EFFECTS OF NON-STANDARD ALTERNATIVE DE NOVO MUTATIONS ON EVOLUTION OF DROSOPHILA MELANOGASTER
Michael Balinski
A Dissertation
Submitted to the Graduate College of Bowling Green State University in partial fulfillment of the requirements for the degree of
DOCTOR OF PHILOSOPHY
August 2020
Committee:
Ronny Woodruff, Advisor
Joshua Briggs Grubbs Graduate Faculty Representative
Maria Gabriela Bidart
Paul Morris
Scott Rogers ii ABSTRACT
Ronny Woodruff, Advisor
Most mutations that occur within the autosomes of eukaryotic multicellular organisms are
known to be mildly deleterious in effect, and are masked from selective pressures governing
removal and fixation by their occurrence in the heterozygous state. Genetic drift, selection, and
dominance all play a role in determining whether a mutation will be fixed or removed from a
population, and affect the ultimate fitness of the organism possessing the new mutational variant.
This understanding, however, applies primarily to mutational events occurring in autosomes during the adult phase of the organism’s life cycle. The effect of a de novo mutations on organismal fitness can differ greatly however, depending upon when in the life cycle and the ploidy of the chromosome these mutations arise in. Mutations arising in the gender with a haploid sex chromosome are immediately expressed and exposed to selective pressures in the hemizygous state, whereas mutations arising in the gender possessing diploid sex chromosomes are concealed from expression and selective forces in the heterozygous state. Due to this heterozygous condition the diploid sex-chromosomes may accumulate a large number of mildly deleterious mutations over an organisms’ life span, resulting in gender-based differences in fitness due to differences in expression and the number of mutations accumulated. Our expectations of how de novo mutations may affect organismal fitness can also be subverted by the effects of a single mutation arising in primordial germ cells (PGC) before they undergo sequestration. PGC’s sequester and suspend almost all genetic processes for a period of time before migrating to their future site of development, and it is believed that part of the reason for this sequestration is to prevent single de novo mutations from developing into cluster mutations. iii In order to understand how new mutations, affect population fitness in a variety of changing
environmental conditions, a greater understanding of conditions that can modify how new
mutations affect population fitness is needed. This work attempts to identify some of these conditions, and to detail how mutations arising in these conditions affect fitness of a population across generations. iv
I would like to dedicate this work to my teachers, and family, who helped nurture the spark of science in me and were always there to provide guidance and confidence when my own waned. v ACKNOWLEDGMENTS
I have more than a few acknowledgements to hand out, as this journey has been one of
many helping hands to be able to stand where I do now. Without their encouragement, examples, and support I would have been lost at sea a long time ago, and never have come close to
achieving these accomplishments
First and foremost, I need to thank my advisor Dr Ronny Woodruff. From being a soundboard for some of my crazier ideas, to helping me work through new methods of teaching, encouraging me before presentations, and always being there to see me on my next step in this academic journey. His creativity and curiosity have shown me how to look beyond the initial results of a finding or discovery, his drive and dedication have inspired me to continue on even when things seemed to have failed, and his knowledge has not only helped to guide me in this scientific journey but always challenged me to learn more, to never be satisfied with what I already know. Thank you for everything Ron.
Next to the members of my committee, Dr. Scott Rogers, Dr, Maria Gabriela Bidart, Dr.
Paul Morris and Dr. Joshua Briggs Grubbs. Each has brought different ideas and ways of looking at the problems I was investigating to the table, and each has influenced my teaching and research styles over the course of this program. They were always free to discuss an idea or to approach with a concern, and were a constant source of encouragement and support over the years.
I also need to thank my collaborator, and current chair of the department, Dr. Juan
Bouzat. His questions brought a depth and unique viewpoint to the study we worked on that I, in particular, lacked. Always challenging me and pushing me to defend my answers and ideas, was sometimes a difficult experience, but I feel was one that has made me a better scientist, and a more confident presenter. vi To the staff, both academic and non, of Bowling Green State University, especially Dotti
Laforce, Susan Schooner, and Chris Hess, for helping me navigate the waters of graduate
college. I sometimes came up with some very silly questions, but they were always more than
willing to provide whatever technical, administrative, and personal experience help that they
could give, always providing a sign-post throughout the university.
An especially large thank-you needs to go out to Dr. Daniel Wiegmann for his assistance
across the years with statistics and statistical testing. Several times I would have been lost in
accurately interpreting my experiments without his aid, and his guidance through a personally
difficult subject was an absolute lifesaver.
