(Fig.
2.3C).
The

significant
overlap
between
categories
suggests
a
similar
or
common
mechanism
for

the
regulation
of
origin
timing
by
both
Fkh1
and
Fkh2.

When
Fkh1/2
OE
activated

and
repressed
origins
were
compared
with
Fkh
origin
classes
derived
under
WT

expression
levels
(from
our
previous
study),
an
interesting
relationship
emerged.
52

of
the
60
Fkh1/2
OE
activated
origins
were
identified
in
both
studies.
Of
these,
16

were
repressed,
25
were
unregulated,
and
11
were
activated.

74
of
the
75
Fkh1/2

OE
repressed
origins
were
identified
in
both
studies.
Of
these,
47
were
activated,
3

were
repressed,
and
24
were
unregulated
(Fig.
2.3D).
These
data
indicate
that

unregulated
origins
make
up
a
large
portion
of
the
newly
identified
Fkh1/2
OE

regulated
origins
in
both
classes.

Fkh1/2OE
repressed
origins
were
also

significantly
enriched
for
Fkh
activated
origins;
meaning
that
OE
of
Fkh1
or
Fkh2

actually
has
a
negative
effect
on
origins
whose
timing
is
normally
positively

controlled
under
WT
conditions
by
Fkh1
and
Fkh2.

We
previously
suggested
that

Fkh
repressed
origins
were
not
directly
controlled
by
Fkh
proteins
but
that
their

advancement
in
timing
was
a
result
of
global
timing
deregulation
in
fkh1∆
fkh2∆

cells
and
that
Fkh
activated
origins
were
advanced
in
timing
due
to
direct
binding
of

Fkh1/2
near
affected
origins
(Knott
et
al.,
2012;
Ostrow
et
al.,
2014).
Interestingly,

62

41
out
of
the
52
Fkh1/2
OE
activated
origins
identified
are
found
at
locations
not

regulated
by
Fkh
under
WT
conditions.

Fkh
OE
regulated
origin
classes
have
different
average
replication
times

To
further
characterize
the
differences
between
the
Fkh
OE
regulated
origin

classes,
we
plotted
each
class
along
a
linear
axis
by
each
origin’s
WT
time
of

replication
(Trep)
(Fig.
2.4A).
Origins
initiate
replication
with
a
mean
Trep
of
~25
min

for
both
the
Fkh1
OE
and
Fkh2
OE
data
sets.
As
expected,
due
to
the
high
overlap

with
Fkh
activated
origins,
Fkh
OE
repressed
origins
replicate
with
an
earlier
mean

Trep
of
~22
min
in
both
Fkh1
OE
and
Fkh2
OE
data
sets
(Fig.
2.4B,C).

Conversely,

Fkh
OE
activated
origins
initiate
replication
later
with
a
mean
Trep
of
~27
and
~28

min
for
Fkh1
OE
and
Fkh2
OE
data
sets,
respectively.
Unregulated
origins
for
both

classes
showed
an
intermediate
mean
Trep
of
~26
minutes.
Taken
as
a
whole,
these

data
suggest
that
Fkh
over-‐expression
generally
stimulates
the
firing
of
normally

later
origins
while
repressing
normally
earlier
firing
origins.

Increased
HU-‐Efficiency
of
Fkh
OE
activated
origins
is
not
a
result
of
increased

nucleotide
pools

Recent
work
has
shown
that
the
number
of
origins
fired
within
a

hydroxyurea
(HU)
block
and
the
distance
of
fork
travel
can
be
altered
by
changing

the
level
of
the
available
nucleotide
pool
(Poli
et
al.,
2012).
Mutations
that
increase

nucleotide
levels
or
decreasing
concentrations
of
HU
allow
for
the
firing
of

63

additional
origins.
We
posited
that
the
increase
in
HU
efficiency
of
Fkh
OE
activated

origins
might
be
the
result
of
increased
dNTP
pools
present
in
Fkh
OE
cells
relative

to
the
WT
control
strain.
Bulk
DNA
synthesis
comparing
WT
to
Fkh
OE
cells
in
HU

did
not
yield
an
observable
difference.
However,
the
sensitivity
of
this
assay
should

be
questioned
as
the
total
replication,
under
both
conditions,
yielded
an
increase
in

DNA
content
that
was
barely
observable
above
that
of
the
G1
control
(Fig.
2.5A).

Figure
2.4.
Time
of
Replication
(Trep)
for
Fkh
over-‐expression
origin
classes.

(A)
Origins
are
plotted
along
the
x-‐axis
according
to
their
TRep
and
color-‐coded

according
to
class.
(B,
C)
Boxplots
of
Fkh1
and
Fkh2
OE
origin
class
Trep.

64

Figure
2.5.
Early
S-‐phase
analysis
of
Fkh
over-‐expression
cells
with
increased

nucleotide
pools.
(A,B)
DNA
content
analysis
of
indicated
strains
in
either
G1
or

after
a
60
min
hydroxyurea
(HU)
block.
(C)
Average
BrdU
incorporation
along

chromosome
11
from
BrdU-‐IP_chip
samples
for
indicates
strains.

65

If
nucleotide
pools
are
in
fact
different
between
WT
and
Fkh
OE
cells,
we
posited

that
increasing
dNTP
pools
under
both
conditions
might
negate
the
observed

difference
in
HU
efficiency
at
Fkh
OE
regulated
origins
and
would
allow
for
a

measurable
difference
in
DNA
synthesis
by
FACS.
To
address
this,
we
constitutively

over-‐expressed
ribonucleotide
reductase
3
(RNR3),
which
is
responsible
for
the
rate

limiting
step
in
dNTP
synthesis.
Indeed,
over-‐expression
of
RNR3
dramatically
up-‐
regulated
dNTP
pools
as
evidenced
by
the
substantial
increase
in
bulk
DNA

synthesis
in
cells
harboring
the
empty
vector
control
or
either
a
pGal-‐Fkh1
OE
or

pGal-‐Fkh2
OE
plasmid
under
inducing
conditions
(Fig.
2.5B).

To
address
whether
RNR3
OE
and,
as
a
result,
increased
dNTP
levels
would

negate
the
observable
difference
in
HU
efficiency
at
Fkh1
OE
activated
origins,
cells

over-‐expressing
RNR3
containing
either
the
empty
vector
control
or
pGal-‐Fkh1

were
treated
as
above,
with
galactose
induction,
and
released
into
an
HU
block

containing
BrdU.
BrdU-‐IP-‐chip
(see
materials
and
methods)
was
performed
to

assess
any
differences
in
HU
efficiency.
Consistent
with
our
earlier
results,
Fkh1
OE

conferred
an
increased
HU
efficiency
onto
Fkh1
OE
activated
origins.
(Fig.
2.5C).

These
results
demonstrate
that
the
difference
in
HU
efficiency
at
Fkh1
OE
activated

origins
cannot
be
simply
attributed
to
an
increase
in
nucleotide
levels
due
to
Fkh1

over-‐expression.
These
results
are
consistent
with
the
hypothesis
that
increased
HU

efficiency
at
Fkh
OE
activated
origins
is
at
the
expense
of
Fkh
OE
repressed
origins.

66

Altered
replication
at
Fkh1
and
Fkh2
OE
regulated
origins
is
not
the
result
of
a

change
in
local
transcript
abundance
or
replication
factor
levels

As
Fkh1
and
Fkh2
are
transcription
factors,
it
is
logical
to
assume
that
over-‐
expression
of
either
could
lead
to
changes
in
transcript
abundance
at
many
genes.

Up-‐
or
down-‐regulation
of
target
genes
proximal
to
an
origin
could
result
in
changes

to
the
local
chromatin
environment
and
could
positively
or
negatively
influencing

that
origins
ability
to
fire
as
a
result.

Alternatively,
up-‐
or
down-‐regulation
of
key

replication
factor
components
could
have
an
affect
on
origin
firing.
Our
previous

study
addressed
both
changes
in
replication
factor
abundance
as
well
as
changes
to

local
transcript
abundance
around
Fkh
regulated
origins
in
fkh1∆
fkh2∆
cells
but

failed
to
identify
a
correlation
to
changes
in
origin
activity
with
either
(see
Chapter

I).
To
address
whether
changes
in
replication
timing
due
to
Fkh
over-‐expression
are

a
result
of
changes
in
transcript
levels
(either
locally
or
at
specific
replication
factor

genes),
cells
were
arrested
and
released
into
S-‐phase
as
described
above
with

galactose
induction.
Samples
were
taken
both
at
the
end
of
the
G1
block
and
after
60

min
post
S-‐phase
release
into
HU.
RNA
was
extracted
and
libraries
were
generated

for
high-‐throughput
sequencing
(see
materials
and
methods).
Differential

expression
analysis
was
performed
with
the
Tophat
and
Cufflinks
packages
(see

materials
and
methods).

Importantly,
and
as
expected,
differential
expression

analysis
showed
a
~70
fold
increase
in
Fkh1
and
a
~150
fold
increase
in
Fkh2

mRNA
transcript
abundance
in
Fkh1
OE
and
Fkh2
OE
cells,
respectively.

Consistent

with
their
roles
as
transcription
factors,
Fkh1
OE
yielded
differential
expression
of

67

682
genes
in
G1
and
521
genes
in
S-‐phase
(HU
block)
while
Fkh2
OE
yielded

differential
expression
of
1908
genes
in
G1
and
1676
genes
in
S-‐phase
when

compared
to
the
empty
vector
control
(q-‐value
≤
0.01).

Due
to
the
high
origin

overlap
observed
between
Fkh1
OE
and
Fkh2
OE
activated
and
repressed
origins

and
the
ability
for
Fkh1
and
Fkh2
to
complement
one
another
transcriptionally

(Murakami
et
al.,
2010);
a
mechanism
of
regulation
resulting
from
altered
transcript

abundance
of
one
or
more
genes
might
be
expected
to
be
shared
between
both

conditions.
Accordingly,
we
refined
our
search
for
particular
candidate
genes
by

determining
the
intersection
of
genes
differentially
expressed
in
both
Fkh1
OE
and

Fkh2
OE
conditions.

From
this,
we
obtained
246
genes
up-‐regulated
and
289
genes

down-‐regulated
in
G1
in
both
Fkh1
and
Fkh2
OE
conditions.

In
S-‐phase,
71
genes

were
up-‐regulated
while
256
were
down
regulated.
With
this
refined
list,
a
Gene

Ontology
(GO)
search
was
performed.
Particular
interest
was
placed
on
genes

classified
as
differentially
expressed
(DE)
in
the
GO
classes
of
DNA
Replication
and

DNA
Replication
Initiation
as
up-‐
or
down-‐regulation
of
key
replication
factor(s)

might
explain
the
Fkh1
and
Fkh2
OE
phenotype.

Surprisingly,
few
genes
were
found

to
be
DE
in
either
of
these
GO
categories
(see
Table
2.1)
and
none
of
them,
alone,

provides
an
obvious
mechanism
for
changes
in
replication
timing
(see
discussion).

To
address
local
transcriptional
changes
as
a
possible
mechanism
for
Fkh1
and
Fkh2

OE
regulation
of
replication
timing,
the
log2
fold
change
in
transcript
abundance

between
Fkh1
OE
or
Fkh2
OE
and
the
empty
vector
control
conditions
were
plotted

in
a
4kb
window
around
the
203
(Fkh1
OE)
and
223
(Fkh2
OE)
origins
called
in
the

two
experiments
in
G1;
when
replication
timing
is
thought
to
be
established

68

(Dimitrova
and
Gilbert,
1999;
Raghuraman
et
al.,
1997).

Origins
were
ordered
by

their
maximum
peak
(summit)
change
in
BrdU
incorporation
(Fig.
2.6A,B).

Consistent
with
our
previous
knockout
studies,
a
correlation
was
not
evident

between
changes
in
transcript
abundance
and
changes
in
maximum
BrdU
peak

height
in
either
Fkh1
OE
or
Fkh2
OE
conditions.
A
correlation
was
also
not
evident

when
comparing
Fkh1
or
Fkh2
OE
activated
or
repressed
classes
separately
(data

not
shown).

Table
2.1
Differentially
expressed
genes
of
both
Fkh1
and
Fkh2
OE
conditions

by
gene
ontology
class
(GO
class).

69

Fkh1
binding
is
enriched
at
origins
with
over-‐expression

Previously,
we
have
shown
that
Fkh
binding
is
enriched
at
Fkh
activated
origins
(ie

a
subset
of
origins
that
fire
earlier
on
average
in
WT)
and
that
there
is
a
lack
of

enrichment
at
Fkh
repressed
origins
(Knott
et
al.,
2012;
Ostrow
et
al.,
2014).
Our

hypothesis,
based
on
this
result,
is
that
Fkh
OE
leads
to
Fkh
binding
at
Fkh
OE

activated
origins
that
doesn’t
occur
under
WT
conditions.
To
test
this,
we
preformed

Chromatin
Immunoprecipitation
analyzed
by
tiling
DNA
microarrays
(ChIP-‐chip)
of

Figure
2.6.
Transcriptional
changes
proximal
to
origins
as
a
result
of
Fkh
OE.

(A,
B)
Log2
fold
change
in
gene
expression
plotted
in
a
4kb
window
around
origins

identified
in
this
study.
Origins
are
ordered
by
their
maximum
change
in
peak
height

(summit)
between
WT
and
Fkh1/2
OE.

70

C-‐terminally
Myc
tagged
Fkh1
with
and
without
Fkh1
OE.

An
over-‐expression

plasmid
containing
a
Myc
tagged
Fkh1
under
control
of
the
Gal1/10
promoter
was

constructed
as
for
other
experiments
and
transformed
into
cells
expressing
Fkh1-‐
myc
at
its
endogenous
locus.
Cells
were
arrested
and
released
(with
galactose

induction)
as
described
above
and
samples
were
taken
for
analysis
at
the
end
of
the

G1
block
as
well
as
at
the
end
of
a
S-‐phase
block
(HU).

The
average
ChIP
signal
at
a

250bp
window
around
each
origin
was
taken
for
further
analysis.
All
203
origins

identified
above
were
subjected
to
a
two-‐sided
T-‐test
to
test
for
a
statistical

difference
in
binding
with
and
with
out
OE
of
Fkh1.
Comparison
of
the
amount
of

Fkh1
binding
in
G1
shows
a
strong
statistical
enrichment
of
Fkh1
binding
with
OE

relative
to
WT
(p-‐value
=
1.01x10
-‐05
)
(Fig.
2.7A).
However,
the
difference
in
binding

during
HU
was
not
statistically
significant.
Importantly,
as
previously
published,

binding
of
Fkh1
(in
WT
cells)
is
enriched
at
origins
in
S-‐phase
(HU
block)
relative
to

G1
with
strong
statistical
significance
(Ostrow
et
al.,
2014).

Next,
we
compared

binding
at
Fkh1
OE
activated
and
repressed
origins
(Fig.
2.7B,C).
When
comparing

WT
versus
Fkh1
OE
at
Fkh1
OE
activated
origins,
binding
is
enriched
with
OE
with

significance
(p-‐value
<
0.01).
Binding
is
also
enriched
at
Fkh1
OE
repressed
origins

although
with
less
significance
(p-‐value
<
0.05).

During
S-‐phase,
Fkh1
OE
activated

origins
exhibit
statistically
more
binding
with
OE
than
under
WT
conditions
(p-‐
value
<
0.05).
Fkh1
OE
repressed
origins
however,
do
not
show
a
statistical

difference
in
binding.
An
important
finding
is
that
under
both
WT
and
OE

conditions,
Fkh1
binding
is
higher
in
the
OE
repressed
class
than
in
the
OE
activated

class.
The
Fkh1
OE
repressed
class,
as
described
above,
is
largely
comprised
of
Fkh

71

Figure
2.7.
Enrichment
of
Fkh1
binding
proximal
to
origins
with
OE.
(A,
B,
C)

Average
Fkh1
ChIP
signal
(average
log2
enrichment)
of
the
250
bp
region

surrounding
origins
from
origin
classes
as
described
in
the
text.
Horizontal
lines

represent
population
means.
(D)
Plots
show
average
Fkh1
ChIP
signal
centered
on

origins
in
each
class
(5kb
window)
as
described
in
the
text.

72

activated
origins,
which
are
enriched
for
Fkh
binding.
Conversely,
the
Fkh1
OE

activated
class
is
largely
devoid
of
Fkh1
binding
under
WT
conditions.
To
determine

the
robustness
of
the
statistical
tests
performed
above,
the
statistical
analysis
was

repeated
with
the
nonparametric
Wilcoxon
Rank
Sum
Test
in
place
of
the
two-‐sided

T-‐test.
Nearly
identical
statistical
significance
cutoffs
were
found
within
each
group

(data
not
shown).
Interestingly,
Linear
regression
analysis
of
maximum
BrdU
peak

height
versus
local
Fkh1
binding

(250bp
window)
did
not
show
a
strong

correlation.
This
finding
suggests
that
an
increasing
amount
of
Fkh1
binding
does

not
lead
to
earlier
origin
timing
but
rather
that
a
minimum
threshold
of
binding
is

most
likely.
Lastly,
the
average
ChIP
signal
was
plotted
in
a
5
kb
window

surrounding
each
origin
class
(Fig.
2.7D).
Figure
2.7D
accurately
recapitulates
the

findings
above
(Fig.
2.7A,B,C)
showing
enrichment
of
Fkh1
binding
at
all
origins
in

G1
as
well
as
in
HU
at
Fkh1
OE
activated
origins.

DISCUSSION

Fkh
over-‐expression
alters
origin
timing
genome
wide.

The
above
studies
further
elucidate
the
role
of
Fkh
proteins
as
important

coordinators
of
the
S.
cerevisiae
timing
program.
Over-‐expression
of
either
Fkh1
or

Fkh2
dramatically
alters
the
timing
of
greater
than
80%
of
the
origins
analyzed
in

73

this
study.
Our
previous
study
showed
that
fkh2∆
alone,
had
a
negligible
effect
on

origin
timing
but
enhanced
the
effect
of
fkh1∆
in
the
double
mutant
(Knott
et
al.,

2012).
Rather
surprisingly,
Fkh2
OE
had
a
similar
effect
on
origin
timing
when

compared
to
Fkh1
OE.
Indeed,
when
comparing
activated
and
repressed
classes
of

Fkh1
OE
and
Fkh2
OE
regulated
origins,
~50%
of
activated
origins
were
common

between
both
conditions
while
~75%
of
repressed
origins
were
common
to
both.

This
data
taken
with
the
known
ability
of
Fkh1
and
Fkh2
to
compliment
each
other

transcriptionally
and
binding
of
both
proteins
to
many
of
the
same
sites
genome

wide,
suggests
a
common
mechanism
for
origin
timing
deregulation
under
over-‐
expressed
conditions
(Murakami
et
al.,
2010;
Ostrow
et
al.,
2014).

Changes
in
transcript
abundance
do
not
provide
an
obvious
mechanism
for

origin
timing
deregulation.

