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Sex differences in aging and the effects of mitochondria
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Sex differences in aging and the effects of mitochondria
by
Benjamin Allen Flanagan
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
(BIOLOGY (MARINE BIOLOGY AND BIOLOGICAL OCEANOGRAPHY))
August 2022
Copyright 2022 Benjamin Allen Flanagan
ii
EPIGRAPH
“Parts and wholes evolve in consequence of their relationship, and the relationship itself evolves.
These are the properties of things that we call dialectical: that one thing cannot exist without the
other, that one acquires its properties from its relation to the other, that the properties of both
evolve as a consequence of their interpenetration.”
- Richard Lewontin, The Dialectical Biologist co-written with
Richard Levins
iii
DEDICATION
This dissertation is dedicated to my parents, John, and Vonda Flanagan, for their unwavering support.
iv
ACKNOWLEDGMENTS
This dissertation would not be possible without continued support from the students and faculty
across the University of Southern California Department of Biological Sciences. First, I would like to
thank my advisor, Suzanne Edmands, who allowed me to develop my own research projects, encouraged
me to apply for external funding, and laid the foundation for what I hope is a successful academic career.
I have learned an incredible amount from her mentorship, and she has helped me develop as a researcher
especially in project design and execution. Thanks are also due to my committee members—Carly
Kenkel, John Tower, and Marc Vermulst—who have all facilitated in their own ways by providing
constructive feedback, assisting in experimental design, and showing excitement for my work.
Thank you to all the Edmands lab members over the years who helped me along the way
including Eric Watson, Jane Pascar, Nicole Adams, Elaine Huang, Mac Partridge, Alice Coleman, Murad
Jah, Jake Denova, and particularly Ning Li who I worked with closely on Chapter 2 of this dissertation.
Ning’s persistence and attention to detail is something I work to emulate daily. Without the lab’s inviting
atmosphere and sense of community I would not have been able to put this body of work together. I
would also like to thank the Biological Sciences staff including Don Bingham, Doug Burleson, Adolfo
dela Rosa, Linda Bazilian, and Helga Schwarz.
Outside of USC, I would like to thank Heath Blackmon for assisting with the application of the
line cross analysis to sex differences presented in Chapter 2, and Filipe Barreto for his guidance when
implementing the DNA damage assay. Also, I’m indebted to the Society for the Study of Evolution for
creating a vibrant academic community of evolutionary biologists and for providing grant support through
the R. C. Lewontin Early Award which allowed me to pursue independent research in Chapter 5. Finally,
I would like to thank my brother, David, for keeping me grounded during my dissertation work and being
there when I needed it most.
v
TABLE OF CONTENTS
EPIGRAPH ................................................................................................................................................... ii
DEDICATION ............................................................................................................................................. iii
ACKNOWLEDGMENTS ............................................................................................................................ iv
LIST OF TABLES ...................................................................................................................................... vii
LIST OF FIGURES ................................................................................................................................... viii
CHAPTER ONE: Introduction ...................................................................................................................... 1
References ...................................................................................................................................................... 6
CHAPTER TWO: Mitonuclear interactions alter sex-specific longevity in a species without sex
chromosomes ................................................................................................................................................. 9
Abstract .......................................................................................................................................................... 9
Introduction .................................................................................................................................................... 9
Materials and methods ................................................................................................................................. 13
Results .......................................................................................................................................................... 18
Discussion .................................................................................................................................................... 21
References .................................................................................................................................................... 25
Figures and tables ........................................................................................................................................ 32
Appendix ...................................................................................................................................................... 38
CHAPTER THREE: Oxidative stressors elicit different age and sex effects ............................................. 52
Abstract ........................................................................................................................................................ 52
Introduction .................................................................................................................................................. 52
Materials and methods ................................................................................................................................. 55
Results .......................................................................................................................................................... 57
Discussion .................................................................................................................................................... 58
References .................................................................................................................................................... 62
Figures and tables ........................................................................................................................................ 67
Appendix ...................................................................................................................................................... 70
CHAPTER FOUR: Which populations bear the curse? An evolutionary simulation study of Mother’s
Curse variants for conservationists and experimentalists. ........................................................................... 75
vi
Abstract ........................................................................................................................................................ 75
Introduction .................................................................................................................................................. 76
Materials and methods ................................................................................................................................. 79
Results .......................................................................................................................................................... 81
Discussion .................................................................................................................................................... 85
References .................................................................................................................................................... 89
Figures and tables ........................................................................................................................................ 92
Appendix ...................................................................................................................................................... 98
CHAPTER FIVE: Mitochondrial influence on sex-specific phenotypes within natural populations ....... 104
Abstract ...................................................................................................................................................... 104
Introduction ................................................................................................................................................ 104
Materials and methods ............................................................................................................................... 107
Results ........................................................................................................................................................ 113
Discussion .................................................................................................................................................. 114
References .................................................................................................................................................. 118
Figures and tables ...................................................................................................................................... 122
Appendix .................................................................................................................................................... 128
CHAPTER SIX: Conclusion ..................................................................................................................... 135
References .................................................................................................................................................. 138
BIBLIOGRAPHY ...................................................................................................................................... 139
vii
LIST OF TABLES
Table 1-1: Analysis of Deviance table summarizing the interactive effects of sex and cross on
survival estimated from a cox mixed effects model. ...................................................................... 37
Table 3-1: Results of the generalized linear mixed effects model evaluating the effect of sex and
age on the proportion alive independently for hydrogen peroxide (A) and paraquat (B)
with random effects of replicate and exposure hour. Significant effects are shown in bold. ......... 70
Table 5-1: Mitochondrial sequencing information for experimental iso-female lines. The genomic
position is relative to the previously sequenced AB81 mitochondrial genome (Burton et
al., 2007; NCBI accession NC_008831). .................................................................................... 127
viii
LIST OF FIGURES
Figure 2-1: Geographic locations of populations used in this study SD (San Diego, CA), FHL
(Friday Harbor Labs, WA) and reciprocal hybrid cross design. Solid bars indicate nuclear
alleles contributed by the mother and the dotted bars indicate nuclear alleles contributed
by the father. ................................................................................................................................... 32
Figure 2-2: T. californicus survival proportions (+/- s.e.m) for all crosses (A) and for sex
differences (male – blue; female – red) within each cross (B). Genetic makeup is
illustrated in each plot and refers to the cross design outlined in Figure 1. Circular color
represents mtDNA genome (black – SD; grey – FHL) while the two vertical bars
represent the nuclear genome (black – SD; grey – FHL). Asterisk indicates significant
post-hoc differences (p-value < 0.05) among pairwise estimated marginal means with
Tukey corrected P-values from the cox mixed effects model estimating the interactive
effects cross and sex (B). ................................................................................................................ 33
Figure 2-3: Sex ratio for each cross independently represented as the number of each sex (male –
blue; female – red) per clutch (A) and the overall proportion for each cross (B). P-values
indicate significance level. Genetic makeup illustrated in the top right corner of refers to
the cross design outlined in Figure 1 (A). Circular color represents mtDNA genome
(black – SD; grey – FHL) while the two vertical bars represent the nuclear genome (black
– SD; grey – FHL). ......................................................................................................................... 34
Figure 2-4: Mitochondrial DNA content for male and female T. californicus 28- and 56-days post
hatching (A). 8-OH-dG DNA damage estimated by ELISA for two ages and each sex
(male – blue; female – red) (B). ..................................................................................................... 35
ix
Figure 2-5: Line cross analysis model weighted average of parameter estimates for mean
longevity, sex ratio, mtDNA content, and DNA damage. Significant composite genetic
elements (CGEs) are autosomal additive (Aa), autosomal dominant by cytoplasmic
additive epistasis (AdCa), and autosomal additive by environment interactions (AaEnv).
Bars represent mean model weighted averages and error bars are unconditional standard
errors (see Blackmon & Demuth 2016) while colors represent relative variable
importance (v i). ............................................................................................................................... 36
Figure 3-1: Experimental design to estimate sex- and age-specific oxidative stress tolerance for
two oxidants, hydrogen peroxide and paraquat. Weekly, 90 gravid females with
developmentally late-stage egg sacs were isolated from a stock population maintained in
a beaker. After isolation, females were given 24 hours for egg sacs to hatch. The females
were then removed and placed back into the stock population beaker. This was repeated
weekly to generate 15 age-classes spanning from four to 22 weeks post-hatching.
Simultaneously for all age-classes, the sexes were separated and exposed to experimental
conditions, including benign control conditions, to estimate hydrogen peroxide and
paraquat tolerance. Dashes indicate treatment exposures were performed for all age-
classes. ............................................................................................................................................ 67
Figure 3-2: The sex-specific (blue – male (M), red – female(F)) oxidative stress tolerance for all
age-classes after 48h of exposure to hydrogen peroxide (H 2O 2). The lower and upper
boxplot hinges are the 25
th
and 75
th
percentiles, with two whiskers extending to the largest
and smallest values if falling within one and a half the inter-quartile range. Points
represent all underlying data summarized by the boxplot. ............................................................. 68
Figure 3-3: Survival curves estimated using the Kaplan-Meier method for each sex within each
oxidant treatment for age quantiles. Letters (a, b, c, d) represent pairwise differences
x
using Log-Rank test (p < 0.05) with the Benjamini & Hochberg (1995) p-value correction
methods. .......................................................................................................................................... 69
Figure 4-1: The effect of male fitness variation across different population sizes on mean male
mitochondrial load (A), the mean length of time a mother’s curse variant took to become
fixed in the simulated population (B), and the coefficient of variation for the mean male
mitochondrial load (bottom left). Female fitness effect of the MC variant was equal to
one (neutral in females) with an equal sex ratio. Error bars represent the standard error of
the mean (C). .................................................................................................................................. 92
Figure 4-2: The effect of sex ratio across population sizes on mean male mitochondrial load (A)
and the mean length of time a mother’s curse variant took to become fixed in the
simulated population (B). The MC variant reduced male fitness to a relative fitness of 0.8
and the MC variant was neutral in females. ................................................................................... 93
Figure 4-3: The effect of female fitness variation across population sizes on mean male
mitochondrial load (A) and the mean time until a mother’s curse variant went to fixation
(B). Simulations wherein a MC variant failed to go to fixation were eliminated. Relative
male fitness effect for the MC variant was 0.8 and the sex ratios were equal. ............................... 94
Figure 4-4: The effect of variation in relative male fitness effects across population sizes on male
mitochondrial load (left) and the detrimental equivalents (right). Simulations were run for
10,000 generations, sex ratios were equal, and mother’s curse variants were neutral in
females. ........................................................................................................................................... 95
Figure 4-5: The effect of variation in sex ratio across population sizes on male mitochondrial load
(A) and the detrimental equivalents (B). Simulations were run for 10,000 generations,
and mother’s curse variants were neutral in females and detrimental to males with a
relative fitness of 0.8. ..................................................................................................................... 96
xi
Figure 4-6: The effect of female fitness variation across population sizes on mean male
mitochondrial load (A) and the detrimental equivalents (B). Simulations were run for
10,000 generations, mother’s curse variants were detrimental to males with a relative
fitness of 0.8, and the sex ratio was equal. ..................................................................................... 97
Figure 5-1: Tigriopus californicus AB mitochondrial genome (Burton et al., 2007; NCBI
accession NC_008831) with four overlapping amplicons used to sequence the
mitochondrial genome. Genome drawing was generated using OGDRAW web-service
(Lohse et al., 2007). ...................................................................................................................... 122
Figure 5-2: Haplotype network for experimental Tigriopus californicus iso-female lines collected
from Abalone Cove, CA. The haplotype network was based on a ClustalW (Larkin et al.,
2007) alignment and assembled using the ape package in R (Paradis et al., 2004). The
AB81 genome was previously sequenced in Burton et al., 2007 (NCBI accession
NC_008831). The roman numerals indicate haplotype, circle size represents haplotype
frequency with two members of haplotype II, and each edge point is a mutational step. ............ 123
Figure 5-3: The proportion of variation in sex-specific death date explained by mitochondrial
genetic variation, calculated using MCMCglmm. The point represents mode, and the
error bars are the 95% credible intervals. Results are presented for two models fit
independently with one representative of the repeated experimental mitochondrial
haplotype (AB054 and AB148). ................................................................................................... 124
Figure 5-4: The proportion of variation in development time explained by mitochondrial genetic
variation, calculated using MCMCglmm. The point represents mode, and the error bars
are the 95% credible intervals. Results are presented for two models fit independently
with one representative of the repeated experimental mitochondrial haplotype (AB054
and AB148). .................................................................................................................................. 125
xii
Figure 5-5: The proportion of variation in sex-specific fitness explained by mitochondrial genetic
variation, calculated using MCMCglmm. The point represents mode, and the error bars
are the 95% credible intervals. Results are presented for two models fit independently
with one representative of the repeated experimental mitochondrial haplotype (AB054
and AB148). .................................................................................................................................. 126
1
CHAPTER ONE: Introduction
Mitochondria are cornerstones of eukaryotic life. As a result of an ancient alphaproteobacterial
endosymbiosis that occurred 1.5 - 2 billion years ago, mitochondria contain their own reduced genome.
Across the shared evolutionary history between mitochondria and nuclear genomes many genes once
contained within the mitochondrial genome have been transferred to the nuclear genome; consequently
mitochondrial function relies on gene products derived from both genomes (Adams & Palmer, 2003).
Genes still encoded on the mitochondrial genome perform essential cellular functions like energy and
protein synthesis, and therefore mitochondria can mediate many biological processes.
Mitochondrial genome evolution is hypothesized to be influenced by the mitochondrial mode of
inheritance. Only females transmit their mitochondrial genomes to the next generation, while males do
not. The matrilineal inheritance pattern of mitochondria leads to an evolutionary hypothesis regarding the
sexual antagonism of mitochondrial genome variation. If a mutation arises in a population which has sex-
specific effects wherein the mutation is neutral or beneficial to females while detrimental to males, this
mutation may not be selected against because males are evolutionary dead ends for mitochondria (Frank
& Hurst, 1996). Negative selection in males fails to remove the male harming mitochondrial variant from
the population and females harboring male harming mitochondrial variants are said to ‘curse’ their male
offspring (Gemmell et al., 2004). This evolutionary hypothesis is referred to as the mother’s curse
(Gemmell et al., 2004). Because male harming variants are naïve to selection, mitochondria may
accumulate male harming variation causing mitochondria to influence sex-specific phenotypes.
Although mitochondria are involved in metabolism for both sexes, the metabolic demand of
males and females often differs. Mitochondrial genes encode for proteins involved in oxidative
phosphorylation which produces usable energy and relies on thirteen mitochondrial protein-encoded
genes and over 1000 nuclear gene products (Bar-Yaacov et al., 2012; Rand et al., 2004). As organisms
age, the mitochondrial function can become impaired leading to senescence and the aging phenotype
2
(Clancy, 2008; López-Otín et al., 2013). Age-associated compromised mitochondrial function contributes
to the production of reactive oxygen species (ROS) (Ristow & Zarse, 2010). A ROS quantity greater than
the reductive capacity of intracellular chemicals and enzymes will cause damage to cellular
macromolecules including DNA, proteins, and lipids. The accumulated damage over an animal’s lifespan
may differ among males and females and influence stressor susceptibility during the aging process.
Mitochondrial genetic variation can influence sex-specific traits. One prediction of the mother’s
curse hypothesis is that the contribution of mitochondrial variation to phenotypic variation will be greater
in males than in females (Dowling & Adrian, 2019). One of the first empirical confirmations of the
prediction comes from a gene expression study in fruit flies wherein mitochondrial variation showed a
greater effect on male gene expression variation (Innocenti et al., 2011). Further work, all in fruit flies,
showed empirical support for the mother’s curse prediction wherein mitochondria variation affects male
sterility (Clancy et al., 2011), fertility (Patel et al., 2016; Yee et al., 2013), and aging (Camus et al., 2012).
Conversely, other fruit fly studies have found mitochondrial variance to have equivalent or even greater
effects on female traits (Đorđević et al., 2017; Immonen et al., 2016; Mossman, Biancani, et al., 2016;
Mossman, Tross, et al., 2016).
This dissertation examines how mitochondria influence sex-specific phenotypes. The first chapter
experimental estimates the mitonuclear contribution to sex-specific aging and age-related phenotypes,
while the second determines how sex-specific aging impacts the susceptibility to two oxidative stressors.
The penultimate substantive chapter makes use of forward evolutionary simulations to characterize
populations which may be useful for experimental detection of mother’s curse variants or of concern for
conservation genetics. The final chapter characterizes the mitochondrial contribution to sex-specific
longevity and reproductive output variation within a single population.
For the three experimental chapters, I focus on the emerging marine model organism Tigriopus
californicus, a harpacticoid copepod occupying supralittoral splashpools on rocky shores from Baja
California through southern Alaska (Edmands, 2001). T. californicus does not have sex chromosomes and
instead sex is determined through the interplay of multiple independent loci throughout the genome (Ar-
3
Rushdi, 1958; B. R. Foley et al., 2013). Moreover, T. californicus is amicable to laboratory studies as
generation time is relatively short (~25 days), and T. californicus performs a mate guarding behavior
where males clasp virgin females until receptive and females store sperm and only mate once (Burton,
1985), allowing for easily controlled crosses. This species has limited dispersal which results in extreme
genetic differentiation over short geographic ranges (Burton, 1998; Edmands, 2001; Willett & Ladner,
2009) and between populations, mitochondrial nucleotide divergence can be greater than 20% (Barreto et
al., 2018; Burton et al., 2007). Even with high levels of genetic divergence among populations, T.
californicus still maintains reproductive compatibility across the geographic range and genetic
incompatibilities arise in recombinant hybrids later than the F 1 generation (Burton, 1990).
Even though T. californicus lacks sex chromosomes, sex differences are common in this species
wherein females are typically more stress tolerant than males when exposed to a multitude of abiotic
stressors (H. B. Foley et al., 2019). Under long term (N. Li et al., 2019) and short term (N. Li et al., 2020)
oxidant exposure, T. californicus males differentially expressed more genes than females, and the
majority of gene expression variance was partitioned between the sexes. These differentially expressed
genes include those known to respond to oxidative stress including superoxide dismutase and glutathione
S-transferase , which both showed greater upregulation in males (N. Li et al., 2019, 2020). Chapter 2 first
robustly estimates sex-specific longevity as well as two age-related phenotypes in T. californicus and by
characterizing F 1 hybrid crosses with over 20% mitochondrial divergence, we can determine how the
mitochondrial and nuclear genome influences sex-specific longevity and age-related phenotypes including
mitochondrial DNA content and oxidative DNA damage.
Further developing T. californicus as an aging model, Chapter 3 estimates sex-specific oxidative
stress tolerance over much of the T. californicus lifespan by exposing fifteen age-classes to two oxidative
stressors, hydrogen peroxide and paraquat. The two oxidative stressors function differently intracellularly
and expose sex-differences and age-differences in stressor tolerance.
The empirical results for the mother’s curse hypothesis are at best mixed as described above, yet
theory predicts mitochondria will accumulate male harming variation. The theory behind the
4
accumulation of male harming mitochondrial variation largely ignores demographic processes occurring
within populations which will influence the evolution of male harming mitochondrial variation. Chapter 4
characterizes the evolution of male harming mitochondrial variation through forward evolutionary
simulations with varied population demographics. By designing two simulation frameworks, the results
depict how populations useful to experimentally characterize the mother’s curse may be different from
those which may be of concern for conservation geneticists.
Selection on functional mitochondrial variation occurs within populations, especially in a species
like T. californicus which has limited effective dispersal among populations. For selection to occur,
mitochondrial genetic variation must be present in a population and that variation must influence fitness
related traits. Chapter 5 experimentally estimates the contribution of mitochondrial genetic variation to
the variation in sex-specific longevity, sex-specific reproductive output, and development time by
sequencing mitochondrial genomes and associating the relatedness with sex-specific trait variation.
Differences among males and females for the mitochondrial contribution to sex-specific trait variation
highlights how mitochondrial variation may influence sex-specific evolution.
In addition to empirical Chapters 2-5, I coauthored three studies on sex-specific phenotypes in T.
californicus. In N. Li et al., (2020) we tested for sex differences in the transcriptomic response to
oxidative stressors and found gene expression variation was greater between sexes than among oxidant
treatments. Additionally, N. Li et al., (2022) built on our previous work in Flanagan et al., (2021) and
showed how the mitonuclear interactions of sex-specific longevity depend on nutritional conditions.
Lastly, in Watson et al., (2022) we used cyto-nuclear hybrids derived from allopatric T. californicus
populations to show that selection has not resulted in the accumulation of male mutation load as
predicted by the mother’s curse hypothesis.