And finally, last but far far from least, I need to thank my family. My parents Theresa and
Allen Balinski, my little sister Amelia, my grandparents Edward and Joyce…. I put them all through the wringer on this journey. I never would have had a prayer of making it without their love, encouragement, advice… really there are too many things to list. Thank you for being their for me whenever I needed you guys, and for all the unconditional love and support you’ve provided. I could never have done it without you. vii
TABLE OF CONTENTS
Page
CHAPTER I: INTRODUCTION ...... 1
Dissertation research ...... 7
CHAPTER II: INCREASE IN VIABILITY DUE TO THE ACCUMULATION OF X
CHROMOSOME MUTATIONS IN DROSOPHILA MELANOGASTER MALES ...... 10
Preface...... 10
Introduction ...... 10
Materials and methods ...... 12
Results ...... 13
Discussion ...... 15
CHAPTER III: GENDER BASED MUTATION ACCUMULATION IN DROSOPHILA
MELANOGASTER COMPOUND X FEMALES AND SINGLE X MALES ...... 18
Preface...... 18
Introduction ...... 18
Materials and methods ...... 22
Drosophila crosses ...... 22
Design of mutation accumulation and control populations ...... 23
Evaluating offspring fitness ...... 24
Results ...... 25
Change in progeny numbers ...... 25
Male progeny ...... 26
Female progeny ...... 27 viii
Experimental and control sex ratios ...... 28
Effects of mutation accumulation upon eclosion rate ...... 29
Discussion ...... 30
CHAPTER IV: THE EVOLUTION OF GERM-CELL DEVELOPMENT AND
GERMINAL MOSAICS OF DELETERIOUS MUTATIONS ...... 35
Preface...... 35
Introduction ...... 35
Evidence of germinal mosaics ...... 38
Evolutionary significance of germinal mosaics ...... 40
Evolutionary role of premeiotic clusters on PGC sequestration ...... 42
CHAPTER V: CONCLUSIONS ...... 46
REFERENCES ...... 49
APPENDIX A: FIGURES FOR CHAPTER II ...... 69
APPENDIX B: FIGURES FOR CHAPTER III ...... 72
APPENDIX C: FIGURES FOR CHAPTER IV ...... 81
APPENDIX D: LETTERS OF CONSENT ...... 82 ix
LIST OF TABLES
Table Page
1 Slopes of male progeny change following 28 generations of male X-chromosome
mutation accumulation ...... 14
2 Breakdown of expected average fitness losses due to accumulation of mildly
deleterious X-chromosome mutations ...... 21
3 Regression slopes of total progeny produced for mutation accumulation (MA)
and control lines following 45 generations ...... 26
4 Results of One-way ANOVA on the effect of mutation accumulation on eclosion
time ...... 29
5 Tuckey’s post t-test with Bonferroni correction comparisons of eclosion times
between different generations of mutation accumulation ...... 30
6 One-way ANOVA on the time of eclosion differences in control lines ...... 30
7 Tuckey’s post t-test with Bonferroni correction comparisons of eclosion times
between different generations of control lines ...... 30
1
CHAPTER I: INTRODUCTION
Population level mechanisms governing the effects and expression of de novo mutations occurring within multi-cellular organisms are well known and broadly accepted. When a mutation first occurs within the autosomes of a diploid organism’s genome, the fate of that mutation is dictated by a series of forces including dominance, and selection. Dominance refers to the expression of a mutation compared to the wild-type mutation and play a vital role in the maintenance of genetic viability, as well as determining how much inbreeding depression is affecting the fitness of a population (Charlesworth and Hughes 1999, Halligan and Kieghtley
2009). Inbreeding affects population fitness by increasing the likelihood of homozygosity among both wild-type and mutated genes; this can lead to a loss of fitness through inbreeding depression, via either overdominance when heterozygotes are more fit than homozygotes, or the partially dominant hypothesis where recessive or partially recessive mutations become fixed in
the population more frequently (Charlesworth and Charlesworth 1987). Finally, selective forces
will remove members of a population that are less fit, with selection efficiency varying greatly
depending upon dominance, inbreeding depression, recombination, and chromosomal linkage.
These forces all play a role in determining whether a new mutation is fixed within the
genome of a population, or if it is removed; mutational fates only become more complex as you
move from considering the forces governing a single mutation within an individual to the
occurrence of multiple mutations in a population across multiple generations. Most mutations
are known to be only mildly deleterious in their effects upon the fitness of an organism, with
fatal or highly deleterious mutations fading from the population soon after their occurrence
(Kimura 1968, 1983; Jensen et al. 2019). The effects of deleterious mutations range from an
average decrease in fitness of -0.02% to as high as a -4% loss of fitness per mutant in studies of 2 homozygous mutations in D. melanogaster, with the exact effect depending upon mutational dominance as well as the effects of selection (Mukai 1964; Mukai et al. 1972; Simmons and
Crow 1977; Gong et al. 2005, 2006; Baer et al. 2007; Haag-Liautard et al. 2007; Halligan and
Keightley 2009; Mallet and Chippindale 2011). Work by Mukai et al. (1972) and Onishi (1977) was the first to show that there is more to the story of mutations than individual phenotypic and genotypic effects, especially if the mutation has little to no effect on fitness traits. These studies focused upon the accumulation of heterozygous mutations within the second chromosome of
Drosophila melanogaster, with the fitness of the experimental line evaluated according to models of expected fitness decline by individual mutations (Mukai 1964; Mukai et al 1972;
Onishi 1977; Keightley and Eyre-Walker 1999).
This was the first time that the effects of multiple mutations accumulating within a heterozygous diploid chromosome were examined, and while later studies would criticize several elements, they laid out the basic concepts of mutation accumulation in multicellular organisms
(Keightley 1996, Garcia-Dorado 1997). Thanks to these studies, we began to understand how the accumulation of deleterious mutations affects population fitness separately from the changes in fitness as a result of selection against individual deleterious mutations. While understanding how accumulating autosomal de novo mutations affect fitness on a population level is vital, there are still many questions to be answered as de novo mutations do not occur solely within diploid autosomes, or as a single mutational event. Ultimately, the accumulation of mutations in different regions of the genome and at different life stages is itself a fundamental force for adaptation and evolution.
Much of the early work in MA studies has focused on the accumulation of new mutations in autosomes using single celled model organisms, and generally addressing questions of 3
mutational load, evolution of sex, and mutation rates (Fisher 1930; Muller 1932; Mukai 1964;
Lynch et al. 1995; Shaw et al. 2002; Otto and Lernormand 2002; Halligan and Keightley 2009).
To address these questions mutation accumulation (MA) studies approached mutations on a
genomic level, where instead of focusing on the effect of one or two mutations leading to a
particular phenotype, research instead focus on considerations of population fitness as multiple
mutations occur and are passed along multiple generations (Muller 1950; Keightley and Eyrie-
Walker 1999; Lynch et al. 1999; Mallet 2011). The haplo-diplo life cycle of many single cell
model organisms allowed the effects of multiple mutations occurring during the haploid life-
stage to be reliably tracked, while directly comparing the fitness of organisms in the diploid
period of their life cycle to the fitness of organisms in the haploid stage as mutations accumulate.
This led to the development of theories regarding the evolutionary advantages behind sexual
reproduction, recombination, limitation of mutation rates, and the rise of sexual reproduction,
such as Muller’s ratchet (Fisher 1930; Muller 1932; Peck 1994).