Consistent
with
our
previous
knock
out
studies,
local
changes
in
gene

regulation
around
Fkh1
OE
and
Fkh2
OE
regulated
origins
did
not
show
an
obvious

correlation
to
changes
in
origin
timing
in
G1
(Fig.
2.6).

Several
genes
annotated
in

the
gene
ontology
classes
of
DNA
replication
and
DNA
replication
initiation
were

found
to
be
differentially
expressed
in
both
Fkh1
OE
and
Fkh2
OE
conditions
(Table

2.1).
While
none
of
these
genes
provided
an
obvious
mechanism
for
the
changes
in

timing
due
to
OE
of
Fkh1/2
they
still
cannot
be
completely
ruled
out.
One

particularly
interesting
candidate
is
Noc3
(up
regulated
by
Fkh1/2
OE
in
G1).
Noc3

was
shown
to
be
an
important
initiation
factor
and
interacts
with
both
MCM
and

74

ORC
(Zhang
et
al.,
2002).
More
recent
work
from
the
same
group
has
expanded

upon
this
finding
and
identified
the
Rix1
complex
(Ipi1p,
Ipi2p,
and
Ipi3p)
as

another
component
of
replication
initiation.
The
Rix1
complex
member(s)
bind

other
pre-‐RC
components
in
a
cell
cycle
and
ORC,
NOC3
dependent
manner
(Huo
et

al.,
2012).
Interestingly,
further
investigation
of
our
RNA-‐seq
data
revealed
up

regulation
of
two
of
the
three
members
of
this
complex
in
G1
(IPI2
and
IPI3).
While

these
results
are
particularly
intriguing,
it
is
important
to
note
the
role
of
these

genes
in
ribosomal
biogenesis.
DE
analysis
in
this
study
revealed
a
significantly
high

number
of
genes
related
to
ribosomal
function.
At
this
point,
it
is
unclear
whether

the
up
regulation
of
these
genes
has
a
direct
consequence
on
the
observed
changes

in
replication
timing
and
will
require
further
investigation.

Fkh1
binds
locally
to
Fkh
OE
activated
origins
with
over-‐expression.

ChIP-‐chip
of
Fkh1
revealed
a
statistical
enrichment
in
binding
at
origins

genome
wide
(Fig.
2.7A).
Interestingly,
this
enrichment
extended
only
to
Fkh1
OE

activated
origins
in
S-‐phase
(Fig.
2.7B).
Previous
studies
have
implicated
that
origin

timing
is
set
up
during
G1
phase
(Dimitrova
and
Gilbert,
1999;
Raghuraman
et
al.,

1997).
As
a
result,
Fkh1
OE
activated
origins,
which
fire
later,
on
average
under
WT

conditions
(Fig.
2.4),
and
have
lower
Fkh1
binding
levels
(on
average)
than
their

Fkh1
OE
repressed
counterparts
(Fig.
2.7
B,C),
may
now
receive
a
required

threshold
level
of
Fkh1
binding
to
increase
their
HU
efficiency.
This
increased
HU

efficiency
may
be
due
to
the
ability
of
Fkh1
to
recruit
replication
factor(s)
that
these

75

origins,
under
WT
conditions,
would
not
have
preferential
access
to.
Our
previous

work
has
also
implicated
Fkh
proteins
as
important
determinants
of
3-‐dimensional

nuclear
architecture
(Knott
et
al.,
2012).
Fkh
binding
proximal
to
Fkh
OE
activated

origins
may
relocate
them
into
new
nuclear
domains
providing
them
with
access
to

key
replication
factors
under
over-‐expressed
conditions.

A
seemingly
contradictory

result
is
that
Fkh1
repressed
origins
are
largely
comprised
of
Fkh
activated
origins

and
that
ChIP-‐chip
data
from
this
study
shows
higher
levels
of
binding
on
average

than
the
Fkh
OE
activated
group.
An
obvious
explanation
for
this
is
that
Fkh
OE

repressed
origins,
even
with
over-‐expression,
largely
remain
early
and
that

additional
Fkh
binding
provides
no
additional
advantage
as
they
already

preferentially
bind
Fkh.
The
finding
that
bulk
DNA
synthesis
shows
identical

kinetics
with
and
without
Fkh
OE
(Fig.
2.2C)
suggests
that
at
least
one
replication

factor
is
limiting
and
that
the
advancement
of
origin
timing
at
Fkh
OE
activated

origins
is
at
the
expense
of
Fkh
OE
repressed
origins
probably
due
to
a
dilution
of

said
limiting
factor(s)
across
more
origins.
These
findings
further
establish
Fkh1

and
Fkh2
as
important
components
of
the
DNA
replication
timing
program.
Further

studies
will
be
needed
to
elucidate
the
full
mechanism
of
how
Fkh1/2
actively

regulate
origin
timing.

76

MATERIALS
AND
METHODS

Yeast
strains
and
methods.
All
strains
are
W303
derived.
Strains
for
BrdU-‐
Incorporation
experiments
are
related
to
CVy63,
MATa
ade2-‐1,
ura3-‐1,
his3-‐11,15

trp1-‐1,
can1-‐100,
bar1∆::hisG,
LEU2::BrdU-‐Inc

or
CVy61
(TRP1::BrdU-‐Inc).
Strains

include:
JPy88
(CVy63
pCD43),
JPy89
(CVy63
pCD43-‐Fkh1),
JPy90
(CVy63
pCD43-‐
Fkh2),
and
JPy103
(CVy61
LEU2::RNR3)
transformed
with
either
pCD43
or
pCD43-‐
Fkh1
(Viggiani
et
al.,
2010).

Strains
for
Fkh1-‐MYC
ChIP
are
related
to
ZOy14
(MATa,

ade2-‐1,
ura3,
his3-‐11,15,
can1-‐100,
bar1Δ::LEU2,
GAL+,
psi+,
Fkh1-‐Myc(TRP1))
which

was
derived
from
Z1448
(Harbison
et
al.,
2004).
Strains
include
JPy105
(ZOy14

pCD43)
and
JPy106
(ZOy14
pCD43-‐Fkh1-‐Myc).
Plasmids
were
introduced
by

lithium
acetate
transformation
and
selection
on
synthetic
media
lacking
uracil.

For
G1-‐phase
block-‐and-‐release,
cells
were
inoculated
into
pre-‐cultures
containing

synthetic
media
lacking
uracil
(-‐URA)
with
2%
glucose
and
grown
to
mid
log
phase.

Mid
log
phase
pre-‐cultures
were
used
to
inoculate
cultures
overnight
in
YEP

containing
2%
raffinose
at
25°C.
Overnight
cultures
(mid
log
phase)
were
re-‐
suspended
in
fresh
YEP+2%
raffinose
at
O.D.
0.5,
and
incubated
with
7.5
nM
α-‐factor

at
25°C
for
3
hrs.
After
3
hours,
cells
were
spun
down
and
re-‐suspended
in
YEP+2%

galactose
with
7.5
nM
α-‐factor
at
25°C
for
an
additional
2
hrs
to
induce
over-‐
expression
of
Fkh1
or
Fkh2.

Arrested
cultures
were
released
from
α-‐factor
arrest
by

re-‐suspension
in
fresh
YEP+2%
galactose
at
O.D.
1.0
with
200
µg/mL
Pronase
E

(Sigma-‐Aldrich,
P5147)
and
gentle
sonication
to
disperse
cells.
Early
S-‐phase

77

analysis
of
replication
was
performed
by
releasing
cells
into
media
containing
0.2M

HU
(Sigma-‐Aldrich,
H8627)
and
BrdU
at
400
µg/mL
(Sigma-‐Aldrich,
B5002)
for
60

min
at
25°C.

Bulk
DNA
content
analysis
was
performed
with
SYTOX
Green

(Molecular
Probes,
S7020)
as
described
previously
(Zhong
et
al.,
2013).

Analysis
of

Fkh1
by
immunoblotting
was
performed
with
anti-‐Fkh1/2
antibody
(Casey
et
al.,

2008)
at
1:1000.

BrdU-‐IP-‐chip.

Genomic
DNA
was
isolated
from
25mL
BrdU-‐labeled
cultures,
1
µg

total
genomic
DNA
was
immunoprecipitated,
and
half
of
the
immunoprecipitated

DNA
was
subjected
to
whole
genome
amplification
(Sigma-‐Aldrich,
WGA2),
labeling,

and
hybridization
as
previously
described
(Viggiani
et
al.,
2010).

Samples
were

hybridized
to
custom-‐designed
DNA
oligonucleotide
tiling
arrays
(Roche-‐
Nimblegen)
containing
135,000
probes,
with
one
~60mer
probe
for
every
~80
bp
of

unique
genomic
sequence.

Array
data
from
two
experimental
replicates
were

processed
as
previously
described
(Knott
et
al.,
2009b,
2012).

BrdU-‐IP-‐Seq.

Genomic
DNA
was
isolated
from
50mL
BrdU-‐labeled
cultures,
5
µg

total
genomic
DNA
was
immunoprecipitated
as
described
(Knott
et
al.,
2012),
and

the
entire
immunoprecipitate
was
amplified
by
Illumina
protocols
with
inclusion
of

barcodes
and
indexes
to
allow
pooling
of
samples
(Dunham
and
Friesen,
2013).

Sequencing
(50
bp
paired-‐end)
was
carried
out
on
the
Illumina
Hi-‐Seq
platform
by

the
USC
Epigenome
Center.

78

Analysis
of
BrdU-‐IP-‐sequencing
data.

Barcodes
were
split
using
the
barcode

splitter
from
the
FAST-‐X
toolkit
(unknown).
Sequence
libraries
were
aligned
to
S.

cerevisiae
genome
release
r.64
using
Bowtie2
(Langmead
and
Salzberg,
2012).
The

first
10bp
were
trimmed
from
the
5ʹ′
end
to
account
for
the
barcode
and
allow
for

proper
alignment.

Aligned
sequences
were
sorted
and
binned
into
50
bp
non-‐
overlapping
bins
(Li
et
al.,
2009;
Quinlan
and
Hall,
2010),
median-‐smoothed
over
a

1kb
window
and
normalized
to
one
another
by
total
read
count.

Two
experimental

replicates
were
averaged
and
smoothed
again.

BrdU
peaks
were
called
using
MACS

(p
<
0.01)
(Zhang
et
al.,
2008).

Called
peaks
were
then
cross-‐referenced
against

origins
defined
in
OriDB
(Siow
et
al.,
2012)
as
“confirmed”
or
“likely”
to
eliminate

any
peaks
not
aligning
with
an
origin.

Origin
peaks
were
subjected
to
DESeq

analysis
(adjusted
p

<
0.1)
for
calling
of
differential
peak
sizes
(Anders
and
Huber,

2010).

RNA-‐Seq
library
preparation.

1.5
ml
of
culture
was
harvested
from
galactose

induced
culture
at
the
appropriate
time
points
(G1
and
60
min
post
release

(hydroxyurea
block)),
washed
with
TBS,
pelleted,
flash
frozen
in
a
dry
ice/
ethanol

bath,
and
stored
at
-‐80°C.

Total
RNA
was
isolated
using
the
MasterPure
Yeast
RNA

Purification
Kit
(Cat.
#MPY03010).
Poly(A)
transcripts
were
isolated
from
5µg
of

total
RNA
using
the
NEB
Poly(A)
mRNA
magnetic
isolation
kit
(Cat.
#
E7490S).
First

and
second
strand
cDNA
synthesis
were
carried
out
using
the
NEB
Next
FSS
and
SSS

kits
(Cat.
#
E7525S
and
E6111S).
cDNA
was
amplified
by
the
standard
Illumina

protocol
with
inclusion
of
indexes
for
multiplexing.
Sequencing
(50
bp
paired-‐end)

79

was
carried
out
on
an
Illumina
Hi-‐Seq
platform
by
the
FSU
College
of
Medicine

Translational
Science
Laboratory.

Analysis
of
RNA-‐Sequencing
data.
To
align
reads
and
call
differential
expression
of

RNA
transcripts,
reads
from
two
independent
replicates,
per
condition,
were
first

aligned
using
the
Tophat2
sequence
aligner
(Kim
et
al.,
2013)
to
S.
cerevisiae

genome
release
r.64
along
with
a
known
transcript
file
(.gtf
format).
Aligned
reads

were
next
subjected
to
the
Cufflinks
transcript
assembly
and
differential
expression

pipeline
including
Cuffdiff
to
call
differentially
expressed
transcripts
(FDR
≤
0.01)

(Trapnell
et
al.,
2010).
Gene
ontology
analysis
was
performed
with
the
GO
term

finder
and
GO
slim
mapper
available
at
yeastgenome.org

Fkh1-‐Myc
ChIP-‐chip.
ChIP-chip experiments were performed as described previously
with three independent replicates (Ostrow et al., 2014). Briefly, immunoprecipitation was
performed on 50ml of 1% formaldehyde cross-linked cells with anti-Myc 9E10 antibody
(Covance, MMS150) at 1:100 and followed by pull-down with Protein G Dynabeads
(Invitrogen, 10004D). Immunoprecipitated DNA
was
subjected
to
whole
genome

amplification
(Sigma-‐Aldrich,
WGA2),
labeling,
and
hybridization
as
previously

described
(Viggiani
et
al.,
2010).

Samples
were
hybridized
to
custom-‐designed
DNA

oligonucleotide
tiling
arrays
(Roche-‐Nimblegen)
containing
135,000
probes,
with

one
~60mer
probe
for
every
~80
bp
of
unique
genomic
sequence.

80

Analysis
of
Fkh1
ChIP-‐chip
data.

Array
normalization
and
detection
of
enriched

regions
was
performed
using
the
model
based
analysis
of
two
color
arrays
method

(MA2C)
(Song
et
al.,
2007).

The
data
was
next
binned
into
each
probes
closest
50bp

non-‐overlapping
bin(s)
(max
distance
from
bin
<
50bp)
(Quinlan
and
Hall,
2010)

and
median
smoothed
over
a
1kb
window.
Next,
samples
were
quantile-‐normalized

among
each
other
and
triplicate
experimental
replicates
were
averaged
and

smoothed
a
second
time
to
yield
final
comparable
experimental
conditions.

81

CHAPTER
III

Rif1
regulates
initiation
timing
of
late
replication
origins
throughout
the
S.

cerevisiae
genome

Adapted
from:

Peace,
J.M.,
Ter-‐Zakarian,
A.,
and
Aparicio,
O.M.
(2014).
Rif1
Regulates
Initiation

Timing
of
Late
Replication
Origins
throughout
the
S.
cerevisiae
Genome.
PLoS
ONE

9,
e98501.

82

INTRODUCTION

In
S.
cerevisiae,
DNA
sequences
near
the
ends
of
chromosomes,
including
the

telomeres
themselves,
the
adjacent
“subtelomeric”
regions,
and
the
subtelomere-‐
proximal
silent
mating-‐type
loci
exhibit
hallmarks
of
heterochromatin,
including

characteristic
chromatin
modifications,
transcriptional
silencing
and
late
replication

(reviewed
in
Rusche
et
al.,
2003).

Replication
origins
in
these
regions
either
initiate

replication
late
during
S-‐phase,
or
fail
to
initiate
before
being
replicated
passively
by

replication
forks
from
earlier
origins,
(reviewed
in
Aparicio,
2013).

Rif1
(Rap1-‐interacting
factor
1)
has
recently
been
implicated
in
the

regulation
of
replication
origin
timing
in
yeast
and
mammalian
genomes

(Cornacchia
et
al.,
2012;
Hayano
et
al.,
2012;
Lian
et
al.,
2011;
Yamazaki
et
al.,
2012).

Rif1
binds
telomeres
and
subtelomeres
through
direct
interaction
with
the
telomere

sequence
binding
protein
Rap1
in
S.
cerevisiae
or
Taz1
in
S.
pombe
(Hardy
et
al.,

1992;
Kanoh
and
Ishikawa,
2001).
In
mammalian
cells,
however,
Rif1
is
recruited
to

telomeres
and
other
chromosomal
loci
upon
DNA
damage,
where
it
functions
in

signaling
and
repair
of
DNA
damage
(reviewed
in
Kumar
and
Cheok,
2014).

In
the

fission
yeast
S.
pombe,
rif1
+

deletion
advances
the
timing
of
many
late/dormant

origins
in
subtelomeric
as
well
as
internal
chromosomal
loci,
while
also
delaying
or

repressing
the
activation
of
normally
early
origins,
including
pericentric
origins

(Hayano
et
al.,
2012).

The
effects
of
Rif1
deletion
in
mouse
cells
or
depletion
in

human
cells
appear
to
be
similar
to
those
in
fission
yeast,
with
advanced
timing
of

late
domains
together
with
delayed
replication
of
early
domains
resulting
in
an

83

overall
compression
of
the
temporal
replication
program
(Cornacchia
et
al.,
2012;

Yamazaki
et
al.,
2012).

Analysis
of
budding
yeast
rif1∆
cells
showed
advanced

replication
timing
of
subtelomeric
regions,
relative
to
an
internal
early
and
an

internal
late
origin,
suggesting
that
origin
regulation
by
Rif1
in
budding
yeast
might

be
limited
to
subtelomeric
domains
(Lian
et
al.,
2011).

However,
these
data
also

appear
to
indicate
that
the
internal
early
origin
used
as
a
standard
(ARS1)
was

delayed,
and
happens
to
reside
near
a
centromere,
consistent
with
the
possibility

that
early
origin
timing,
particularly
of
pericentric
regions,
is
regulated
by
Rif1
in

budding
yeast
as
in
fission
yeast.

This
might
also
explain
how
pericentric
origins

remain
early-‐firing
in
the
absence
of
transcription
factors
Fkh1
and
Fkh2,
which
are

required
for
early-‐firing
of
most
non-‐pericentric
early
origins
in
budding
yeast

(Knott
et
al.,
2012).

The
mechanism
of
Rif1
function
in
origin
regulation
also
requires
further

elucidation.

Rif1
regulates
telomere
length,
which
has
been
implicated
in
the

control
of
telomere
replication
timing
in
S.
cerevisiae
(reviewed
in
Bianchi
and

Shore,
2007).

Thus,
Rif1’s
effect
on
subtelomeric
replication
timing
has
been

attributed
to
its
function
in
controlling
telomere
length.

However,
this
mechanism

does
not
easily
account
for
effects
of
Rif1
at
internal
chromosomal
loci
as
observed

in
S.
pombe
(Hayano
et
al.,
2012).

In
both
yeasts,
Rif1
binds
internal
chromosomal

loci
independently
of
its
telomere-‐binding
partner
Rap1
or
Taz1,
although
the

significance
of
this
binding
has
not
been
carefully
examined
(Hayano
et
al.,
2012;

Smith
et
al.,
2003).

Rif1
may
perform
a
scaffolding
function
to
organize
or
localize

chromatin
domains.