Sex differences are common in species with separate sexes and these differences may be
influenced by mitochondrial genome evolution. Mitochondrial function, being central to energy
production, impacts aging while contributing to senescence and age-related phenotypes through the
5
production of damaging chemicals. Because of the known central function of mitochondria, they provide
an ideal starting point to characterize the complex relationship among sex differences, aging, and
evolution.
6
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and longevity in Tigriopus californicus contradict predictions of the mother's curse hypothesis.
BioRxiv. https://doi.org/10.1101/2022.04.20.488069
Willett, C. S., & Ladner, J. T. (2009). Investigations of fine-scale phylogeography in Tigriopus
californicus reveal historical patterns of population divergence. BMC Evolutionary Biology, 9(1), 1–
20. https://doi.org/10.1186/1471-2148-9-139
Yee, W. K. W., Sutton, K. L., & Dowling, D. K. (2013). In vivo male fertility is affected by naturally
occurring mitochondrial haplotypes. Current Biology, 23(2), R55--R56.
9
CHAPTER TWO: Mitonuclear interactions alter sex-specific
longevity in a species without sex chromosomes
Ben A. Flanagan, Ning Li and Suzanne Edmands
Abstract
Impaired mitochondrial function can lead to senescence and the aging phenotype. Theory predicts
degenerative aging phenotypes and mitochondrial pathologies may occur more frequently in males due to
the matrilineal inheritance pattern of mitochondrial DNA observed in most eukaryotes. Here we estimated
the sex-specific longevity for parental and reciprocal F1 hybrid crosses for inbred lines derived from two
allopatric Tigriopus californicus populations with over 20% mitochondrial DNA divergence. T.
californicus lacks sex chromosomes allowing for more direct testing of mitochondrial function in sex-
specific aging. To better understand the aging mechanism, we estimated two age-related phenotypes
(mtDNA content and 8-OH-dG DNA damage) at two timepoints in the lifespan. Sex differences in
lifespan depended on the mitochondrial and nuclear backgrounds, including differences between
reciprocal F1 crosses which have different mitochondrial haplotypes on a 50:50 nuclear background, with
nuclear contributions coming from alternative parents. Young females showed the highest mtDNA
content which decreased with age, while DNA damage in males increased with age and exceed that of
females 56 days after hatching. The adult sex ratio was male-biased and was attributed to complex
mitonuclear interactions. Results thus demonstrate that sex differences in aging depend on mitonuclear
interactions in the absence of sex chromosomes.
Introduction
Species with separate sexes typically exhibit aging dimorphism where one sex experiences
greater mortality than the other (Austad & Fischer, 2016; Lemaître et al., 2020). Many explanations, both
proximate and ultimate, have been proffered for these sex differences. In species with heteromorphic sex
10
chromosomes, the homogametic sex typically lives longer (Xirocostas et al., 2020) suggesting the
expression of unguarded deleterious variants in the heterogametic sex may drive lifespan reduction. But
many taxa have separate sexes without sex chromosomes (Bachtrog et al., 2014), and such taxa allow
characterization of additional factors underlying sex differences in lifespan and aging including sex-
specific tradeoffs between mortality and reproduction (e.g. Williams, 1957).
Mitochondrial function has been associated with aging (Clancy, 2008; López-Otín et al., 2013)
and may explain sex differences in lifespan (Tower, 2006) and contribute to the development age-related
disease (Wallace, 2005). The mitochondrial genome (mtDNA) is almost exclusively maternally inherited
in bilaterians. Due to the matrilineal inheritance patterns, mtDNA variants could arise in a population that
negatively impact male fitness, yet those variants may not be purged from the population through natural
selection because males do not transmit their mtDNA to the next generation (Frank & Hurst, 1996;
Gemmell et al., 2004). Natural selection can operate in females, therefore, male harming mtDNA
mutations may accumulate if they fail to decrease female fitness, referred to as the Mother’s Curse
(Gemmell et al., 2004). Although under thermally stressful conditions, functional mitochondrial variation
can result in sexually concordant selection (Immonen et al., 2020). The most rigorous tests of the
Mother’s Curse hypothesis have been conducted in Drosophila, where some studies find support for the
hypothesis (e.g. Aw et al., 2017; Camus et al., 2012, 2015; Innocenti et al., 2011) while others do not (e.g.
Mossman, Biancani, et al., 2016; Mossman, Tross, et al., 2016). Therefore, the Mother’s Curse genetic
conflict is highly variable across eukaryotes and may be difficult to detect due to nuclear suppression of
sexually antagonistic mitochondrial variants (Havird et al., 2019).
Mitochondria are involved in metabolism for both sexes, yet the metabolic demands for males
and females often differ. Oxidative phosphorylation (OXPHOS) produces usable energy and relies upon
the functional coordination of over 1000 nuclear and 13 mitochondrial protein-encoded genes (Bar-
Yaacov et al., 2012; Rand et al., 2004). OXPHOS complexes have subunits encoded by both nuclear and
mitochondrial genes. The nuclear products are synthesized in the cytosol and then imported to the
mitochondria to form functional proteins (Burton et al., 2013). When genetic incompatibilities are
11
exposed either in late-generation interpopulation hybrids (Barreto & Burton, 2013) or known mitonuclear
combinations (Matoo et al., 2019), animals harboring incompatibilities show phenotypes associated with
altered OXPHOS efficiencies including increased oxidative damage to DNA (Barreto & Burton, 2013)
and elevated levels of hydrogen peroxide (Matoo et al., 2019).
Males and females may show different levels of DNA damage because reactive oxygen species
(ROS) produced by leaky OXPHOS enzymes depends on metabolic demand which may differ between
the sexes. Even though ROS are important in cellular signaling (Shadel & Horvath, 2015), if production
exceeds the equilibrium capacity of the reducing chemicals and enzymes, the organism experiences
oxidative stress. Oxidative stress can damage OXPHOS adjacent cellular macromolecules including the
mtDNA (Andreyev et al., 2005). Oxidative damage to macromolecules lies at the center of one of the
most highly tested aging theories, the free radical theory of aging (Harman, 1956, 1972). Multiple
critiques of the free radical theory of aging exist (Gladyshev, 2014; Lewis et al., 2013; Montgomery et al.,
2012), including evidence that ROS produced by a mitochondrion can induce hormesis (mitohormesis)
where low levels of cellular stress induce a physiological change which has a positive relationship to
stress tolerance later in life and can result in increased lifespan (Schulz et al., 2007).
Mitochondrial copy number (mtDNA content) often differs between sexes (Ballard et al., 2007) and
may shed light on sex differences in lifespan. MtDNA copy number has been proposed as a biomarker
that negatively correlates with age (Kristensen et al., 2019; Mengel-From et al., 2014) and positively
associates with physiological robustness (Kristensen et al., 2019). Mitochondrial numbers are dynamic
and depend on biogenesis and mitophagy, both of which are influenced by ROS (Dogan et al., 2018;
Palmeira et al., 2019). MtDNA content has been found to both increase and decrease with increased ROS
levels. For example, mitochondrial malfunction in Drosophila has been shown to increase both ROS
levels and mtDNA content (Correa et al., 2012) while in a human diseased state associated with decreased
mtDNA content, ROS levels were higher than under healthy conditions (Hao et al., 2016). Therefore, the
relationship between mtDNA content and ROS levels remains unclear (Malik & Czajka, 2013).
12
Here we use the harpacticoid copepod Tigriopus californicus to explore the mitochondrial effects of
sex specific aging. T. californicus occupies supralittoral zone of rocky shores from northern Mexico
through southern Alaska (Edmands, 2001) where populations show high genetic differentiation even
when separated by geographic short distances (Aigaki & Ohba, 1984; Burton, 1998; Edmands, 2001) and
the mitochondrial sequence divergence between populations can exceed 20% (Barreto et al., 2018;
Edmands, 2001). Sex determination in T. californicus does not rely on sex chromosomes and instead, sex
is determined polygenically where multiple loci throughout the genome contribute to sex (Alexander et
al., 2015; Ar-Rushdi, 1958; B. R. Foley et al., 2013). Like other bilaterians, T. californicus displays
maternal mtDNA inheritance (B. R. Foley et al., 2013).
Even though T. californicus lacks sex chromosomes, sex differences are apparent in this species.
Females are typically more tolerant than males when exposed to a multitude of abiotic stressors including
high salinity, low salinity, and high temperature (H. B. Foley et al., 2019). H. B. Foley et al. 2019
reported no difference in sex-specific longevity except in one replicate at high temperature where median
longevity was slightly higher in females. Also, when challenged by both chronic (N. Li et al., 2019) and
acute (N. Li et al., 2020) exposure to exogenous oxidative stress, males and females had divergent
transcriptomic responses, suggesting that longevity and age-related phenotypes may differ between the
sexes.
Characterizing sex-specific aging in a species without sex chromosomes provides a simpler system to
probe mitochondrial effects. Sex bias in mitochondrial effects can be confounded with the effects of sex
chromosomes, which can have sex-specific effects due to both asymmetric inheritance and incomplete
dosage compensation (Ågren et al., 2019; Hudson et al., 2005). Further, the movement of genes on or off
sex chromosomes can both cause and resolve sexual conflicts (Ågren et al., 2019; Hill, 2014). Here we
build T. californicus as an alternative invertebrate aging model first by robustly estimating sex-specific
lifespan using reciprocal F1 hybrid crosses from two populations with 20.6% mtDNA divergence
(Barreto et al., 2018). By using reciprocal hybrid crosses that have a 50:50 nuclear background with
alternative mitochondrial haplotypes and nuclear contributions coming from alternative parents, we can
13
more directly test mitochondrial effects. Then, because mitochondrial malfunction can lead to
macromolecule damage and senescence (Clancy, 2008; López-Otín et al., 2013), we estimate two age-
related phenotypes (8-hydroxy-2′-deoxyguanosine (8-OH-dG) DNA damage and mtDNA content)
longitudinally for two age classes. These results will have implications for human health and will further
our understanding of how mitochondria contribute to sex-specific aging.
Materials and methods
(a) Population sampling and culture maintenance
Copepods were collected from supralittoral pools at San Diego, CA, USA (SD; 32.74 N 117.25
W) and Friday Harbor Labs, WA, USA (FHL; 48.55 N 123 W; Figure 1), and we established inbred lines
under full-sib mating for at least 10 generations before the experiment began. All animals were
maintained at 20ºC in the same incubator with a 12:12 light:dark cycle. During the experiment, animals
were fed ground Spirulina (Nutraceutical Science Institute, USA) and ground Tetramin fish food (Tetra
Holding Inc., USA) with each at a concentration of 0.1 g per liter of seawater. Seawater used in this
experiment was collected from the USC Wrigley Marine Science Center (Catalina Island, CA, USA) and
triple filtered using a 37 μm filter.
(b) Experimental crosses, longevity, and fertility estimates
Using inbred lines from SD and FHL, we generated parental (FF and SS) and reciprocal hybrid
crosses (FS and SF) (Figure 1) where the first letter represents the female parental line while the second
represents the male parental line. T. californicus adult males perform a mate-guarding behavior where
they clasp virgin females until the females become reproductively receptive (Burton, 1985). Importantly,
unmated females that reach sexual maturity can still mate and produce viable offspring well after reaching
the terminal molt (Jillison and Edmands, unpublished data). To ensure females used in designed crosses
were unmated, we removed clasping males from virgins using a needle probe under a dissecting scope on
filter paper. The virgin females were paired with the appropriate males and allowed to mate. After a
14
female was successfully fertilized and the pairs were no longer clasped, the fertilized female was
monitored daily for the appearance of an egg sac and then the hatching of larvae. Once larvae were
observed, they were counted, and the female was moved to a new dish to allow for subsequent clutch
development. Larvae were fed weekly with co-occurring water changes and were allowed to mature and
undergo full-sib mating. We acknowledge that mating and reproduction can impact longevity and
oxidative damage in both sexes (e.g. Aigaki & Ohba, 1984; Burton, 1985; Hood et al., 2018), and chose
to assess sex differences in the more natural scenario that includes mating and reproduction. Twenty-eight
days after hatching, males were identified by their diagnostic geniculate first antennae commonly referred
to as claspers. The sexes were enumerated to estimate the adult sex ratio (hereafter called sex ratio) and
separated. Animals were not sexed before adulthood because sexes are difficult to distinguish at immature
developmental stages. After the males and females were separated, we monitored each family weekly to
determine the number of animals that died until all animals perished. Twenty-eight days and 56 days after
hatching, male and female animals were stored by rinsing individuals with water on filter paper and then
freezing at -80ºC. Archived samples were used to estimate mtDNA content and 8-OH-dG DNA damage.
Survival was fit to a semi-parametric Cox-proportional hazard model with mixed effects
(Therneau, 2018) and a fully parametric Gompertz model (Jackson, 2016). For the Cox-proportional
hazard model with mixed effects, we estimated the interactive fixed effects of sex and cross. Model
selection was performed by comparing Akaike’s information criterion (AIC) values using the anova()
function in R ver. 3.5.0 (R Core Team, 2018). The best fit model included the random effects of family
and clutch nested within a family. Post-hoc testing was performed using least-square means with Tukey
adjusted p-values.
We fit a two parameter Gompertz survival model where the family mortality rate (R) at any age
(t) can be expressed as
𝑅(𝑡) = 𝐴𝑒
!"
eq. 1
15
where A represents a theoretical initial mortality rate and G represents the rate of mortality acceleration
(Finch, 1994; Hughes & Hekimi, 2016). The Gompertz model was fit for each sex within each family for
families that had more than ten individuals per sex because Gompertz parameter estimation is sensitive to
small sample sizes (Finch & Pike, 1996). Gompertz parameters were fit to a linear-mixed effects model
with random effects of family to explore the interactive effects of cross and sex (Bates et al., 2015). Post-
hoc testing was performed using least-square means with Tukey adjusted p-values.
(c) MtDNA content estimation
To extract DNA, individual copepods were incubated for 1 h at 65ºC in 50 μL proteinase-K (200
ug/ml) cell-lysis buffer (10 mM TRIS, 50 mM KCl, 0.5% Tween 20, at pH 8.8) followed by denaturation
for 15 min at 100ºC.
Using individual DNA lysate, we estimated mtDNA copy number through quantitative
polymerase chain reaction (qPCR) for individuals sampled 28- and 56-days post-hatching. To estimate
mtDNA content we targeted single-copy genes for the mitochondrial and nuclear genomes (Table A1).
We designed primers using Primer-BLAST (Ye et al., 2012) to target the AtpC nuclear gene and the Atp6
mitochondrial gene. Because SD and FHL mtDNA sequences are highly divergent (Barreto et al., 2018),
we performed pairwise sequence alignment (Madeira et al., 2019) (EMBOSS Needle) to generate a
consensus sequence upon which we designed mtDNA primers. Primer annealing temperatures were
optimized by gradient PCR, and we followed amplification with a melt curve and agarose gel to ensure
each primer pair generated a single amplicon. To generate the standard curves for each primer pair, we
performed five, 10-fold serial dilutions on DNA extracted from pooled animals. The efficiencies of each
primer set were 90% - 100% with r
2
> 0.99 (Table A1). The qPCR reaction mixture consisted of 1X
HotStart ReadyMix (Kapa Biosystems), 1X EvaGreen® Dye (Biotium), 0.5 uM Primers (Table A1), and
1 uL DNA lysate. Reaction conditions were as follows: 95ºC for 3 min for initial denaturation step,
followed by denaturation at 95ºC for 15 s, annealing (Table A1) for 15 s, and extension at 72ºC for 20 s
repeated 35 times. qPCR reactions were run on a CFX96 Touch Real-Time PCR Detection System (Bio-
Rad), and threshold values (Ct) were obtained using CFX Maestro™ Software for CFX Real-Time PCR
16
Instruments (Bio-Rad) using regression. Each reaction was performed in triplicate and the mean was used
to calculate mtDNA content in a delta-Ct manner according to Rooney et al., 2015.
To meet the statistical model assumptions of normality, mtDNA content was log-transformed.
Using R version 3.5.0 (R Core Team, 2018) and the lme4 package, we fit data to a linear-mixed effects
model with random effects of family and clutch within each family (Bates et al., 2015). Similar to hazard
model fitting, we determined the best fit model using the anova() function. After determining the best fit
random effects, we estimated the fixed effects of sex, cross, age, and their interactions on mtDNA
content. Post-hoc testing was performed using least-square means with Tukey adjusted p-values.
(d) Oxidative DNA damage assay
Oxidative stress is the result of the imbalance between total antioxidant defenses and the
production of ROS (Andreyev et al., 2005). When more reactive oxygen species are produced than can be
reduced, organisms experience oxidative stress which can damage lipids, proteins, and DNA. Here we
estimated DNA damage caused by oxidative stress by measuring 8-hydroxy-2′-deoxyguanosine (8-OH-
dG) content; DNA damage which is the result of guanosine oxidation. Samples frozen at 28- and 56-days
post-hatching were combined by sex within each family and age class to estimate 8-OH-dG damage using
enzyme-linked immunosorbent assay (ELISA; Cayman Chemical cat. 589320). As determined through
serial dilution, the minimum amount of DNA required for the ELISA reaction is 10 ng. To maximize
DNA extraction yield, we used a phenol-chloroform extraction technique. First, individuals underwent
proteinase K-lysis buffer extraction (see mtDNA content estimation). Then 100 uL of the phenol-
chloroform mixture (pH 8.0: VWR) was added to each lysate and the mixture was vortexed and then
centrifuged for 5 min. The aqueous layer was removed and an additional 80 uL of 0.5x TE (pH 8.0) was
added and samples were briefly vortexed then centrifuged for 5min. The second aqueous layer was
combined with the first and 500 uL ice-cold 95% ethanol, 1 uL GlycoBlue (Invitrogen), and 78 uL of 3 M
NaOAc. The samples were inverted and incubated at -20ºC for 1 h and then centrifuged for 30 min. The
ethanol was decanted leaving the pellet and which was washed again with 300 uL ice-cold 70% ethanol
17
and centrifuged for 10 min. The ethanol was again decanted, and the remaining DNA was dried by
vacuum centrifuge. DNA samples were resuspended in 60 uL molecular grade water and DNA was
quantified using Qubit™ 3 Fluorometer (Invitrogen) using Qubit™ dsDNA HS Assay Kit (Invitrogen).
Samples were then treated with P1 nuclease (New England Biolabs) then rSAP (New England Biolabs),
replicate individuals were pooled by sex within each family and age. 8-OH-dG damage ELISA was
performed according to the manufacturer’s protocol. For each sample, the four technical replicates were
averaged, and data were analyzed as the ratio of DNA damage to total DNA.
To estimate the effects of age, sex, and cross and their interactions on DNA damage, we
performed an ANOVA. Data were log-transformed to meet normality assumptions. Post-hoc testing was
performed using least-square means with Tukey adjusted p-values.
(e) Line cross analysis and heterosis
To estimate the underlying genetic architecture of the traits measured (longevity, sex ratio,
fertility, mtDNA content, 8-OH-dG DNA damage, initial mortality rate and rate of mortality
acceleration), we performed a line cross analysis (LCA) using the R package SAGA2 (Blackmon &
Demuth, 2016) to estimate the composite genetic effects (CGEs) contributing to population trait
divergence. The SAGA2 software uses weighted least square means regression weighted by cohort mean
variance to determine phenotypic contribution of CGEs and automatically generates the C-matrix based
on breeding design (Table A2). Using corrected AICs to explore all models, this method estimates
unbiased contribution for each CGE to cohort mean. To determine the relative importance of each CGE
contributing to population phenotype divergence, the variable importance is calculated (v i). Because sex
determination in this system is polygenic, we treated sex as a binary environment. A CGE is considered
significant if v i > 0.9 and the confidence intervals do not overlap with zero as described in Blackmon &
Demuth 2016.
Previous work on T. californicus F 1 interpopulation hybrids revealed heterosis for a variety of
traits including fertility, survivorship, and development rate (Edmands, 1999; Edmands & Deimler,
18
2004). Here, we tested for heterosis (specifically mid-parent heterosis, MPH) for longevity, fertility, and
mtDNA content using:
where 𝐹
)
is the mean offspring trait value and 𝑃
)
is the mean parental trait value (Falconer & Mackay,
1996). Heterosis was evaluated using linear contrasts with significance level estimated by t-tests.
(f) Data manipulation and plotting
All analyses were carried out in R ver. 3.5.0 (R Core Team, 2018) with the use of dplyr
(Wickham & Francois, 2016) for data manipulation and ggplot2 (Wickham, 2016) for data visualization.