It was Mukai’s work, however, that brought the discussion of accumulating mutations
and their role in evolution to the eukaryotic kingdom, investigating the effects of multiple
mutations arising in D. melanogaster (Mukai 1964; Mukai et al 1972; Onishi 1977). As de novo
mutations arise in diploid organisms, they are most often low in dominance, resulting in a
recessive deleterious mutation. These heterozygotic mutations are considered masked from
selective forces, resulting in very small effects on fitness, both deleterious and beneficial. Mukai
was the first to show the implications of mutational load, where population fitness decreases as mildly deleterious mutations accumulate within an organism’s genome (Crow and Simmons
1983; Kondrashov 1984; Lande 1998). This decrease in fitness due to the accumulation of new mutations is particularly important when mutations themselves are neutral in effect, having little 4 impact upon organismal fitness traits in the current environment. While such mutations do provide an increase in genetic diversity, potentially allowing a population to respond more effectively to environmental changes, MA studies have shown that the inability of selection to effectively remove these accumulating mutations from a diploid genome sometimes resulted in diploid populations having a lower overall fitness compared to haploid populations (Orr and Otto
1994; Mallet and Chippendale 2011; Gerstein and Otto 2011; Gerstein 2012; Sellis et al. 2016).
Questions began to rise amongst population geneticists researching rates of mutation and the effects mutations can have upon the overall fitness of a population; even in diploid organisms, not all de novo mutations occur in a heterozygous state, and not all mutations arise as single events in the population. How could genomic location, and timing of when a mutation occurred affect the fitness of a population as a whole as more mutations occurred in future generations?
To address some of these questions, one of the most straightforward methods of investigation was to consider the occurrence of mutations in different genders. De novo mutations can arise both within autosomes, and sex chromosomes (haploid in one gender, while diploid in the other in most eukaryotic species), leading to significant differences in the expression patterns of new mutations. Studies have shown that this allows gender-based responses to new environments, or sudden drastic changes in the current environment, to arise; as selective forces are able to act more efficiently in one gender as deleterious mutations arise, the population as a whole is likely to see an increase in fitness as deleterious mutations are eliminated in the haplo-X gender. This purging of deleterious mutations in one gender (a theory known as the mutational clearing house), has a second beneficial effect that is only visible when mutational load is factored into the equation (Agrawal 2001; Whitlock and Agrawal 2009; Mallet and Chippendale 2011; Roze and Otto 2011; Sharp and Agrawal 2012). 5
The male-clearing house theory proposes that this was the second evolutionarily
beneficial effect of the degradation of one sex-chromosome in what would become the haplo-X
gender; by removing minor-effect mutations that are normally masked in the heterozygous state,
the overall fitness of both genders improves (Haldane 1933). Even though the accumulation of
mutations within sex-chromosomes is likely to be a rare event among natural populations, its
likelihood grows through events such as population bottlenecks where the populations genetic
diversity can be lost. A greater focus upon the effects of mutations arising and accumulating in
locations other than diploid autosomes is needed in studies of mutations arising in multicellular
population, especially when those mutations occur in the sex-chromosomes. The current practice among such studies is to assume that when a de novo mutation occurs within the population, the effect of the mutation is the same in both genders. Multiple studies of adaptation to new environments and stressors have shown that this is not the case, and while the effects of mutations accumulating within the autosomes are reasonably well known, the effect of gender upon mutation accumulation studies is still a debated topic (Gong et al 2005, 2006; Whitlock and
Agrawal 2009; Mallet 2011; Balinski and Woodruff 2016; Woodruff and Balinski 2018; Balinski and Woodruff submitted; reviewed in Halligan and Keightly 2009; Charlesworth 2018).
Clarifying how populations are affected by the accumulation of mutations within a haploid sex- chromosome compared to a diploid sex chromosome, is therefore of vital importance to help elucidate details about the role of multiple mutations in the evolution of gender and of differential sex chromosome ploidy between those genders.
A second source of variation in the expected patterns of population fitness due to changes in the mutational load can occur within the germ cells. As population fitness can be significantly affected by a mutation occurring in the haploid or diploid sex-chromosome, depending upon 6
gender, so to can a de novo mutation arising in the genome of the germ cells before the events of
sequestration, have a surprising impact upon the future fitness of the population as a whole.
Primordial germ cells (PGC’s), before their migration to the posterior region of the developing
larva, enter into a period of senescence. During this time, these PGC’s exist in a near hibernating
state, where they do not undergo any cellular processes, including mitosis (Sonnenblick 1965;
Underwood et al 1980; Drost and Lee 1998). This is not a permanent sequestration, but instead
serves to protect against the possibilities of de novo mutations arising in the PGC’s before
gamete formation, while also preserving PGC fitness for selection events that may occur during
migration of the PGC’s (Wolpert et al 2011).
As PGC’s undergo several rounds of meiosis and mitosis to produce haploid gamete cells
in the adult organisms, newly occurring mutations in PGC’s can have a unique impact upon
population fitness. As new mutations arise in somatic cells, those mutations can usually only be
passed on to one to two daughter cells, depending upon many of the conditions already discussed. As mutations arise in the PGC’s either before or soon after the period of sequestration, however, the number of offspring that inherit the new mutations can vary drastically, from as few as 35% of offspring in some studies to around 96% of offspring in others (Woodruff et al
1996)
Known as a mutational mosaic, a single mutational event occurring the sequestered germ
cells can result in many offspring possessing a copy of that mutation. Even if this mutation is
only weakly deleterious, this can equate to several generations of the deleterious mutation
persisting among the population. The more prevalent the deleterious mutation is throughout the
population, the weaker the population will be overall, and if the mutation is sufficiently
deleterious it can possibly result in large decrease in the fitness of the population; this is 7 especially true if the mutation affects mutation rates, possibly leading to greater rates of future deleterious mutations (Woodruff and Thompson 1992; Woodruff et al 1996; Drost and Lee
1998; Selby 1998; Woodruff and Zhang 2009; Gao et al 2011, 2014; Woodruff et al 2015).
While this is not the only way in which a mutational mosaic may occur, mutations arising in the
PGC before sequestration are most likely to have a large impact on the fitness of the population as a whole due to the large number of offspring they can affect (Woodruff and Thompson 1992;
Woodruff et al 1996; Drost and Lee 1998; Selby 1998; Woodruff and Zhang 2009; Gao et al
2011, 2014). The effects of mutational load can be compounded by a mutational mosaic, particularly if the genes affected regulate rates of mutation and mutational repair. A population that was very resistant to mutational changes may suddenly seeing multiple mutations per generation within only a few generations of time due to mosaic effects. Identifying how common these mosaics are in humans will allow researchers to more accurately predict when a mosaic might occur, and if they do arise, what kind of effect they might have on the propagation and spread of genetic disorders, as well as their role in genetic elements such as the development of the molecular clock (Woodruff et al. 2015). Furthermore, identifying some of the common causes of these mosaics and the size of the effect they have had in model organisms will allow us to investigate the role that such clusters of mutations have had in the evolution of multicellular life (Thompson et al 1998; Fu and Huai 2003; Woodruff and Zhang 2009).