In
mammalian
cells,
Rif1
fractionates
with
the
insoluble

84

nuclear
scaffold,
and
the
structure
of
Rif1
(in
yeast
and
mammals)
contains
motifs

that
mediated
protein-‐protein
interaction,
consistent
with
a
scaffolding
function

(Cornacchia
et
al.,
2012;
Xu
et
al.,
2010;
Yamazaki
et
al.,
2012).

In
S.
cerevisiae,

palmitoylation
of
Rif1
is
required
for
localization
of
telomeres
to
the
nuclear

periphery,
which
is
typically
associated
with
late
replication
(Park
et
al.,
2011).

Thus,
Rif1’s
function
in
telomere
localization
may
contribute
to
its
role
in
origin

timing,
at
least
in
yeast.

Whether
Rif1
plays
a
similar
function
to
localize
internal

chromosomal
loci
to
the
nuclear
periphery
remains
to
be
determined.

Here,
we
investigate
the
role
of
Rif1
in
regulation
of
replication
origin
timing

in
budding
yeast
by
analyzing
replication
genome-‐wide
in
cells
lacking
Rif1
function.

We
have
also
addressed
the
importance
of
palmitoylation
of
Rif1
in
replication

timing
control
by
analyzing
replication
in
cells
lacking
Pfa4,
which
is
required
for

Rif1
palmitoylation
and
its
localization
to
the
nuclear
periphery
(Park
et
al.,
2011).

RESULTS

Rif1
regulates
origin
firing
independently
of
Pfa4

To
examine
the
role
of
Rif1
in
controlling
replication
timing
of
the
yeast

genome,
we
began
by
analyzing
origin
firing
in
in
the
presence
of
hydroxyurea
(HU),

which
arrests
cells
in
early
S-‐phase
after
early
origin
firing
while
inhibiting
unfired

(late
or
dormant)
origins
through
intra-‐S
checkpoint
signaling
(Santocanale
and

Diffley,
1998).

Thus
in
WT
cells,
early
origins
fire
efficiently
in
HU
while
later

origins
fire
inefficiently,
whereas
conditions
or
mutations
that
alter
replication

85

timing
or
intra-‐S
checkpoint
signaling
result
in
changes
to
the
HU
replication
profile

(Aparicio
et
al.,
2004;
Knott
et
al.,
2009a;
Santocanale
and
Diffley,
1998).

Our

previous
studies
show
that
bromodeoxyuridine
(BrdU)
incorporation
levels
at

origins
in
HU-‐arrested
cells
are
inversely
related
to
those
origins’
replication

timings
(TRep)
in
untreated
cells
(Knott
et
al.,
2009a,
2012).

We
released
G1-‐
synchronized
WT
and
rif1∆
cells
into
S-‐phase
in
the
presence
of
BrdU
and
HU,
and

detected
BrdU
incorporation
into
nascent
DNA
using
BrdU-‐immunoprecipitation

(IP)
analyzed
with
tiling
DNA
microarrays
(BrdU-‐IP-‐chip).

Budding
morphology

and
DNA
content
analyses
show
that
WT
and
rif1∆
cells
entered
S-‐phase
with

indistinguishable
kinetics
and
arrested
DNA
synthesis
with
indistinguishable
DNA

contents
(data
not
shown).

In
WT
cells,
BrdU
was
robustly
detected
at
early
origins,

while
its
incorporation
at
later-‐firing
origins
was
substantially
reduced,
as
expected

(Fig.
3.1).

For
example,
plots
of
data
for
chromosome
VI
show
a
strong
BrdU
signal

at
early
origins
(e.g.:
ARS606,
ARS607)
in
comparison
to
weak
BrdU
signal
at
later

origins
(e.g.:
ARS600.3/4,
ARS603,
and
ARS609).

In
rif1∆
cells,
strong
BrdU
signals,

comparable
to
those
in
WT
cells,
are
observed
at
early
and
late/dormant
origins,

including
subtelomeric
and
internal
origins,
on
chromosome
VI
and
throughout
the

genome
(Fig.
3.1
and
data
not
shown).

Thus,
Rif1
regulates
the
activation
of

late/dormant
origins
in
response
to
HU
throughout
the
budding
yeast
genome.

To
ascertain
whether
the
function
of
Rif1
in
regulating
origin
firing
in
HU

depends
on
the
putative
role
of
Rif1
in
anchoring
DNA
sequences
to
the
nuclear

envelope,
we
analyzed
origin
firing
in
pfa4∆
cells
that
are
defective
in
palmitoylation

of
Rif1,
which
is
required
for
its
localization,
and
that
of
telomeres,
to
the
nuclear

86

periphery,
presumably
through
anchoring
of
palmitoylated
Rif1
to
the
inner
nuclear

membrane
(Park
et
al.,
2011).

G1-‐synchronized
pfa4∆
cells
were
released

synchronously
into
S-‐phase
in
the
presence
of
HU
and
analyzed
using
BrdU-‐IP-‐chip.

Budding
morphology
and
DNA
content
analyses
show
that
pfa4∆
cells
entered
S-‐
phase
with
similar
timing
and
arrested
DNA
synthesis
with
similar
DNA
content
as

WT
cells
(data
not
shown).

In
the
BrdU-‐IP-‐chip
analysis,
cells
lacking
PFA4

exhibited
a
replication
profile
indistinguishable
from
that
of
WT
cells
(Fig.
3.1).

Thus,
palmitoylation
of
Rif1
by
Pfa4
is
not
required
for
Rif1’s
function
in
regulating

replication
origin
firing.

Figure
3.1.
Analysis
of
early
S-‐phase
by
BrdU-‐chip.

Plots
show
BrdU

incorporation
in
HU-‐arrested
cells.

Plot
colors
are
keyed
above.

Boxed
origins
are

labeled
and
discussed
in
the
text.

87

Figure
3.2.
DNA
content
analysis
of
S-‐phase.
DNA
content
analysis
of
cells

released
into
S-‐phase
for
the
temporal
analysis
of
replication
in
Fig.
3.3.

Rif1
regulates
replication
origin
timing

Previous
studies
have
shown
that
earlier
firing
of
late/dormant
origins
can

enable
their
activation
in
HU
in
otherwise
checkpoint-‐proficient
cells
(Aparicio
et
al.,

88

2004).

However,
the
global
firing
in
rif1∆
cells
of
late/dormant
origins
in
HU
is
also

consistent
with
deregulation
of
the
intra-‐S
checkpoint’s
function
in
origin
inhibition.

To
determine
whether
Rif1
regulates
replication
origin
timing
in
the
absence
of

checkpoint
activation
by
HU,
we
analyzed
replication
timing
in
WT
and
rif1∆
cells

progressing
synchronously
through
S-‐phase
using
BrdU-‐IP-‐chip.

G1-‐synchronized

cells
were
released
into
S-‐phase
in
the
presence
of
BrdU
and
cells
were
harvested
at

25
min
and
35
min
after
release
to
examine
temporal
replication
profiles.

Bulk
DNA

content
analysis
shows
that
WT
and
rif1∆
cells
progressed
through
S-‐phase
with

indistinguishable
kinetics
(Fig.
3.2).

At
25
min,
both
WT
and
rif1∆
cells
showed
low

levels
of
BrdU
incorporation
at
representative
very
early
origins
ARS806,
ARS815,

ARS820
consistent
with
cells
of
both
strains
having
entered
S-‐phase
simultaneously

(Fig.
3.3A).

In
WT
cells,
as
expected
at
this
early
S-‐phase
time
point,
BrdU

incorporation
signals
were
low
or
undetectable
at
most
other
origins
on
this

chromosome,
consistent
with
their
later
activation.

However,
rif1∆
cells
showed

substantial
BrdU
incorporation
at
many
additional
origin
loci
at
25
min,
indicating

that
these
loci
initiate
replication
earlier,
relative
to
the
earliest
origins,
than
in
WT

cells
(Fig.
3.3A
and
data
not
shown).

By
35
min,
robust
BrdU
incorporation
was

detected
at
(and
surrounding)
early
and
late
origins
in
both
WT
and
rif1∆
cells,

while
the
convergence
(or
greater
convergence)
at
termination
(TER)
sites
of
some

BrdU-‐labeled
replicons
from
later
origins
reflects
the
earlier
firing
of
these
origins
in

89

Figure
3.3.
Temporal
analysis
of
replication
by
BrdU-‐IP-‐chip.

Plot
colors
are

keyed
above.

(A,
B)
Plots
show
average
BrdU
incorporation
from
duplicate

experiments.

Boxed
origins
and
termination
sites
(TER)
are
labeled
and
discussed

in
the
text.

(C,
D)
Plots
show
average
BrdU
incorporation
signals
centered
on

origins
in
each
TRep
quartile.

90

rif1∆
cells
(Fig.
3.3A).

We
examined
these
data
genome-‐wide
by
dividing
origins

into
replication
timing
quartiles
according
to
their
published
TRep
and
plotting
the

average
BrdU-‐IP
signal,
centered
on
the
ARSs,
for
both
time
points
(Fig.
3.3C).

This

analysis
shows
that
RIF1
deletion
affected
the
level
of
BrdU
incorporation
at
origins

at
25
min
in
the
two
later
timing
quartiles,
while
earlier
origins
were
unaffected.

By

35
min,
incorporation
at
the
later
origins
was
observed
in
WT
cells,
but
still
trailed

the
levels
in
rif1∆
cells.

Levels
at
the
earlier
origins
showed
no
effect
of
RIF1

deletion
at
25
or
35
min.

These
finding
demonstrate
that
Rif1
specifically
regulates

the
activation
timing
of
subtelomeric
and
internal
late
origins
during
normal
S-‐
phase
progression.

Rif1
and
Mec1
regulate
replication
timing
through
distinct
pathways

Mutation
of
intra-‐S
checkpoint
regulator
RAD53
has
been
reported
to

advance
activation
timing
of
a
late
origin
in
untreated
cells,
raising
the
possibility

that
Rif1
regulates
replication
timing
as
a
mediator
of
the
intra-‐S
checkpoint.

To

determine
whether
elimination
of
intra-‐S
checkpoint
signaling
might
explain
the

altered
replication
timing
in
rif1∆
cells,
we
examined
replication
timing
in
mec1-‐100

mutant
cells,
which
are
defective
in
late
origin
regulation
through
the
intra-‐S

checkpoint
(Tercero
et
al.,
2003).

This
analysis
was
conducted
identically
to
and
in

parallel
with
the
WT
and
rif1∆
analyses
presented
in
the
previous
section.

Analysis

of
bulk
DNA
content
shows
that
mec1-‐100
cells
progressed
through
an
unperturbed

S-‐phase
with
similar
overall
kinetics
as
WT
and
rif1∆
cells
(Fig.
3.2).

BrdU

incorporation
analysis
of
mec1-‐100
cells
shows
replication
timing
profiles
similar
to

91

WT
cells,
with
only
the
earliest
origins
showing
clear
BrdU
peaks
at
25
min
and

relative
BrdU
peak
sizes
at
35
min
reflecting
normal
timing
differences
as
well
(Fig.

3.3A,C).

Interestingly,
the
average
signal
at
the
latest
origin
quartile
was
slightly

higher
in
mec1-‐100
than
in
WT
cells,
consistent
with
the
previous
report
of
a
partial

advancement
of
late
origin
timing
in
rad53-‐1
cells
(Shirahige
et
al.,
1998).

Overall,

however,
the
results
indicate
that
the
intra-‐S
checkpoint
plays
a
minor
role
in

maintaining
the
temporal
program
of
replication
origin
firing
in
budding
yeast.

To
address
the
possibility
that
potential
residual
function
of
mec1-‐100

maintains
normal
replication
timing,
we
examined
replication
timing
in
mec1∆
cells.

Viability
of
mec1∆
cells
depends
on
an
alternative
means
of
upregulating

ribonucleotide
reductase
activity,
which
can
be
accomplished
by
deletion
of
SML1,

which
inhibits
ribonucleotide
reductase.

Thus,
we
compared
sml1∆,
sml1∆
rif1∆,

and
sml1∆
mec1∆
cells
in
an
experiment
carried
out
identically
to
the
previous.

The

results
show
qualitatively
similar
results
with
advanced
timing
of
many
later
origins

in
sml1∆
ri1∆
cells,
while
sml1∆
mec1∆
are
similar
to
sml1∆
(Fig.
3.3B,
D).

Compared

with
the
WT
cells
in
the
previous
analysis
(Fig.
3.3A,
C),
deletion
of
SML1
resulted
in

a
lower
BrdU
signal
at
25
min
(Fig.
3.3B,
D),
which
was
likely
due
to
higher

endogenous
pools
of
deoxyribonucleotides
reducing
the
effective,
initial
BrdU

concentration.

The
sml1∆
strains
also
showed
slightly
reduced
synchrony
than
the

SML1
strains,
which
may
also
have
contributed
to
the
slightly
reduced
signals
at
25

min
(Fig.
3.2).

These
results
clearly
allow
us
to
conclude
that
the
function
of
Rif1
in

replication
origin
timing
control
does
not
reflect
a
role
in
intra-‐S
checkpoint

signaling.

92

To
test
the
integrity
of
the
intra-‐S
checkpoint
in
rif1∆
cells,
we
examined
two

indicators
of
a
functional
checkpoint
response:
Rad53
phosphorylation
in
response

to
HU
treatment,
and
slowing
of
bulk
DNA
synthesis
in
the
presence
of
the
DNA

damaging
agent
methyl-‐methansulfonate
(MMS)
(Paulovich
and
Hartwell,
1995;

Sanchez
et
al.,
1996;
Sun
et
al.,
1996).

First
we
analyzed
Rad53
phosphorylation
in

WT
and
rif1∆
cells
released
into
S-‐phase
in
the
presence
of
HU.

Rad53

phosphorylation
retards
its
mobility
in
SDS-‐PAGE,
which
can
be
detected
by

immunoblotting
(Pellicioli
et
al.,
1999).

In
WT
cells,
phosphorylation
of
Rad53
was

apparent
as
a
slower
migrating
form
that
began
to
appear
at
30
min
and
became
the

predominant
form
by
45
min
after
release
(Fig.
3.4A).

In
rif1∆
cells,
the
timing
and

degree
of
phosphorylation
of
Rad53
were
indistinguishable
from
WT
under
these

conditions
(Fig.
3.4A).

Thus,
intra-‐S
checkpoint
signaling
to
activate
Rad53
in

response
to
HU
is
intact
in
rif1∆
cells.

Next,
we
analyzed
replication
slowing
in
response
to
MMS
treatment.

We
released

G1-‐synchronized
WT,
rif1∆,
and
mec1-‐100
cells
into
S-‐phase
in
the
presence
of
MMS

and
analyzed
bulk
DNA
content
by
flow
cytometry.

WT
and
rif1∆
cells
exhibited

slow
progression
of
bulk
DNA
replication,
with
most
cells
requiring
over
2
hrs
to

reach
fully
replicated
(2C)
DNA
content
(Fig.
3.4B).

In
contrast,
mec1-‐100
cells

attained
~2C
DNA
content
by
1
hr,
reflecting
their
intra-‐S
checkpoint
defect

(Paulovich
and
Hartwell,
1995;
Tercero
et
al.,
2003).

These
results
indicate
that

replication
slowing
dependent
on
intra-‐S
checkpoint
signaling
is
functional
in
rif1∆

cells.

Taken
together,
our
results
demonstrate
that
Rif1
regulates
origin
initiation

93

Figure
3.4.
Analysis
of
intra-‐S
checkpoint
response.

(A)
Immunoblot
analysis
of

Rad53
phosphorylation
in
cells
released
into
HU.

(B)
DNA
content
analysis
of
cells

released
into
MMS.

timing
throughout
the
genome,
through
a
mechanism
independent
of
intra-‐S

checkpoint
signaling.

Landscape
of
Rif1
function/Rif1
recruitment

To
gain
a
better
understanding
of
how
Rif1
regulates
replication
timing,
we

wished
to
define
its
target
origins
for
further
examination.

To
facilitate
comparison

of
replication
origin
activities
in
WT
versus
rif1∆
cells,
we
repeated
the
analysis
of

BrdU
incorporation
in
HU-‐arrested
cells,
this
time
using
BrdU-‐IP
analyzed
by

massively
parallel
DNA
sequencing
(BrdU-‐IP-‐Seq),
which
permits
more
reliable

quantification
of
the
immunoprecipitated
material
and
better
genome
coverage,

94

Figure
3.5.
Analysis
of
early
S-‐phase
by
BrdU-‐IP-‐Seq.

Plot
colors
are
keyed

above.

(A)
Plots
show
average
BrdU
incorporation
from
duplicate
experiments.

Origin
classes
are
color-‐coded
below
each
plot.

(B)
Plots
show
average
BrdU

incorporation
signals
centered
on
origins
in
each
TRep
quartile.

(C)
Plots
show

average
BrdU
incorporation
signals
centered
on
origins
in
each
class
as
described
in

the
text.

(D)
Origins
are
plotted
along
the
x-‐axis
according
to
TRep
rank
and
color-‐
coded
according
to
class
and
genomic
location.

95

particularly
of
pseudo-‐repetitive
sequences,
such
as
subtelomeric
regions.

The

resulting
replication
profiles
recapitulate
the
previous
BrdU-‐IP-‐chip
results,

showing
widespread
deregulation
of
normally
HU-‐dormant
origins
throughout

internal
and
subtelomeric
regions
in
rif1∆
cells
(Fig.
3.5A
and
S2.1-‐16).

Genome-‐
wide
analysis
using
MACS
shows
significant
(p<0.01)
BrdU
incorporation
at
241

known
origins
in
HU
in
WT
cells
versus
373
in
rif1∆
cells,
together
accounting
for

392
total
origins.

We
directly
examined
the
relationship
of
Rif1
regulation
to
origin

timing
by
dividing
the
identified
origins
into
TRep
quartiles
and
plotting
the
averaged

BrdU
signal
at
each
group
of
origins,
centered
on
the
origin
sequences
(Fig.
3.5B).

The
results
show
similar
levels
of
BrdU
incorporation
at
origins
in
the
earliest
two

timing
quartiles
in
WT
and
rif1∆
cells,
while
rif1∆
cells
show
markedly
higher
levels

at
origins
in
the
later-‐firing
quartiles.

These
data
confirm
that
Rif1
specifically

regulates
later-‐firing
origins.

We
further
examined
these
data
to
classify
origins
according
to
their
changes

in
signal
between
WT
and
rif1∆
cells.

Analysis
of
392
total
origins
using
DiffBind

(q<0.05)
determined
that
174
(44%)
showed
higher
signals
in
rif1∆
cells,
137
(35%)

showed
no
change,
and
81
(21%)
showed
lower
signals
in
rif1∆
cells;
these
origins

are
termed,
Rif1-‐repressed,
Rif1-‐unregulated,
and
Rif1-‐activated,
respectively
(Fig.

3.5A,C).

Rif1-‐activated
origins
showed
a
relatively
small
change
in
signal

magnitude,
whereas
Rif1-‐repressed
origins
showed
several-‐fold
greater
average

signal
magnitude
in
rif1∆
cells
(Fig.
3.5C).