Results
(a) Survivorship and longevity
In total, we observed mortality for 5,973 animals which included 35 FF, 26 FS, 16 SF, and 27 SS
families, each representing biological replicates (Figure 1). Mean male longevity was 84.0 ± 0.639 days
(± s.d.) while female longevity was 71.5 ± 0.807 days representing a 15.6% mean decrease. Experimental
survival data was fit to a cox mixed effects model. The parental FF cross experienced high mortality early
in life resulting in lower longevity when compared to the remainder of the crosses (coxme, χ
2
(3) = 739.99,
p < 2.2e
-16
). No remaining crosses exhibited differences in survivorship (Figure 2A). We detected a
significant interaction of sex and cross (Table 1; Table A3A), and post-hoc (Table A4) testing indicated
the FF cross showed no difference among sexes (log(hazard ratio) = -0.071 ± 0.061, Z-ratio = -1.156, p =
0.944), while males in the parental SS cross lived longer than SS females (log(hazard ratio) = 0.5612 +/-
0.0944, Z-ratio = 5.948, p < 0.001).
Among the two hybrid crosses which differ at the mitochondria and the parental source of nuclear
contributions, the effect sizes were in opposite directions. For the FS cross with the FHL mitochondria,
𝑀𝑃𝐻 =
𝐹
!
'
− 𝑃
)
𝑃
)
,
eq. 2
19
female FHL contribution and male SD contribution, males lived longer than females (log(hazard ratio) =
0.569 ± 0.086, Z-ratio = 6.621, p < 0.001). In the reciprocal F1 hybrid with the SD mitochondria, female
SD contribution and male FHL contribution, females had a tendency to live longer (log(hazard ratio) = -
0.237 ± 0.095, Z-ratio = -2.603, p < 0.154) (Figure 2B). Further, linear mixed effects modeling
investigating the interactive effects of sex and cross on lifespan corroborated the cox mixed effects
modeling (Table A5).
To determine the way sex alters lifespan in T. californicus, we assessed the impact of sex and
cross on both the initial mortality rate and the rate of mortality acceleration estimated from the Gompertz
model (eq. 1). For initial mortality rate (Figure A5), the rate was lower in males than in females (Table
A6; Table A7; lmer, χ
2
(1) = 10.713, p = 1.064e-3). Cross had a significant effect (Table A6, lmer, χ
2
(1) =
13.4, p = 3.846e-3) with the FF parental cross showing the highest initial mortality rate and no differences
detected among the remaining three crosses (Table A7). No interaction among sex and cross was
detected for the initial mortality rate (Table A6; lmer, χ
2
(3) = 0.878, p = 0.831). For the rate of mortality
acceleration (Figure A5), the main effects of sex (Table A8; lmer, χ
2
(1) = 5.308, p = 0.021) and cross
(Table A8; lmer, χ
2
(3) = 36.646, p = 5.469e-8) and their interaction (Table A9; lmer, χ
2
(3) = 7.66, p =
0.054) tended to impact the rate of mortality acceleration. Post-hoc testing indicated males from the FF
cross have the highest rate of mortality acceleration when compared to the other sexes and crosses (Table
A7).
(b) Sex ratio
The sex ratio was male-biased in two of the four crosses: the parental SS cross and the FS hybrid
cross with the FHL mitochondria (Figure 3A; Figure 3B; t-test, p < 0.05). If the male-biased sex ratio was
driven by sex-biased survivorship during development, we would expect crosses FS and SS to show a
positive association between the proportion of males assigned at day 28, and the number of individuals
that died during development from hatching through larval and copepodite molts to sexual maturity and
assignment of sex at day 28. Instead, we found no correlation for crosses FS, SS and SF, and a negative
correlation for cross FF (Figure A1).
20
(c) MtDNA content
Sex had a strong effect on mtDNA content (Table A10A, lmer, χ
2
(3) = 23.1, p = 1.54e-6), with
mean mtDNA copy number in females (182 ± 13.4) being greater than in males (121 ± 11.6). No cross
effect was observed. Age and sex effects tended to interact (Table A10A, lmer, χ
2
(3) = 3.07, p = 0.079)
and post-hoc testing revealed male mtDNA content is invariant with age while as females age, their
mtDNA content decreases. Further, 28 days after hatching, males had lower mtDNA content than females
(Figure 4A; Figure A3; Table A11).
(d) 8-OH-dG DNA damage
Sex and age interactively impacted 8-OH-dG DNA damage (Figure 4B; Figure A4; Table A12).
For males, DNA damage increased with age to the point where 56 days post-hatching male damage
tended to be higher than female damage (Table A13).
(e) Line cross analysis and heterosis
To estimate the sex-specific genetic architecture of longevity, an LCA was performed where sex
was treated as an environmental condition. Following Blackmon & Demuth 2016, CGEs were considered
significant if they had a variable importance (v i) greater than 0.9 and a parameter estimate where the
confidence interval excluded zero. For longevity, autosomal additive variation significantly contributed to
population trait divergence where the confidence intervals did not overlap zero with v i = 0.976 while all
other CGEs, including those with the sex term, had v i less than 0.5 (Figure 5). For sex ratio, the epistatic
interaction of autosomal additive variation with cytoplasmic additive variation significantly contributed to
the population divergence in sex ratio where v i = 0.91 (Figure 5) indicating a mitonuclear interaction for
sex ratio. As for mtDNA content, the sexual state treated as an environment significantly contributed to
the variation in mtDNA where we observed a v i = 0.95 (Figure 5). The only significant genetic effect
detected contributing to DNA damage was the epistatic interaction of autosomal dominant variation
interacting with the environment of sex v i = 0.979 and non-zero overlapping confidence intervals. Both
autosomal additive variation and variation due to the environment of sex significantly contributed to the
21
initial mortality rate (Figure A2). No significant CGEs were detected for fertility and the rate of mortality
acceleration.
Both SF and FS F1 hybrid crosses showed heterosis for clutch size and longevity, but not mtDNA
content (Table A14).
Discussion
This study represents the first large-scale estimation of sex-specific lifespan in this species. Here we find
autosomal nuclear variation primarily contributed to the variation in longevity, yet by utilizing F1 hybrids
which share a 50:50 nuclear background but differ at the mitochondria and sex-specific parental
contributions, and by comparing parentals to hybrids, we detected a mitonuclear effect for sex-specific
longevity. The FS hybrid cross showed male-biased longevity, yet no sex difference was detected for the
reciprocal SF hybrid which differ at the mitochondria and the parental source of nuclear contributions.
Male-biased longevity was also observed in the parental SS cross indicating sex-differences in longevity
depend both on nuclear and mitochondrial genotype. This represents a mitonuclear interaction for sex-
specific aging. In those crosses with male-biased longevity (FS and SS), we also observed a male-biased
sex ratio. The only significant genetic element that contributed to the sex ratio divergence was the
epistatic interaction of autosomal and cytoplasmic variation, indicating the observed male-biased sex ratio
is a result of mitonuclear interactions.
Males were found to live longer than females in two of the four crosses, which was unexpected
because T. californicus males are less tolerant to a variety of abiotic stressors (H. B. Foley et al., 2019),
and stress tolerance in other taxa is often positively associated with lifespan (Kirkwood & Austad, 2000;
Niveditha et al., 2017). There is even evidence for a causal relationship between stress tolerance and
longevity, with selection for increased stress resistance resulting in increased lifespan (Rose et al., 1992)
and vice versa (Service et al., 1985). The two crosses sired by the San Diego population showed male-
biased longevity and male-biased sex ratio. The change in sex ratio was attributed a mitonuclear
interaction, but the LCA models could not detect a sex effect because sex ratio is a composite
22
male/female trait. The sex ratio differences could be the result of sex-specific developmental mortality,
but the absence of a correlation between sex ratio and mortality during development in the two male-
biased crosses argues against this hypothesis. An alternative explanation is the presence of a sex ratio
distorter, as suggested by (B. R. Foley et al., 2013). While, sex-specific effects in this system are not
complicated by the effects of sex chromosomes (Alexander et al., 2015; Ar-Rushdi, 1958; B. R. Foley et
al., 2013), inferring mitochondrial effects in F1 hybrids may be confounded by sex-specific paternal
genetic or non-genetic contributions which differ between reciprocal hybrid crosses. Under polygenic sex
determination, multiple portions of the genome contribute to sex and those genomic regions could
contribute to sexually dimorphic life history traits in this species.
The relative differences in longevity between males and females may depend on lifetime energy
expenditure. T. californicus females can produce more than ten egg clutches over their lifespan (Egloff,
1966; Powers et al., 2020) and as females age, they produce smaller clutches in terms of quantity and size
(Powers et al., 2020). Here we find young females had the highest mtDNA content and as females aged,
mtDNA content decreased while male mtDNA content remained invariant irrespective of the age or the
cross. Further, sex primarily contributed to the variation in mtDNA content. This suggests that metabolic
demands differ among the sexes and the decrease in mtDNA content with age in females may be related
to reproductive senescence. In Drosophila, longitudinal mtDNA content decline in males was associated
with reduced stress tolerance later in life (Kristensen et al., 2019). The decrease in female mtDNA content
with age may represent increased mitochondrial malfunction resulting from sex-specific energetic
demands. Age associate stress tolerance decline has not been documented in this species yet may give
insight into the relationship between female mtDNA content decline and aged physiologies.
Hormetic effects on lifespan are characterized by exogenous stress exposure resulting in lifespan
extension (Hercus et al., 2003; Masoro, 2006; Moskalev et al., 2011) and these effects are not consistent
across sexes where one sex is more responsive to hormetic intervention and thus show a greater increase
in lifespan (Moskalev et al., 2011; Sørensen et al., 2007). ROS induced oxidative DNA damage increased
with age in males and was greater in males 56 days after hatching. If the measured DNA damage is
23
representative of endogenous ROS levels, male and females may experience different levels of oxidative
damage throughout their lives. In T. californicus, gene expression was more greatly affected by sex
differences than exogenous oxidant exposure, where male copepods differentially expressed more genes
than females (N. Li et al., 2019, 2020), including the up regulation of antioxidant associated genes.
Elevated endogenous ROS levels could result in the male-specific hormetic response especially if the
ROS is mitochondrially derived. Schaar et al. 2015 found cytoplasmic ROS negatively impacted lifespan
while ROS localized to the mitochondria extended lifespan in Caenorhabditis elegans. The mechanism
leading to increased male lifespan in T. californicus remains unclear, yet we postulate it occurs due to
ROS induced mitohormesis. The hypothesized mechanism could be tested by assessing the response of
lifespan to experimental manipulation of ROS (Shields et al., 2021).
Ultimately, extrinsic mortality rates shape the evolution of aging (Stearns et al., 2000), and the
sex that experiences the higher extrinsic mortality is predicted to have a shorter life (Williams, 1957).
Therefore, longevity represents a tradeoff between mortality and reproduction (Hood et al., 2018;
Williams, 1957) and selection can act upon the tradeoff resulting in sex-specific life-history optima
(Bonduriansky et al., 2008; Maklakov & Lummaa, 2013). If we consider the T. californicus mating
system where females only mate once and continually produce offspring throughout the lifespan (Burton,
1985; Powers et al., 2020) while males can mate multiply, the senescent reproductive decline may
negatively impact males more than females. If male mating success fails to decrease with age, selection
may favor increased lifespan in males (Graves, 2007; Partridge & Barton, 1996). While males do live
longer than females in half of the crosses in this study, we did not determine the reproductive value of
males as we only characterized mortality. Estimation of the reproductive value of males and females may
elucidate the selective pressures potentially leading to lifespan dimorphism observed in T. californicus.
One hypothesis which describes the evolution of sex-specific mitochondrial effects is the
Mother’s Curse (Frank & Hurst, 1996; Gemmell et al., 2004). Under the hypothesis, the prediction is
decreased male lifespan (Camus et al., 2012; Tower, 2017) which was not supported by our study.
Another prediction (Dowling & Adrian, 2019) is that mitonuclear mismatch may cause more fitness
24
related problems in males than in females, yet recent work in Drosophila failed to detect this
hypothesized effect (Vaught et al., 2020). Our study is not well-suited to test this prediction as the F1
hybrids did not show fitness problems, instead the reciprocal crosses both showed hybrid vigor for
lifespan, clutch size and mtDNA content.
In sum, sex differences in T. californicus longevity depended mitochondrial and nuclear genotype
and the male-biased sex ratio was the result of mitonuclear effects. MtDNA content decreased in females
which may be an indication of senescence related to mitochondrial dysfunction while males showed an
increase in DNA damage with age. One hypothesis for the longevity dimorphism is the sex-specific action
of mitohormesis in males. This is consistent with the findings of accelerated accumulation of oxidative
damage in males but would require further experimentation to confirm. In this system where
mitochondrial effects are not confounded by sex chromosomes, the comparison of reciprocal F1 hybrids
and parental crosses revealed sex differences in longevity were the result of mitonuclear interactions.
Acknowledgements
We would like to thank Dr. Heath Blackmon for discussion implementing LCA in SAGA2, and
Dr. Felipe Barreto with assistance in ELISA methodology. Thanks to Dr. Eric Watson, Dr. Scott
Applebaum, Alice Coleman and two anonymous reviewers for input which improved an earlier version of
this manuscript.
Funding
This work was supported by the National Institute on Aging of the U.S. National Institutes of
Health (R21AG055873 awarded to SE) and the U.S. National Science Foundation (DEB-1656048
awarded to SE).
25
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32
Figures and tables
Figure 2-1: Geographic locations of populations used in this study SD (San Diego, CA), FHL (Friday
Harbor Labs, WA) and reciprocal hybrid cross design. Solid bars indicate nuclear alleles contributed by
the mother and the dotted bars indicate nuclear alleles contributed by the father.
FF FS SF SS
♂ ♀
♀
♂ ♂
♀ ♂ ♀
SD FH
L
33
Figure 2-2: T. californicus survival proportions (+/- s.e.m) for all crosses (A) and for sex differences
(male – blue; female – red) within each cross (B). Genetic makeup is illustrated in each plot and refers to
the cross design outlined in Figure 1. Circular color represents mtDNA genome (black – SD; grey – FHL)
while the two vertical bars represent the nuclear genome (black – SD; grey – FHL). Asterisk indicates
significant post-hoc differences (p-value < 0.05) among pairwise estimated marginal means with Tukey
corrected P-values from the cox mixed effects model estimating the interactive effects cross and sex (B).
A
B
*
*
34
Figure 2-3: Sex ratio for each cross independently represented as the number of each sex (male – blue;
female – red) per clutch (A) and the overall proportion for each cross (B). P-values indicate significance
level. Genetic makeup illustrated in the top right corner of refers to the cross design outlined in Figure 1
(A). Circular color represents mtDNA genome (black – SD; grey – FHL) while the two vertical bars
represent the nuclear genome (black – SD; grey – FHL).
*
*
A B
35
Figure 2-4: Mitochondrial DNA content for male and female T. californicus 28- and 56-days post
hatching (A). 8-OH-dG DNA damage estimated by ELISA for two ages and each sex (male – blue;
female – red) (B).
A B
36
Figure 2-5: Line cross analysis model weighted average of parameter estimates for mean longevity, sex
ratio, mtDNA content, and DNA damage. Significant composite genetic elements (CGEs) are autosomal
additive (Aa), autosomal dominant by cytoplasmic additive epistasis (AdCa), and autosomal additive by
environment interactions (AaEnv). Bars represent mean model weighted averages and error bars are
unconditional standard errors (see Blackmon & Demuth 2016) while colors represent relative variable
importance (v i).
37
Table 1-1: Analysis of Deviance table summarizing the interactive effects of sex and cross on survival
estimated from a cox mixed effects model.
Df Chi Sq. P-value
Sex 1 14.225 1.622-4
Cross 3 739.711 <2.2e-16
Sex:Cross 3 71.966 9.472e-15
38
Appendix
Table A1: Summary table of qPCR primer sequence and parameters from a fit linear model. Linear model
was parametrized by performing five, 10-fold DNA dilution (log transformed) fit to resultant Ct values
for each primer pair.
Target
genome
Targ
et
gene
Forward primer
(5’ -> 3’)
Reverse primer
(5’ -> 3’)
T a Slope
E
(%
)
r
2
Nuclear Atp6 CCAAGTTCATCGGA
GCTGGT
TACGGGCGTAACC
GATGATG
65º
C
-
3.288
101 0.99
9
Mitochond
rial
AtpC TGAGAACCAGAAT
GAACGGCT
AGGGTCTTCTCGTC
CCTGAA
55º
C
-
3.446
95 0.99
8
Table A2: C-matrix automatically generated by SAGA2 based on breeding design (see Blackmon &
Demuth 2016).
Crosses M Aa Ad Ca Env AaAa AaEnv AdCa AdEnv CaEnv
P1 1 1 0 1 -1 1 -1 0 0 -1
P1 1 1 0 1 1 1 1 0 0 1
F1 1 0 1 1 -1 0 0 1 -1 -1
F1 1 0 1 1 1 0 0 1 1 1
rF1 1 0 1 -1 -1 0 0 -1 -1 1
rF1 1 0 1 -1 1 0 0 -1 1 -1
P2 1 -1 0 -1 -1 1 1 0 0 1
P2 1 -1 0 -1 1 1 -1 0 0 -1
39
Table A3: Summary hazard ratios for fixed effects of sex and cross and their interactive effects (A).
Sample sizes for estimated hazard ratios (B).
A)
exp(hazard ratio) SE Z-score P-value
Sex [Female] reference
Sex [Male] 1.074 0.061 1.16 0.25
Cross [FF] reference
Cross [FS] 0.23 0.139 -10.63 <2e-16
Cross [SF] 0.136 0.159 -12.84 <2e-16
Cross [SS] 0.186 0.14 -12.33 <2e-16
Sex:Cross
[Male - FS]
0.526
0.106
-6.06
1.4e-9
[Male - SF] 1.182 0.114 1.56 0.12
[Male - SS] 0.531 0.114 -5.62 1.9e-8
B)
Sex
Cross f m
FF 924 980
FS 255 1651
SF 679 561
SS 343 665
40
Table A4: Post-hoc pairwise estimated marginal means with Tukey corrected P-values from the
interactive coxme model. Contrasts include all pairwise sex and cross comparisons.
Sex:Pops log(hazard ratio) S.E. Z-ratio P-value
f FF - m FF -0.0709 0.0613 -1.156 0.944
f FF- f FS 1.4797 0.1392 10.63 <.0001
f FF - m FS 2.0484 0.1197 17.108 <.0001
f FF - f SF 2.0252 0.1577 12.84 <.0001
f FF - m SF 1.7779 0.1615 11.007 <.0001
f FF - f SS 1.721 0.1396 12.329 <.0001
f FF- m SS 2.2822 0.125 18.256 <.0001
m FF - f FS 1.5506 0.1419 10.928 <.0001
m FF - m FS 2.1193 0.1229 17.239 <.0001
m FF - f SF 2.0961 0.1595 13.139 <.0001
m FF - m SF 1.8487 0.1634 11.315 <.0001
m FF - f SS 1.7919 0.1406 12.742 <.0001
m FF - m SS 2.3531 0.1262 18.646 <.0001
f FS - m FS 0.5687 0.0859 6.621 <.0001
f FS - f SF 0.5456 0.2208 2.47 0.2081
f FS - m SF 0.2982 0.2254 1.323 0.8904
f FS - f SS 0.2413 0.1874 1.288 0.9037
f FS - m SS 0.8025 0.1766 4.544 0.0001
m FS - f SF -0.0231 0.2091 -0.111 1
m FS - m SF -0.2705 0.2139 -1.265 0.9118
m FS - f SS -0.3274 0.1709 -1.915 0.5403
m FS - m SS 0.2339 0.1592 1.469 0.8243
f SF - m SF -0.2474 0.095 -2.603 0.1545
f SF - f SS -0.3042 0.212 -1.435 0.8409
f SF - m SS 0.257 0.2021 1.272 0.9094
m SF - f SS -0.0569 0.2141 -0.266 1
m SF - m SS 0.5044 0.2047 2.464 0.211
f SS - m SS 0.5612 0.0944 5.948 <.0001
41
Table A5: Analysis of deviance table for the linear mixed effects model estimating the interactive effects
of sex and cross on lifespan.
Df Chi Sq. P-value
Sex 1 63.319 1.758e-15
Cross 3 180.5 <2e-16
Sex:Cross 3 86.396 <2e-16
Table A6: Analysis of deviance table for the linear mixed effects model estimating the interactive effects
of sex and cross on the initial mortality rate (ln(A)) (eq. 1).
Df Chi Sq. P-value
Sex 1 10.713 1.064e-3
Cross 3 13.4 3.846e-3
Sex:Cross 3 0.878 0.831
Table A7: Post-hoc pairwise estimated marginal means with Tukey corrected P-values from linear mixed
effects model estimating the effects of sex and cross on initial mortality rate (ln(A)). Contrast for the main
effects of sex and cross.