Dissertation research
In these studies, I sought to address the primary question of how location changes the effects of de novo mutations upon population fitness. In the first study, the effects of accumulating mutations in the haplo-X chromosome was evaluated using inbred male
Drosophila melanogaster that pass their X-chromosomes from father to son, while females were 8
constantly introduced from a standard population. This sought to provide an investigation of how
the accumulating mutations affect the fitness of males with a haplo-X chromosome, without any
environmental interactions or selective pressures that may have masked fitness changes due to
accumulating mutations (Woodruff and Balinski 2018). By examining the fitness effects of these
accumulating mutations, we were able to establish a baseline expectation of the strength and
direction of haploid male fitness change as de novo mutations arose across multiple generations.
To observe how the accumulation of de novo mutations in the haploid sex chromosome
of male D. melanogaster affected male fitness, mutations where passed from father to son each
generation, while female D. melanogaster were continually replaced from a wild-type stock to
prevent mutations from accumulating in the diploid female sex-chromosomes (Woodruff and
Balinski 2018). As mutations accumulated in the male haplo-X sex chromosome a significant positive fitness change was seen in male offspring fitness; this led to investigations of how gender and differential ploidy of the sex chromosomes in male and female D. melanogaster
disrupt the expected effects of newly occurring mildly deleterious mutations.
This investigation was carried out in a second study where the inheritance of the sex
chromosomes in male and female D. melanogaster were passed along gender lines, from father to sons, and from mothers to daughters. In this second study, new mutations accumulated in the haploid sex-chromosome in males, and in the diploid sex-chromosomes in females at the same time. Starting from a single lab-raised population, we sought to evaluate differences in fitness of male and female D. melanogaster as mutations accumulate on the sex-chromosomes in each gender (Balinski and Woodruff submitted). Crosses were designed to ensure that mutations that arose in haploid male sex chromosomes were passed from fathers to sons, while mutations arising in the diploid sex-chromosomes were maintained in the female lineage, passing from 9
mothers to daughters (Balinski and Woodruff submitted). These two studies sought to identify patterns in how the accumulation of new mutations in male and female sex-chromosomes with differential ploidy affects population fitness traits, to result in better predictions about how future
adaptational events might be disrupted by the number of mutations that are being retained in the
chromosome.
Mutations can also break from expected fitness predications when they occur during
specific points in organismal development, not just as multiple mutations accumulate across
multiple generations. In this third study we sought to propose the potential importance of clusters
of mutations in evolutionary and mutational theory. By examining how PGC are sequestered
from development and mutations early on in organismal development we sought to propose that
cluster mutations should be recognized as an underlying force in evolution of mutation rates and
in the outcome of mutational studies (Woodruff et al. 2015). Ultimately, sex chromosome
ploidy, and the possibility of cluster mutations, are not outliers that can be ignored or removed
from the investigation of mutational events and their deeper role in evolution; arguments can be
made to indicate that where and when new mutations arise in the genome have a more significant
impact on population fitness, and on adaptation to rapidly changing environments than is
currently believed. 10
CHAPTER II: INCREASE IN VIABILITY DUE TO THE ACCUMULATION OF X
CHROMOSOME MUTATIONS IN DROSOPHILA MELANOGASTER MALES
Preface This chapter was originally published in Genetica journal in 2018 (Woodruff and Balinski 2018).
It has been modified to meet the requirements for the format of a Dissertation at BGSU.
Introduction
Most mutation accumulation experiments result in reductions in fitness (usually measured
by changes in viability) due to new deleterious mutations (for reviews see, Charlesworth and
Charlesworth 1998; Lynch et al. 1999; Bataillon 2000, 2003; Baer et al. 2007; Halligan and
Keightley 2009). Some mutation accumulation experiments, however, show increases or no
changes in fitness, possibly due to new beneficial or compensatory mutations, which may be more
frequent than previously believed (Paquin and Adams 1983; Peck 1994; Hartl and Taubes 1996;
Garcia-Dorado 1997; Gilligan et al. 1997; Whitlock and Otto 1999; Poon and Otto 2000; Shaw et
al. 2002; Ajie et al. 2005; Vicoso and Charlesworth 2006; Orr 2010; Sniegowski and Gerrish 2010;
Rutter et al. 2012; Schaack et al. 2013; Woodruff 2013; Krasovec et al. 2016; Penisson et al. 2017,
and references in Azad et al. 2010; Zhang et al. 2011).
Mutation accumulation experiments using Drosophila melanogaster have focused on
collecting mutations on the autosomes (Halligan and Keightley 2009). While these studies have
given essential estimations of mutation parameters, it is also important to measure the effect of the
accumulation of mutations on the X chromosome, which in D. melanogaster are diploid in females and haploid in males. This difference in ploidy causes recessive mutations, both beneficial and deleterious, to be expressed in haplo-X (hemizygous) males, but not in diplo-X females. In addition, the expression of alleles of X-linked genes is not always the same in females and males, 11
there are over-dominant mutations that would be expressed in diplo-X females, and X-linked
deleterious mutations may be more strongly expressed in males than in females (Mallet et al. 2011;
Sellis et al. 2016). Furthermore, germinal selection against recessive deleterious mutations and
for recessive beneficial mutations may occur in haplo-X males but be absent in diplo-X females
(Otto and Hastings 1998). Beneficial mutations may also accumulate faster on X chromosomes than on autosomes, a phenomenon known as the faster-X hypothesis (Vicoso and Charlesworth
2006).
Four studies have tested the effects of X-chromosome mutation accumulation on the viability or lifespan of D. melanogaster, with conflicting results (Gong et al. 2005; Gong et al.