To
reveal
the
distribution
of
these
origin

classes
in
relation
to
replication
timing,
we
arranged
origins
according
to
their

replication
timings
and
annotated
the
origins
by
class
(Fig.
3.5D).

Consistent
with

96

Rif1
regulating
later-‐firing
origins
genome-‐wide,
the
data
show
that
virtually
all

later-‐firing
origins
are
in
the
Rif1-‐repressed
class.

Interestingly,
Rif1-‐activated
and

Rif1-‐unregulated
origins
are
similarly
distributed
across
the
earlier
half
of
origins.

These
data
also
show
the
greater
relative
effect
of
Rif1
on
later-‐firing
versus
earlier-‐
firing
origins.

To
examine
the
genomic
distribution
of
Rif1-‐regulated
origins
more

precisely,
we
determined
the
numbers
of
origins
in
each
Rif1-‐regulation
class
with

respect
to
major
chromosomal
landmarks
like
centromeres
(CENs)
and
telomeres

(TELs).

Among
392
origins
identified
in
this
study,
41
are
within
20kb
of
CENs.

15

of
these
41
(37%)
are
classified
as
Rif1-‐unregulated,
26
(63%)
are
Rif1-‐activated,

and
zero
(0%)
are
Rif1-‐repressed
(Fig.
3.5D).

Thus,
pericentric
regions
contain
an

over-‐representation
of
Rif1-‐unregulated
and
-‐activated
origins
and
are
devoid
of

Rif1-‐repressed
origins.

Similar
analysis
finds
39
origins
within
20kb
of
TELs,
of

which
six
(15%)
are
Rif1-‐unregulated,
zero
(0%)
are
Rif1-‐activated,
and
33
(85%)

are
Rif1-‐repressed
(Fig.
3.5D).

Thus,
subtelomeric
regions
contain
a
predominance

of
Rif1-‐repressed
origins
and
are
devoid
of
Rif1-‐activated
origins.

Although
the

effect
of
CENs
and
TELs
on
replication
origins
appear
to
be
limited
to
a
distance
of

~20kb
(Knott
et
al.,
2012;
Natsume
et
al.,
2013;
Pohl
et
al.,
2012;
Raghuraman
et
al.,

2001;
Stevenson
and
Gottschling,
1999),
we
wondered
whether
there
might
be
a

distance
effect
along
chromosome
arms
relative
the
centromeres.

To
address
this

question
we
determined
the
average
distance
of
origins
in
each
of
the
Rif1

regulation
classes
after
excluding
pericentric
and
subtelomeric
origins,
which
would

skew
these
results.

Interestingly,
the
results
show
that
on
average,
Rif1-‐repressed

97

origins
(349kb,
n=141)
lie
significantly
(p<0.001,
two-‐sided
t-‐tests)
more
distal

from
CENs
than
Rif1-‐activated
(230kb,
n=55)
and
Rif1-‐unregulated
origins
(212
kb,

n=116).

This
finding
suggests
that
linear
chromosomal
distance
from
CENs
favors

origin
repression
by
Rif1.

We
wished
to
determine
how
chromatin
binding
of
Rif1
relates
to
its
function

in
origin
regulation
throughout
the
genome,
particularly
at
internal
chromosomal

loci.

Rif1
binds
telomeric
and
subtelomeric
chromatin
through
interaction
with
the

DNA
binding
protein
Rap1
(Smith
et
al.,
2003).

However,
Rif1
also
binds
internal

chromosomal
loci,
most
of
which
do
not
appear
to
bind
Rap1,
suggesting
a
novel

mode
of
Rif1
recruitment
to
these
loci(Smith
et
al.,
2003).

We
used
the
available

Rif1
genome-‐wide
binding
data
(ChIP-‐chip)
to
compare
against
the
Rif1-‐regulated

origin
loci
identified
here
(Smith
et
al.,
2003).

We
used
the
top
10%
of
Rif1
binding

sites
(the
least
stringent
cutoff
used
in
the
previous
study),
comprising
543
non-‐
telomeric
binding
loci,
and
tested
for
proximity
(<~1kb)
to
Rif1-‐regulated
origins.

We
excluded
subtelomeric
origins
to
focus
the
analysis
on
the
possibility
of
Rif1

recruitment
to
internal
origin
loci.

The
results
show
35
origins
(n=
353)
proximal
to

Rif1
binding
sites,
which
includes
14
Rif1-‐repressed
(n=141),
12
Rif1-‐unregulated

(n=
131),
and
nine
Rif1-‐activated
(n=
81).

Thus,
there
appears
to
be
no
specific

enrichment
of
Rif1
binding
near
internal
Rif1-‐regulated
origins.

Similar
analysis

with
601
non-‐telomeric
Rap1
binding
sites
shows
20
proximal
origins,
of
which
14

are
Rif1-‐repressed,
one
is
Rif1-‐unregulated,
and
five
are
Rif1-‐activated,
yet
none
of

these
loci
show
Rif1
binding.

98

DISCUSSION

Rif1
is
a
global
regulator
of
late
origins

We
set
out
to
determine
the
genomic
landscape
of
Rif1’s
function
in

regulation
of
replication
origin
timing
in
S.
cerevisiae,
whether
palmitoylation
of

Rif1,
and
by
implication
peripheral
nuclear
localization
of
origins,
is
required
for

this
regulation,
and
whether
Rif1’s
reported
checkpoint
functions
are
involved
in

origin
control.

Our
results
clearly
reveal
that
Rif1
regulates
the
initiation
timing
of

later-‐firing
origins
in
subtelomeric
as
well
as
internal
chromosomal
loci.

The

regulation
of
internal
origins
suggests
that
Rif1
delays
origin
firing
through
a

mechanism
independent
of
telomere
proximity,
although
the
results
are
fully

consistent
with
the
idea
that
telomere
length
can
modulate
the
amount
of
Rif1

binding
and
hence,
the
replication
timing
of
subtelomeric
origins
(Marcand
et
al.,

1997).

The
independence
of
replication
timing
control
from
PFA4
function
is

further
consistent
with
the
telomere-‐independence
of
Rif1’s
mechanism,
and

suggests
strongly
that
Rif1’s
function
in
timing
regulation
does
not
require
Rif1

anchoring
to
the
nuclear
envelope.

Whereas
the
major
effect
of
RIF1
deletion
is
to
advance
timing
of
later-‐firing

origins,
deletion
of
RIF1
also
results
in
slightly
lower
HU
efficiency
of
some
early

origins
(Rif1-‐activated),
suggesting
a
slight
delay
in
their
initiation
timing.

For

example,
the
majority
of
pericentric
origins
fall
into
this
group.

The
much
greater

relative
magnitude
of
change
in
Rif1-‐repressed
origins
than
Rif1-‐activated
origins
as

a
result
of
RIF1
deletion
suggests
that
Rif1
plays
a
direct
role
to
delay
origin

99

activation
while
the
effect
on
early
origins
is
likely
an
indirect
consequence
of
more

origins
competing
in
G1
or
early
S-‐phase
for
limiting
factors.

In
S.
pombe,
deletion
of

rif1
+

strongly
reduced
the
HU
efficiency
of
pericentric
origins,
consistent
with
an

indirect
effect
due
to
titration
of
replication
factors
(Hayano
et
al.,
2012).

The

relatively
minor
effect
on
pericentric
origin
firing
in
S.
cerevisiae
likely
reflects
the

efficiency
of
the
dedicated
mechanism
of
DDK
recruitment
by
the
kinetochore

complex
to
promote
early
CEN
replication
(Natsume
et
al.,
2013),
whereas
S.
pombe

uses
a
different
mechanism
to
recruit
DDK
and
promote
early
firing
of
pericentric

origins
(Hayashi
et
al.,
2009;
Li
et
al.,
2011),
which
is
insufficient
in
the
absence
of

rif1
+
.

Rif1
as
a
checkpoint
regulator

Our
results
show
that
loss
of
Rif1
deregulates
replication
timing
but

maintains
intra-‐S
checkpoint
signaling
to
Rad53
and
inhibits
replication
rate
in

response
to
MMS.

In
contrast,
checkpoint-‐defective
mec1-‐100
and
mec1∆
cells

maintain
replication
timing
similar
to
WT
cells,
while
they
are
defective
in

replication
inhibition
in
response
to
DNA
damage.

These
findings
strongly
suggest

that
Rif1
regulates
origin
timing
independently
of
the
intra-‐S
checkpoint
pathway.

Similar
conclusions
were
drawn
regarding
Rif1
in
S.
pombe
(Hayano
et
al.,
2012).

In

addition,
recent
reports
that
Rif1
regulates
origin
timing
by
recruiting
a

phosphatase
that
opposes
DDK-‐dependent
phosphorylation
of
Mcm4
are
also

consistent
with
our
conclusion
(Davé
et
al.,
2014;
Hiraga
et
al.,
2014;
Mattarocci
et

al.,
2014).

Rif1
has
been
characterized
as
an
anti-‐checkpoint
factor
in
the
DNA

100

damage
response
to
uncapped
telomeres
in
S.
cerevisiae,
which
appears
to
involve

suppression
of
checkpoint
signaling
from
single-‐stranded
DNA
(ssDNA)
(Hirano
et

al.,
2009;
Xue
et
al.,
2011).

It
is
unclear
whether
origin
regulation
by
Rif1
has
any

connection
to
its
role
in
the
uncapped
telomere
response;
however,
it
is
feasible
that

Rif1’s
function
in
temporally
distributing
initiation
events
might
reduce
the
total

amount
of
ssDNA
contributing
to
a
checkpoint-‐signal
threshold.

Consistent
with
a

primordial
role
of
Rif1
in
DNA
damage
sensing
in
yeast,
mammalian
Rif1
has
clearly

evolved
a
critical
function
in
DNA
damage
signaling
and
processing
in
addition
to
its

role
in
replication
timing
control
(Zimmermann
and
de
Lange,
2014).

How
does
Rif1
act
at
internal
chromosomal
loci?

An
important
question
that
remains
is
whether
and
how
Rif1
is
recruited

independently
of
Rap1
or
Taz1
to
chromatin
to
regulate
internal
origin
firing.

In
S.

pombe,
origins
delayed
by
Rif1
are
found
more
proximal
to
Rif1
binding
sites
than

other
origins
suggesting
a
direct,
or
at
least
localized,
effect
(Hayano
et
al.,
2012).

We
did
not
detect
a
similar
relationship
in
budding
yeast;
however,
this
may
reflect

limitations
of
the
data
due
to
experimental
differences.

The
available
budding
yeast

Rif1
ChIP-‐chip
data
are
from
unsynchronized
cells,
whereas
the
S.
pombe
data
show

peak
binding
of
Rif1
to
internal
chromosomal
loci
in
cells
at
G1/S
(Hayano
et
al.,

2012).

Rif1
has
also
been
suggested
to
act
in
higher-‐level
chromosome

organization,
potentially
drawing
distal
DNA
sequences
together
(Cornacchia
et
al.,

2012;
Hayano
et
al.,
2012;
Yamazaki
et
al.,
2012).

Thus,
the
role
of
Rif1
in
origin

regulation
may
not
require
direct
binding
to
an
origin
in
cis
to
regulate
its
function.

101

Future
studies
should
examine
the
cell
cycle
binding
of
Rif1
throughout
the
genome,

as
well
as
its
role
in
three-‐dimensional
genome
organization.

MATERIALS
AND
METHODS

Yeast
strains
and
methods.

All
strains
are
related
to
CVy63,
which
is
W303-‐
derived,
MATa
ade2-‐1
ura3-‐1
his3-‐11,15
trp1-‐1
can1-‐100
bar1∆::hisG
LEU2::BrdU-‐Inc

(Viggiani
et
al.,
2010).

TRy1
(rif1∆)
and
TRy3
(pfa4∆)
were
constructed
by
deletion

of
RIF1
and
PFA4,
respectively,
in
CVy63
by
long
oligonucleotide-‐based
replacement

and
selection
for
KanMx.

YZy52
(mec1-‐100)
is
congenic
with
the
above
strains
and

has
been
described
previously
(Zhong
et
al.,
2013).

OAy1050
(sml1∆
rif1∆)
is
a

haploid
segregant
derived
from
a
cross
of
TRy1
and
SSy164
(Matα
sml1∆::HIS3),
and

OAy1056
(sml1∆)
and
OAy1059
(sml1∆
mec1∆)
are
haploid
segregants
derived
from

a
cross
of
DGy159
(Gibson
et
al.,
2004)
and
CVy70
(Matα
URA3::BrdU-‐Inc),

respectively.

For
G1-‐phase
block-‐and-‐release,
log-‐phase
cell
cultures
were

resuspended
in
fresh
YEPD
at
O.D.
0.5,
and
incubated
with
7.5
nM
α-‐factor
at
23°C

for
4
hrs.

Arrested
cultures
were
released
from
α-‐factor
arrest
by
resuspension
in

fresh
YEPD
at
O.D.
1.0
with
200
µg/mL
Pronase
E
(Sigma-‐Aldrich,
P5147)
and
gentle

sonication
to
disperse
cells.

BrdU
(Sigma-‐Aldrich,
B5002)
was
used
at
400
µg/mL.

For
early
S-‐phase
analysis
of
replication,
cells
were
released
into
the
presence
of

0.2M
HU
(Sigma-‐Aldrich,
H8627)
45
min
at
23°C.

MMS
(Sigma-‐Aldrich,
129925)

was
added
to
0.033%
to
cells
released
from
α-‐factor
arrest
at
30°C.

DNA
content

analysis
was
perfomed
with
SYTOX
Green
(Molecular
Probes,
S7020)
as
described

previously
(Zhong
et
al.,
2013).

Analysis
of
Rad53
by
immunoblotting
was

102

performed
with
anti-‐Rad53
antibody
(SC6749;
Santa
Cruz
Biotech.)
at
1:1000
using

previously
described
conditions
(Gibson
et
al.,
2004).

BrdU-‐IP-‐chip.

Genomic
DNA
was
isolated
from
25mL
BrdU-‐labeled
cultures,
1
µg

total
genomic
DNA
was
immunoprecipitated,
and
half
of
the
immunoprecipitated

DNA
was
subjected
to
whole
genome
amplification
(Sigma-‐Aldrich,
WGA2),
labeling,

and
hybridization
as
previously
described
(Viggiani
et
al.,
2010).

Samples
were

hybridized
to
custom-‐designed
DNA
oligonucleotide
tiling
arrays
(Roche-‐
Nimblegen)
containing
135,000
probes,
with
one
~60mer
probe
for
every
~80
bp
of

unique
genomic
sequence.

Array
data
from
two
experimental
replicates
were

processed
as
previously
described
(Knott
et
al.,
2009b,
2012).

A
final
.txt
file

containing
averaged
data
from
the
two
experimental
replicates
was
used
for

generating
plots
and
TRep
quartile
analysis.

BrdU-‐IP-‐Seq.

Genomic
DNA
was
isolated
from
50mL
BrdU-‐labeled
cultures,
5
µg

total
genomic
DNA
was
immunoprecipitated
as
described
(Knott
et
al.,
2012),
and

the
entire
immunoprecipitate
was
amplified
by
Illumina
protocols
with
inclusion
of

barcodes
and
indexes
to
allow
pooling
of
samples
(Dunham
and
Friesen,
2013).

Sequencing
(50
bp
paired-‐end)
was
carried
out
on
the
Illumina
Hi-‐Seq
platform
by

the
USC
Epigenome
Center.

Analysis
of
sequencing
data.

Barcodes
were
split
using
the
barcode
splitter
from

the
FAST-‐X
toolkit
(unknown).
Sequence
libraries
were
aligned
to
S.
cerevisiae

103

genome
release
r.64
using
Bowtie2
(Langmead
and
Salzberg,
2012).
The
first
10bp

were
trimmed
from
the
5ʹ′
end
to
account
for
the
barcode
and
allow
for
proper

alignment.

Aligned
sequences
were
sorted
and
binned
into
50
bp
non-‐overlapping

bins
(Li
et
al.,
2009;
Quinlan
and
Hall,
2010),
median-‐smoothed
over
a
1kb
window

and
quantile-‐normalized
between
replicates.

Two
experimental
replicates
were

averaged
and
smoothed
again.

BrdU
peaks
were
called
using
MACS
(p
<
0.01)

(Zhang
et
al.,
2008).

Called
peaks
were
then
cross-‐referenced
against
origins

defined
in
OriDB
(Siow
et
al.,
2012)
as
“confirmed”
or
“likely”
to
eliminate
any
peaks

not
aligning
with
an
origin.

Origin
peaks
were
subjected
to
DiffBind
analysis
(FDR
<

0.05)
for
calling
of
differential
peak
sizes
(Stark
and
Brown,
2013).

A
final
.txt
file

containing
averaged
data
from
the
two
experimental
replicates
was
used
for

generating
plots
and
for
further
analysis.

Analysis
of
origins
in
relation
to
genomic
features
and
other
datasets.

Origin

Trep
was
taken
from
OriDB;
Trep
data
for
the
392
origins
called
in
this
study
were

divided
into
four
quartiles
based
on
their
Trep
rank,
and
the
average
signal
from
the

.bed
file
was
aligned
on
the
midpoint
of
the
origin
(ARS)
sequence
as
defined
in

OriDB.

Data
were
plotted
for
a
40kb
(Fig.
3.3C,D)
or
5kb
(Fig.
3.5B)
window
around

the
origins
for
each
quartile.

For
analysis
of
intersection
of
origins
with
other

features,
a
1kb
window
was
centered
on
the
midpoint
of
the
origin
sequences
as

defined
in
OriDB.

For
analysis
of
overlap
with
origins,
Rif1
binding
sites
were

assigned
coordinates
corresponding
to
the
feature
they
were
associated
with
in
the

published
dataset
(Smith
et
al.,
2003),
as
follows:
for
ORFs,
the
whole
ORF

104

coordinates
were
used;
for
intergenics,
1kb
of
the
intergenic
sequence
nearest
to
the

gene
for
which
the
intergenic
is
named
was
used.

Any
overlap
(≥1bp)
between

these
defined
windows
was
determined
using
Bedtools
intersect
(Quinlan
and
Hall,

2010).

The
average
distance
from
CENs
of
all
non-‐telomeric
and
non-‐pericentric

origins
was
determined
by
using
Bedtools
closest
function
(Quinlan
and
Hall,
2010).

105

Chapter
IV

The
level
of
origin
firing
inversely
affects
the
rate
of
replication
fork

progression

Adapted
from:

Zhong,
Y.,
Nellimoottil,
T.,
Peace,
J.M.,
Knott,
S.R.V.,
Villwock,
S.K.,
Yee,
J.M.,
Jancuska,

J.M.,
Rege,
S.,
Tecklenburg,
M.,
Sclafani,
R.A.,
et
al.
(2013).
The
level
of
origin
firing

inversely
affects
the
rate
of
replication
fork
progression.
J.
Cell
Biol.
201,
373–383.