Contrast estimate S.E. df T-ratio P-value
Sex
f - m 0.606 0.186 65.6 3.26 0.0018
Cross
FF - FS 0.9519 0.306 91.6 3.114 0.0129
FF - SF 0.8823 0.335 83.1 2.633 0.0486
FF - SS 0.7622 0.302 88.5 2.52 0.0637
FS - SF -0.0696 0.371 93.5 -0.188 0.9976
FS - SS -0.1896 0.337 97 -0.563 0.9428
SF - SS -0.12 0.367 90.7 -0.327 0.9878
42
Table A8: Analysis of deviance table for the linear mixed effects model estimating the interactive effects
of sex and cross on rate of mortality acceleration (G) (eq. 1).
Df Chi Sq. P-value
Sex 1 5.308 0.021
Cross 3 36.646 5.469e-8
Sex:Cross 3 7.66 0.054
43
Table A9: Post-hoc pairwise estimated marginal means with Tukey corrected P-values from linear mixed
effects model estimating the effects of sex and cross on rate of mortality acceleration. Contrast for the
main effects of sex and cross.
Sex:Cross estimate S.E. df T-ratio P-value
f FF - m FF -0.04611 0.0137 58.5 -3.363 0.0278
f FF - f FS 0.03514 0.0237 127.5 1.486 0.8138
f FF - m FS 0.02575 0.0163 130.1 1.581 0.7608
f FF - f SF 0.04216 0.0191 130.7 2.207 0.3547
f FF - m SF 0.02721 0.0202 131 1.349 0.8779
f FF - f SS 0.02269 0.0208 130.3 1.09 0.9579
f FF - m SS 0.04019 0.0167 130.4 2.412 0.2444
m FF - f FS 0.08125 0.0228 128.2 3.571 0.0114
m FS - m FS 0.07186 0.0149 127.3 4.809 0.0001
m FF - f SF 0.08827 0.018 129.5 4.912 0.0001
m FF - m SF 0.07332 0.0191 130.6 3.841 0.0046
m FF - f SS 0.0688 0.0198 130.8 3.479 0.0153
m FF - m SS 0.0863 0.0153 128.3 5.623 <.0001
f FS - m FS -0.00939 0.0222 79.4 -0.422 0.9999
f FS - f SF 0.00701 0.0256 129.4 0.274 1
f FS - m SF -0.00794 0.0264 129 -0.301 1
f FS - f SS -0.01246 0.0269 127.3 -0.464 0.9998
f FS - m SS 0.00505 0.0238 128.9 0.212 1
m FS - f SF 0.01641 0.019 129.2 0.865 0.9886
m FS - m SF 0.00146 0.02 130.3 0.073 1
m FS - f SS -0.00306 0.0207 131 -0.148 1
m FS - m SS 0.01444 0.0165 127.9 0.875 0.9877
f SF - m SF -0.01495 0.0206 69.1 -0.726 0.9959
f SF - f SS -0.01947 0.023 130.9 -0.848 0.9899
f SF - m SS -0.00196 0.0193 129.6 -0.102 1
m SF - f SS -0.00452 0.0238 130.7 -0.19 1
m SF - m SS 0.01299 0.0203 130.5 0.639 0.9982
f SS - m SS 0.01751 0.0197 81 0.888 0.9863
44
Table A10: Analysis of deviance table for linear mixed effects model estimating the interactive effects of
sex and age on mtDNA content (A). Sample size for data fit to the linear mixed effects model (B).
A)
Df Chi Sq. P-value
Sex 1 23.096 1.541e-06
Age 1 3.024 0.082
Sex:Age 1 3.066 0.079
B)
Sex
f m
Cross 28 days 56 days 28 days 56 days
FF 18 11 17 11
FS 21 20 23 17
SF 27 25 27 22
SS 25 23 17 18
Table A11: Post-hoc pairwise estimated marginal means with Tukey corrected P-values from the
interactive for linear mixed effects model estimating the interactive effects of sex and age on mtDNA
content. Contrasts include all pairwise sex and age comparisons.
Sex:Age estimate S.E. Df T-ratio
P-value
28 f - 56 f 0.11014 0.0451 300 2.439 0.072
28 f - 28 m 0.19391 0.0406 261 4.778 <.0001
28 f - 56 m 0.19499 0.046 298 4.242 0.0002
56 f - 28 m 0.08377 0.0457 303 1.835 0.2591
56 f - 56 m 0.08486 0.0483 296 1.758 0.2956
28 m - 56 m 0.00109 0.0461 299 0.024 1
45
Table A12: ANOVA table for model estimating the interactive effects of sex and age on DNA damage
(A). Sample size for data used to fit ANOVA (B).
A)
Df Sum Sq. Mean Sq. F-value P-value
Sex 1 0.5 0.495 0.427 0.51492
Age 1 1.12 1.12 0.965 0.32798
Sex:Age 1 8.57 8.573 7.387 0.00755
Residuals 119 138.10 1.161 - -
B)
Sex
f m
Cross 28 days 56 days 28 days 56 days
FF 8 8 8 7
FS 8 8 7 7
SF 8 8 7 7
SS 8 8 8 8
Table A13: Post-hoc pairwise estimated marginal means with Tukey corrected P-values from the
interactive anova model estimating the effects of sex and age on DNA damage. Contrasts include all
pairwise sex and age comparisons.
Sex:Age estimate S.E. Df T-ratio
P-value
f 28 - m 28 0.4078 0.276 119 1.476 0.4549
f 28 - f 56 0.3161 0.269 119 1.174 0.6446
f 28 - m 56 -0.3331 0.274 119 -1.217 0.6175
m 28 - f 56 -0.0917 0.276 119 -0.332 0.9873
m 28 - m 56 -0.7409 0.281 119 -2.641 0.0457
f 56 - m 56 -0.6492 0.274 119 -2.371 0.0883
46
Table A14: Heterosis (eq. 2) and linear contrasts (LC) for clutch size, longevity and mtDNA content.
Heterosis LC for Heterosis (p-values)
Trait FS SF FS SF
Clutch size 0.429 0.467 2.05e-3 1.22e-3
Longevity 0.309 0.336 <2e-16 <2e-16
mtDNA content -0.072 0.149 0.653 0.638
47
Figure A1: The correlation of male sex ratio and developmental mortality occurring between hatching and
sex assignment 28 days after hatching with estimated linear regression.
48
Figure A2: Line cross analysis model weighted average of parameter estimates for rate of mortality
acceleration, initial mortality rate, and fertility. Composite genetic elements (CGEs) include autosomal
additive (Aa), autosomal additive by autosomal additive epistatic interactions (AaAa), autosomal additive
by environment of sex interactions (AaEnv), autosomal dominant (Ad), autosomal dominant by
cytoplasmic additive epistatic interactions (AaCa) and cytoplasmic additive effects (Ca), cytoplasmic
additive effects by environment of sex interaction (CaEnv), and environment of sex (Env). Bars represent
mean model weighted averages and error bars are unconditional standard errors (see Blackmon & Demuth
2016) while colors represent relative (v i).
49
Figure A3: Mitochondrial DNA content estimates for each age, sex (male – blue; female – red), and cross
independently. Genetic makeup illustrated in the top right corner of each plot refers to the cross design
outlined in Figure 1. Circular color represents mtDNA genome (black – SD; grey – FHL) while the two
vertical bars represent the nuclear genome (black – SD; grey – FHL).
50
Figure A4: DNA damage estimates for each age, sex (male – blue; female – red), and cross
independently. Genetic makeup illustrated in the top right corner of each plot refers to the cross design
outlined in Figure 1. Circular color represents mtDNA genome (black – SD; grey – FHL) while the two
vertical bars represent the nuclear genome (black – SD; grey – FHL).
51
Figure A5: Gompertz parameters estimated for each sex (male – blue; female – red) and family within
each cross. Ln(A) represents the initial mortality rate, and the G parameter represents the rate of mortality
acceleration while (eq. 1). Genetic makeup illustrated in the top right corner of each plot refers to the
cross design outlined in Figure 1. Circular color represents mtDNA genome (black – SD; grey – FHL)
while the two vertical bars represent the nuclear genome (black – SD; grey – FHL).
52
CHAPTER THREE: Oxidative stressors elicit different age and sex
effects
Ben A. Flanagan, Elaine Huang, and Suzanne Edmands
Abstract
As organisms age, cellular function declines in a time-dependent manner. Oxidative stress
induced by reactive oxygen species damages cellular machinery and contributes to senescence which
narrows the homeostatic window needed to maintain function and survive stress. Sex differences in
longevity are apparent in many species and may be related to sex-specific homeostatic responses. Here we
use the emerging aging model system Tigriopus californicus, the splashpool copepod, to estimate sex-
and age-specific tolerances to two chemical oxidants, hydrogen peroxide and paraquat. Sex-specific
tolerance was estimated for both oxidants simultaneously for 15 age-classes. As animals aged, hydrogen
peroxide tolerance decreased but paraquat tolerance increased. Also, we observed no sex difference for
hydrogen peroxide tolerance, while females were more tolerant of paraquat. Our results demonstrate that
oxidative stressors can have dramatically different sex and age effects in Tigriopus californicus. These
findings underscore the challenges ahead in understanding relationships among oxidative stressors, sex,
and aging.
Introduction
Aging manifests as the time-dependent decline in cellular function resulting in compromised
physiologies which elevate the risk of death (López-Otín et al., 2013). The resultant age associated
progressive increase in cellular dysfunction, especially in the enzymatic synthesis of energy, contributes
to an increase in reactive oxygen species (ROS) (Harman, 1956, 1992). Organisms experience oxidative
stress when ROS levels exceed the reductive antioxidant capacity of intracellular chemicals and enzymes
(Beckman & Ames, 1998), and oxidative stress can further damage cellular macromolecules leading to
53
impaired function. The cellular effects of ROS tend to be dependent on quantity; for example, small
increases in ROS production can sometimes promote longevity whereas high ROS levels are detrimental
(Ristow & Zarse, 2010). ROS are important signaling molecules, therefore complete depletion disrupts
cellular function while too high of levels result in cellular damage. Drosophila melanogaster selected for
increased oxidative stress resistance showed increased life span (Arking et al., 2000; Rose et al., 1992),
and vice versa (Harshman & Haberer, 2000) indicating a positive relationship between longevity and
oxidative stress resistance. Further, in Caenorhabditis elegans, single-gene mutations that increase life
span typically also increase oxidative stress resistance (Honda & Honda, 1999; Murakami & Johnson,
1998). Typically, oxidative stress tolerance correlates with life span and life span extending single gene
mutations increases oxidative stress tolerance. However, studies have also demonstrated the opposite (e.g.
Csiszar et al., 2007), indicating a complex relationship between ROS and life span which has been
difficult to generalize across species (Shields et al., 2021).
Adaptive homeostasis is a mechanism wherein organisms maintain function by rapidly altering
their homeostatic window to withstand damaging molecules or stressful conditions (Davies, 2016;
Pomatto & Davies, 2018). As organisms age, the ability to modify the adaptive homeostatic response to
stressors weakens and therefore the ability to mitigate damage declines (Pomatto et al., 2019). Sex also
influences the homeostatic response (Pomatto et al., 2018; Pomatto, Wong, Carney, et al., 2017; Pomatto,
Wong, Tower, et al., 2017). In D. melanogaster, females pretreated with low levels of hydrogen peroxide
(H 2O 2) survived a subsequent toxic H 2O 2 challenge better than untreated females, while this was not
observed in males (Pomatto, Wong, Tower, et al., 2017). In turn, males pretreated with low levels of the
redox cycler paraquat had increased survival during a subsequent toxic paraquat challenge, while this was
not observed in females (Pomatto, Wong, Tower, et al., 2017). These results underscore the importance of
sex as a biological determinate of oxidative stress resistance (Tower et al., 2020)
Here, we use the aquatic invertebrate Tigriopus californicus to estimate the sex and age specific
effects of two exogenous oxidative stressors. T. californicus occupies the supralittoral splash pools from
northern Baja California to Southern Alaska (Edmands, 2001) which can experience high daily
54
environmental fluctuations (Leong et al., 2018). Adult males perform a mate-guarding behavior where
males use modified antennae to clasp virgin females until they become receptive. The male will then mate
with the female and release her (Burton, 1985). Females mate once and iteratively produce clutches sired
by a single male (Burton, 1985). Mitochondria in this species are maternally inherited (B.-N. Lee, 1993).
T. californicus lacks canonical sex chromosomes and instead sex is polygenic where multiple independent
loci throughout the genome determine sex as a threshold quantitative trait (Alexander et al., 2015; Ar-
Rushdi, 1958; Voordouw & Anholt, 2002). Male-female divergence occurs across the genome and is not
restricted to sex chromosomes, but members of the same sex within a population can show variation at
these sex determining regions. Fixed male-female differences are therefore expected to be minimal under
polygenic sex determination. In this alternative sex determination system, sex-specific phenotypes are not
complicated by the presence of sex chromosomes which influence sex differences in life span (Xirocostas
et al., 2020) and can result in dosage compensation (Disteche, 2012).
Even without sex chromosomes, sex differences are pervasive in T. californicus. Females are
larger and show higher acute stress tolerance to multiple stressors including heat (H. B. Foley et al., 2019;
Kelly et al., 2012; Willett, 2010), salinity, copper, and bisphenol A (H. B. Foley et al., 2019), while males
have a longer life span, increased DNA damage with age and a lower mitochondrial DNA content
(Flanagan et al., 2021). Under long term (N. Li et al., 2019) and short term (N. Li et al., 2020) oxidant
exposure, T. californicus males differentially expressed more genes than females, and the majority of
gene expression variance was partitioned between the sexes. These differentially expressed genes include
those known to respond to oxidative stress including superoxide dismutase and glutathione S-transferase ,
which both showed greater upregulation in males (N. Li et al., 2019, 2020).
In the current study, we use T. californicus to investigate age and sex differences in acute
tolerance to two exogenous oxidative stressors, H 2O 2 and paraquat (1,1′-dimethyl-4,4′-bipyridinium
dichloride). Intracellularly, paraquat reacts with NADPH oxidase enzymes and oxygen in the
mitochondria and at the cell membrane to produce superoxide ions, which are in turn enzymatically
55
dismutated into H 2O 2 (Cochemé & Murphy, 2008). Paraquat is an effective redox cycler causing
continuous production of superoxide ions, while H 2O 2 induced oxidative stress occurs only through
chemical exposure and does not react with cellular chemicals to produce additional oxidants.
Materials and methods
(a) Sample collection and experimental design
Wild copepods were collected from San Diego, CA (25 June 2018) and taken to the lab at the
University of Southern California. The wild collections were maintained in 1L beakers containing triple
filtered (37μm) natural seawater collected from Wrigley Marine Science Center, Catalina Island, CA.
Animals were fed the blue-green alga Spirulina (Nutraceutical Science Institute, USA) and Tetramin fish
food (Tetra Holding Inc., USA) mixture (0.01% MV) and incubated at 20°C on a 12:12 light: dark cycle
throughout the experiment.
The experiment was designed so that copepods of different ages were assayed at the same time,
with cohorts split between experimental treatments (Figure 1). To generate cohorts of copepods with
known age, 90 gravid females with orange egg sacs were isolated and held at 20°C overnight to allow
eggs to hatch. Females with orange eggs were targeted because the orange coloration is indicative of late-
stage development just prior to hatching. Larvae were incubated at 20°C on a 12:12 light: dark cycle and
were allowed to develop for four weeks or until gravid females were observed. After we observed gravid
females, to ensure age identity, all animals were transferred weekly to remove newly hatched larvae.
Transfers were repeated weekly to generate 15 age-classes ranging from four to 22 weeks post-hatching
with a four-week gap between the 17
th
and 22
nd
week cohort. All ages overlapped and oxidant exposure
for all age classes was performed at the same time. All experimental animals were cultured in the same
incubator at 20°C on a 12:12 light: dark cycle.
This range of ages was chosen based on previous longevity estimates where 10% of animals
survive until 22 weeks of age after reaching sexual maturity (Flanagan et al., 2021). Four weeks was
chosen as the lower limit for the age range because juvenile T. californicus stages (copepodite stages I -
56
V) occurring earlier in life have not developed diagnostic sexual structures making it difficult to
distinguish males from females (Egloff, 1966). Additionally, no sex-biased mortality occurred in the San
Diego population during the first 28 days following hatching (Flanagan et al., 2021).
To estimate oxidative stress tolerance age- and sex-specifically, each age-matched cohort was
first split based on sex. T. californicus males can be identified by a diagnostic modified antenna under a
dissecting scope at 40x. For each sex of each age, tolerance was estimated by exposing three replicates of
seven to ten individuals to either benign control conditions containing triple filtered seawater, 1.2mM
H 2O 2 or 0.31mM paraquat, two chemical oxidants. These oxidant concentrations were based on mean 24h
LC50 (the oxidant concentration required to kill 50% of the population) for wild animals from the San
Diego population (unpublished data). Further, previous work in T. californicus has indicated these
concentrations of both oxidants alter the gene expression of proteases and antioxidant genes including
glutathione S-transferase (N. Li et al., 2020). The oxidant concentrations employed are above those in
natural conditions but were chosen to induce an oxidative stress response under acute conditions.
Oxidant exposure occurred in 90mm diameter Petri dishes with 20mL of seawater (7-10
individuals/sex/age/treatment). Three benign seawater-only control replicates of each were included for
each age and sex to ensure death was due to oxidant exposure. To document the mortality, animals were
observed every four hours up to 32h of exposure at which point mortality was observed intermittently up
to 120h of exposure (timepoints for mortality observation; 0, 4, 8, 12, 16, 20, 24, 28, 32, 44, 48, 52, 72,
76, 80, 96, 100, 104, 120). This method of oxidant exposure is different from those typically employed in
terrestrial systems where oxidants are administered through ingestion (see Arking et al. 1991) because
here the oxidant is a component in the respiratory medium (but see Landis et al., 2004).
(b) Statistical analysis
To estimate sex- and age-specific oxidant tolerance, the proportion of surviving individuals was
fit to a generalized linear mixed effects model with a binomial error distribution in R (R Core Team,
2021) using the lme4 package (Bates et al., 2015), and models were fit by maximum likelihood.
Treatment showed a significant effect on the proportion of surviving individuals (Table S1) and because
57
the load of oxidative stress is not equivalent among our two pro-oxidant treatments. The proportion of
alive individuals in each replicate was fit to a generalized linear mixed effects model with fixed effects of
sex, age, and hour and their two-way interactions with a random effect of replicate (subject) within
exposure hour (glmer, Proportion alive ~ Sex + Age + Hour + Sex:Hour + Age:Hour + Sex:Age +
(Hour|Subject). The interaction terms were sequentially dropped to determine the minimum adequate
model by selecting the model with the lowest Akaike’s information criterion (AIC) and Bayesian
information criterion (BIC) for each oxidant exposure (Table S2).
Survival data was fit to a non-parametric Kaplan-Meier survival model to investigate the effects
of age and sex on survival within each treatment. To estimate the age effect, we divided ages into
quantiles (Q1 4-7 weeks; Q2 7-10 weeks; Q3 11-14 weeks; Q4 15-17 and 22 weeks) in R (R Core Team,
2021) and fit survival models using the survfit() function in the survival package (Therneau, 2022).
Pairwise survival differences were estimated using the pairwise survdiff() function in the survminer R
package (Kassambara et al., 2021) with correction for multiple tests using the method of Benjamini and
Hochberg (1995).
Results
In all, survival was estimated for 2571 animals which included three replicates of seven to ten
individuals for each age, sex, and treatment including benign control conditions. Mortality was not
observed for all individuals and there were 334 and 156 animals surviving at the end of the 120h exposure
to H 2O 2 and paraquat respectively.