2006; Mallet et al. 2011; Woodruff 2013). Gong et al. (2005, 2006) investigated mutations that accumulated on the X chromosome in females and measured their effect on viability and lifespan in males. Mallet et al. (2011) examined mutations that accumulated on the X chromosome in males and measured viability in males and females. In these studies, viability and lifespan decreased over generations. In fact, Halligan and Keightley (2009) reported that there was an abnormally high mutation rate in the study by Gong et al. (2005). In contrast, however, there was an increase in fitness (average number of progeny) and early productivity over time in mutation accumulation experiments using inbred lines, where mutations could occur on both autosomes and X chromosomes (Fernandez and Lopez-Fanjul 1996; Woodruff 2013)
To help to clear up these conflicting results regarding the influence of X-linked mutations on fitness, we tested whether the accumulation of mutations on the single X chromosome of D. melanogaster males would result in decreases or increases in viability over time. Viability was predicted to decrease in hemizygous males because of the expression of recessive X-linked deleterious mutations, while remaining unchanged in diplo-X females. Contrary to our hypothesis, 12
and the results of Gong et al. (2005) and Mallet et al. (2011), viability significantly increased in
males over 28 generations. Such an increase in viability could be due to germinal selection against
deleterious mutations in germ cells and to the faster-X hypothesis, where adaptive evolution due
to recessive X-linked beneficial mutations will be faster than evolution due to autosomal mutations
(Charlesworth et al. 1987; Otto and Hastings 1998; Presgraves 2008; Vicoso and Charlesworth
2006; Baines et al. 2008; Meisel et al. 2012; Avila et al. 2014; Kousathanas et al. 2014; Payseur
2014; Casillas and Barbadilla 2017).
Materials and methods
The mating scheme in Fig. 1 was used to accumulate new mutations on the male X chromosome over 28 generations (Appendix A). Sixty lines were established the first generation
by mating one white-eyed (w1118 / Y) male from a laboratory stock with three virgin C(1)DX, y f /
Y females, taken from a laboratory stock of C(1)DX, y f / Y females and Binscy / Y males. In
subsequent generations, one male offspring from each line was randomly chosen and mated with
three virgin C(1)DX, y f females from the laboratory stock. The C(1)DX, y f chromosome has two
X chromosomes attached to a single centromere, is marked with the y (yellow body) and f (forked bristle) mutations, and consists of one normal X chromosome joined to an inverted X chromosome.
This heterozygous X-chromosome inversion prevents recovery of X-chromosome female recombinants (Sturtevant and Beadle 1936; Hawley and Ganetzky 2016). A more detailed description of the structure and genetics of the attached-X and Binscy chromosomes, and visible mutants, are discussed in Lindsley and Zimm (1992). In case of progeny failure or non-virgin
C(1)DX, y f females, back-up vials were also set up for each line; one line was lost during this study, due to a lack of progeny. After a few generations, male autosomes in each line were the 13 same as those in the C(1)DX, y f stock. Hence, only the X chromosomes in w1118 / Y males accumulated new mutations.
The G2 and subsequent generations were scored for w1118 / Y patroclinous males, which inherit their X chromosome from their fathers, and C(1)DX, y f matroclinous females, which inherit their attached-X chromosome from their mothers. One G2 w1118 / Y male from each line was then mated to three virgin C(1)DX, y f females, again taken from the C(1)DX, y f / Y female and Binscy / Y male stock, to set up the next generation. This mating scheme was repeated for
28 generations. The number of males and females was recorded for each line every generation and the male count was used as a measure of male viability. For each line after 28 generations, we regressed the number of males and females on generation and used a two-tail, one sample, t- test to compare the mean of the sample of 59 slopes to the expectation of zero. If there is a reduction in male viability, the number of males will decrease over time, whereas, if male viability increases, the number of males will increase over time. Yet, since females are taken from the C(1)DX, y f stock each generation, the number of females should remain unchanged over time.
Results
A total of 1,652 progeny counts were performed (59 lines x 28 generations), giving 43,539 total males and 32,148 total females, with a mean (±SD) progeny per generation of 26.36 ± 8.90 for males and 19.46 ± 7.37 for females. As shown in Fig. 2, the mean number of males for the 59 lines increased over 28 generations (t-test P < 0.001; slope = 0.124) (Appendix A). Hence, male viability increased significantly over time. Of the 59 lines, 46 showed a positive increase in viability versus 13 with decreased viability; the range of positive lines was 0.6962 to 0.00246, 14 whereas the range of negative lines was -0.3681 to -0.01697. In addition, beneficial mutations on average had larger effects on fitness (mean positive effect ±SD = 0.2149 ± 0.1432) than deleterious mutations (mean negative effect = -0.1462 ± -0.1042) (Table 1).
Table 1 Slopes of male progeny change following 28 generations of male X- chromosome mutation accumulation Positive slopes Negative slopes 0.6962 0.269 0.153 0.06951 -0.3681 0.5501 0.2438 0.1385 0.06787 -0.2843 0.4877 0.2438 0.1352 0.06568 -0.202 0.4209 0.2378 0.1349 0.0364 -0.1981 0.4067 0.2362 0.1344 0.02217 -0.1779 0.382 0.2198 0.1316 0.002463 -0.1754 0.3771 0.2143 0.1177 -0.1393 0.3268 0.2135 0.1117 -0.1327 0.3065 0.1959 0.1097 -0.07334 0.2843 0.1875 0.1026 -0.0613 0.2843 0.1847 0.09934 -0.04762 0.2748 0.1746 0.09825 -0.02299 0.2698 0.1568 0.09442 -0.01697 Regression slopes were calculated separately for each line following 28 generations of mutation accumulation. The average positive slope was 0.2149 calculated from 47 positive lines, indicating an increase in average male progeny of about 21.5 percent, while the average negative slope was -0.1462 calculated from 15 negative lines, indicating a decrease in average male progeny over 28 generations of about 15 percent
As predicted, however, the mean number of C(1)DX, y f females were not significantly different for the 28 generations (t-test P = 0.31; slope = 0.018)(Appendix A:Fig. 3). The results of this study that male viability increased over generations while females did not change were confirmed by comparing the viabilities of male and female progeny over the 28 generations by an unpaired t-test
(P = 0.003). 15
Discussion
This male X-chromosome mutation accumulation study resulted in a significant increase in viability over 28 generations, which was unexpected because the majority of new mutations in accumulation experiments are assumed to be recessive and deleterious, and these mutations will, therefore, be expressed in hemizygous males (Crow and Simmons 1983; Charlesworth and
Charlesworth 1998; Lynch et al. 1999). In addition, most mutation accumulation experiments resulted in a decrease in fitness. For example, Gong et al. (2005) and Mallet et al. (2011) reported that the accumulation of mutations on the X-chromosomes of D. melanogaster led to decreases in fitness. This is expected because about one new deleterious mutation occurs each generation in the haploid genome of D. melanogaster, giving about 0.16 new deleterious mutations per X chromosome (about 0.16 of the haploid genome) each generation, with each new mutation reducing fitness by about three percent (Adams et al. 2000; Haag-Liautard et al. 2007; Halligan and Keightley 2009). This would result in every line in this study containing more than four new deleterious mutations on each male X chromosome by 28 generations, leading to an expected loss of fitness of about 12 percent per line.