My
primary
contributions
to
this
project
included
cumulative
BrdU
time

course
experiments
in
cdc7-‐as3
cells
(Fig.
4.2),
strain
construction,
and
additional

experiments
for
peer
reviews.
Additionally,
I
contributed
to
discussion
and
analysis

of
data.

106

Introduction

The
replication
of
eukaryotic
chromosomes
requires
the
cell
cycle-‐regulated

initiation
of
numerous
replication
origins
on
each
chromosome.

Coordinating
much

of
this
process
are
two
highly
conserved
kinases,
S-‐phase
Cdk
and
Dbf4-‐dependent

kinase
(DDK),
which
become
active
at
the
G1-‐S
transition
(reviewed
in
(Labib,

2010)).

During
early
G1-‐phase,
prior
to
S-‐phase
Cdk
and
DDK
activation,
ORC,
Cdc6,

and
Cdt1
load
MCM
helicase
complexes,
in
an
inactive
state,
onto
DNA
at
potential

origin
loci.

A
key
step
in
replication
initiation
is
the
conversion
of
MCM
into
the

active
helicase,
resulting
in
DNA
unwinding,
replisome
assembly
and
DNA
synthesis.

DDK
plays
an
essential
role
in
MCM
activation
by
phosphorylating
MCM,
particularly

the
Mcm4
(and
Mcm6)
subunit.

In
fact,
this
is
the
only
essential
function
of
DDK
in

yeast,
as
mutations
in
MCM
subunits
that
mimic
the
DDK-‐phosphorylated
state
or

cause
conformational
changes
that
activate
the
helicase,
obviate
the
normal

requirement
for
DDK
function
for
DNA
replication
and
cell
viability
(Fletcher
et
al.,

2003;
Hardy
et
al.,
1997;
Sheu
and
Stillman,
2010).

As
the
name
implies,
DDK
is
composed
of
a
catalytic
kinase
subunit,
Cdc7,

whose
activity
depends
on
Dbf4
(reviewed
in
(Masai
and
Arai,
2002)).

Dbf4
binds

Cdc7,
activating
the
kinase
and
targeting
it
to
specific
substrates,
such
as
Mcm4.

Dbf4
also
negatively
regulates
DDK
function
as
a
target
of
the
intra-‐S
checkpoint

pathway
in
response
to
replication
stress
or
DNA
damage
(reviewed
in
(Duncker

and
Brown,
2003)).

Activated
checkpoint
kinase
Rad53
phosphorylates
Dbf4,

inhibiting
DDK-‐dependent
activation
of
unfired
origins
(Lopez-‐Mosqueda
et
al.,

107

2010;
Zegerman
and
Diffley,
2010).

There
are
conflicting
reports
as
to
whether
this

regulation
directly
inhibits
DDK
activity
or
affects
its
targeting
to
substrate,
or
both

(Oshiro
et
al.,
1999;
Sheu
and
Stillman,
2006;
Weinreich
and
Stillman,
1999).

Rad53

activity
also
regulates
the
rate
of
replication
fork
progression
through
damaged

DNA,
suggesting
that
Rad53
might
modulate
replication
fork
progression
by

regulating
DDK
activity
(Szyjka
et
al.,
2008).

In
this
study,
we
have
examined

replication
fork
dynamics
in
cells
depleted
of
Cdc7
function
and
find
that
replication

forks
progress
more
rapidly
than
in
wild-‐type
(WT)
cells.

Together
with
analysis
of

Orc1-‐
and
checkpoint-‐defective
cells
we
show
that
replication
fork
rate
is
sensitive

to
the
level
of
origin
firing.

Results
and
Discussion

Cdc7
activity
regulates
replication
fork
progression

To
address
the
potential
function
of
DDK
at
replication
forks,
we
analyzed
the
rate

of
DNA
synthesis
across
two
long
replicons
using
BrdU
immunoprecipitation

analyzed
by
microarray
(BrdU-‐IP-‐chip)
in
cells
depleted
of
Cdc7
function.
To
deplete

Cdc7
function,
we
used
two
well-‐characterized
alleles:
cdc7-‐as3
(L120A,
V181A),
the

catalytic
activity
of
which
is
directly
inhibited
by
binding
of
ATP
analog
PP1
within

the
ATP
binding
site
(Wan
et
al.,
2006),
and
cdc7-‐1,
a
temperature-‐sensitive
kinase

hypomorph,
in
the
presence
of
the
bob1
allele
of
MCM5,
which
enables
reduced
but

sufficient
origin
firing
for
viability
in
the
absence
of
Cdc7
kinase
function
(Hardy
et

108

al.,
1997;
Hoang
et
al.,
2007).
WT
and
cdc7-‐as3
cells
were
synchronized
in
late
G1-‐
phase
with
α-‐factor
and
treated
with
PP1
25
min
before
release
into
S-‐phase;
upon

release
into
S-‐phase,
aliquots
of
each
culture
were
pulse-‐labeled
with
BrdU
for

discrete
intervals
(Fig.
4.1A).

Analysis
of
bulk
DNA
content
by
fluorescence-‐
activated
cell
scanning
(FACScan)
showed
rapid
progression
of
WT
cells
through
S-‐
phase,
unaffected
by
the
presence
of
PP1,
whereas
cdc7-‐as3
cells
were
delayed
in

bulk
DNA
synthesis,
in
a
PP1-‐dependent
manner
(Fig.
4.1B).

Analysis
of
BrdU

incorporation
showed
depletion
of
origin
firing
in
PP1-‐treated
cdc7-‐as3
cells,
both
in

the
number
of
origins
that
fired
genome-‐wide
and
in
their
levels
of
BrdU

incorporation
(see
Methods).

We
estimated
that
234
origins
fired
in
WT
cells
and

157
in
cdc7-‐as3
cells;
these
represent
mainly
earlier-‐firing
origins
as
determination

of
later
origins
was
precluded
by
possible
BrdU
signal
from
converging
replication

forks.

In
addition
to
fewer
origins
detected
to
fire,
the
level
of
BrdU
incorporation

was
lower
at
these
origins
in
cdc7-‐as3
cells,
consistent
with
less
efficient
activation

(Fig.
4.1C).

Arrangement
of
the
origins’
BrdU
incorporation
levels
according
to
their

replication
timing
(see
Methods)
showed
that
later
origins
were
more
diminished

than
earlier
origins
in
cdc7-‐as3
cells
(Fig.
4.1C).
This
pattern
of
origin
firing
was

observed
along
the
chromosome
III
and
VI
regions
that
we
analyzed
in
detail.

In

PP1-‐treated
WT
and
cdc7-‐as3
cells,
BrdU-‐IP-‐chip
at
10-‐30
min
showed
similar
levels

of
DNA
synthesis
occurring
at
the
early
origins,
ARS306
and
ARS607
(Fig.
4.1D).

109

Figure
4.1.

Cdc7
function
regulates
replication
fork
progression.

A.
WT
and

cdc7-‐as3
cells
were
synchronized
with
α-‐factor
for
3
hours
35
min,
treated
with
PP1

for
25
min,
and
released
from
α-‐factor
with
PP1
and
with
or
without
0.033%
MMS.

B.
DNA
content
analysis
by
FACScan.

Analysis
of
PP1-‐untreated
cells
is
also
shown.

C.
Heat
maps
of
BrdU
incorporation
levels
at
origins
are
arranged
according
to
each

origin’s
published
replication
timing
from
early
to
late
(left
to
right).

D.
Aliquots

were
pulsed
with
BrdU
for
the
indicated
intervals
and
analyzed
by
BrdU-‐IP-‐chip.

Results
for
segments
of
chromosomes
III
and
VI
are
plotted,
with
origin
locations

indicated
above.

Data
shown
are
from
a
single
representative
experiment
out
of
two

replicates,
except
data
in
(C)
were
calculated
from
both
replicates.

110

Figure
4.2.
Cdc7
function
regulates
replication
fork
progression
(part
2).

A.

Experimental
scheme:
WT
and
cdc7-‐as3
cells
were
synchronized
in
G1-‐phase
with

α-‐factor
for
4
hours,
treated
with
PP1
25
min
before
release,
and
released
from
α-‐
factor
into
the
presence
of
PP1
and
400
µg/mL
BrdU.

B.
Aliquots
of
the
cultures

were
harvested
for
analysis
by
BrdU-‐IP-‐chip
at
the
indicated
times.

C.
Experimental

scheme:
cdc7-‐as3
cells
were
synchronized
in
G1-‐phase
with
α-‐factor
for
4
hours,

treated
or
not
with
PP1
25
min
before
release,
and
released
from
α-‐factor
into
the

presence
or
absence
of
PP1
and
presence
of
0.033%
MMS.

D.
Samples
were

withdrawn
at
the
indicated
times
for
DNA
content
analysis
by
FACScan.

E.
Aliquots

of
the
cultures
were
pulsed
with
BrdU
for
the
indicated
intervals
and
harvested
for

analysis
by
BrdU-‐IP-‐chip.

Data
shown
are
from
a
single
representative
experiment

out
of
two
replicates,
except
the
-‐PP1
sample
in
(E),
which
was
done
once.

111

However
at
10-‐30
and
25-‐45
min,
BrdU
incorporation
at
slightly
later
origins,

ARS603.5
and
ARS605,
was
diminished
in
cdc7-‐as3
cells,
consistent
with
depletion

of
Cdc7
function.

The
activity
of
the
earliest
origins
may
reflect
residual
activity
of

Cdc7-‐as3
resistant
to
PP1
(perhaps
bound
to
ATP)
or
instead
may
reflect
the

execution
of
Cdc7
function
at
these
origins
prior
to
Cdc7-‐depletion
in
late
G1.

We

exploited
this
early
origin
firing
to
examine
the
consequences
of
Cdc7
inactivation

on
fork
progression.

During
the
25-‐45
and
40-‐60
min
intervals,
the
extent
of
BrdU

incorporation
along
the
ARS306
and
ARS607
replicons
was
greater
in
cdc7-‐as3
than

WT
cells,
suggesting
a
faster
rate
of
replication
fork
progression
in
Cdc7-‐depleted

cells.

The
distal
BrdU
incorporation
apparent
in
WT
cells
during
the
55-‐75
min

pulse
likely
reflects
subtelomeric
origin
activity.

We
also
compared
fork

progression
in
WT
and
cdc7-‐as3
cells
by
analyzing
the
cumulative
incorporation
of

BrdU
over
time
(Fig.
4.2B).

This
method
yielded
similar
results
as
the
pulse-‐labeling

approach,
showing
more
rapid
progression
of
replication
forks
through
the
ARS306

and
ARS607
replicons
in
cdc7-‐as3
than
in
WT
cells.

Together,
these
results
indicate

that
Cdc7
is
dispensable
for
replication
fork
progression,
and
suggest
that
Cdc7

regulates
the
rate
of
replication
fork
progression
along
an
undamaged
DNA

template.

Next,
we
analyzed
whether
Cdc7
function
regulates
the
progression
of

replication
forks
traversing
a
damaged
DNA
template.

G1-‐synchronized
WT
and

cdc7-‐as3
cells
were
treated
with
PP1
and
released
into
S-‐phase
in
the
presence
of

the
DNA
alkylating
agent
methyl-‐methane-‐sulfonate
(MMS);
aliquots
of
each
culture

were
pulsed
with
BrdU
at
defined
intervals
(Fig.
4.1A).

FACScan
analysis
showed

112

slower
progression
of
WT
and
cdc7-‐as3
cells
through
S-‐phase
as
expected
due
to
the

presence
of
MMS,
with
somewhat
slower
bulk
DNA
replication
in
the
cdc7-‐as3
cells,

consistent
with
their
reduced
efficacy
of
origin
firing
(Fig.
4.1B).

We
estimated
that

219
origins
fired
in
WT
and
134
in
cdc7-‐as3
cells
treated
with
MMS,
and
the

efficiency
of
origin
firing
based
on
the
level
of
BrdU
incorporation
was
lower
at
most

origins
in
cdc7-‐as3
cells
(Fig.
4.1C).

The
number
of
origins
detected
in
MMS-‐treated

versus
-‐untreated
cells
was
only
modestly
decreased
because
the
measurement
in

cells
without
MMS
did
not
effectively
detect
later-‐firing
origins.
However,

comparison
of
WT
and
checkpoint-‐defective
(mec1-‐100)
cells
indicates
that
>90

origins
are
detected
as
checkpoint-‐inhibited
by
MMS
treatment
by
our
analysis
(see

below).

In
WT
and
cdc7-‐as3
cells,
BrdU-‐incorporation
was
similar
for
ARS306
and

ARS607
at
10-‐30
min,
while
BrdU
incorporation
at
the
slightly
later
ARS603.5
and

ARS605
was
reduced
in
cdc7-‐as3
cells
(Fig.
4.1D).

As
in
the
absence
of
MMS,
the
rate

of
BrdU
incorporation
along
the
ARS306
and
ARS607
replicons
was
greater
in
cdc7-‐
as3
than
in
WT
cells.

We
estimated
replication
fork
rates
in
MMS
using
regression

analysis
based
on
the
leading
edge
of
BrdU
incorporation
across
the
ARS607
to
VI-‐R

region
(see
Methods).

The
firing
of
subtelomeric
origins
in
WT
cells
precluded

unambiguous
determination
of
fork
rate
in
the
absence
of
MMS;
however,
the

presence
of
MMS
facilitated
this
analysis
by
inhibiting
firing
of
subtelomeric
origins

through
the
intra-‐S
checkpoint
(Tercero
et
al.,
2003).

This
analysis
yielded
an

average
rate
of
446
bp/min
in
MMS-‐treated
WT
cells
and
1031
bp/min
in
MMS-‐
treated
cdc7-‐as3
cells.
The
more
rapid
progression
of
BrdU
incorporation
in
cdc7-‐

113

Figure
4.3.

Cdc7
functions
upstream
of
Rad53
in
fork
regulation.

A.
WT,
cdc7-‐1

mcm5-‐bob1
and
cdc7-‐1
mcm5-‐bob1
pph3∆
cells
were
synchronized
with
α-‐factor
for

3
hours
at
23°C,
shifted
to
32°C
for
1
hour,
and
released
from
α-‐factor
at
32°C
with

0.033%
MMS.

B.
DNA
content
analysis
by
FACScan.

C.
Heat
maps
of
BrdU

incorporation
levels
at
origins
are
arranged
according
to
each
origin’s
published

replication
timing
from
early
to
late
(left
to
right).

D.
Aliquots
were
pulsed
with

BrdU
for
the
indicated
intervals
and
analyzed
by
BrdU-‐IP-‐chip.

Results
for
segments

of
chromosomes
III
and
VI
are
plotted,
with
origin
locations
indicated
above.

E.
WT

and
cdc7-‐1
mcm5-‐bob1
cells
expressing
Rfa1-‐Myc18
were
treated
as
in
(A)
and

analyzed
by
ChIP-‐chip
35
min
after
release;
plots
are
color-‐coded
as
in
(D).

F.

Immunoblot
analysis
of
unphosphorylated
(*)
and
phosphorylated
Rad53
(**);

molecular
weight
markers
were
visualized
with
Ponceau
S.

Data
shown
are
from
a

single
representative
experiment
out
of
two
replicates,
except
data
in
(C)
were

calculated
from
both
replicates.

114

as3
cells
was
dependent
on
PP1
(Fig.
4.2E).

Thus,
Cdc7
is
required
for
the
normal

rate
of
replication
fork
progression
along
undamaged
and
MMS-‐damaged
templates.

To
corroborate
these
unexpected
findings,
we
used
the
cdc7-‐1
allele
in
a

similar
analysis.

G1-‐synchronized
WT
and
cdc7-‐1
mcm5-‐bob1
cells
were
shifted
to

32˚C
for
1
hr
before
release
into
S-‐phase
in
the
presence
of
MMS,
and
pulsed
with

BrdU
(Fig.
4.3A).

Total
DNA
content
analysis
showed
similar
slow
rates
of
DNA

synthesis
in
WT
and
cdc7-‐1
mcm5-‐bob1
cells
in
the
presence
of
MMS
(Fig.
4.3B),

while
cdc7-‐1
cells
lacking
the
mcm5-‐bob1
suppressor
allele
showed
tight
arrest
of

DNA
synthesis
(Fig.
4.4B),
demonstrating
the
effective
inhibition
of
Cdc7-‐1
function

under
these
conditions,
and
at
least
partial
restoration
of
origin
firing
by
mcm5-‐
bob1,
as
reported
previously
(Hoang
et
al.,
2007).

BrdU
incorporation
showed

similar
effects
on
origin
firing
of
Cdc7
inhibition
by
cdc7-‐1
mcm5-‐bob1
as
by
cdc7-‐
as3;
we
estimated
that
221
origins
fired
in
WT
and
175
in
cdc7-‐1
mcm5-‐bob1
cells.

As
in
cdc7-‐as3
cells,
the
level
of
BrdU
incorporation
at
most
origins
was
decreased;

however,
the
earliest
origins
were
least
affected
(Fig.
4.3C).

This
result
is
consistent

with
the
previous
demonstration
that
the
earliest
origins
are
partially
resistant
to

elimination
of
Cdc7
function
in
the
presence
of
the
mcm5-‐bob1
allele;
the
mcm5-‐
bob1
allele
alone
does
not
affect
origin
firing
(Hoang
et
al.,
2007).

BrdU
incorporation
at
ARS306
and
ARS607
was
similar
between
WT
and

cdc7-‐1
mcm5-‐bob1
cells,
while
the
firing
of
the
slightly
later
origins
was

compromised
specifically
in
the
cdc7-‐1
mcm5-‐bob1
cells
(Fig.
4.3D).

The

incorporation
of
BrdU
along
the
chromosome
III
and
VI
replicons
progressed
more

rapidly
in
cdc7-‐1
mcm5-‐bob1
than
WT
cells,
with
rates
of
1364
and
541
bp/min,

115

respectively
(Fig.
4.3D).

The
more
rapid
BrdU
incorporation
in
the
cdc7-‐1
mcm5-‐
bob1
strain
was
accompanied
by
association
of
RPA,
which
binds
ssDNA
at

replication
forks,
consistent
with
more
rapid
progression
of
bona
fide
replication

forks
(Fig.
4.3E).

These
observations
support
the
results
with
the
cdc7-‐as3
allele

and
indicate
a
role
for
DDK
in
regulating
the
rate
of
fork
progression.

Figure
4.4.

Effective
depletion
of
Cdc7
function
with
the
cdc7-‐1
allele.
A.

Experimental
scheme:
WT,
cdc7-‐1,
and
cdc7-‐1
mcm5-‐bob1
cells
were
synchronized

in
G1-‐phase
with
α-‐factor
for
3
hours
at
23°C,
shifted
to
32°C
for
1
hour,
and

released
from
α-‐factor
at
32°C
into
the
presence
of
0.033%
MMS.

B.
Samples
were

withdrawn
at
the
indicated
times
for
DNA
content
analysis
by
FACScan.

Data
shown

are
from
a
single
representative
experiment
out
of
two
replicates.