The control treatment experienced mortality and 17% died after 120h (n = 857). While this
mortality was higher than expected, the proportion alive for the two pro-oxidant treatment groups was
lower than the control indicating both oxidant treatments effectively increased mortality (Figure 2; Figure
2; Table S1). The best fit generalized linear mixed effects models were different for the two pro-oxidant
treatments. The best fit model for H 2O 2 included the fixed effects of age, sex, and hour as well as the
interactive effects of age and hour and sex and hour (Proportion alive ~ Sex + Age + Hour + Age:Hour +
58
Sex:Hour; Table S2A), while the best fit model for paraquat included the same fixed effect and only the
interactive effect of sex and hour (Proportion alive ~ Sex + Age + Hour + Sex:Hour + Hour|Subject;
Table S2B). Here we are particularly interested in the age and sex effects within each treatment and not
the relationship between the two pro-oxidant treatments, therefore we estimated the age and sex effects
independently for each oxidant (Table 1). When animals spanning 18 weeks of age were exposed to H 2O 2,
there was no difference between the two sexes (Table 1A; glmm, z-value = -0.63, p-value = 0.529) while
age significantly affected the proportion alive (Table 1A; glmm, z-value = 36.86, p-value < 0.001) and
interacted with exposure hour wherein the proportion alive decreased with increasing age (Table 1A;
glmm, z-value = - 0.002, p-value < 0.001) (Figure 2; Figure A2). The interaction of age and hour is driven
by the H 2O 2 sensitivity of young males at four weeks of age (Figure A1). For the paraquat treated animals,
sex affected the proportion alive (Table 1B; glmm, z-value = 3.626, p-value < 0.001) and was dependent
on the exposure hour (Table 1B; glmm, z-value = -0.138, p-value < 0.001) where females were more
tolerant than males (Figure A3). Additionally, the proportion alive over the course of paraquat exposure
increased for older animals (Table 1B; glmm, z-value = 0.0125, p-value < 0.001).
In an alternative modeling approach, survival was fit to the Kaplan-Meier model to estimate the
effects of sex and age. Ages were divided into quantiles, and similarly to the results of the generalized
linear mixed effects model, sex did not affect H 2O 2 survival (p-value = 0.58), and H 2O 2 survival decreased
with increasing age quantile (Figure 3). Sex did affect paraquat survival where females were more
tolerant (p-value < 0.001), and paraquat tolerance increased with increasing age quantile (Figure 3).
Discussion
Acute exposure to two oxidants resulted in differing age and sex effects where males were more
sensitive to paraquat while we detected no sex difference for H 2O 2 tolerance. For both males and females,
paraquat tolerance increased with age whereas H 2O 2 tolerance decreased with age.
The decrease in paraquat sensitivity for older male and female animals was unforeseen based on
the expected age-related decline in physiological function and homeostasis (López-Otín et al., 2013). This
59
expected age-related decline has been specifically demonstrated for paraquat tolerance in Drosophila
(Belyi et al., 2020). In our study, H 2O 2 tolerance exhibited the expected age-associated decline in
tolerance while the pattern was reversed for paraquat, even for males and females originating from the
same egg sacs and assayed simultaneously. This indicates that these two commonly used oxidative
stressors elicit markedly different responses, at least in T. californicus. Hydrogen peroxide exposure
results in a static load of oxidative stress while paraquat, due to its activity as a redox cycler, continuously
generates superoxide radicals. Both H 2O 2 and paraquat induce the expression of key antioxidants
(Abrashev et al., 2011) whereas only paraquat exposure depletes NAD(P)H (Forman et al., 1980; Suntres,
2002). While further experimentation is required, we hypothesize the opposite age-associated tolerances
in both sexes for the two oxidative stressors may be related to membrane depolarization because paraquat
uptake requires a membrane potential (Cochemé & Murphy, 2008) and may be related to age-associated
declines mitochondrial respiration rates (Ferguson et al., 2005).
Notably, the electron transport chain in T. californicus differs from many other organisms,
including Drosophila, due to an alternative pathway in the mitochondrial respiratory system. In addition
to the mitochondrial proteins responsible for oxidative phosphorylation (Complexes I – V), T.
californicus (along with a variety of other taxa) has a nuclear gene which encodes for the enzyme
alternative oxidase (AOX) (Tward et al., 2019). Like nuclear encoded oxidative phosphorylation
enzymes, alternative oxidase localizes to the inner mitochondrial membrane but allows for electrons to
bypass Complexes III and IV and yields no contribution to the proton motive force because the energy is
released as heat (McDonald, 2008). AOX reduces the mitochondrial membrane potential in non-
chemically inhibited human cell lines (Cannino et al., 2012). In the tardigrade Hypsibius exemplaris
natively expressing AOX, mitochondrial membrane potential was maintained when mitochondria
respiratory Complexes III and IV were chemically inhibited (Wojciechowska et al., 2021). These results
in the tardigrade are concordant with findings in non-natively AOX expressing mouse models (Szibor et
al., 2020). The presence of AOX in T. californicus represents a respiratory pathway that may influence
60
age-related mitochondrial membrane potential, though more work is necessary to understand the
relationship.
Sex differences for abiotic stressors are common in T. californicus where females are more
tolerant to a multitude of abiotic stressors including high salinity, low salinity, and high temperature (H.
B. Foley et al., 2019). Experimental animals were derived from the wild San Diego population and
previous work has shown males from this population consistently outlive females (Flanagan et al., 2021).
Further, males were found to have a lower mitochondrial DNA content, and oxidative DNA damage
increased with age in males, but not in females (Flanagan et al., 2021). Our finding of sex differences in
paraquat tolerance is consistent with work in Drosophila, where the genetic architecture for paraquat
susceptibility (assayed via climbing ability) appears to be largely sex-specific, as only two out of nearly
two million polymorphisms associated with this trait are shared between males and females, while over
90% of the associated genes were sex-specific (Lovejoy et al., 2021). Further, variation in paraquat
susceptibility in males was associated with over twice as many genes as in females (Lovejoy et al., 2021).
In T. californicus, under short-term exposure to paraquat and H 2O 2 using the same oxidant concentrations
in this study, males and females have different transcriptional profiles where males differentially express
more than four times as many genes in response to both oxidants, including up-regulation of more
antioxidant genes, heat shock proteins and protease genes (N. Li et al., 2020). The contrasting sex-specific
effects of the same two oxidants in Drosophila and Tigriopus underscore the importance of addressing
sex as a biological variable across different species.
In sum, exogenous oxidative stressors elicited differing age and sex effects. Old male and female
animals were more sensitive to H 2O 2 while both sexes derived from the same families were more resistant
to paraquat when compared with younger animals, and overall females were more resistant to paraquat.
Here, we used only a single concentration of both H 2O 2 and paraquat and patterns may change with
differing oxidant concentrations, and, like all studies observing phenotypes of old animals, the animals
alive in the older age-classes are the result of survivorship bias. Although further work is required to
identify the mechanism, our findings that two chemical oxidants cause opposing age effects, as well as
61
contrasting sex effects, illustrate some of the challenges ahead in understanding the relationships among
oxidative stress, sex, and aging.
Funding
This work was supported by funds from the National Institute on Aging of the U.S. National
Institutes of Health (R21AG055873 awarded to SE) and the U.S. National Science Foundation (DEB-
1656048 awarded to SE).
Acknowledgments
Thanks to Dr. John Tower who provided comments which improved an earlier version of this
manuscript.
62
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Figures and tables
Figure 3-1: Experimental design to estimate sex- and age-specific oxidative stress tolerance for two
oxidants, hydrogen peroxide and paraquat. Weekly, 90 gravid females with developmentally late-stage
egg sacs were isolated from a stock population maintained in a beaker. After isolation, females were
given 24 hours for egg sacs to hatch. The females were then removed and placed back into the stock
population beaker. This was repeated weekly to generate 15 age-classes spanning from four to 22 weeks
post-hatching. Simultaneously for all age-classes, the sexes were separated and exposed to experimental
conditions, including benign control conditions, to estimate hydrogen peroxide and paraquat tolerance.
Dashes indicate treatment exposures were performed for all age-classes.
68
Figure 3-2: The sex-specific (blue – male (M), red – female(F)) oxidative stress tolerance for all age-
classes after 48h of exposure to hydrogen peroxide (H 2O 2). The lower and upper boxplot hinges are the
25
th
and 75
th
percentiles, with two whiskers extending to the largest and smallest values if falling within
one and a half the inter-quartile range. Points represent all underlying data summarized by the boxplot.
69
Figure 3-3: Survival curves estimated using the Kaplan-Meier method for each sex within each oxidant
treatment for age quantiles. Letters (a, b, c, d) represent pairwise differences using Log-Rank test (p <
0.05) with the Benjamini & Hochberg (1995) p-value correction methods.
aa
bb
aa
bb
a
b
c
a
b
c
d
a
c
b
ab
a
b
ab
a
ab
70
Table 3-1: Results of the generalized linear mixed effects model evaluating the effect of sex and age on
the proportion alive independently for hydrogen peroxide (A) and paraquat (B) with random effects of
replicate and exposure hour. Significant effects are shown in bold.
A) H2O2 (Proportion alive ~ Sex + Age + Hour + Age:Hour + Sex:Hour)
Estimate Std. Error Z-value P-value
Sex(male) -0.212 0.348 -0.63 0.529
Age 0.036 0.001 36.86 <0.001
Hour 0.102 0.001 100.71 <0.001
Age:Hour -0.002 0.001 -26.08 <0.001
Sex(male):Hour 0.001 0.001 1.19 0.234
B) Paraquat (Proportion alive ~ Sex + Age + Hour + Sex:Hour)
Estimate Std. Error Z-value P-value
Sex(male) 3.626 0.71 4.961 <0.001
Age 0.0125 0.04 3.96 <0.001
Hour -0.08 0.006 -14.133 <0.001
Sex(male):Hour -0.138 0.019 -7.147 <0.001
Appendix
Table S1: Generalized linear mixed effects model estimating the effect of treatment on the proportion of
animals alive during exposure (glmer, Proportion alive ~ Treatment + (hour | subject)).
Estimate Std. Error Z-value P-value
Treatment (H 2O 2) -2.367 0.0003 -6984.16 <0.001
Treatment (Paraquat) -1.975 0.158 -12.51 <0.001
71
Table S2: Model comparison for generalized linear mixed effects models to identify the minimal adequate
model
A) H 2O 2
Predictor AIC BIC
Proportion alive ~ Sex + Age + Hour + (Hour|Subject) 848.86 886.89
Proportion alive ~ Sex + Age + Hour + Age:Hour + (Hour|Subject) 765.15 808.61
Proportion alive ~ Sex + Age + Hour + Sex:Hour + (Hour|Subject) 850.51 893.98
Proportion alive ~ Sex + Age + Hour + Sex:Age + (Hour|Subject) 849.2 892.67
Proportion alive ~ Sex + Age + Hour + Sex:Hour + Age:Hour + (Hour|Subject) 750.16 799.06
Proportion alive ~ Sex + Age + Hour + Sex:Age + Age:Hour +
(Hour|Subject) 747.28 796.18
Proportion alive ~ Sex + Age + Hour + Sex:Hour + Age:Hour + (Hour|Subject) 850.94 899.84
Proportion alive ~ Sex + Age + Hour + Sex:Age + Sex:Hour + Age:Hour +
(Hour|Subject) 748.89 803.22
72
B) Paraquat
Predictor AIC BIC
Proportion alive ~ Sex + Age + Hour + (Hour|Subject) 878.88 916.99
Proportion alive ~ Sex + Age + Hour + Age:Hour + (Hour|Subject) 906.92 950.48
Proportion alive ~ Sex + Age + Hour + Sex:Hour + (Hour|Subject) 790.18 833.74
Proportion alive ~ Sex + Age + Hour + Sex:Age + (Hour|Subject) 877.99 921.55
Proportion alive ~ Sex + Age + Hour + Sex:Hour + Age:Hour + (Hour|Subject) 859.8 908.8
Proportion alive ~ Sex + Age + Hour + Sex:Age + Age:Hour + (Hour|Subject) 896.71 945.71
Proportion alive ~ Sex + Age + Hour + Sex:Hour + Sex:Age + (Hour|Subject) 792.18 896.88
Proportion alive ~ Sex + Age + Hour + Sex:Age + Sex:Hour + Age:Hour +
(Hour|Subject) 842.44 896.88
73
Figure A1: The relationship between the mean proportion animals alive (n = 3) for hours of treatment
exposure (y-axis) and the age of the animals (x-axis). Animals were exposed to control seawater
conditions, hydrogen peroxide, and paraquat for up to 120h.
74
Figure A2: Hydrogen peroxide interaction plots for generalized linear mixed effects model fit exploring
the interaction for Age:Hour and Sex:Hour (Proportion alive ~ Sex + Age + Hour + Sex:Hour +
Age:Hour + (Hour|Subject)).
Figure A3: Paraquat interaction plot for generalized linear mixed effects model fit exploring the
interaction for sex and hour (Proportion alive ~ Sex + Age + Hour + Sex:Hour + (Hour|Subject)).
75
CHAPTER FOUR: Which populations bear the curse? An
evolutionary simulation study of Mother’s Curse variants for
conservationists and experimentalists.
Ben A. Flanagan and Suzanne Edmands
Abstract
Mitochondria are maternally inherited in the vast majority of bilaterian animals and the
matrilinear inheritance pattern is hypothesized to result in the accumulation of mitochondrial variants
which affect sex-specific fitness. Because only females transmit their mitochondrial DNA to the next
generation, mitochondrial DNA mutations which decrease male fitness may be transmitted and evade
selection while selection can act in females; this is referred to as the mother’s curse hypothesis. The
evolutionary dynamics of mitochondrial variants with sex-specific fitness effects depends on the
demographic properties of the population including population size, sex ratio, and the sex-specific fitness
of the mitochondrial mutation. Here, I designed two types of forward evolutionary simulations to estimate
the genetic load imparted by mitochondrial mutations with varied population demographics to
characterize which populations are useful for experimentally detecting mother’s curse and which
populations may be of concern for conservation geneticists. Results suggest that species with large
population sizes may be tractable systems to identify and study mother’s curse mutations, while small
populations will likely accumulate fixed mother’s curse variants and may be of concern for
conservationists. By highlighting the demographic and selective control of mother’s curse variant
accumulation and penetrance, I illustrate how drift dynamics influence the evolution of male harming
mitochondrial variants.
76
Introduction
The mitochondrial genome encodes essential cellular function for both sexes, yet in most
bilaterian animals the mitochondrial genome is only inherited through mothers. As a result of an ancient
alpha-proteobacterial endosymbiosis 1.5–2.0 billion years ago, mitochondria contain their own haploid
circular genome which encodes proteins that perform diverse functions, including enzymes responsible
for energy synthesis. The endosymbiosis gave rise to eukaryotic life with the major innovation being
multiple intracellular membranes used to compartmentalize varied homeostatic conditions, creating ion
gradients used to do work. The evolution of separate sexes to alleviate detrimental mitochondrial
mutations by recombining nuclear compensatory mutations has been a theorized result of the female-
biased mitochondrial inheritance (Havird et al., 2015; Radzvilavicius & Blackstone, 2015). The evolution
of the mitochondrial genome will be fundamentally different from the nuclear genome due to the female-
biased inheritance pattern. Because only females transmit their mitochondrial genomes to the next
generation, selection on mitochondrial polymorphism will only occur in females. As a result males are
functionally evolutionary dead ends for the mitochondria, barring male transmission which has been
documented at low levels across taxa (Dokianakis & Ladoukakis, 2014; J. Lee & Willett, 2021;
McCauley, 2013) or doubly uniparental inheritance as seen in some bivalves (Passamonti & Ghiselli,
2009). If a mitochondrial mutation arises in the population that is selectively neutral in females, but
shows negative fitness consequences for males, the variant may exist at intermediate frequency in the
population and may even become fixed (Dowling and Adrian, 2019). Further, the mutation could
increase female fitness, still to the detriment of males, which can undergo positive selection in females
resulting in mutation fixation, decreasing male fitness population wide caused by male mitochondrial
genetic load (Dowling and Adrian, 2019). Both evolutionary possibilities with neutral or positive female
benefits are described as the mother’s curse (MC) hypothesis (Frank & Hurst, 1996; Gemmell et al.,
2004).
77
The sex-specific effects of mitochondrial variation have garnered much attention in recent years.
The prediction that mitochondrial variation should confer greater variation for fitness related traits in
males has at best mixed support. One of the first empirical confirmations of the prediction comes from a
gene expression study in fruit flies wherein mitochondrial variation showed a greater effect on male gene
expression variation (Innocenti et al., 2011). Further work, all in fruit flies, showed empirical support for
MC predictions through male mitochondrial effects on sterility (Clancy et al., 2011), fertility (Patel et al.,
2016; Yee et al., 2013), and aging (Camus et al., 2012). Conversely, other fruit fly studies have found
mitochondrial variance to have equivalent or even greater effects on female traits (Đorđević et al., 2017;
Immonen et al., 2016; Mossman, Biancani, et al., 2016; Mossman, Tross, et al., 2016).
Intrapopulation nuclear mutation could result in compensatory changes ameliorating male
harming mitochondrial genetic load (Dowling & Adrian, 2019). Yet, the rate of nuclear compensatory
evolution will be dramatically small and may be ineffective. Wade (2014) describes a few reasons as to
why the nuclear compensatory evolution will be nearly negligible; (i) fitness of the compensatory nuclear
allele will only be under selection in males, not females, and (ii) only males with the male harming
mitochondria and nuclear compensatory mutation exhibit the fitness advantage. While inefficient, when
nuclear compensatory mutations are modeled, male harming genetic load depends on population size
illustrating the importance of demographic variation in species susceptibility to the mother’s curse and its
resolution (Connallon et al., 2018). Assortative mating (or inbreeding) can also resolve the mother’s curse
because when assortative mating occurs, male fitness influences the fitness of closely related females
allowing selection to effectively remove male harming mitochondrial variants from a genetic lineage
(Hedrick, 2012; Unckless & Herren, 2009; Wade & Brandvain, 2009). Much of the population genetic
models fail to incorporate the effects of population size and the associated effects of genetic drift (but see
Smith & Connallon, 2017), yet drift will likely play a significant role in the persistence of male harming
mitochondrial genetic variation especially when mitochondrial variation limitedly effects fitness in
females.
78
Persistent male harming mitochondrial variation may contribute to reduced population viability
because males carrying the mitochondrial mutation bear genetic load and have reduced fitness. Genetic
load being the normalized difference between mean population (or male) fitness and the maximum fitness
of an idealized population (B. Charlesworth & Charlesworth, 2010). To detect a mother’s curse variant
within wild populations experimentally, the male harming variants must be segregating. When a mother’s
curse mutation has become fixed, there is no alternative mitochondrial haplotype with which to compare;
therefore, they will go undetected experimentally. Although, the failure to detect mother’s curse variants
experimentally when no alternative haplotype is present does not preclude the possibility that mother’s
curse variants are fixed with the population experiencing decreased fitness. Therefore, when considering
conservation implications of the mother’s curse variants, one must estimate fitness deficit imposed on a
given population because of both fixed and segregating male harming genetic variants.
Understanding long-term population fitness is essential for conservationists interested in both
small and large populations but the contribution of sex-specific mitochondrial variation remains unclear.
Population size variation influences the pace of evolutionary change which, under a mother’s curse
scenario, affects the amount of genetic load. In addition to population size, sex-specific mutational effects
and the population sex ratio will influence evolutionary change altering genetic load experienced by a
population.
Here I focus on simulating the demographic control of male harming genetic load imparted by
mother’s curse variants to 1) identify which populations are tractable for experimentally investigating the
mother’s curse hypothesis, and 2) determine the cumulative load experienced by a population for a given
amount of evolutionary time. To estimate the former, a single male harming mitochondrial genetic variant
is introduced and then followed until the variant has reached fixation. Alternatively, the second approach
relies upon introducing mother’s curse variants at a given mutation rate. While the rate of mother’s curse
mutations is unknown, we are guided by mitochondrial mutation rates estimated through mutation
accumulation experiments in Drosophila melanogaster (Haag-Liautard et al., 2008). This will be an over
estimation of the mother’s curse mutation rate because experimentally only about 0.1% - 5% of mutations
79
have discernable fitness effects with the majority being mildly deleterious (Fry, 2004; Lynch et al., 2008)
and fewer having explicit sex-specific fitness effects required to meet the mother’s curse definition.
Materials and methods
(a) Overview of the simulations
To investigate the demographic control of mother’s curse (MC) variants with varied sex-specific
fitness, I estimated male harming genetic load and mother’s curse variant residence time using individual-
based forward evolutionary simulations with the SLiM3 software (Haller & Messer, 2019). The
demographic parameters of interest include the population size and sex ratio with varied sex-specific
fitness effects. The simulations are based on a Wright-Fisher model which includes non-overlapping
generations where the probability of producing offspring is directly proportional to fitness. The Wright-
Fisher model was altered to simulate non-recombining haploid genomes (i.e. mitochondrial genetics). The
individual’s fitness is calculated multiplicatively across mutations contained within the mitochondrial
genome and is proportional to the offspring contribution in subsequent generations. The simulated
genome was 20,000bp which is larger than typical mtDNA genomes, but the Tigriopus californicus
mtDNA genome is likely larger than previously reported (Burton et al., 2007) due to repeats in the control
region (C. Willett, personal communication).