Some studies, including the current results, have reported, however, that the accumulation of mutations in Drosophila, Arabidopsis, Daphnia, Saccharomyces, and algae species can lead to fitness increases over time (Paquin and Adams 1983; Fernandez and Lopez-Fanjul 1996; Garcia-
Dorado 1997; Bataillon 2000, 2003; Zeyl and DeVisser 2001; Zeyl et al. 2001; Shaw et al. 2002;
Joseph and Hall 2004; Dickinson 2008; Rutter et al. 2012; Schaack et al. 2013; Woodruff 2013;
Krasovec et al. 2016). Within these studies, what genetic changes could lead to the observed increases in fitness during mutation accumulation experiments, where new deleterious mutations should be prevalent? 16
Increases in fitness observed in mutation accumulations may be caused by beneficial,
compensatory, over dominant, and back mutations, as well as by unequal recombination. Since
mutations accumulated on the single X chromosome in males in this study, over dominant
mutations and unequal recombination events were not possible. In addition, back mutations are
very rare, although they may be selected for even in the presence of deleterious mutations
(Woodruff et al. 1983; Lande 1998; Teotonio and Rose 2001; Charlesworth and Eyre-Walker
2007). Hence, the best explanation for the results of this study is that new beneficial and/or
compensatory mutations, counteracting the harmful effects of accumulated deleterious mutations,
are the cause of the observed fitness increase.
Although increases in fitness have been observed in mutation accumulation studies, it is difficult to determine which increases are due to beneficial or compensatory mutations. Full recovery of fitness in mutation accumulation lines of Caenorhabditis elegans, however, has been
attributed to compensatory mutations (Estes and Lynch 2003). Considering the effects of only
new mutations, beneficial ones would cause a sudden increase in fitness, whereas compensatory
mutations would usually act following deleterious mutations that reduce fitness, restoring fitness
to a level similar to that seen prior to the deleterious mutations (Whitlock and Otto 1999).
Another possible reason that this study did not show the expected decrease in viability at
generation 28 is germinal selection in individuals, where some X-linked deleterious mutations in
males may have been selected against, whereas X-linked beneficial mutations would be
maintained by positive selection (Muller 1954; Hastings 1991; Otto and Orive 1995; Otto and
Hastings 1998). Hence, individual selection for X-linked mutations in males that are essential
for germ-cell development and function, and against X-linked mutations that inhibit germ-cell
development, would increase male viability in this study. 17
Although the viability effects of accumulated mutations on the X chromosome compared to autosomal mutations were not examined in this study, the recovery of beneficial and/or compensatory mutations on the single X chromosome in males may also support the faster-X hypothesis. This hypothesis predicts that the accumulation of advantageous changes on the X chromosome, including recessive beneficial mutations expressed in males, would allow for faster adaptation compared to adaptation due to autosomal mutations. On the other hand, some mutations in female X chromosomes or male and female autosomes may have heterozygous advantages (Hedrick 2012; Sellis et al. 2016). With this in mind, we are currently evaluating the effect of new viability mutations over generations on the single X chromosome in males versus the two X chromosomes in sibling attached-X females. Such a study should help us to understand the adaptive role of mutations in haploids versus diploids (Otto and Gerstein 2008;
Gerstein et al. 2011; Gerstein and Otto 2011; Sellis et al. 2016, and references therein). 18
CHAPTER III: GENDER BASED MUTATION ACCUMULATION IN DROSOPHILA
MELANOGASTER COMPOUND X FEMALES AND SINGLE X MALES
Preface
This chapter is currently under review by Genetica journal for a 2020 publication (Balinski and
Woodruff submitted). It has been formatted to meet the requirements for a Dissertation at BGSU.
Introduction
Deleterious mutations, and their rate of occurrence, play a key role in a variety of biological and evolutionary processes, such as the evolution and maintenance of ploidy levels, sexual reproduction, degeneration of the Y chromosome, DNA repair, and senescence (reviews of this topic can be found in (Lynch et al. 1995, 1998; Charlesworth and Charlesworth 1998;
Lynch et al. 1999; Kneightly and Eyre-Walker 1999; Gong et al. 2005; Baer et al. 2007; Otto and
Gerstein 2008; Sellis et al. 2011, 2016; McDonald et al. 2016). Drosophila melanogaster are often used as test subjects in studies of the influence of mutations on viability, and other measures of fitness, with most studies focusing upon the effects of accumulating autosomal deleterious mutations. Many contradictions exist on the nature of these effects, including mutational rates, the dominance of deleterious mutations, and the frequency of beneficial mutations (Muller 1950; Mukai 1964; Crow 1970, 1992; Mukai et al. 1972; Onishi 1977;
Simmons and Crow 1977; Caballero et al. 2002; Gong et al 2005; Halligan and Kneightly 2009;
Zhang et al. 2011; Woodruff 2013; Woodruff and Balinski 2018).