116

Cdc7
acts
upstream
of
Rad53
in
fork
regulation

The
results
above
show
that
Cdc7
function
controls
the
rate
of
replication

fork
progression
on
undamaged
and
MMS-‐damaged
DNA.

We
showed
previously

that
deactivation
of
Rad53
promotes
progression
of
forks
slowed
in
response
to

MMS
(Szyjka
et
al.,
2008),
and
previous
reports
have
shown
differences
in
Rad53

activation
in
cells
lacking
Cdc7
activity
(Dohrmann
and
Sclafani,
2006;
Ogi
et
al.,

2008;
Sheu
and
Stillman,
2010;
Tercero
et
al.,
2003).

Thus,
reduced
Cdc7
activity

might
permit
rapid
replication
fork
progression
through
damaged
DNA
by

diminishing
checkpoint
signaling
leading
to
Rad53
activation.

To
investigate

whether
Cdc7
depletion
affects
the
level
of
checkpoint
activation,
we
examined

Rad53
activation
as
reflected
in
its
altered
electrophoretic
mobility
due
to
its

phosphorylation
(Pellicioli
et
al.,
1999).

Under
the
conditions
of
the
above

experiment(s),
Rad53
activation
was
reduced
in
cdc7-‐1
mcm5-‐bob1
compared
with

WT
cells
based
on
the
smaller
proportion
of
slower-‐
to
faster-‐migrating
Rad53
(Fig.

4.3F).

This
result
is
consistent
with
previous
findings
that
Cdc7
is
required
for
the

normal
level
of
checkpoint
activity
in
cells
undergoing
replication
stress,
and
is

consistent
with
the
idea
that
reduced
checkpoint
activation
resulting
from
reduced

Cdc7
activity
affects
the
rate
of
fork
progression.

A
previous
study
concluded
that
the
requirement
of
Cdc7
for
checkpoint

activation
in
response
to
DNA
damage
reflects
its
function
in
initiation
and
the

establishment
of
replication
forks
(Tercero
et
al.,
2003).

Cdc7
activity
also
is

regulated
as
a
direct
target
of
the
checkpoint
via
Rad53-‐dependent
phosphorylation

117

of
Dbf4,
which
inhibits
DDK
function
in
origin
firing.

If
Cdc7
is
upstream
of
Rad53
in

activation
of
the
checkpoint,
then
fork
slowing
should
occur
in
response
to

increased
Rad53
activity,
even
in
the
absence
of
Cdc7
function.

Conversely,
if
Cdc7

activity
is
a
downstream
target
or
effector
of
the
checkpoint
required
for
regulation

of
fork
rate
then
increased
Rad53
activity
should
fail
to
slow
forks
in
the
absence
of

Cdc7
function.

To
increase
Rad53
activity,
we
exploited
our
previous
finding
that

deletion
of
the
Rad53
phosphatase
PPH3
results
in
Rad53
hyperactivity
and
slower

replication
fork
progression
in
MMS
(O'Neill
et
al.,
2007;
Szyjka
et
al.,
2008).

As

predicted,
pph3∆
resulted
in
increased
Rad53
activity
in
WT
and
Cdc7-‐deficient,

MMS-‐treated
cells,
although
the
level
of
Rad53
activity
was
lower
in
cells
lacking

Cdc7
function,
consistent
with
reduced
origin
activation

(Fig.
4.3F).

The
increased

Rad53
activity
correlated
with
slower
bulk
DNA
replication
and
slower
fork

progression
(Fig.
4.3B,
D).

Thus,
enhanced
Rad53
activity
slows
forks
in
the
absence

of
Cdc7
activity,
which
is
consistent
with
Cdc7
acting
upstream
of
Rad53
in
fork

slowing
in
response
to
replication
stress.

Decreased
initiation
from
Orc1-‐depletion
also
deregulates
fork
progression

Our
results
suggest
that
the
deregulated
fork
progression
of
Cdc7-‐depleted

cells
derives
from
Cdc7’s
function
in
replication
initiation.

To
address
whether
a

decreased
level
of
replication
initiation
is
sufficient
to
deregulate
fork
progression,

we
examined
fork
progression
in
cells
harboring
orc1-‐161,
a
temperature-‐sensitive

118

allele
of
ORC1,
which
is
required
for
replication
initiation;
incubation
of
G1-‐arrested

orc1-‐161
cells
at
the
non-‐permissive
temperature
reduces
MCM
occupancy
at

origins
(Aparicio
et
al.,
1997;
Gibson
et
al.,
2006).

We
performed
the
same

temperature-‐shift
regimen
and
release
into
MMS
as
we
did
for
the
cdc7-‐1
cells
(Fig.

4.5A).

Total
DNA
content
analysis
showed
diminished
progression
through
S-‐phase

of
orc1-‐161
cells
compared
with
WT,
consistent
with
reduced
origin
firing
in
the

mutant
cells
(Fig.
4.5B).

Rad53
activation
also
was
reduced
in
orc1-‐161
cells,
only

reaching
levels
comparable
to
those
of
WT
cells
at
~90
min
(Fig.
4.5C).

Interestingly,
these
higher
levels
of
Rad53
activation
coincided
with
reduced

progression
of
total
DNA
content
in
orc1-‐161
cells
at
these
later
times
(Fig.
4.5B),

consistent
with
checkpoint
regulation
of
fork
rates
(analysis
of
fork
rates
by
BrdU-‐IP

is
not
feasible
at
these
later
times).

Analysis
of
BrdU
incorporation
showed
a
global

reduction
in
the
number
of
origins
that
fired
and
their
BrdU
incorporation
levels
in

orc1-‐161
cells,
consistent
with
depletion
of
Orc1
function.

We
estimated
that
230

origins
fired
in
WT
and
192
in
orc1-‐161
cells.

BrdU
incorporation
levels
were
also

lower
at
most
origins,
including
very
early
origins,
which
were
only
modestly

affected
in
Cdc7-‐depleted
cells
(Fig.
4.5D).

Cells
with
diminished
Orc1
activity
exhibited
initiation
of
ARS306
and

ARS607
along
with
reduced
initiation
of
the
slightly
later
origins
(ARS603.5
and

ARS605)
(Fig.
4.5E).

Inactivation
of
Orc1
also
affected
the
rate
of
fork
progression

like
Cdc7
inactivation,
with
an
average
rate
of
1202
bp/min
compared
with
732

bp/min
in
WT
cells
(Fig.
4.5E).

Given
the
distinct
roles
of
Cdc7
and
Orc1
in

119

Figure
4.5.

Orc1
function
regulates
replication
fork
progression.

A.
WT
and

orc1-‐161
cells
were
synchronized
with
α-‐factor
for
3
hours
at
23°C,
shifted
to
32°C

for
1
hour,
and
released
from
α-‐factor
at
32°C
with
0.033%
MMS.

B.
DNA
content

analysis
by
FACScan.

C.
Immunoblot
analysis
of
phosphorylated
Rad53
(Rad53-‐P);

both
panels
are
from
the
same
blot
and
exposure.

Molecular
weight
markers
were

not
run
on
this
gel;
for
the
migration
of
size
markers
relative
to
the
bands
detected

by
this
antibody,
see
Figure
2F.

D.
Heat
maps
of
BrdU
incorporation
levels
at
origins

are
arranged
according
to
each
origin’s
published
replication
timing
from
early
to

late
(left
to
right).

E.
Aliquots
were
pulsed
with
BrdU
for
the
indicated
intervals
and

analyzed
by
BrdU-‐IP-‐chip.

Results
for
segments
of
chromosomes
III
and
VI
are

plotted,
with
origin
locations
indicated
above.

Data
shown
are
from
a
single

representative
experiment
out
of
two
replicates,
except
data
in
(D)
were
calculated

from
both
replicates.

120

replication
initiation,
we
conclude
that
the
common
deficiency
in
origin
activation

best
explains
the
diminished
Rad53
activation
and
rapid
fork
rate.

Checkpoint
elimination
is
not
sufficient
to
deregulate
fork
rate

We
have
shown
that
decreased
levels
of
initiation
result
in
decreased
Rad53

activation
levels
and
faster
fork
rates.

However,
another
feature
of
reduced
Cdc7

and
Orc1
activity
that
we
hypothesized
might
contribute
to
faster
fork
rates
is
the

reduced
overall
number
of
active
forks,
which
might
increase
the
availability
of

normally
rate-‐limiting
factors
to
the
fewer
active
forks.

To
evaluate
the
effect
of
the

number
of
active
forks,
we
examined
mec1-‐100
cells,
which
only
weakly
activate

Rad53
in
response
to
MMS
(but
sufficiently
to
maintain
fork
stability)
while

activating
a
larger
than
normal
complement
of
origins
including
late
and
normally

dormant
origins
(Paciotti
et
al.,
2001;
Tercero
et
al.,
2003).

Therefore,
these
cells

allow
us
to
test
the
effect
of
higher
numbers
of
active
forks
in
combination
with
low

levels
of
active
Rad53.

As
shown
previously,
G1-‐synchronized
mec1-‐100
cells

released
into
MMS
(Fig.
4.6A)
exhibit
more
rapid
progression
through
S-‐phase
as

measured
by
total
DNA
content
(Fig.
4.6B),
and
decreased
Rad53
activation
(Fig.

4.6C)
(Paciotti
et
al.,
2001).

BrdU
incorporation
analysis
showed
increased
numbers

of
active
origins
genome-‐wide
in
mec1-‐100
cells,
with
219
firing
in
WT
and
310
in

mec1-‐100
cells,
the
latter
including
many
later
origins
(Fig.
4.6D).

Analysis
of
the

chromosome
III
and
VI
regions
showed
similar
levels
of
BrdU
incorporation
at

121

Figure
4.6.

Deregulated
origin
firing
in
mec1-‐100
slows
replication
forks.

A.

WT
and
mec1-‐100
cells
were
synchronized
with
α-‐factor
for
4
hours
at
23°C
and

released
from
α-‐factor
at
23°C
with
0.033%
MMS.

B.
DNA
content
analysis
by

FACScan.

C.
Immunoblot
analysis
of
phosphorylated
Rad53
(Rad53-‐P);
both
panels

are
from
the
same
blot
and
exposure.

Molecular
weight
markers
were
not
run
on

this
gel;
for
the
migration
of
size
markers
relative
to
the
bands
detected
by
this

antibody,
see
Figure
2F.

D.
Heat
maps
of
BrdU
incorporation
levels
at
origins
are

arranged
according
to
each
origin’s
published
replication
timing
from
early
to
late

(left
to
right).

E.
Aliquots
were
pulsed
with
BrdU
for
the
indicated
intervals
and

analyzed
by
BrdU-‐IP-‐chip.

Results
for
entire
chromosome
VI
are
plotted,
with
origin

locations
indicated
above.

Data
shown
are
from
a
single
representative
experiment

out
of
two
replicates,
except
data
in
(D)
were
calculated
from
both
replicates.

122

earlier
origins
and
higher
levels
at
late
origins
like
ARS603
in
mec1-‐100
cells
(Fig.

4.6E).

Replication
forks
progressed
more
slowly
in
mec1-‐100
cells
than
in
WT
cells

(Fig.
4.6E),
with
rates
of
242
and
517
bp/min,
respectively,
despite
lower
levels
of

Rad53
activation
in
mec1-‐100
cells.

We
have
observed
similar
BrdU
incorporation

profiles
as
in
mec1-‐100
cells,
including
more
origins
firing
and
slower
forks,
in
other

intra-‐S
checkpoint
mutant
strains,
including
rad53∆
and
rad53∆
exo1∆
(EXO1

deletion
suppresses
the
MMS
sensitivity
of
rad53∆
cells
(Segurado
and
Diffley,

2008))
(Fig.
4.7).

A
recent
study
in
human
cells
reported
slower
fork
progression
in

Ckh1-‐depleted
cells,
which
was
suppressed
by
additional
depletion
of
Cdc7
activity

(Petermann
et
al.,
2010).

These
findings
suggest
that
increased
numbers
of

replication
forks
suppress
more
rapid
fork
progression,
perhaps
by
depleting

essential
factors.

Replication
fork
and
checkpoint
levels
regulate
replication
fork
progression

Comparison
of
origin
firing
rates
and
replication
fork
rates
across
the

experiments
in
MMS
supports
a
model
in
which
the
rate
of
replication
fork

progression
is
inversely
related
to
the
number
of
active
replication
forks,
which
is

determined
by
the
level
of
origin
firing
(Fig.
4.8).

We
propose
that
the
number
of

active
forks
influences
overall
fork
rate
in
checkpoint-‐dependent
and
-‐independent

ways.

Robust
checkpoint
activation
associated
with
substantial
numbers
of

123

Figure
4.7.

Deregulated
origin
firing
in
rad53∆
slows
replication
forks.

A.

Experimental
scheme:
WT,
rad53,
exo1∆,
and
rad53∆
exo1∆
cells
(all
strains
are

sml1∆)
were
synchronized
in
G1-‐phase
with
α-‐factor
for
4
hours
at
23°C
and

released
from
α-‐factor
at
23°C
into
the
presence
of
0.033%
MMS.

B.
Samples
were

withdrawn
at
the
indicated
times
for
DNA
content
analysis
by
FACScan.

C.
Aliquots

of
the
cultures
were
pulsed
with
BrdU
for
the
indicated
intervals
and
harvested
for

analysis
by
BrdU-‐IP-‐chip.

Data
shown
are
from
a
single
experiment.

124

replication
forks
encountering
DNA
damage
slows
fork
progression.

Additionally,

large
numbers
of
forks
deplete
available
replication
factors
or
dNTPs,
which
limits

fork
rate
even
with
a
reduced
or
absent
checkpoint.

However,
when
fork
numbers

are
reduced,
as
in
cdc7
and
orc1
mutant
cells,
reduced
checkpoint
activation
and

reduced
competition
from
other
forks
for
limiting
factors
allows
more
avid
fork

progression.

In
mec1-‐100
cells,
where
deficiency
of
Rad53
activation
is
associated

with
an
excess
of
replication
forks,
replication
factor
depletion
results
in
slower
fork

progression
despite
the
lack
of
checkpoint
activation.

This
model
is
based
in
part
on

our
previous
demonstration
that
suppression
of
Rad53
activity
restores
robust
fork

progression
through
MMS-‐damaged
DNA
(Szyjka
et
al.,
2008).

Further
supporting

the
idea
that
fork
rate
is
under
checkpoint
regulation,
a
recent
study
has
shown
that

Ckh2
kinase
(the
metazoan
equivalent
of
Rad53)
inhibits
the
replicative
helicase

complex
(Cdc45-‐MCM-‐GINS)
(Ilves
et
al.,
2012).

In
addition,
recent
studies
have

shown
that
DDK
and
several
other
replication
proteins,
as
well
as
dNTPs,
are
rate

limiting
for
chromosomal
DNA
replication
in
yeast
(Mantiero
et
al.,
2011;
Patel
et
al.,

2008;
Poli
et
al.,
2012;
Tanaka
et
al.,
2011).

Taken
together,
we
conclude
that

replication
fork
rate
is
sensitive
to
levels
of
origin
firing
and
checkpoint
activity.

125

Figure
4.8.

Replication
fork
and
checkpoint
levels
regulate
replication
fork

progression.

A.
Genome-‐wide
origin
firing
and
local
fork
rate
for
the
experiments

in
MMS
are
plotted;
average
and
standard
deviation
are
shown
(n=2).

Data
points

are
color-‐coded
for
the
experimental
group
represented.

B.
The
model
depicts
fork

rate
regulation
in
wild-‐type
and
mutant
strains
with
different
levels
of
origin
firing

and
checkpoint
functions.

The
font
intensities
and
line/arrow
thicknesses
represent

the
relative
strength
of
the
corresponding
pathway
or
signal.

For
example,

translucent
fonts
indicate
a
weak
or
defective
function
or
pathway
and
bold
fonts

indicate
a
hyperactive
function
or
pathway.

The
chromosome
graphic
below
each

model
depicts
the
levels
of
origin
firing
and
fork
rate
in
each
condition.

Open
circles

represent
fired
origins
and
filled
circles
represent
unfired
origins;
E,
M,
and
L

indicate
early-‐,
middle-‐
and
late-‐firing
origins,
respectively.

126

Materials
and
methods

Plasmid
and
strain
constructions:
All
strains
are
derived
from
W303
and
are

described
in
Table
4.1.

Gene
disruptions
were
constructed
by
PCR-‐based
methods

(Guldener
et
al.,
1996;
Longtine
et
al.,
1998).

Plasmid
p306-‐ars305∆-‐BrdU-‐Inc
was

constructed
by
three-‐way
ligation
of
620bp
NotI-‐BglII
PCR-‐amplified
fragment
5ʹ′-‐
flanking
ARS305
and
560bp
BglII-‐SacI
PCR-‐amplified
fragment
3ʹ′-‐flanking
ARS305

into
NotI-‐SacI-‐digested
p306-‐BrdU-‐Inc
(Viggiani
and
Aparicio,
2006).

Plasmid

p306-‐ars305∆-‐BrdU-‐Inc
digested
with
BglII
was
used
to
simultaneously
delete

ARS305
and
integrate
the
10.3kb
plasmid
with
BrdU-‐Inc
cassette
by
gene

replacement.

Correct
replacement
was
confirmed
by
PCR.

The
1.6kb
HindIII-‐EcoRI

fragment
of
cdc7-‐as3
containing
the
kinase-‐inactivating
mutations
L120A
and

V181A
was
isolated
from
pRS551-‐cdc7-‐as3
(L120A,
V181A)
(Wan
et
al.,
2006)
and

subcloned
into
EcoRI-‐HindIII-‐digested
pRS306.

The
resulting
plasmid,
pRS306-‐
cdc7-‐as3,
was
linearized
with
EcoRI
and
used
to
exchange
CDC7
with
cdc7-‐as3
by

pop-‐in/pop-‐out
replacement.

pPP117,
which
contains
a
3.6kb
EcoRI-‐SalI
cdc7-‐1

fragment
from
pRH301
(Hollingsworth
et
al.,
1992)
in
URA3
integrating
vector

pRS306,
was
linearized
with
ClaI
and
used
to
exchange
CDC7
with
cdc7-‐1
by
pop-‐
in/pop-‐out
replacement
followed
by
screening
for
temperature-‐sensitivity
at
37°C.

The
resultant
cdc7-‐1
strain
was
then
transformed
with
MluI-‐digested
pRAS490

(Dohrmann
and
Sclafani,
2006),
which
contains
mcm5-‐bob1-‐2
(CT
to
TC
change
at

codon
83
to
create
DdeI
site
and
P83L
mutation)
in
pRS306,
to
exchange
MCM5
with

mcm5-‐bob1-‐2
by
pop-‐in/pop-‐out
replacement
followed
by
screening
for

127

suppression
of
temperature-‐sensitivity
at
37°C.

The
7.5kb
SacI-‐SpeI
fragment

containing
the
mec1-‐100
allele
was
isolated
from
plasmid
pML258.51
(Paciotti
et
al.,

2001)
and
subcloned
into
SacI-‐SpeI-‐digested
pRS406.