To characterize which populations may be useful for experimental characterization of the MC and
determine conservation implications, I designed two different simulation types. The first set of
simulations describing populations where I expect one could detect MC experimentally, hereafter referred
to as fixation simulations, begin by defining population size, female fitness effects, male fitness effects
and the sex ratio. Then, MC variants are introduced at a frequency of 1/N in the first generation. Here,
individuals of the same sex harboring the MC mutation will have equivalent fitness. Following the
introduction of the MC variant, maternal haploid inheritance is ensured, and the sex-specific fitness is
altered based on the desired sex-specific fitness effects for individuals harboring the MC variant. If the
MC variant is lost, another is introduced at the above stated frequency, and the simulation terminates
80
when the MC variant has fixed or if no fixation occurred in 100,000 generations. For each generation, I
recorded the mean male fitness, mean female fitness and the MC variant allele frequency. For
intrapopulation studies of MC, one cannot detect the fitness effects of fixed mutations because they
impart no fitness variation therefore, experimentally, segregating mutations should be the focus.
The second type of simulations were used to determine conservation implications of the MC,
hereafter referred to as fixed-time simulations. The fixed-time simulations begin by defining mutation
rate, population size, female fitness effects, male fitness effects and the sex ratio. Here, MC variants have
a predetermined mutation rate, therefore multiple variants can exist in the population at a single time, and
the simulated populations are allowed to evolve for 10,000 generations. In the 10,000
th
generation, I
recorded MC variant frequency for all segregating variants present in the population, and for the MC
variants that went to fixation, I recorded the generation when the fixed MC variant first appeared and then
when it subsequently went to fixation.
I estimated the effects due to varied population size by simulating populations of sizes 10, 20, 50,
100, 150, 200, 250, 300, 350, 400, 450, 500. Additionally, to estimate the effects of sex specific fitness I
used female fitness values of 0.8, 0.85, 0.9, 0.95, 1.0, 1.05, 1.1, 1.15, 1.2, 1.25, and 1.3, and male fitness
values of 0.7, 0.75, 0.8, 0.85, 0.9, 0.95, and 1.0. I also investigated the effects of sex ratio with the
proportion of males set at 0.30, 0.35, 0.40, 0.45, 0.50, 0.55, 0.60, 0.65, 0.70, 0.75, 0.80, 0.85 and 0.90. In
addition, select simulations were used to characterize mutation rate effects (1e
-7
, 1e
-8
, 1e
-9
) for fixed-time
simulations. I ran 25 replicate simulations for all combinations of population size, sex ratio and sex-
specific fitness.
(b) Estimating male mitochondrial genetic load
MC variants impart male harming genetic load when they occur in a population. Genetic load is
the reduced fitness of the population when compared to the fitness of the population if all individuals had
the high-fitness genotype (Crow, 1958). To determine how the population parameters influence male
harming genetic load, I calculated male load by considering n male genotypes A 1 … A n, which have
fitnesses ω 1 … ω n, with frequencies p 1 … p n wherein the mean fitness ω bar is as follows:
81
Considering the mean fitness, genetic load (L) is
where ω max is the genotypic fitness for highest fitness genotype and for utility here is defined as the fitness
of a male not harboring MC variants. In SLiM3 fitness is multiplicative, wherein the relative fitness of all
variants in a genotype are multiplied. I calculated male mitochondrial genetic load for every fixation
simulation and fixed-time simulations to find the mean male mitochondrial genetic load over the
simulation.
Additionally, for fixed-time simulations, I estimated an analogous load parameter, detrimental
equivalents which is the average number of harming variants present in a single individual that alter
fitness (Morton, 1960). Detrimental equivalents is an extension of lethal equivalents used for non-
mortality traits (Morton, 1960).
(b) Data manipulation and plotting
All analyses were carried out in R ver. 3.5.0 (R Core Team, 2018) with the use of the tidyverse
(Wickham et al., 2019).
Results
Each simulation began with a population of an identified size, sex ratio, and sex-specific fitness,
then a MC variant was introduced in a single copy and the simulation continued until an MC variant went
𝜔 ' = , 𝜔
"
𝑝
"
#
"$!
.
Eq. 1
𝐿 =
𝜔
%&'
− 𝜔 '
𝜔
%&'
,
Eq. 2
82
to fixation (fixation simulations) or MC variants were continuously introduced with a given mutation rate
and those populations were evolved for 10,000 generations (fixed-time).
(a) Fixation simulations: Population size and male fitness effects
By analyzing simulations with equal sex ratio and neutral female fitness effects for the MC
variant, I can explore the effects of population size and male fitness effects on male mitochondrial load
and the amount of time it takes for an MC variant to go to fixation. Decreasing relative male fitness effect
increases the male harming genetic load present in the population (Eq. 2; Figure 1a; Figure A1). When the
introduced MC variant harbors deleterious fitness effects, the male harming genetic load increases with
increasing population size until the male load appears to reach an asymptote. The asymptote in load
appears to increase at higher population sizes for more deleterious effects. MC variant time until fixation
increases with increasing population size (Figure 1b). Ultimately these sets of simulations are modeling
neutral processes because no natural selection occurs in females and the segregating variants impart male
harming genetic load. The mean normalized standard deviation (coefficient of variation) for male load is
highest for small populations, yet there appears to be little to no influence of the male fitness effects
(Figure 1c) indicating greater relative variation in male load at small population sizes.
(b) Fixation simulations: Sex ratio effects
To observe the effects of altered sex ratio on male mitochondrial load and MC time until fixation,
I kept relative female fitness equivalent to one and imparted a relative fitness deficit to 0.8 for males
harboring the MC variant. At the smallest population size the male harming genetic load is minimized and
when the population size increases, male load also increases (Figure 2a; Figure A2). As the proportion of
males in the population decreases, the male harming genetic load increases. The fewer males present in
female-biased populations increases the population size and with a larger population, the MC variant will
take a longer time to go to fixation (Figure 2b), existing at higher frequencies for longer imparting more
genetic load on female-biased populations. The trend of decreased proportion males resulting in the
increase of male load appears to occur at low population size. The ordinality of sex ratio effects collapses
at larger population sizes (>50). Sex ratio effects show the largest effect on male harming mitochondrial
83
load at small population sizes. Further, MC variant time until fixation increases with increasing
population size and is dependent on sex ratio. As the sex ratio becomes more female-biased the time until
fixation increases again due to the sex ratio effect on the number of individuals transmitting their
mitochondrial genome to the subsequent generations.
(c) Fixation simulations: Female fitness effects
By keeping the sex ratio equal and male fitness effects (ω m) imparted by the MC variant constant
at 0.8, I estimated the effect of varying the relative female fitness (ω f) imparted by the MC variant on
male harming mitochondrial load and MC variant time until fixation. With neutral or positive female
fitness effects male load increases with increasing population size, and the degree of sexual antagonism
(ω f - ω m) appreciably impacts male harming genetic load especially at large population sizes (Figure 3a;
Figure A3). When the MC variant imparts negative female fitness effects at low population sizes, males
still experience load, while when the population size increases, selection can effectively remove the low
fitness female MC variants and larger populations experience decreased male load. Even when the female
fitness is maximized for my simulation conditions, the males in the simulated population do not
experience higher genetic load when compared to neutral female fitness effects.
Further, when the female effects are deleterious the time until fixation decrease and are
intermediate with positive fitness effects, while when the MC variant is neutral in females the time until
fixation increases (Figure 3b).
(d) Fixed-time simulations: Population size and male fitness effects
To determine the effect of population size and male fitness effects, I varied population size and
male fitness effects while maintaining an equal sex ratio with neutral female fitness effects. As population
size increased, the male harming genetic load (Figure 4a) and the number of detrimental equivalents
(Figure 4b) decreased. Variation in male fitness effects did not impact the total number of mutations
present but increasing the detriment to males resulted in higher load when lower fitness variants were
introduced by mutation. More mild fitness deficits in males resulted in a lower difference from the
84
maximum male fitness (Eq. 2). Male fitness effects have no bearing over the number of detrimental
equivalents and displays the neutral behavior of the MC variants (Figure 4).
(e) Fixed-time simulations: Mutation rate effects
To determine how mutation rate affects the persistence and accumulation of MC mutations, I
varied the mutation rate over three orders of magnitude (1e
-5
, 1e
-6
, 1e
-7
) for both neutral female effects and
beneficial female effects with a constant male fitness detriment. These mutation rates are guided by
mitochondrial mutation rates estimated through mutation accumulation experiments in Drosophila
melanogaster (Haag-Liautard et al., 2008), although mutations meeting the definition of the MC, wherein
they negatively affect male fitness while being neutral or beneficial to females, is expected to be lower
than the mutation rate estimated by mutation accumulation. As mutation rate increases, the male harming
mitochondrial genetic load increases and this effect is countered by an increase in population size (Figure
A4). When the effect is neutral in females and detrimental in males the accumulation of male harming
mitochondrial variants is strictly a neutral process (no selection), and load decreases with increasing
population size, while when the mother's curse variant is beneficial to females, positive selection occurs
and the load increases. Detrimental equivalents are more strongly impacted by mutation rate than the
genetic load, and the two parameters increase in a similar manner where higher mutation rate also
increases the number detrimental equivalents present in the populations (Figure A4).
(f) Fixed-time simulations: Sex ratio effects
To determine how sex ratio impacts the male detriment imparted by MC variants, I altered sex
ratio while holding sex-specific fitness consequences constant with relative male fitness at 0.8 and no
fitness effects in females. As the sex ratio, represented as the proportion of males present in the
population of a specified size, become male-biased, the load increases (Figure 5a). This parallels
observations for variation in population size where reducing the number of females lessens the number of
individuals contributing genetic material to the next generation, resulting in higher load in populations
85
with a lower size. At larger population sizes, the male-biased sex ratio slightly increases the number of
detrimental equivalents (Figure 5b).
(g) Fixed-time simulations: Female fitness effects
Variation in the relative female fitness effects influences the male harming genetic load and the
detrimental equivalents imparted on a population of a given size with an equal sex ratio and a male fitness
deficit. When population size increases, the male harming genetic load decreases for neutral or
detrimental female fitness effects (Figure 6a). When the MC variants can undergo positive selection with
a female fitness benefit, the male harming genetic load in a population of given size is highest (Figure 6).
Accordingly, when selection can act to remove the MC variants the load decreases when population size
increases, but selection fails to remove all MC variants, still imparting genetic load even when the MC
variant is detrimental to both males and females. At large population sizes, variants harming both sexes
persist due to mutational input. The load imparted on small populations is due primarily to fixed
mutations (Figure A5), while at larger population sizes segregating mutations predominate, causing
genetic load even with detrimental female fitness effects (Figure A5). The frequency of segregating MC
variant with negative female fitness effects is lower than MC variants that impart a female fitness benefit,
but the number of segregating MC variants increases with increasing population size (Figure A5). The
interplay between the frequency and number of MC variants results in the maintenance of genetic load
even in large populations.
Detrimental equivalents increase with a benefit to females while with a when the MC variants
harm females, detrimental equivalents decrease (Figure 6b). At large population sizes there are many low
frequency variants imparting load on the population, but the low frequency variants do not increase the
number of harmful fitness MC variants per individual (detrimental equivalents).
Discussion
The evolution of mother’s curse (MC) variants will be influenced by the demography of the
populations in which they arise. To address how MC variants influence the fitness of populations with
86
varied size, sex ratio and sex-specific fitness effects, I designed two different simulations. The first
addresses which populations one could expect to experimentally detect MC variants by observing
segregating dynamics of a single MC variant until it goes to fixation. The second addresses the
conservation genetics concerns of MC variants, wherein I simulate a population for a specific amount of
time and MC variants are introduced using a constant mutation rate. I show populations useful to
experimentally detect MC variants are different from those of concern for conservation geneticists.
The introduction of MC variants into a population by mutation is expected to be exceedingly rare.
Mutation accumulation experiments in Drosophila melanogaster estimate mitochondrial mutation rate at
6.2 × 10
−8
per base per generation (Haag-Liautard et al., 2008) and only a small percentage of those will
have discernable fitness effects (Fry, 2004; Lynch et al., 2008). Because of the unknown and expected
extreme low frequency of MC mutations, by tracking single introduced MC variants I show that
population size has a large control on the amount of load imparted on a population and the time a variant
takes to go to fixation. Large populations (with or without a female-biased sex ratio) where the fitness
effects are neutral in females and detrimental to males may be most suited to experimentally detect MC
variants because under those demographic conditions, the male harming load and time until fixation are
maximized. The MC variants remain in the population for longer, imparting more genetic load.
Experimentally isolating mitochondrial lines from within a population meeting the appropriate
demography and comparing sex-specific fitness among lines may provide the best opportunity to
experimentally detect an MC variant. Experimental identification of MC variants will allow us to
reductively explore how a mitochondrial mutation effects sex-specific physiologies beyond estimates of
reproductive output or longevity. Three documented nonsynonymous MC mutations which depress male
fertility in Drosophila melanogaster alter proteins involved in oxidative phosphorylation (Clancy et al.,
2011; Patel et al., 2016; Xu et al., 2008) indicating systems involved in sex-specific energetic
requirements may be particularly prone to MC mutations.
Although the rate at which MC variants will be introduced to a population through mutation is
exceedingly low, the long-term evolutionary dynamics including continued mutational input will be
87
relevant for managing populations of concern for conservation geneticists. Small populations are
particularly drift prone and may undergo inbreeding which can reduce population viability (D.
Charlesworth & Charlesworth, 1987). When exploring the accumulation of MC variants through a given
length of evolutionary time, the total male harming mitochondrial load and the number of detrimental
equivalents was largest in the smallest populations and decreased with increasing population size. Further,
when the MC variants imparted a female fitness benefit, the male harming genetic load was maximized.
Although small populations may be prone to accumulate MC variants, nearly all are fixed making
intrapopulation experimental detection difficult because no alternative haplotype exists. With a female
benefit, positive selection can act upon the MC variants increasing in frequency imparting higher amounts
of load increasing the number of detrimental equivalents. Male harming mitochondrial load is still
maintained at levels like neutral female MC variants when females experience a fitness deficit at high
population sizes. Although the genetic load is similar among neutral and negative female MC variants at
high population size, the number of detrimental equivalents is reduced when selection can remove female
harming variants. When MC variants cause female fitness decline, few variants go to fixation at large
population sizes, and the MC variants imparting genetic load occur at large numbers in low frequency.
Male-biased small populations may be prone to accumulate male harming mitochondrial genetic load
when the variant is neutral in females, while all populations wherein females receive a fitness advantage
from MC variants may accumulate male harming mitochondrial genetic load. At these small population
sizes the MC variants in males may succumb to natural selection. When populations undergo inbreeding,
male and female fitnesses within a family are interdependent meaning male fitness impacts female fitness
and selection can act to remove male harming MC variants (Wade & Brandvain, 2009) which may be a
means for resolving the MC in small populations.
The differential fitness effects among males and females and population sizes impact the
evolution mitochondrial mutations. Here, I selected, a priori, sex-specific fitness of a given mitochondrial
mutation and observed drift effects by varying population sizes. Variation in population sizes largely
contribute to the genetic load for both fixed-time and fixation simulations. Similarly, Smith & Connallon,
88
2017 varied population sizes and drew sex-specific fitness effects from a distribution, and when male-
female fitness effects are weakly correlated and population size is large, mitochondrial DNA contributed
more to male fitness variation than female. Species with large population sizes may be particularly prone
to segregating male harming mitochondrial load while in small populations MC variants are rapidly fixed.
The differential fitness effects of random mitochondrial mutations are not well characterized, and
mitochondrial mutation accumulation experiments describing the sex-specific effect of random
mitochondrial mutations have long been proposed (Frank & Hurst, 1996), but no experimental estimate
exists.
Here I show how population size, sex ratio and sex-specific fitness effects control the evolution of
MC variants. Further, populations which may be amicable to studying the mother’s curse hypothesis in
wild populations are likely those with large number of individuals like many tractable invertebrate
systems. While when considering how the demographic control of MC variants impacts conservation
genetics, small populations will likely accumulate many MC variants of which all are fixed. These results
underscore the utility of simulations in studying evolutionary hypothesis and how populations prone to
MC variant accumulation are not the same as experimentally tractable systems to investigate the MC
hypothesis.
89
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Figures and tables
Figure 4-1: The effect of male fitness variation across different population sizes on mean male
mitochondrial load (A), the mean length of time a mother’s curse variant took to become fixed in the
simulated population (B), and the coefficient of variation for the mean male mitochondrial load (bottom
left). Female fitness effect of the MC variant was equal to one (neutral in females) with an equal sex ratio.
Error bars represent the standard error of the mean (C).
A B
C
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Figure 4-2: The effect of sex ratio across population sizes on mean male mitochondrial load (A) and the
mean length of time a mother’s curse variant took to become fixed in the simulated population (B). The
MC variant reduced male fitness to a relative fitness of 0.8 and the MC variant was neutral in females.
A B
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Figure 4-3: The effect of female fitness variation across population sizes on mean male mitochondrial
load (A) and the mean time until a mother’s curse variant went to fixation (B). Simulations wherein a MC
variant failed to go to fixation were eliminated. Relative male fitness effect for the MC variant was 0.8
and the sex ratios were equal.
A B
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Figure 4-4: The effect of variation in relative male fitness effects across population sizes on male
mitochondrial load (left) and the detrimental equivalents (right). Simulations were run for 10,000
generations, sex ratios were equal, and mother’s curse variants were neutral in females.
A B
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Figure 4-5: The effect of variation in sex ratio across population sizes on male mitochondrial load (A) and
the detrimental equivalents (B). Simulations were run for 10,000 generations, and mother’s curse variants
were neutral in females and detrimental to males with a relative fitness of 0.8.
A
B
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Figure 4-6: The effect of female fitness variation across population sizes on mean male mitochondrial
load (A) and the detrimental equivalents (B). Simulations were run for 10,000 generations, mother’s curse
variants were detrimental to males with a relative fitness of 0.8, and the sex ratio was equal.
A
B
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Appendix
Figure A1: The effect of male fitness variation and population size variation on mean male mitochondrial
load (top left), the mean length of time a mother’s curse variant took to become fixed in the simulated
population (top right), the standard deviation of male load (bottom left), and the standard deviation in the
time a mother’s curse variation took to go to fixation. Female fitness effect of the mother’s curse variant
was equal to one (neutral in females) with an equal sex ratio.
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Figure A2: The effect of sex ratio across population sizes on mean male mitochondrial load (top left) and
the mean length of time a mother’s curse variant took to become fixed in the simulated population (top
right), the standard deviation of male load (bottom left), and the standard deviation in the time a mother’s
curse variation took to go to fixation. The mother’s curse variant reduced male fitness to a relative fitness
of 0.8 and the MC variant was neutral in females.
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Figure A3. The effect of female fitness variation across population sizes on mean male mitochondrial load
(top left), the mean time until a mother’s curse went to fixation (top right), the standard deviation of male
load (bottom left), and the standard deviation in the time a mother’s curse variation took to go to fixation.
Relative male fitness effect for the mother’s curse variant was 0.8 and the sex ratios were equal.
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Figure A4: The effect of mother’s curse variant mutation rate across population sizes on the
accumulation of male mitochondrial load (A) and detrimental equivalents (B; C) during a 10,000
generation simulation with neutral female fitness effects (left panel) or beneficial female fitness effects
(right panel) when the mother’s curse variant reduced male relative fitness to 0.8.
A
B C
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Figure A5: The effect of variable female fitness effects on the count distribution of fixed (A) and
segregating (B) mother’s curse variants present at the end of 10,000 generation simulations. Panel headers
indicate population size. mother’s curse variants were detrimental to males with a relative fitness of 0.8,
and sex ratio was equal.
A
B
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Figure A6: The effect of variable female fitness effects across population size on the frequency (A) and
count (B) of segregating mother’s curse variants across population sizes. mother’s curse variants were
detrimental to males with a relative fitness of 0.8, and sex ratio was equal.
A B
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CHAPTER FIVE: Mitochondrial influence on sex-specific
phenotypes within natural populations
Ben A. Flanagan and Suzanne Edmands
Abstract
Mitochondrial genetic variation can influence sex-specific fitness related traits. The matrilineal
mitochondrial inheritance pattern is theorized to result in the accumulation of male harming
mitochondrial genetic variation that is either neutral or beneficial to females. This evolutionary hypothesis
is known as the mother’s curse. While empirical investigations have focused largely on the mitochondrial
variation segregating among populations, fewer have observed the contribution of mitochondrial genetic
variation to trait variation within populations. Here, I investigate the contribution of mitochondrial genetic
variation to the variation in sex-specific longevity, development time and sex-specific reproductive output
within a single Tigriopus californicus population. First, I isolated female lineages and used mitochondrial
genome amplicon sequencing to identify unique mitochondrial haplotypes. Then using the relationship
among mitochondrial genotypes, I estimate the proportion of trait variation explained by the
mitochondrial variation. Mitochondrial variation explained a greater proportion of variation in female
longevity than in male, while I detected no sex-difference for in sex-specific reproductive output.