Mutations arising in the sex chromosomes represent a further level of complexity, as most sexually reproducing species exhibit differential sexual ploidy. While the sex chromosomes are passed between sexes in each generation, mutations arise within the single sex chromosome 19
(haplo-X) in males and within the two sex chromosomes (diplo-X) in females, resulting in gender-based expression patterns for these newly mutated genes. Gender-based differences in gene expression are thought to be the source of much of the variation in fitness traits between males and females, including longevity and adaptation to stressful environments (Bernstein and
Bernstein 1991; Goldstein 1992; Orr and Otto 1994; Orr 1995; Crow 1997; Drake et al. 1998;
Otto and Hastings 1998; Gong et al. 2005, 2006; Mallet and Chippindale 2011; Woodruff 2013;
Sellis et al. 2016; Balinski and Woodruff 2017; Woodruff and Balinski 2018). Yet, few studies agree on how these differences in mutated gene expression affect fitness and fertility in haplo-X- chromosome males and diplo-X-chromosome females, demonstrating that the effects of sexual ploidy upon adaptation, evolution, and de novo mutations remain unclear. (Kondrashov and
Crow 1991; Goldstein 1992; Orr and Otto 1994; Orr 1995; Joseph and Hall 2004; Gong et al.
2005, 2006; Mallet and Chippindale 2011; Gerstien and Otto 2011; Woodruff 2013; Sellis et al.
2016; Sultanova et al. 2017; Woodruff and Balinski 2017; Woodruff and Balinski 2018; Marad et al. 2018).
The efficiency of selection and the fitness effects of de novo sex-chromosome mutations are dependent upon the sexual ploidy in which they arise (Gerstein 2012). As an example, any new recessive mutations arising within single X-chromosome males, whether deleterious or beneficial, will be immediately expressed, allowing selective pressures to be highly efficient in these haplo-X chromosome males (Gerstein 2012; Payseur 2014). This immediate expression carries risks of fitness losses due to the frequent occurrence of deleterious mutations, but also acts as the driving force of the faster-X evolution theory (Charlesworth et al. 1987; Anderson et al. 2004; Meisel et al. 2012). In addition, the improved selection efficiency that drives faster-X evolution is theorized to also offset the effects of accumulating deleterious mutations in the 20
diplo-X female chromosomes. Deleterious mutations, masked in the heterozygous state in diplo-
X mothers, can be exposed to selective forces in haplo-X male offspring as they are expressed in the hemizygous state. This process, known as the male-clearing house theory, is believed to result in a fitness gain for females that may offset some the two-fold cost of sexual reproduction
(Redfield 1994; Hurst and Peck 1996, Whitlock and Agrawal 2009).
Increased selection efficiency, however, means that haplo-X chromosome males are frequently less fit than diplo-X chromosome females with the same recessive deleterious X- chromosome mutation. It should also be noted that while the heterozygous state of a de novo mutation in the diplo-X chromosome protects females against most effects of new recessive deleterious mutations, the difficulty of removing accumulating deleterious mutations is also significantly greater for diplo-X females compared to haplo-X males.(Otto and Gerstein 2008;
Zhang et al. 2011; Sellis et al. 2016). This means that the effects of de novo X-chromosome mutations may differ between the genders.
As shown in Table 2, D. melanogaster have around 1.2 de novo deleterious mutations per generation across their entire genome, with the X-chromosome accounting for a greater percentage of genes in the female diploid genome (~15%) than in the male diploid genome
(~8%) (Mukai 1964; Mukai et al. 1972; Simmons and Crow 1977; Gong et al. 2005, 2006; Baer et al. 2007; Haag-Liautard et al. 2007; Halligan and Keightley 2009; Mallet and Chippindale
2011). Differential X-chromosome ploidy in males and females results in roughly half the number of X-chromosome mutations in D. melanogaster males compared to females. With about
0.09 de novo mutations arising per generation in the X-chromosome of haplo-X males, a decrease in population fitness of about 0.5% can be expected per generation. Diplo-X females, in contrast, would have about 0.18 deleterious X-chromosome mutations per generation, with an 21
average decrease in heterozygous fitness of about 1.03% per generation (Simmons and Crow
1977; Drake et al. 1998; Garcia-Dorado et al. 1998; Keightley and Eyre-Walker 1999; Lynch et
al. 1999; Fry 2001; Avila and Garcia-Dorado 2002; Charlesworth et al. 2004; Gong et al. 2005;
Haag-Liautard 2007; Charlesworth 2012; reviewed in: Halligan and Keightley 2009).
Table 2 Breakdown of expected average fitness losses due to accumulation of mildly deleterious X-chromosome mutations Sexual Ploidy Haplo-X Diplo-X males females 1. X-chromosome genomic percentage ~8.23% ~15.26% 2. # of mutations per diploid genome per generation ~1.11 ~1.2 3. Average fitness reduction per generation across ~6.3% ~6.8% diploid genome due to deleterious mutations 4. Expected # X-chromosome mutations per ~0.091 ~0.183 generation 5. Expected fitness decrease per generation due to ~0.50% ~1.03% accumulating X-chromosome mutations 6. Expected fitness decrease for each de novo X- ~1.64% ~1.69% chromosome mutation
7. Expected number of de novo X-chromosome ~4.11 de novo ~8.26 de novo mutations following 45 generations of mutation mutations mutations accumulation 8. Expected loss of fitness in each line due to 45 ~23% ~46% generations of X-chromosome mutation accumulation
Therefore, we predict that after 45 generations of X-chromosome mutation
accumulation, 8.26 new deleterious mutations should arise in each compound-X female, while
haplo-X males should have 4.11 new mutations (Table 2). From this expected per generation decrease in fitness due to new X-chromosome mutations we predicted that, following 45 22
generations of mutation accumulation, we would see an average fitness loss of about 46% in
heterozygous females compared to a fitness loss of about 23% in hemizygous m ales (Table 2).
Hence, with diplo-X females accumulating twice as many X-chromosome mutations as haplo-X
chromosome males, we predict that diplo-X females would have a greater loss of fitness
following 45 generations of X-chromosome mutation accumulation than D. melanogaster males.
Materials and methods
Drosophila crosses
Two crosses were established in this study: a mutation accumulation cross of single male
and single female siblings, where de novo mutations accumulated on the X-chromosomes; and a negative control cross of multiple male and female siblings, where newly occurring X- chromosome mutations were likely to be eliminated by selection. Control lines served as a mutation accumulation comparison, as no significant changes in offspring fitness were expected
among the control crosses. Therefore, any significant changes in control line offspring fitness
could be attributed to husbandry errors instead of the accumulation of X-chromosome mutations.