The
resulting
plasmid,

pRS406-‐mec1-‐100,
was
linearized
with
BstEII
and
used
to
exchange
MEC1
with

mec1-‐100
by
pop-‐in/pop-‐out
replacement.

All
allele
replacements
were
confirmed

by
DNA
sequencing.

Primer
sequences
are
available
upon
request.

Yeast
methods:
Cells
were
grown
in
YEPD
for
all
experiments.

Cell
were

synchronized
in
G1-‐phase
by
incubation
with
5
nM
α-‐factor
(Sigma,
T6901)
for
4

hours
at
23°C
and
released
by
resuspension
and
gentle
sonication
in
fresh
YEPD

lacking
α-‐factor
and
containing
200
µg/mL
Pronase
E
(Sigma,
P5147).

For
DNA

content
analysis,
cells
were
fixed
with
70%
ethanol
overnight,
washed
and

resuspended
in
50
mM
sodium
citrate
(pH
7.4),
and
RNAseA
was
added
to
0.2

mg/mL
and
incubated
for
3
hours
at
50°C.

Proteinase
K
was
added
to
0.5
mg/mL

and
incubated
50°C
for
2
hours,
after
which
Sytox
Green
(Mol
Probes)
was
added
to

1
µM
for
at
least
30
min
before
analysis
on
a
Becton-‐Dickinson
FACScan
instrument.

PP1
(Tocris
Biosciences)
was
used
at
25
µM.

For
BrdU-‐IP-‐chip,
20mL
culture

(OD~1)
was
pulse-‐labeled
with
800
µg/mL
BrdU
(Sigma,
B5002),
harvested
with

addition
of
NaN3
to
0.1%,
and
genomic
DNA
was
prepared
by
disruption
with
glass

beads.

1
µg
genomic
DNA
was
sonicated
to
~500bp,
denatured,
and

immunoprecipitated
with
anti-‐BrdU
antibody
(GE
Healthcare,
RPN202)
at
1:1000.

For
chromatin
immunoprecipitation
analyzed
by
microarray
(ChIP-‐chip),
50mL

culture
(OD~1)
was
fixed
with
formaldehyde,
chromatin
was
isolated
by
disruption

128

with
glass
beads
and
sonicated
to
~500bp.

Chromatin
was
immunoprecipitated

with
anti-‐MYC
9E10
antibody
(Covance,
MMS150)
at
1:100.

Immunoprecipitated

and
total
DNA
samples
(from
BrdU-‐IP-‐chip
and
ChIP-‐chip)
were
amplified
using

WGA2
(Sigma),
labeled
with
Cy5
and
Cy3,
respectively,
and
hybridized
to
custom-‐
designed
oligonucleotide-‐based
tiling
microarrays
(Roche-‐Nimblegen)
using
the

Maui
hybridization
system
according
to
the
manufacturer’s
instructions;
further

details
are
provided
in
(Knott
et
al.,
2012;
Viggiani
et
al.,
2009;
Viggiani
et
al.,
2010).

Rad53
immunoblot
analysis
was
performed
with
anti-‐Rad53
at
1:1000
(Santa
Cruz

Biotechnology,
SC6749)
as
described
previously
(Gibson
et
al.,
2004).

Microarray
normalization:
BrdU-‐IP-‐chip
normalization
from
the
Nimblegen
arrays

was
performed
as
described
(Knott
et
al.,
2009).

Briefly,
probes
from
the
most

dense
regions
of
the
corresponding
MA
plot
were
isolated
and
principle
component

analysis
was
performed
on
their
corresponding
M
(=
log(IP/Total))
and
A
(=

log(IP*Total))
values.

The
resultant
first
and
second
principle
components
were

then
taken
to
represent
each
probe's
normalized
A
and
M
values,
respectively.

Following
this,
loess
normalization
was
performed
to
remove
any
residual
array

artifacts
(Smyth
and
Speed,
2003).

Analysis
of
Rfa1
ChIP
was
performed
using

MA2C
(Song
et
al.,
2007).

Data
filtering:
We
used
the
values
of
ϕ
=
exp(M)
obtained
from
the
previous
step
in

the
subsequent
analysis.

An
enriched
probe
was
defined
as
one
with
ϕ-‐value

greater
than
one.

An
enriched
region
was
defined
as
a
sequence
of
consecutive

129

enriched
probes.

Each
enriched
region
was
given
an
enrichment
score
(E-‐score),

which
was
the
sum
of
the
ϕ-‐values
of
the
probes
within
the
region.

In
most
cases,

there
was
a
single,
clearly
enriched
region
of
BrdU
signal
to
the
right
of
ARS607.

In

cases
with
more
than
one
enriched
region,
for
the
purpose
of
estimating
the
fork

speed
we
chose
the
region
with
the
maximum
E-‐score.

Column
F
of
Table
S1

indicates
which
time
intervals
were
included
in
the
analysis.

Fork
rate
analysis:
For
each
experiment,
we
examined
the
ϕ-‐values
in
the
single

enriched
region
identified
above.

We
assumed
that
the
probability
of
having
a
fork

in
the
interval
defined
by
the
position
of
a
single
probe
is
proportional
to
the
ϕ-‐
value
of
that
probe.

To
estimate
the
leading
edge
of
the
replication
fork,
we
used
P,

the
90
th

percentile
of
the
resulting
probability
distribution.

For
each
experiment,
we

write
T
for
the
mean
time
of
the
BrdU
pulse
(if
the
pulse
occurred
between
time

points
𝑎
and 𝑏,
then
𝑇 =
!
!
(𝑎+𝑏)).

For
each
strain
and
experimental
condition,
we

calculate
the
values
of
𝑃
and
𝑇,
and
fit
a
linear
regression
of
the
form

𝑃=𝑢+𝑣𝑇

to
the
data.

We
obtained
estimated
values
of
𝑢
and
𝑣.
The
estimate
of
the
fork
rate
is

given
by
𝑣.

We
note
that
an
analysis
along
the
same
lines,
but
using
the
values
of
M

in
place
of
ϕ,
gives
essentially
the
same
results.

Origin
firing
analysis:
Using
the
Piecewise
Cubic
Hermite
Interpolating
Polynomial

(PCHIP),
we
interpolated
the
normalized
and
smoothed
M-‐value
of
the
probes
for

every
10
bp
of
the
genome.

Under
the
null
hypothesis
of
no
enrichment
around
an

130

origin,
the
sum
of
the
N
interpolated
M-‐values
of
the
probes
in
this
region
will
have

approximately
a
Normal
distribution
with
mean
𝜇
and
variance
𝜎
!
,
where
𝜇
and
𝜎
!
,

are
the
mean
and
variance
of
a
typical
interpolated
M-‐value.

Using
all
the
observed

M-‐values,
we
can
estimate
the
𝜇
and
𝜎
!
.

For
each
origin,
the
sum
S
of
signal
from
the
N
interpolated
probes
within
a
distance

of
1500
bp
was
calculated.

An
origin
is
determined
to
have
significantly
enriched

signal
if
S
lies
in
the
tails
of
the
null
distribution,
using
a
significance
cutoff
of
0.05.

We
use
a
Bonferroni
correction
for
multiple
testing.
In
all
cases
we
either
used
the

earliest
time
point,
or
the
sum
of
two
earliest
time
points
as
a
representative
early

signal
for
determining
if
the
origin
fired.
Column
C
of
Table
S1
indicates
which
time

intervals
were
included
in
this
analysis.

The
color
of
individual
cells
in
the

heatmaps
in
Figures
1-‐4
represent
this
sum
S
assigned
to
each
origin.
Column
D
of

Table
S1
indicates
which
time
intervals
were
included
in
calculating
S
for
the

heatmap
visualizations.
We
used
the
origin
dataset
from
(Knott
et
al.,
2012)
and

timing
data
from
(Raghuraman
et
al.,
2001).

Table
4.1.
Strain
List.

Strain
Genotype

All
strains
share
the
W303a
RAD5
genotype:
MATa
ade2-‐1
ura3-‐1
his3-‐11,15
trp1-‐1
leu2-‐
3,112
can1-‐100
bar1::hisG

Except
as
noted
below

JPy8
ars608Δ::HIS3
ars609Δ::TRP1
ars305Δ::BrdU-‐Inc
(TRP1)
RFA1-‐18Myc
(KanMX)

JPy9
ars608Δ::HIS3
ars609Δ::TRP1
ars305Δ::BrdU-‐Inc
(TRP1)
RFA1-‐18Myc
(KanMX)
cdc7-‐1

131

mcm5-‐bob1

JYy3
ars608Δ::HIS3
ars609Δ::TRP1
ars305Δ::BrdU-‐Inc
(TRP1)
sml1Δ::HIS3

JYy4
ars608Δ::HIS3
ars609Δ::TRP1
ars305Δ::BrdU-‐Inc
(TRP1)
sml1Δ::HIS3
exo1Δ::TRP1

RSy1298
ars608Δ::HIS3
ars609Δ::TRP1
ars305Δ::BrdU-‐Inc
(TRP1)
cdc7-‐1

RSy1307
ars608Δ::HIS3
ars609Δ::TRP1
ars305Δ::BrdU-‐Inc
(TRP1)
cdc7-‐1
mcm5-‐bob1

T2y41
ars608Δ::HIS3
ars305Δ::BrdU-‐Inc
(KanMX)
orc1Δ::hisG
leu2::ORC1
(LEU2)

T2y42

ars608Δ::HIS3
ars609Δ::TRP1
ars305Δ::BrdU-‐Inc
(KanMX)
orc1Δ::hisG
leu2::orc1-‐161

(LEU2)

YZy2
lys2Δ::hisG
trp1::BrdU-‐Inc
(TRP1)
orc1Δ::hisG
leu2::ORC1
(LEU2)

YZy3
lys2Δ::hisG
trp1::BrdU-‐Inc
(TRP1)
orc1Δ::hisG
leu2::orc1-‐161
(LEU2)

YZy8
ars608Δ::HIS3
ars609Δ::TRP1
leu2::BrdU-‐Inc
(LEU2)

YZy10
ars608Δ::HIS3
ars609Δ::TRP1
leu2::BrdU-‐Inc
(LEU2)
cdc7-‐as3

YZy18
ars608Δ::HIS3
ars609Δ::TRP1
ars305Δ::BrdU-‐Inc
(URA3)
leu2::BrdU-‐Inc
(LEU2)

YZy19
ars608Δ::HIS3
ars609Δ::TRP1
ars305Δ::BrdU-‐Inc
(URA3)
leu2::BrdU-‐Inc
(LEU2)
cdc7-‐as3

YZy34
ars608Δ::HIS3
ars609Δ::TRP1
ars305Δ::BrdU-‐Inc
(TRP1)
pph3Δ::KanMX

YZy35
ars608Δ::HIS3
ars609Δ::TRP1
ars305Δ::BrdU-‐Inc
(TRP1)
cdc7-‐1
mcm5-‐bob1
pph3Δ::KanMX

YZy50
ars608Δ::HIS3
ars609Δ::TRP1
ars305Δ::BrdU-‐Inc
(TRP1)

YZy52
ars608Δ::HIS3
ars609Δ::TRP1
ars305Δ::BrdU-‐Inc
(TRP1)
mec1-‐100

YZy60

ars608Δ::HIS3
ars609Δ::TRP1
ars305Δ::BrdU-‐Inc
(TRP1)
bar1Δ::LEU2
sml1Δ::HIS3

rad53Δ::KanMX
exo1Δ::TRP1

YZy61

ars608Δ::HIS3
ars609Δ::TRP1
ars305Δ::BrdU-‐Inc
(TRP1)
bar1Δ::LEU2

sml1Δ::HIS3
rad53Δ::KanMX

132

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APPENDIX
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152

APPENDIX

Does
phospho-‐regulation
of
Fkh1/2
control
replication
timing?

We
have
recently
shown
cell
cycle
regulation
of
Forkhead
binding
genome

wide
(Ostrow
et
al.,
2014).
Previous
findings
have
also
indicated
transcriptional

regulation
of
Fkh2
by
phosphorylation
(Pic
et
al.,
2000;
Pic-‐Taylor
et
al.,
2004).

Additionally,
the
phosphoPep
database
identifies
multiple
Fkh2
phosphorylation

sites
and
a
single
Fkh1
site
(Bodenmiller
et
al.,
2007).

Based
on
these
findings,
it
is

plausible
that
replication
control
by
Fkh
proteins
may
be
under
similar
regulation.

In
order
to
address
whether
the
role
of
Fkh1/2
in
replication
timing
is
regulated
by

phosphorylation,
we
created
phosphomutants
of
multiple
residues
on
Fkh1
and

Fkh2
in
an
attempt
to
deregulate
replication
timing.
Mutations
were
created

through
site-‐directed
mutagenesis
of
a
plasmid
containing
either
full
length
Fkh1
or

Fkh2.
Either
the
predicted
residue
for
phosphorylation
was
targeted
for
mutation
or

an
adjacent
residue
necessary
for
the
consensus
motif
of
the
particular
kinase
was

mutated.
Particular
interest
was
placed
on
the
DNA
binding
Domain
(DBD)
or
Fkh

Domain
of
Fkh1
and
Fkh2.
Recent
work
from
our
group
(Ostrow
et
al.,
unpublished)

has
shown
that
dimerization
of
Forkhead
proteins,
through
the
domain
swapping
of

the
alpha
helix
encoded
in
the
DBD,
is
important
for
Forkhead
regulated
replication

timing
control.
Interestingly,
the
DBD
of
Fkh1/2
is
highly
conserved
among
higher

eukaryotes
(Fig.
A.1).
This
suggests
evolutionary
importance
in
the
maintenance
of

residues
in
this
region.
Here
we
posited
that
regulation
of
dimerization
might
be

controlled
through
phosphorylation
of
adjacent
residues
in
this
region.

153

The
majority
of
our
efforts
were
primarily
focused
on
identifying
key

residues
in
Fkh1,
as
it’s
phenotypic
effect
on
replication
timing
is
more
dramatic.
We

identified
consensus
phosphorylation
sites
for
CDK,
DDK
(Cdc7),
and
CKII
kinases

(Fig.
A.2)
and
used
these
to
guide
our
selection
of
residues
to
mutate
(Table
A.1).

As

mentioned,
we
created
phospho-‐knock
outs
(S/T
to
A
mutations)
of
all
consensus

phosphorylation
sites
in
the
DBD
(Fig.
A.1,
A.2,
Table
A.1).

We
also
attempted
to

create
phosphomimics
of
several
residues
in
this
region
(S/T
to
D
mutations)
(Table

A.1).
Additionally,
we
attempted
to
mimic
the
conserved
DBD
residues
in
higher

eukaryotic
Forkhead
homologs
by
creating
a
S318E
mutation
(Fig.
A.1,
Table
A.1).

To
address
the
role
of
the
C-‐terminal
consensus
sites
we
created
a
C-‐terminal

truncation
at
reside
A421
by
introducing
a
premature
stop
codon.
Lastly,
we
created

the
R80A
mutation
shown
to
be
defective
in
proper
mating-‐type
switching
donor

preference
(Li
et
al.,
2012).
We
limited
our
analysis
of
Fkh2
to
S356
(found
in
the

DBD
domain)
as
well
as
S683
and
T697,
which
were
shown
to
be
transcriptionally

important
targets
of
CDK

(Fig.
A.1,
Table
A.1)(Pic-‐Taylor
et
al.,
2004).

Mutagenized
plasmids
were
integrated
by
pop
in,
pop
out
at
the
endogenous

locus
or
expressed
on
a
high
copy
plasmid
in
the
fkh1∆
fkh2∆
background.
Strikingly,

all
constructs
complemented
transcriptional
deregulation
of
the
double
mutant
as

evidenced
by
a
loss
of
pseudohyphal
growth.
Bulk
DNA
synthesis
by
FACS
of

asynchronously
growing
culture
did
not
reveal
any
obvious
differences
in
total
DNA

content
when
compared
to
control
strains
as
evidenced
by
the
majority
of
cells

exhibiting
a
typical
2C
peak.
The
one
exception
to
this
was
the
Fkh2
S683D
T697D

mutation
that
revealed
a
more
dramatic
1C
peak
when
compared
to
fkh2∆
cells,

154

consistent
with
these
residues
playing
an
important
role
in
control
of
the
Clb2
gene

cluster
and
the
G2/M
cell
cycle
transition

(Fig.
A.3)
(Pic-‐Taylor
et
al.,
2004).
To

address
the
effect
on
replication
timing,
strains
were
subjected
to
G1
block
and

release
into
media
containing
BrdU
and
hydroxyurea.
Samples
were
taken
and

analyzed
by
BrdU-‐IP-‐chip.
Introduction
of
WT
Fkh1
or
Fkh2
back
into
the
fkh1∆

fkh2∆
background
advanced
the
timing
of
the
Fkh
activated
origins
ars305
and

ars607
to
approximate
WT
levels
(data
not
shown).
Interestingly,
all
of
the

phosphomutants
constructed
had
a
similar
effect
by
rescuing
the
activity
of
these

origins.
In
total,
no
obvious
differences
were
seen
between
the
reintroduction
of
WT

Fkh1
or
Fkh2
versus
any
of
the
phosphomutant
constructs.
Further
analysis,

including
a
more
thorough
genome
wide
analysis
into
changes
to
replication
timing,

as
well
as
replication
of
the
above
results
are
needed.

Additionally,
phosphorylation

sites
may
need
to
be
knocked
out
in
combination
with
one
another
in
order
to
see
a

replication
related
effect.

Figure
A.1.
Multiple
Sequence
Alignment
of
Forkhead
family
transcription

factor
DNA
binding
domains
in
S.
cerevisiae
and
higher
homologs.
Boxes

indicate
conservation
or
divergence
of
key
amino
acids
for
dimerization.
Divergence

of
blue
and
yellow
(E
and
S)
boxed
residues
are
of
potential
interest
in
relation
to

phosphorylation
of
adjacent
residues.

155

Figure
A.2.
Fkh1
Coding
sequence
with
various
highlighted
features.

Table
A.1.
List
of
base
strains
and
introduced
mutations
analyzed.

156

Figure
A.3
Bulk
DNA
content
analysis
of
asynchronously
growing
cultures
by

indicated
strain.

157

Visualization
of
replication
foci
formation
and
relative
origin
positioning
in

fkh1∆
fkh2∆
cells
through
live
cell
imaging.

A
recent
study
has
shown
the
formation
of
replication
foci
in
live
cells
during

S-‐phase
(Kitamura
et
al.,
2006).
These
studies,
using
fluorescently
tagged

constructs,
revealed
that
in
early
S-‐Phase,
Pol1
and
several
other
components
of
the

replication
fork
complex
aggregate
into
distinct
globular
domains
through
out
the

nucleus.
These
domains
are
transient
and
resolve;
returning
to
background
signal

levels
by
the
end
of
S-‐phase.