Mitochondrial genetic variation influences sex-specific phenotypes and these results counter the
prediction made by the mother’s curse hypotheses and support previous work in T. californicus
suggesting this species may not accumulate male harming mitochondrial genetic variation.
Introduction
Evolution by natural selection requires heritable trait variation segregating among individuals
within a population. An early mathematical model from the modern synthesis, Fisher’s fundamental
theorem, posited the rate of evolutionary change is equal to the amount of additive genetic variation in
fitness (Fisher, 1930). Therefore, for evolutionary change to occur, genetic variation must be present in
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the population. This genetic variation can be introduced to populations by mutation, although most new
mutations confer reduced fitness (Eyre-Walker & Keightley, 2007). Only about 0.1% - 5% of mutations
have detectable fitness effects with most mildly reducing fitness (Lynch 2008).
Genetic variation in mitochondrial genomes can show functional consequences. Mitochondria
perform critical cellular functions and their genome codes for genes whose products are essential for
energy and protein synthesis. Therefore, unsurprisingly, natural mitochondrial genetic variation can
influence fitness related traits within populations (Dowling et al., 2007; Rand et al., 2001), although
mitochondrial DNA was previously thought to be an appropriate molecular marker reflecting neutral
genetic diversity which was employed in many early phylogenetic studies (Avise, 1986). Further,
mitochondria may be prone to accumulate harming genetic variation because 1) they have a higher
mutation rate than the nuclear genome, 2) the effective population size of the mitochondrial genome is
approximately one-quarter of the nuclear genome making it more drift prone (Ballard & Whitlock, 2004),
and 3) recombination is infrequent with limited DNA repair mechanisms (Alexeyev et al., 2013).
Additionally, mitochondria are maternally inherited in most bilaterian animals which may
influence the sex-specific fitness effects of mitochondrial mutations. Theory predicts that if a
mitochondrial mutation arises in a population which negatively impacts male fitness but is either neutral
or beneficial to females, the mutation may undergo positive selection ultimately leading to fixation while
harming males (Frank & Hurst, 1996). For mitochondrial genomes, males are functionally evolutionary
dead ends because they do not transmit their DNA to the next generation therefore selection fails to
remove male harming mitochondrial mutations from the population. Thus, females harboring male
harming mitochondrial mutations are said to ‘curse’ their offspring, hence the name for this evolutionary
hypothesis, the mother’s curse (Gemmell et al., 2004).
One approach used to experimentally test the mother’s curse hypothesis is to introgress
mitochondrial haplotypes into the nuclear background of a different population through a series of
backcrossing to create cyto-nuclear hybrids (Dowling & Adrian, 2019). This approach disentangles the
nuclear effects from the mitochondrial effects because the mitochondria have not co-evolved with the
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alternate nuclear background. Using an alternative nuclear background may avoid the effect of nuclear
compensatory evolution restoring male fitness (Dowling & Adrian, 2019), but this approach fails to
capture the evolutionary systems in natural population in which mother’s curse variants operate. Studying
natural populations wherein appreciable mitochondrial variation exists may provide insight into the
mitochondrial control of sex-specific phenotypes.
Tigriopus californicus, a harpacticoid splashpool copepod, occupies supralittoral splash pools on
rocky headlands from Baja California through southern Alaska (Edmands, 2001). It differs from most
model systems in evolutionary biology in that it does not have sex chromosomes. Instead sex is
determined through the interplay of multiple independent loci throughout the genome (Ar-Rushdi, 1958;
B. R. Foley et al., 2013). Moreover, T. californicus is amicable to laboratory studies as generation time is
relatively short (~25 days), and T. californicus performs a mate guarding behavior where males clasp
virgin females until receptive and females store sperm and only mate once (Burton, 1985), allowing for
easily controlled crosses.
This species has limited dispersal which results in extreme genetic differentiation over short
geographic ranges (Burton, 1998; Edmands, 2001; Willett & Ladner, 2009) and mitochondrial nucleotide
divergence between populations can be greater than 20% (Barreto et al., 2018; Burton et al., 2007). Even
with high levels of genetic divergence among populations, T. californicus still maintains reproductive
compatibility across the geographic range and genetic incompatibilities arise in recombinant and non-
recombinant hybrids later than the F 1 generation (Burton, 1990; Edmands, 1999, 2008) (Burton, 1990).
Although most of the work on T. californicus has focused on the genetic variation differences among
populations to study the consequences of hybrid breakdown and mitonuclear coevolution (Barreto et al.,
2015, 2018; Ellison & Burton, 2008; Willett & Burton, 2001, 2002), substantial mitochondrial genetic
variation exists within populations. Willett and Ladner (2009) estimated fine-scale phylogeography based
upon the mitochondrial encoded cytochrome b (CYT-B) gene sequencing and observed within population
haplotype diversity ranging from 0.35 –. 0.5. The T. californicus mitochondrial genome contains 13
protein coding genes, two rRNA genes, and 22 tRNA genes (Burton et al., 2007) and the size was
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previously estimated at ~14kb, but this is likely a severe underestimate due to supernumerary complex
repeats present in the control region (C. Willett, personal communication). Across the genus, Tigriopus
maintains mitochondrial protein coding gene synteny and all genes are encoded on the same strand
(Burton et al., 2007)
Here, I experimentally determine the contribution of intrapopulation mitochondrial genetic
variation to sex-specific longevity and fitness variation by employing a single T. californicus population,
Abalone Cove, CA. First, I establish genetic lines derived from single wild caught gravid female and
sequence most of the mitochondrial genome by constructing amplicon sequencing libraries. Following
sequence analysis, I identify genetic lines with unique mitochondrial haplotypes and phenotype those
lines for sex-specific longevity and sex-specific reproductive output, a metric of fitness. I focus on these
traits because mitochondria have been implicated in the aging process (López-Otín et al., 2013) and may
influence sex differences in fitness. Finally, I estimate the proportion of sex-specific trait variation
explained by mitochondrial genetic variation to determine if there is a difference between males and
females.
Materials and methods
(a) Animal collection and iso-female line generation
Wild copepods were collected from supralittoral pools at Abalone Cove, CA (AB; 33.44 N
118.22 W), and I established isolated female lines by separating gravid females bearing egg sacs into
unique Petri dishes to generate unique mitochondrial lineages. Females were allowed to produce offspring
and to undergo full-sib mating for a minimum of three months prior to experimentation. Iso-female lines
were maintained in the same incubator at 20°C with a 12:12 light:dark cycle in Petri dishes containing
culture media consisting of natural seawater collected from Wrigley Marine Science Center at Catalina
Island, CA USA, Spirulina (Nutraceutical Science Institute, USA) and ground Tetramin fish food (Tetra
Holding Inc., USA) with each at a concentration of 0.1 g per liter of seawater.
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(b) MtDNA primer design and amplification
To amplify the mitochondrial genome in overlapping fragments (sensu Nunez & Oleksiak, 2016),
primer pairs were developed based upon a previously published Abalone Cove mitochondrial genome
(Burton et al., 2007). I designed primers using Primer-BLAST (Ye et al., 2012) to target approximately
2000 – 4000 bp overlapping fragments with a primer size of 20bp (Figure 1). The mitochondrial control
region was not included because the T. californicus control region is highly expanded including a range of
15 to 20 repeats with a modal size of 8320bp (C. Willett, personal communication). Integrated DNA
Technologies (Coralville, Iowa) synthesized the primers with standard desalting purification. The primer
annealing temperatures were optimized by gradient PCR and amplicon length was confirmed by agarose
gel electrophoresis (Table A1). PCR reaction conditions were as follows: 94ºC for 30s for initial
denaturation step, followed by denaturation at 95ºC for 30 s, annealing (Table A1) for 30 s, and extension
at 65ºC for 5 min repeated 35 times with a final extension of 65ºC for 10 min.
To extract DNA, three to five copepods from each iso-female line were incubated for 1 h at 65ºC
in 50 μL proteinase-K (200 ug/ml) cell-lysis buffer (10 mM TRIS, 50 mM KCl, 0.5% Tween 20, at pH
8.8) followed by denaturation for 15 min at 100ºC. The PCR amplifications were performed in 25uL
reactions with 2uL of DNA lysate and remaining components and final concentrations as follows:
LongAmp® Taq DNA Polymerase (New England Biolabs Inc.) at 5 units, 1x LongAmp® buffer (New
England Biolabs Inc.), 300uM dNTPs and 0.4uM both primers. All amplifications were confirmed by
agarose gel electrophoresis and quantified using Qubit™ 3 Fluorometer (Invitrogen) with the Qubit™
dsDNA HS Assay Kit (Invitrogen). Within each iso-female line, amplicons were pooled in equimolar
amounts for a total of 100ng of DNA, and the pooled amplicons were dried by Speed-Vac.
(c) MtDNA amplicon sequencing
Amplicon sequencing libraries were created according to Nunez & Oleksiak, 2016 with
modification to make use of previously synthesized oligos for double digest restriction-site associated
DNA sequencing according to Peterson et al., 2012. The dried 100ng DNA amplicon pools originating
from each iso-female line was reconstituted in 2uL of molecular grade water and then enzymatically
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fragmented by adding 0.5 uL Fragmentase® Buffer (New England Biolabs Inc.), 0.5 uL Fragmentase®
(New England Biolabs Inc.) and 2uL of molecular grade water to each sample. The samples were then
incubated at 37ºC for 30 min, and the reaction was terminated chemically by adding 45uL of a 100 mM
EDTA, 8 mM Tris solution. Following fragmentation, size selection was performed by magnetic beads at
a 0.55x concentration to bind fragments greater than 300bp to the magnetic beads (AMPure XP, Beckman
Coulter). Four microliters of 100uM P1 adapter (see Figure 1 in Peterson et al., 2012) was added to the
DNA bound to the magnetic beads and because the P1 adapter were modified from use with restriction
enzymes requiring end repair for both DNA and P1 barcode prior to ligation. Each P1 adapter contains a
unique five base pair molecular barcode used to determine sample origin during bioinformatic analysis.
Following the addition of the P1 adapter to the DNA, end repair was performed by adding 1 uL 10x
ligation buffer, 0.4 uL10 mM dNTPs, 0.25 uL T4 polynucleotide kinase (New England Biolabs Inc.), 0.25
uL T4 DNA polymerase (New England Biolabs Inc.) and 4.1 uL molecular grade water for a total of 6 uL
of end repair mix added to each sample. To perform the end repair reaction, samples were incubated at
20ºC for 30 min then the reaction was terminated by heat denaturation at 75ºC for 20 min. Following end
repair, the adapters were ligated to the DNA. To perform ligation 4 uL 100uM P2 adapter was added to
each sample. The P2 adapter was adapted from Peterson et al., 2012 to include the y-fork, but the
restriction site overhang was removed to produce a blunt end ligating terminus. Three uL ligation
mixtures were prepared by combining 0.3 uL 10x ligation buffer, 0.25 T4 DNA ligase (New England
Biolabs Inc.) and 2.45 uL of molecular grade water which were added to each sample. Ligation was
performed by incubating samples at 16ºC for 14 hrs. The sample volume was then increased to 40 uL by
adding 27 uL 0.1x TE buffer. Samples were bead cleaned again using magnetic beads (AMPure XP,
Beckman Coulter) at a 1x concentration to remove DNA fragments less than 200 bp. DNA was eluted
from the magnetic beads in 30 uL 0.1x TE. Next, samples were PCR amplified in 50 uL reactions using
an indexing primer and the PCR components include 25 uL of 2x Taq Master Mix (New England Biolabs
Inc.), 2 uL 10uM forward Illumina PCR primer 1 for a final concentration of 0.4 uM, 2 uL 10uM reverse
indexing PCR primer P2 adapter which contains a second molecular barcode, 2 uL of DNA from the
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previous step and 19 uL of molecular grade water. The libraries were PCR amplified by the following
reaction conditions: initial denaturation at 95ºC for 30 s, denaturation at 95ºC for 15 s, annealing 65ºC for
30 s, extension at 68ºC for 30 s, repeated 18x, and a final extension at 68ºC for 10 min. Following PCR
amplification, samples underwent a final clean using magnetic beads (AMPure XP, Beckman Coulter) at
0.9x and elution was performed in 40 uL 10 mM Tris, pH 8.5, 0.1 mM EDTA. The protocol results in the
mitochondrial genome being duel-indexed with molecular identifiers both upstream and downstream of
the DNA sequence of interest.
Samples were pooled prior to sequencing on a partial Illumina MiSeq (San Diego, CA USA) run
targeting 100 million reads for these libraries.
(c) Bioinformatic analysis
Sequencing reads were demultiplexed and trimmed using Cutadapt 3.5 (Martin, 2011) specifying
both the forward and reverse barcodes with a 10 minimum quality score. Demultiplexed quality filtered
reads were mapped to the AB mitochondrial genome (Burton et al., 2007) using bowtie2 v. 2.3.3.1
(Langmead & Salzberg, 2012) with the ‘very-sensitive-local’ options. Mapped reads in the sequence
alignment map format were converted to binary alignment files then sorted and merged using samtools
v.1.5 (H. Li et al., 2009). Variable sites were identified using freebayes (Garrison & Marth, 2012)
specifying haploidy with a minimum alternative fraction of 0.8 because no mtDNA should be
heterozygous and a minimum average coverage of 10.
Using identified variable sites, consensus sequences were generated for each iso-female line
using samtools consensus function (H. Li et al., 2009). Then using the ape package in R (Paradis et al.,
2004), I performed a ClustalW alignment (Larkin et al., 2007) and generated a haplotype network for all
iso-female lines and the four experimental iso-female lines.
(d) Longevity experiment
To estimate sex-specific longevity for each iso-female line, six to eight gravid females were
isolated in a petri dish at 25°C with a 12:12 light:dark cycle and monitored daily until the eggsac hatched.
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Following hatching, the dam was moved to a new petri dish to allow for the subsequent clutchs to hatch
for up to three clutches. Offspring were fed weekly and were allowed to mature until 21 days post
hatching. Twenty-one days after hatching, males were identified by their diagnostic geniculate first
antennae commonly referred to as claspers, and females and males were counted and separated into
dishes. Mortality was monitored weekly co-occurring with culture media changes which consist of natural
seawater collected from Wrigley Marine Science Center at Catalina Island, CA USA, Spirulina
(Nutraceutical Science Institute, USA) and ground Tetramin fish food (Tetra Holding Inc., USA) with
each at a concentration of 0.1 g per liter of seawater until all animals died.
(e) Sex-specific fertility estimate
For fertility experiments, six gravid females from each iso-female line were isolated in petri
dishes at 25°C with a 12:12 light:dark cycle and were monitored daily until the eggsac hatched. After
hatching, dams were removed and placed in a new dish, and this was repeated for up to three clutches per
female. The larvae underwent full-sib mating and dishes were monitored daily to estimate the time until
eggsacs were extruded (e.g. “development time”).
To estimate female fertility, twenty-one days after hatching three females from each replicate iso-
female line were isolated in new petri dishes, and the females were monitored until the eggsac hatched.
The larval nauplii were counted under a dissecting microscope to measure female hatching number.
While for male remating experiments, 21 days after hatching, three males from each replicate iso-female
line were isolated into individual petri dish with six virgin females derived from a wild Abalone Cove
stock population collected on March 3, 2022. Each experimental male and the six wild-caught females
were allowed 10 days to mate in a Petri dish. After 10 days, females were isolated into well plates and
scored for the presence or absence of any offspring indicating a successful mating. Male remating success
scored as the ratio of successful matings to the number of surviving females.
(f) Polygenic modeling
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Each trait—longevity, development time, female fertility, and male fertility— was fit to a mixed
linear model to determine the contribution of mitochondrial variation to trait variation commonly referred
to as the animal model for heritability. Here I am not estimating heritability, the contribution of additive
variance to phenotype variance, but analogously I am estimating the contribution of mitochondrial
relationship to phenotypic variability. To estimate the effect of mitochondrial variation, I first calculated a
genotype relationship matrix (GRM) by determining the proportion of variable mitochondrial sites with
alleles shared among iso-female lines. The GRM was used to associate relatedness with trait variation. To
determine how the GRM associates with trait variation, I fit a Bayesian model using the MCMCglmm R
package (Hadfield, 2010) and estimated the proportion of trait variation explained (PVE) by the GRM. Of
the four iso-female lines retained after sequencing, two shared the same mitochondrial haplotype.
Therefore, for each trait, I fit two different models for each with one iso-female line member of the shared
haplotype.
For sex-specific longevity, the PVE by mitochondrial contribution was estimated by fitting a
MCMCglmm linear mixed model with an Inverse-Gamma (V = trait variation * 0.1, nu = 1000) prior,
random effect of iso-female line with the general inverse of the GRM, and a response variable of sex-
specific death date with a Gaussian distribution. Because mortality was observed on a weekly interval,
death date was assumed to have occurred mid-week. The model was run for 500000 iterations with a 3000
burn-in period with a thinning interval of 1000 iterations to limit auto coordination and return large
samples sizes. Convergence of MCMC mixing and autocorrelation was assessed visually by examining
the MCMC trace and posterior density (Appendix I - V) in with accordance De Villemereuil, 2012. The
model outputs were used to calculate the mode and 95% credible intervals for the PVE attributed to the
mitochondrial variation by dividing the iso-female line variance component by total phenotypic variance
across each sampled chain. The development time and female fertility PVE by mitochondrial variation
was fit identically to sex-specific death date.
To estimate the PVE by mitochondrial variation for male remating success or fertility, a similar
model was fit with different priors, a covariance matrix, and a zero-inflated binomial distribution. The
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priors were Inverse-Gamma (V = 0.1, nu = 1000) and the covariance matrix contained the covariance
among the two-response variable; one with the number of successful rematings and the with the number
of unsuccessful rematings.
Results
(a) DNA sequencing
Illumina MiSeq sequencing effort yielded 8.65x10
7
unmapped demultiplexed reads while only
3.4% (2.9x10
6
) reads successfully mapped to the AB081 mitochondrial reference genome from Abalone
Cove (Burton et al., 2007). The poor mapping efficiency was driven by P1 barcoded adapters ligating in
tandem without specificity during the library preparation and was confirmed bioinformatically. With a
minimum sequencing depth of 10 reads per base, 25 of the 73 iso-female lines were retained and I
identified 112 variable sites among the remaining 25 iso-female lines which included 20 unique
mitochondrial haplotypes resulting in a haplotype diversity of 0.8. Of the 25 successfully sequenced iso-
female lines, four had not gone extinct in the laboratory and were available for experimentation. Five
variable sites occurred among the four experimental iso-female lines with one repeated haplotype (AB054
and AB148) including one synonymous change and four non-synonymous changes (Table 1; Figure 2).
Using the five variable sites, I estimated the GRM by calculating the proportion of shared alleles among
the four remaining iso-female lines (Table A2).
(b) Sex-specific longevity mitochondrial polygenic modeling
In all, I measured mortality for 1924 copepods which ranged from 107 to 392 individuals per sex
per iso-female line. Because two of the iso-female lines (AB054 and AB148) had the same mitochondrial
haplotype, I fit two models independently for each sex: each with one member of the repeated haplotype.
Mitochondrial variation explained a higher proportion of variation (PVE) in female longevity than in male
longevity for models fit independently to both repeated haplotype lines (Figure 3). For the model with
AB0148, the mode PVE by mitochondrial variation for female longevity was 12.9% (95% CI: 11.6% -
14.44%) while in males, mitochondrial variation only explained 9.2% (95% CI: 7.72% - 10.34%) of the
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PVE. Similarly, in the model with AB054, the PVE by mitochondrial variation in female longevity was
13.93% (95% CI: 12.59% - 13.93%), again higher than males which was estimated at 10.51% (95% CI;
9.16 – 11.81%).
(c) Development time mitochondrial polygenic modeling
The mitochondrial PVE in development time, measured as the time until the first eggsac
appeared, was non-zero indicating mitochondrial variation impacts development time. The mitochondrial
PVE 95% credible interval across both replicated mitochondrial haplotypes ranged from 4.25 % - 17.67%
(Figure 4).
(d) Sex-specific fertility mitochondrial polygenic modeling
The PVE by mitochondria in sex-specific fertility were not different among males and females. In
the model with AB0148, the mitochondrial PVE were 8.29% (95% CI: 6.43% – 11.7%) and 9.08% (95%
CI: 8.22% – 10.13%) for females and males respectively and for the model including the AB054 iso-
female line, the mitochondrial PVE were 8.3% (95% CI: 5.88% – 12.16%) and 8.87% (95% CI: 8.21% –
10.22%) for females and males respectively. For both sexes, the mitochondria PVE was greater than zero
indicating mitochondrial variation influences the variation in sex-specific reproductive output (Figure 5).
Discussion
This study the first to estimate the contribution of mitochondrial genetic variance to sex-specific
traits within T. californicus populations. The proportion of longevity variation explained by mitochondrial
genetic variation was greater in females than males and was consistent across replicated mitochondrial
haplotypes. I failed to detect any sex differences among males and females for the sex-specific fitness
related trait estimates including the number of hatched individuals for females and remating success for
males. Further, the mitochondrial haplotype diversity was high for the Abalone Cove population
estimated at 0.8, yet comparable to haplotype diversity estimated in pelagic harpacticoid copepods (Eberl
et al., 2007)
115
In addition to the high levels of genetic differentiation among T. californicus populations (Barreto
et al., 2018), here I detect high levels of haplotype diversity by sequencing the majority of the
mitochondrial genome. Single gene mitochondrial markers indicated similar levels of diversity with
haplotype diversity estimates near 0.5 (Willett & Ladner, 2009). There is limited detectable gene flow
among T. californicus populations which results in the accumulation of high levels of genetic
differentiation between populations and, although supralittoral pools can be ephemeral, T. californicus
populations show long term persistence (Burton, 1997). The ephemeral nature of the habitat does cause
short term reduction in population sizes when supralittoral rock pools dry up on a regular basis. The
stochastic variation in population size leading to localized pool extinction within a T. californicus
population occupying a single rock headland may lead to high levels of genetic diversity when extinct
pools undergo recolonization. The population expansion following splashpool recolonization can result in
strong genetic drift (Peischl et al., 2015) leading to decreased selective pressures (Gravel, 2016) which
may encourage the persistence of high levels of genetic diversity within a population through the
preservation of new mutations.
The mitochondrial haplotype diversity captured in this experiment includes both non-synonymous
and synonymous changes, and non-synonymous variants may have a larger effect on fitness related traits
(Bailey et al., 2021). Two non-synonymous changes occurred in two NADH dehydrogenase genes (nad5,
nad4l). The NADH dehydrogenase protein complex is localized to the inner mitochondrial membrane and
is a part of the electron transport chain. In humans, variants in the nad4l gene are associated with
ophthalmological diseases and body fat composition (Flaquer et al., 2014; Man et al., 2002). Because
mitochondria’s primary function is to produce large amounts of usable energy in the form of ATP from
sugars, gene variants in the cellular machinery can play large roles in affecting fitness related traits.
Altered protein structure due to non-synonymous changes within protein complexes responsible for
energy synthesis may alter the rate of oxygen consumption and subsequently the production of reactive
oxygen species leading to phenotypic consequences. Specifically, changing the production of reactive
oxygen species not only may lead to cellular macromolecule damage which may contribute to aging
116
differences, but reactive oxygen species can modify signaling molecules which mediate disease
pathologies in humans (Zhang et al., 2016). In addition to the variants in NADH dehydrogenase, I
detected two additional non-synonymous variants, one occurring in the ribosomal RNA gene and the
other occurring in a transfer RNA, both of which may alter protein synthesis. It is difficult to point to a
specific mutation leading to the altered sex-specific mitochondrial variation contributing to sex-specific
longevity variation because mitochondrial genomes are in complete linkage making association testing
which relies on recombination challenging. But here I show how variation in mitochondrial genomes
comprised of synonymous and non-synonymous mutations impacts the sex-specific variance in longevity
explained by mitochondrial variation, although I failed to detect a difference among males and females
for fitness metrics.
One prediction of the mother’s curse hypothesis is that mitochondrial variation will explain a
larger proportion of variation of phenotypic variation in males than in females (Dowling & Adrian, 2019).
Based on this prediction I do not find support for the mother’s curse hypothesis operating among the
sampled mitochondrial haplotypes from the Abalone Cove population. The contribution of mitochondrial
variation to sex-specific longevity was higher in females than in males, and I found no difference among
males and females for fitness related traits. Interpopulation cybrid T. californicus wherein the
mitochondrial genomes of multiple population are introgressed into the nuclear background of another
also failed to detect support for the mother’s curse hypothesis (Watson et al., 2022). Instead, the effects of
mitochondrial variation in longevity and fitness were larger in females than in males (Watson et al.,
2022). Sympatric mitochondrial variation in Drosophila obscura impacts fitness related traits but the
mitochondrial interaction with the nuclear genome was more influential across all fitness components
(Erić et al., 2022). Nuclear compensatory mutations may ameliorate the negative effects of male harming
mitochondrial mutations. Here, segregating nuclear variation exists within and between each experimental
iso-female line, and ideally this approach would capture the effects of nuclear variation within each
experimental iso-female line. Further, due to the specific mitonuclear genotypes where selection can act
on both the nuclear compensatory mutation and the male harming mitochondrial genotype, nuclear
117
compensatory mutations are thought to be exceedingly rare (Wade, 2014) and therefore nuclear variation
may be of limited importance. Additionally, here the results were consistent across duplicated
mitochondrial haplotypes (AB054 and AB148) indicating the effect of mitochondrial variation on the
variation in sex-specific longevity may be robust to the effects of nuclear variation, at least nuclear
variation segregating among the two repeated mitochondrial haplotypes.
Here, I found substantial mitochondrial genetic variation existing within a single T. californicus
population, and the mitochondrial genetic variation explained a greater proportion of variation in female
longevity than in male longevity while no difference in the proportion of development time variation
explained by mitochondrial variation was observed among duplicate mitochondrial haplotypes. Also, the
contribution of mitochondrial variation to variation in fitness related traits did not differ between males
and females. These results contradict the prediction of the mother’s curse hypothesis, yet still highlight
the influence of intrapopulation mitochondrial genetic variation on sex-specific longevity. Considering
the evidence presented here along with Watson et al., (2022), T. californicus mitochondrial genomes do
not appreciably accumulate male-harming mitochondrial mutations within or among populations.
Acknowledgements
We would like to thank Dr. Marc Verhulst for providing sequencing support.
Funding
This work was funded by a R. C. Lewontin Early Award from the Society for the Study of
Evolution awarded to B.A.F.
118
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Figures and tables
Figure 5-1: Tigriopus californicus AB mitochondrial genome (Burton et al., 2007; NCBI accession
NC_008831) with four overlapping amplicons used to sequence the mitochondrial genome. Genome
drawing was generated using OGDRAW web-service (Lohse et al., 2007).
Amplicon 1
Amplicon 2
Amplicon 3
Amplicon 4
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Figure 5-2: Haplotype network for experimental Tigriopus californicus iso-female lines collected from
Abalone Cove, CA. The haplotype network was based on a ClustalW (Larkin et al., 2007) alignment and
assembled using the ape package in R (Paradis et al., 2004). The AB81 genome was previously sequenced
in Burton et al., 2007 (NCBI accession NC_008831). The roman numerals indicate haplotype, circle size
represents haplotype frequency with two members of haplotype II, and each edge point is a mutational
step.
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Figure 5-3: The proportion of variation in sex-specific death date explained by mitochondrial genetic
variation, calculated using MCMCglmm. The point represents mode, and the error bars are the 95%
credible intervals. Results are presented for two models fit independently with one representative of the
repeated experimental mitochondrial haplotype (AB054 and AB148).
125
Figure 5-4: The proportion of variation in development time explained by mitochondrial genetic variation,
calculated using MCMCglmm. The point represents mode, and the error bars are the 95% credible
intervals. Results are presented for two models fit independently with one representative of the repeated
experimental mitochondrial haplotype (AB054 and AB148).
126
Figure 5-5: The proportion of variation in sex-specific fitness explained by mitochondrial genetic
variation, calculated using MCMCglmm. The point represents mode, and the error bars are the 95%
credible intervals. Results are presented for two models fit independently with one representative of the
repeated experimental mitochondrial haplotype (AB054 and AB148).
127
Table 5-1: Mitochondrial sequencing information for experimental iso-female lines. The genomic position
is relative to the previously sequenced AB81 mitochondrial genome (Burton et al., 2007; NCBI accession
NC_008831).
Mitochondrial position (bp) Mutation type Gene location Haplotype members
1686 Synonymous Transition trnD AB054, AB148
8906 Non- synonymous Transition rRNA AB118
11332 Non- synonymous Transversion nad5 AB118
12848 Non- synonymous Transition nad4l AB108
14123 Non- synonymous Transition Non-coding AB108
128
Appendix
Table A1: PCR primer sequence for mitochondrial genome sequencing
Table A2: Mitochondrial genotype relationship matrix based on allele sharing.
AB108 AB118 AB148 AB054
AB108 1 0.2 0.4 0.4
AB118 0.2 1 0.2 0.2
AB148 0.4 0.2 1 1
AB054 0.4 0.2 1 1
Target Ta Forward primer
(5’ -> 3’)
Reverse primer
(5’ -> 3’)
Amplicon 1 58°C GGGTCATCCAGGAAGTTCAGTT ATCGGGTAAGAGTAGCGTTGTC
Amplicon 2 58°C TAGAACGGAGAGGTCGGATCTT GGTCTTCTCGTCCCTGAATTGT
Amplicon 3 58°C AGCAAAGCGCTAAGCACCTAT AGGCAGACACTCATACCCCT
Amplicon 4 56°C CGTTTTTGACGTTGAGCTCCT CGTTAATCAGCCGTCAAGCG
129
Figure A1:Haplotype network for all sequenced Tigriopus californicus mitochondrial genomes from
Abalone Cove, CA. The haplotype network was based on a ClustalW (Larkin et al., 2007) alignment and
assembled using the ape package in R (Paradis et al., 2004). The AB81 genome was previously sequenced
in Burton et al., 2007 (NCBI accession NC_008831). The roman numerals indicate haplotype, circle size
represents haplotype frequency with two members of haplotype II, and each edge point is a mutational
step.
130
Figure A2: Summary plot for Markov Chain intercept and variance with a model fit to female death date.
Within each panel, the left plot is a trace of sampled posterior across chains while the left is a smoothed
histogram for the posterior. Model traces are presented for two unique models fit independently with one
representative of the repeated experimental haplotype (AB148 and AB054).
AB148 AB054
Intercept Variance
131
Figure A3: Summary plot for Markov Chain intercept and variance with a model fit to male death date.
Within each panel, the left plot is a trace of sampled posterior across chains while the left is a smoothed
histogram for the posterior. Model traces are presented for two unique models fit independently with one
representative of the repeated experimental haplotype (AB148 and AB054).
AB148 AB054
Intercept Variance
132
Figure A4: Summary plot for Markov Chain intercept and variance with a model fit to development time.
Within each panel, the left plot is a trace of sampled posterior across chains while the left is a smoothed
histogram for the posterior. Model traces are presented for two unique models fit independently with one
representative of the repeated experimental haplotype (AB148 and AB054).
AB148 AB054
Intercept Variance
133
Figure A5: Summary plot for Markov Chain intercept and variance with a model fit to male remating
success. Within each panel, the left plot is a trace of sampled posterior across chains while the left is a
smoothed histogram for the posterior. Model traces are presented for two unique models fit independently
with one representative of the repeated experimental haplotype (AB148 and AB054).
AB148 AB054
Intercept Variance
134
Figure A6: Summary plot for Markov Chain intercept and variance with a model fit to female
reproductive output. Within each panel, the left plot is a trace of sampled posterior across chains while the
left is a smoothed histogram for the posterior. Model traces are presented for two unique models fit
independently with one representative of the repeated experimental haplotype (AB148 and AB054).
AB148 AB054
Intercept Variance
135
CHAPTER SIX: Conclusion
This dissertation illustrates how mitochondria influence sex difference in aging, oxidative stress
tolerance, the evolution of male harming load, and the variation in sex-specific traits. Mitochondria are
highly dynamic organelles that produce energy and contain their own genome which can influence
numerous sex differences. Key findings include that mitonuclear interactions influence sex-specific
longevity, oxidative stressors elicit different age and sex effects, demographic processes contribute to the
evolution of male harming mitochondrial load, and mitochondrial genetic variation influences sex-
specific variation in longevity.
Mitochondrial genetic effects on sex differences
In species with discrete sexes, trait dimorphism among males and females is common.
Mitochondria are hypothesized to contribute to these sex differences through the evolution of male
harming mitochondrial variation (Frank & Hurst, 1996; Gemmell et al., 2004), and mitochondrial
malfunction may contribute to the aging phenotype (Tower, 2006). In Chapter 2, we utilized the emerging
aging model system Tigriopus californicus, to estimate the contribution of mitochondrial and nuclear
genetic effects on longevity by hybridizing inbred generic lines derived from two allopatric populations
with over 20% mitochondrial divergence. Overall, males lived longer than females, yet the sex
differences depended on both the mitochondrial and the nuclear backgrounds in the absence of sex
chromosomes. Our subsequent work showed that in a food-limited environment the mitonuclear effects
were absent, indicating that mitonuclear interactions are dependent on nutritional conditions (N. Li et al.,
2022).
Chapter 3 describes the evolution of male harming mitochondrial genetic load by using forward
evolutionary simulations. The simulations were designed to determine how population demography
influences which populations are expected to manifest experimentally detectable male harming
mitochondrial variation, and which populations may be of concern for conservation genetics because of
136
the accumulation of male harming mitochondrial variation. Population size, sex ratio and sex-specific
fitness effects control the evolution of male harming mitochondrial variants. Populations which may be
amicable to studying the mother’s curse hypothesis in wild populations are likely those with large
population sizes like many tractable invertebrate systems. While, in considering the conservation genetics
implications, small populations will likely accumulate many male harming mitochondrial variants of
which all are fixed and would go undetected experimentally.
In the final experimental chapter, I determined how mitochondrial genetic variation within a
population contributes to the variation in sex-specific longevity, development time, and sex-specific
reproductive output. I uncovered substantial mitochondrial genetic variation within a T. californicus
population, and the experimental mitochondrial genetic lines included four non-synonymous changes and
one synonymous change. The mitochondrial genetic variation explained a higher proportion of the female
longevity variation than male longevity variation which was consistent across repeated mitochondrial
haplotypes. However, there was no difference between males and females for the contribution of
mitochondrial variation to the variation in sex-specific metrics of reproductive success. These results are
consistent with our recent study (Watson et al., 2022), showing that T. californicus mitochondrial
genomes do not appreciably accumulate male-harming mitochondrial mutations within or among
populations.
Although the mitochondrial inheritance pattern has been predicted to contribute to the
accumulation of male harming mitochondrial genetic variation, we find no strong evidence suggesting
this is universal for aging in the T. californicus system while nuclear variation present among divergent
populations influences aging, but not sex-specifically.
Sex differences in age-related phenotypes
Aging manifests as the time-dependent decline in cellular function (López-Otín et al., 2013).
Mitochondria produce cytotoxic chemicals during the enzymatic synthesis of energy and as organisms
age, cellular dysfunction contributes to an increase in the production of cytotoxic chemicals like reactive
oxygen species (Harman, 1972). If reactive oxygen species concentrations exceed the reductive capacity
137
of intracellular chemicals and enzymes, oxidative stress can occur which will damage cellular
macromolecules like DNA, proteins, and lipids (Beckman & Ames, 1998). Because of the different
energetic requirements for male and females and the matrilinear mode of inheritance, mitochondria may
play a physiological role in the sex difference in age-related phenotypes. In Chapter 2, we estimated the
sex differences for oxidative DNA damage and mitochondrial DNA content across two timepoints in the
T. californicus lifespan. Young females showed the highest mitochondrial DNA content which decreased
with age, while DNA damage in males increased with age exceeding that of old females.
Under long term (N. Li et al., 2019) and short term (N. Li et al., 2020) paraquat and hydrogen
peroxide exposure, T. californicus males differentially expressed more genes than females, and the
majority of gene expression variance was partitioned between the sexes. These differentially expressed
genes include those known to respond to oxidative stress including superoxide dismutase and glutathione
S-transferase , which both showed greater upregulation in males (N. Li et al., 2019, 2020). In Chapter 3,
we determined how tolerance to two oxidative stressors, paraquat and hydrogen peroxide, changed with
age and sex. Old males and females were more sensitive to hydrogen peroxide, and overall females were
more tolerant of paraquat. Markedly, paraquat tolerance increase with age for both males and females.
The mechanism leading to the unexpected increase in paraquat tolerance is unknown and warrants further
investigation, and the results illustrate some of the challenges ahead in understanding the complex
relationship among oxidative stress, sex, and aging.
Final remarks
Emerging evidence suggests mitochondria play a role in sex differences, but the effects may not
reliably follow prediction of the mother’s curse evolutionary hypothesis. Understanding the generality of
this hypothesis requires experimental work from diverse taxa including those lacking sex chromosomes
because co-segregating sex chromosomes may confound results. Further, experimentalists need to
consider the population demographics and the difference between mitochondrial genetic variation within
and among populations to determine how mitochondria influence sex differences
138
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Abstract (if available)
Abstract
Sex differences in aging occur in many organisms with separate sexes and include sex differences in lifespan and age-associated decline in cellular function. Theory predicts degenerative aging phenotypes and mitochondrial pathologies may occur more frequently in males due to the matrilineal inheritance pattern of mitochondrial DNA observed in most eukaryotes. The female-biased inheritance pattern of mitochondria is predicted to result in the accumulation of male harming mitochondrial mutations. Using the emerging model aging system Tigriopus californicus which lacks sex chromosomes, mitochondrial effects can be more directly assessed experimentally. In estimating longevity among two reciprocal F1 hybrid crosses for inbred lines derived from two allopatric populations with over 20% mitochondrial DNA divergence, sex differences in T. californicus lifespan depended on both the mitochondrial and nuclear genetic backgrounds. Further, by determining the sex-specific oxidative stress tolerance over the T. californicus lifespan to two oxidants, oxidative stress tolerance increased with age for the oxidant, paraquat. In contrast, predictably, tolerance decreased with age for hydrogen peroxide. Then by simulating the evolution of male harming mitochondrial mutations and the population characteristics which control the accumulation of male harming genetic load, species with large population sizes may be tractable systems to experimentally identify and study male harming mitochondrial mutations, while small populations will likely accumulate male harming mitochondrial mutations. Lastly, in determining how mitochondrial genetic variation affects sex differences, I show mitochondrial variation explains more female longevity variation than male longevity variation. These findings highlight the importance of mitochondria in the evolution of sex differences and aging.
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Asset Metadata
Creator
Flanagan, Benjamin Allen
(author)
Core Title
Sex differences in aging and the effects of mitochondria
School
College of Letters, Arts and Sciences
Degree
Doctor of Philosophy
Degree Program
Biology (Marine Biology and Biological Oceanography)
Degree Conferral Date
2022-08
Publication Date
07/27/2023
Defense Date
06/16/2022
Publisher
University of Southern California
(original),
University of Southern California. Libraries
(digital)
Tag
aging,Evolution,mitochondria,OAI-PMH Harvest,sex differences
Format
application/pdf
(imt)
Language
English
Contributor
Electronically uploaded by the author
(provenance)
Advisor
Edmands, Suzanne (
committee chair
), Kenkel, Carly (
committee member
), Tower, John (
committee member
), Vermulst, Marc (
committee member
)
Creator Email
bflanaga@usc.edu,flanaganbena@gmail.com
Permanent Link (DOI)
https://doi.org/10.25549/usctheses-oUC111375274
Unique identifier
UC111375274
Legacy Identifier
etd-FlanaganBe-11023
Document Type
Dissertation
Format
application/pdf (imt)
Rights
Flanagan, Benjamin Allen
Type
texts
Source
20220728-usctheses-batch-962
(batch),
University of Southern California
(contributing entity),
University of Southern California Dissertations and Theses
(collection)
Access Conditions
The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the author, as the original true and official version of the work, but does not grant the reader permission to use the work if the desired use is covered by copyright. It is the author, as rights holder, who must provide use permission if such use is covered by copyright. The original signature page accompanying the original submission of the work to the USC Libraries is retained by the USC Libraries and a copy of it may be obtained by authorized requesters contacting the repository e-mail address given.
Repository Name
University of Southern California Digital Library
Repository Location
USC Digital Library, University of Southern California, University Park Campus MC 2810, 3434 South Grand Avenue, 2nd Floor, Los Angeles, California 90089-2810, USA
Repository Email
cisadmin@lib.usc.edu
Tags
mitochondria
sex differences