The
interpretation
of
these
findings
is
that
replication

factories
form
early
in
S-‐phase
to
facilitate
DNA
replication.
This
system
provides
a

method
for
examining
potential
mutants
defective
in
proper
replication
foci

(factory)
formation.

With
the
evidence
that
Fkh
proteins
are
involved
in
coordination
of
proper

nuclear
architecture,
we
hypothesized
that
visible
differences
in
replication
foci

formation
might
be
seen
when
the
above
experiment
was
performed
on
cells
lacking

Fkh1
and
Fkh2
(fkh1∆
fkh2∆)
(Knott
et
al.,
2012).
Haploid
segregants
of
T3030

(Kitamura
et
al.,
2006)
were
crossed
with
SKy1
(fkh1∆
fkh2∆
pFkh2∆C)
and

sporulated,
generating
isogenic
WT
and
fkh1∆
fkh2∆
pFkh2∆
MATa
cells
containing

DNA
Pol1
C-‐terminally
tagged
with
four
tandem
copies
of
green
fluorescent
protein

(Pol1-‐4GFP).
Cells
were
blocked
and
released
into
S-‐phase
and
time-‐lapse
images

were
taken
(at
5
min
intervals
throughout
S-‐phase)
using
a
Deltavision
microscope

with
z-‐sections
through
the
nucleus.
Images
were
deconvoluted
and
projected
as
2-‐
dimensional
images
for
comparison
(Fig.
A.5A).

Figure
A.5.A
shows
a
diffuse

158

background
signal
in
both
WT
as
well
as
fkh1∆
fkh2∆
pFkh2∆C
cells
at
18
minutes.

By
43
minutes
obvious
globular
foci
are
visible
in
both
strains.
Visual
analysis
of
the

two
strains
revealed
no
obvious
difference
in
the
timing
(start
or
end)
of
foci

appearance
or
in
the
approximate
number
or
size
of
replication
foci
formed.
This

indicates
that
replication
foci,
although
potentially
containing
different

chromosomal
regions
(origins),
still
form
in
the
absence
of
Fkh1/2.
Similar

experiments
comparing
WT
cells
and
cells
over-‐expressing
Fkh1
were
also

performed.
As
in
the
knockout
studies,
these
experiments
did
not
yield
an
obvious

difference
in
phenotype
between
strains.
Similar
conclusions
were
also
obtained

with
immunohistochemistry
(data
not
shown).

To
further
investigate
the
dependency
of
origin
clustering
on
Fkh1/2,
we

implemented
a
system
to
fluorescently
tag
individual
origins
for
the
purpose
of

determining
their
relative
spatial
location
to
one
another
within
the
nucleus.

WT

and
fkh1∆
fkh2∆
pFkh2∆
cells
were
transformed
with
integrating
vectors
pRS404-‐
LacI-‐GFP
(subcloned
from
pAFS135
into
pRS404)
and
pRS402-‐TetR-‐tomato.
Both

constructs
are
under
control
of
the
His3
promoter.
We
next
tagged
two
Fkh

activated
origins
in
each
strain,
one
with
a
10
kb
LacO
repeat
(ars305)
and
another

with
an
8
kb
TetO
repeat
(ars607
or
ars306)
~1kb
from
the
ARS.
LacO
and
TetO

arrays
were
subcloned
from
pJBN164
and
pGS004
(Bachant
et
al.,
2002),

respectively.
LacI-‐GFP
binds
tightly
to
the
LacO
array
and
TetR-‐tomato
to
the
TetO

array
allowing
for
visualization
of
the
two
loci
within
the
nucleus
and
determination

of
the
distance
between
them.
Importantly,
introduction
of
the
LacO
and
TetO
arrays

proximal
to
ars305,
ars306,
and
ars607
did
alter
the
early,
robust
firing
of
these

159

origins
in
WT
cells
(Fig.
A.4)
or
the
observed
decrease
in
HU-‐efficiency
of
these

origins
in
fkh1∆
fkh2∆
pFkh2∆C
cells
(data
not
shown).
Cells
were
arrested
in
G1

phase
and
imaged,
as
above,
under
the
appropriate
wavelengths
(Fig,
A.5B).
The

distance
between
the
brightest
focal
point
of
each
channel
was
calculated
through

the
z-‐sections
(excluding
cells
with
multiple
foci
of
a
single
wavelength).
We

compared
the
intrachromosomal
(ars305
and
ars306)
and
interchromosomal

(ars305
and
ars607)
origin
distances
between
WT
and
fkh1∆
fkh2∆
pFkh2∆
cells

using
a
two-‐sided
student’s
T-‐test
(n=~60).
A
statistically
significant
difference
was

not
observed;
however,
the
above
experiments
require
repetition
with
more
cells

for
higher
statistical
power.

While
the
above
experiments
did
not
yield
an
obvious
difference
in

replication
foci
formation
or
of
replication
origin
distance,
additional
experiments

are
necessary
to
fully
characterize
the
relationship
of
Fkh
activated
origins
with

each
other
within
the
nucleus.
Release
of
the
LacO/TetO
harboring
strains
into
S-‐
phase
and
calculation
of
origin
distances
with
time-‐lapse
microscopy
may
provide

more
insight
than
G1
block
alone.
Additionally,
more
origins
need
to
be
tagged
and

analyzed
in
order
to
draw
proper
conclusions.
TetO
arrays
could
also
be
integrated

near
Fkh
activated/repressed
origins
in
combination
with
the
Pol1-‐4GFP
construct

detailed
above
to
look
for
changes
in
the
time
of
origin
association
with
replication

foci.

160

Figure
A.4.
Copy
Number
Analysis
(CNA)
of
fluorescently
tagged
strains.

CNA
of
WT
and
ars305-‐LacO
ars306-‐TetO
strains
(top
panels)
or
WT
and
ars305-‐
LacO
ars607-‐TetO
strains
(bottom
panels)
by
indicated
chromosome
after
G1
block

and
release
into
media
containing
0.2M
HU.
Strains
are
hybridized
against
a
WT
G1

sample
to
identify
replicated
regions.

161

Figure
A.5.
Live
Cell
Imaging
of
fkh1∆
fkh2∆
pFkh2∆
cells.
All
images
shown
are

deconvoluted
and
projected
two-‐dimensional
images
(A)
Pol1-‐4GFP
nuclear

localization
at
indicated
time
points
post
G1
block
and
release.
(B)
Spatial

localization
of
ars305
(LacO
array
bound
by
LacI-‐GFP)
in
green
and
ars607
(TetO

array
bound
by
TetR-‐tomato)
in
red
during
G1
block.

162

Carbon
source
availability
and
changes
to
replication
dynamics

During
analysis
of
control
strains
for
the
galactose
induction
experiments

detailed
in
chapter
one,
an
interesting
and
unexpected
result
emerged.
When
WT

cells
for
BrdU-‐IP-‐chip
experiments
were
grown
in
raffinose
and
switched
to

galactose,
prior
to
S-‐phase
release,
were
compared
to
cells
grown
exclusively
in

glucose,
a
noticeable
decrease
in
HU
efficiency
was
apparent
at
many
origins

genome
wide.
To
further
investigate
this
phenomenon,
we
grew
WT
cells
under

varying
carbon
sources
for
analysis
by
FACS
and
BrdU-‐IP-‐Seq.
Cultures
were
grown

exclusively
in
media
containing
glucose,
raffinose,
or
galactose
overnight,
to
mid-‐log

phase,
and
through
G1
block
and
release.
For
comparison,
we
also
switched
cells

from
raffinose
to
galactose
or
glucose
during
the
G1
block.
For
these
cultures,
cells

were
grown
to
mid-‐log
phase
in
media
containing
raffinose,
followed
by
arrest
with

α-‐factor
for
three
hours
with
raffinose.
At
three
hours,
cells
were
spun
down
and

resuspended
in
media
containing
either
galactose
or
glucose
and
the
α-‐factor
block

was
continued
for
an
additional
two
hours
before
release
into
media
containing
the

same
sugar.
These
conditions
will
be
termed
Raffinose
to
Galactose
(RGal)
and

Raffinose
to
Glucose
(RGlu),
respectively.

Analysis
by
FACS
revealed
noticeable
differences
in
the
time
of
S-‐phase
entry

between
carbon
sources.

(Fig
A.6).

Cells
grown
exclusively
in
glucose
initiated
bulk

DNA
synthesis
(measurable
by
FACS)
earlier
than
either
raffinose
or
galactose

containing
cultures.
Raffinose
cultures
were
by
far
the
most
delayed
in
S-‐phase

entry
(~10
minutes
slower
than
glucose)
with
galactose
cultures
exhibiting
an

163

intermediate
delay.

Analysis
of
RGlu
compared
to
raffinose
revealed
a
slight

advancement
in
S-‐phase
entry,
however
the
change
in
carbon
source
two
hours

prior
to
release
was
not
sufficient
to
fully
restore
earlier
S-‐phase
kinetics
as

observed
in
cultures
grown
exclusively
in
glucose.
RGal
exhibited
similar
kinetics
to

those
observed
in
raffinose
(Fig
A.6).
Interestingly,
all
carbon
sources
completed

replication
(as
evidenced
by
a
full
2C
peak)
with
roughly
the
same
kinetics
(~30

minutes)
after
their
entry
into
S-‐phase
despite
their
differences
in
entry
time.

To
understand
replication
differences
between
carbon
sources
at
the
origin

level,
we
next
used
BrdU-‐IP-‐Seq
to
analyze
replication
genome
wide.
Samples
were

prepared
as
detailed
in
Chapter
One
Materials
and
Methods
except
for
the

differences
in
carbon
source
utilized.
All
sugars
were
added
at
a
final
concentration

of
2%.
Additionally,
for
BrdU-‐IP-‐Seq
samples,
a
deviation
in
the
normalization

method
was
used.
Samples
were
normalized
using
a
maximum-‐minimum

normalization
where
count
reads
were
normalized
with
the
following
equation:

Normalized(xi)=
(xi-‐Xmin)/
(Xmax-‐
Xmin).
The
normalized
value
of
xi
is
for
the
variable

X
in
the
i
th

row
where
Xmin
is
the
minimum
value
in
variable
X
and
Xmax
is
the

maximum.
Consistent
with
bulk
DNA
synthesis
by
FACS,
cells
grown
exclusively
in

glucose
exhibited
broader
peaks
when
compared
to
galactose
and
raffinose
cultures

(Fig
A.7A).
In
addition
to
broader
peaks,
glucose
cultures
widely
exhibited
either
an

increased
number
of
detectable
origin
peaks
or
higher
peaks
when
compared
to

galactose
and
raffinose
cultures
(Fig
A.7A).
In
contrast,
raffinose
cultures
exhibited

very
narrow
peaks
and
fewer
detectable
peaks
genome
wide
while
galactose

cultures
exhibited
an
intermediate
phenotype
(Fig
A.7A)

164

Figure
A.6.
DNA
content
analysis
through
S-‐phase
by
FACS
with
indicated

carbon
sources.

Next
we
compared
the
change
in
carbon
source
during
G1
arrest.
Consistent

with
FACS,
RGlu
exhibits
higher
peak
amplitude
at
many
origins
relative
to
raffinose,

while
RGal,
which
did
not
show
an
obvious
difference
by
FACS,
exhibited
a
slight

increase
in
peak
height
at
many
origins
although
at
an
intermediate
level
between

raffinose
and
RGlu
(Fig
A.7B)
Peaks
widths
remained
largely
comparable
between

all
samples.
These
results
suggest
that
changing
the
carbon
source
from
raffinose
to

galactose
or
glucose
has
a
positive
effect
on
origin
HU
efficiency
with
glucose
being

the
preferential
sugar.
However,
this
change,
two
hours
prior
to
S-‐phase
release,

was
not
sufficient
to
restore
S-‐phase
entry
to
the
level
observed
in
cells
grown

exclusively
in
glucose.

165

The
above
results
suggest
that
the
differences
observed
between
carbon

sources
may
be
a
result
of
S-‐phase
entry
time
and
not
an
inherent
difference
in

origin
usage
or
in
the
total
number
of
origins
utilized.
For
comparison
we
plotted

the
60-‐minute
HU
glucose
and
RGlu
samples
alongside
a
45-‐minute
HU
sample

grown
exclusively
in
glucose
from
another
experiment.
As
expected,
the
peak
widths

in
the
45-‐minute
glucose
sample
relative
to
the
60
min
glucose
sample
are

narrower,
most
likely
due
to
decreased
replication
time
post
release
in
HU.
Also

consistent
with
reduced
replication
time
was
the
decreased
amplitude
at
many

origins,
particularly
those
with
lower
HU-‐
efficiency
(Fig
A.7C)
suggesting
that
these

origins
were
not
given
ample
time
to
fire
in
all
cells.
Interestingly,
the
45-‐minute

glucose
sample
exhibits
somewhat
of
an
intermediate
phenotype
between
the
60-‐
minute
glucose
and
RGlu
conditions
in
both
peak
width
and
peak
height
especially

at
lower
HU-‐efficiency
origins.
These
results
are
consistent
with
RGlu
cells
being

delayed
in
S-‐phase
entry
(behind
even
the
45
minute
glucose
condition)
and

therefore
having
less
time
to
replicate
during
the
HU
block.

The
available
carbon
source,
as
shown
here,
has
a
clear
effect
on
DNA

replication.
Less
optimal
sources
create
the
previously
known
delay
in
cell
cycle

progression,
but
here
we
extend
that
delay
to
be
partially
due
to
a
delayed
entry

into
S-‐phase.

From
our
studies,
it
is
unclear
whether
the
delay
in
S-‐phase
entry
in

raffinose
or
the
more
modest
delay
in
galactose
can
fully
explain
the
differences

observed
in
an
HU
block.
The
distance
traveled
by
replication
forks
in
HU
has
been

shown
to
correlate
with
mean
replication
time.
Early
replication
time
yields
longer

replication
tracks
while
late
replication
time
yields
shorter
tracks
(Poli
et
al.,
2012).

166

This
is
due
to
the
transition
from
normal
replication
kinetics
to
slowed
replication

as
a
result
of
the
depletion
of
available
nucleotides.
Consequently,
a
defined
time
in

hydroxyurea
could
potentially
create
differences
in
observed
HU-‐efficiencies
in

situations
where
S-‐phase
entry
is
delayed.
Consistent
with
the
observed
differences

being
a
result
of
changes
in
S-‐phase
entry
time,
all
conditions
finished
replication

with
similar
kinetics
(~30
min)
after
S-‐phase
entry
as
measured
by
FACS.

Alternatively,
sub
optimal
carbon
sources
could
specifically
alter
origin
selection

and
or
the
total
number
of
origins
used.
The
number
of
origins
utilized
by
cells
can

be
quite
dynamic
without
changing
the
total
time
of
replication
as
evidenced
by

experiments
on
Rif1
(see
Chapter
III).

To
fully
elucidate
the
changes
in
replication
dynamics
under
varying
carbon

sources,
additional
experiments
will
be
required.
A
time
course
throughout
S-‐phase

lacking
hydroxyurea
would
allow
for
the
determination
of
origin
usage
post
S-‐phase

entry
and
would
allow
for
normalization
of
the
data
to
the
S-‐phase
entry
time
point

across
multiple
conditions
with
varying
S-‐phase
entry
times.
2-‐D
gels
could
also

confirm
whether
a
difference
in
origin
efficiency
existed
between
conditions
at

specific
origins.

167

Figure
A.7.
Analysis
of
early
S-‐phase
by
BrdU-‐IP-‐Seq.

(A,B,C,D)
Plots
show

average
BrdU
incorporation
from
replicate
experiments
for
comparison
of
strains

grown
with
the
indicated
sugar(s)

168

SUPPLEMENTAL
FIGURES

Figure
S1.1-‐16.
Analysis
of
early
S-‐phase
by
BrdU-‐IP-‐Seq
for
all
chromosomes

with
Fkh
OE.

Plots
show
average
BrdU
incorporation
from
duplicate
HU

experiments.

Strains
and
origin
classes
are
keyed
above.

169

Figure
S1:
Continued

170

Figure
S1:
Continued

171

Figure
S1:
Continued

172

Figure
S1:
Continued

173

Figure
S1:
Continued

174

Figure
S1:
Continued

175

Figure
S1:
Continued

176

Figure
S2.1-‐16.
Analysis
of

early
S-‐phase
by
BrdU-‐IP-‐Seq
for
all
chromosomes

in
rif1Δ.

Plots
show
average
BrdU
incorporation
from
duplicate
HU
experiments.

Strains
and
origin
classes
are
keyed
above.

177

Figure
S2:
Continued

178

Figure
S2:
Continued

179

Figure
S2:
Continued

180

Figure
S2:
Continued

181

Figure
S2:
Continued

*
signal
from
rDNA
origins
(at
~4.6x10
5

bp
on
Chromosome
12)
removed
to
allow
for

comparison
of
signal
along
the
remainder
of
the
chromosome

182

Figure
S2:
Continued

183

Figure
S2:
Continued

Abstract (if available)

Abstract Eukaryotic cells initiate DNA replication from hundreds to thousands of origins genome wide. The coordinated firing of these origins across a range of times throughout S-phase is a well-conserved feature of replication initiation and is essential to ensure faithful duplication of the genome. Differences in replication timing can be attributed to epigenetic regulation of origins through chromatin environment and spatial localization within the nucleus. Here we address several important factors that regulate and coordinate the replication timing program of the budding yeast, Saccharomyces cerevisiae. Our studies reveal the role of Forkhead transcription factors as modulators of DNA replication timing. Here we find that Forkhead proteins regulate origin timing through binding proximal to certain origins and mediate clustering of these origins. This process is tightly controlled at the protein level. Over-expression of either Fkh1 or Fkh2 causes drastic changes in replication timing genome wide and these changes are the result of an increase in protein binding proximal to regulated origins. Many origins with normally lower levels (or an absence of) Forkhead binding show an advancement in timing due to an increase in Forkhead binding with over-expression. The advancement in timing at these origins comes at the expense of Forkhead unregulated origins and those origins that already preferentially bind Forkhead proteins under WT conditions. This is probably due to increased competition for limiting factors. While Fkh1 and Fkh2 over-expression can advance origin timing through proximal binding, Rif1 actively represses it. Here we show that Rif1 regulates most late and dormant origins genome wide including telomere proximal origins. Deletion of Rif1 advances the timing of almost all of these origins. Similar to the effect seen with Forkhead over-expression, the advanced timing of late origins in rif1∆ cells appears to be at the expense of early robust firing origins probably because of increased competition for limiting factors. Lastly, and consistent with these results, we show that cells lacking Cdc7 or Orc1 function fire fewer origins genome wide. This decrease in competition for limiting factors leads to faster fork rates of origins that do fire and a subsequent reduction in response to DNA damage as evidenced by a reduction in Rad53 checkpoint signaling. This evidence, combined with analysis of checkpoint defective cells, reveals that fork rate is sensitive to the level of origin firing. The findings detailed here suggest a tight regulation of origin initiation timing and replication fork elongation. Here we discuss these findings, the roles of these factors, and their importance to replication timing genome wide.

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