Mutation accumulation (MA) lines and control lines were established using the same
stock: C(1)DX, y f /Y females mated to w1118/Y males. This stock consisted of compound diplo-
X-chromosome females, carrying the markers y (yellow bodies) and f (forked bristles), mated with haplo-X-chromosome males carrying a white-eyed mutation (w1118) (Lindsley and Zimm
1992). Female compound X-chromosomes consist of a X-chromosome fused via the centromere
region to a reversed X-chromosome; this configuration prevents female X-chromosome
recombination, while males lack recombination on all chromosomes. Females and males of this
stock both possess a Y chromosome, resulting in a unique and artificial pattern of X- 23
chromosome inheritance; males inherit their X-chromosome from their father (patroclinous inheritance), while females inherited their compound X-chromosome from their mother
(matroclinous inheritance). These stocks allow for an investigation of the effects of de novo sex-
chromosome mutations on viability when they occur in haplo-X-chromosome males compared to
diplo-X-chromosome females. All lines in this study were from a C(1)DX, y f/Y X w1118/Y stock, maintained via brother-sister inbreeding for over 200 generations. Due to this long-term inbred state, the autosomes of this parent stock are homozygous, resulting in males and females
possessing the same autosomal genetic background with autosomes passed back and forth
between sexes each generation.
Design of mutation accumulation and control populations
To establish the MA lines, five males and five females were randomly selected from the
inbred C(1)DX, y f/Y x w1118/Y stock, and mated with each other in five vials to ensure an
adequate starting population size. From these five vials, 30 MA lines were established by mating
one w1118/Y male to a single C(1)DX, y f/Y female from the same vial (brother-sister mating
scheme) (Appendix B:Fig. 1). MA lines were cleared of adults following pupation of offspring,
and all offspring were counted for 15 days after all 30 MA lines showed at least one fly.
Subsequent generations were established using a single randomly chosen brother and sister from
each MA line, taken during first offspring collections. Backup vials were established in each
generation to minimize the risk of loss of MA lines due to husbandry errors. When these backup
MA lines were required, full counts of offspring numbers from the backup MA line were made,
and a randomly chosen brother and sister were used to establish the next generation.
Nine control lines were also established as a negative mutation accumulation comparison,
each line consisting of seven males and seven females randomly chosen from the laboratory C(1) 24
DX, y f/ Y x w1118/Y stock used to establish experimental MA lines. From this laboratory stock,
seven randomly chosen males were mated to seven randomly chosen females to establish each of
the nine control lines. Each subsequent generation was established by mating seven random male
offspring to seven random female offspring from the same line. Multiple parents and subsequent
offspring within each line allowed selection pressures to eliminate less-fit offspring leading to
the prevention of X-chromosome mutations accumulating among control lines (Appendix B:Fig.
2). This allowed us to directly compare our MA lines to our control lines, and to identify changes
in MA lines that may have husbandry causes. All lines were maintained on a standard laboratory
cornmeal-yeast-agar medium.
Evaluating offspring fitness
As offspring eclosed in each MA and control line, the date of the first adult fly eclosion was recorded and used to determine eclosion times, measured as the time from first parental mating to first offspring eclosion. Once adult offspring emerged in all lines, the number of male and female offspring produced by each line was recorded over fifteen days and used to calculate the sex ratio (number males/total number of offspring) as a third measure of male offspring fitness. Each generation the total number of offspring, the number of male and female offspring,
and the sex ratio was calculated for each experimental and control line and evaluated through
regression analysis following 45 generations of mutation accumulation. In order to determine
whether the fitness of the experimental and control lines had changed as a group, the average
regression slope was calculated for the total offspring, number of male and female offspring, and
sex ratios of the 30 MA lines and the nine control lines. This average regression was then
evaluated using a one sample t-test against a regression slope of zero to determine if male and
female offspring fitness had significantly changed across 45 generations. Fitness values from the 25
first generation were excluded from our analysis as outliers due to significant changes in progeny
fitness when moved from population bottles to establish experimental lines. Eclosion times for
MA lines were analyzed by one-way ANOVA, with first mating and eclosion dates recorded
from the experiments first, 20th and 45th generations. Control lines were analyzed in the same
fashion, with first mating and eclosion times taken from the second, 40th and 45th generations for analysis and comparison to MA lines. Regression analysis, t-tests, and one-way ANOVA were
performed using the Prism 8 statistical software package.
Results
Change in progeny numbers
During 45 generations of mutation accumulation, four MA lines were lost from the original
30 established at the beginning of the experiment; losses in all cases were due either to a lack of
female progeny or adult sterility. The average number of progeny (+/- SD) produced in the 26
surviving MA lines decreased non-significantly from the beginning of the experiment, producing
an average of 49 (+/- 4.68) progeny per line in generation two compared to an average of 47 (+/-
3.65) progeny per line in generation 45 (regression slope = -0.0362, t test P = 0.437) (Appendix
B:Fig. 3). Control lines showed a non-significant increase in total progeny numbers across 45
generations, with 62 (+/- 4.65) offspring produced per line on average in the second generation
compared to an average of 66 (+/- 5.90) offspring per line in generation 45 (regression slope =
0.0867, t test P = 0.434) (Appendix B:Fig. 3). Table 3 lists regression slopes for each line across
45 generations for the 26 MA lines and nine control lines. Among MA lines, 17 produced fewer
progeny following 45 generations of mutation accumulation, while 12 showed an increase in total offspring production. In control lines, four lines decreased in total progeny numbers, while five
lines exhibited a small increase in progeny totals across 45 generations. 26
Table 3 Regression slopes of total progeny produced for mutation accumulation (MA) and control lines following 45 generations. MA GEN 45 PROGENY SLOPES CONTROL GEN 45 PROGENY SLOPES (26 lines) (nine lines) -0.08182 -0.1208 0.5821
-0.05406 -0.458 0.1579
-0.05018 0.0443 0.1856
-0.2864 -0.1089 0.08386
-0.09161 -0.05758 0.1455
-0.02029 0.2096 -0.2017
-0.06677 -0.597 -0.4505
-0.2391 -0.00412 -0.1399
-0.2436 -0.1244 0.3441
-0.1476 0.1947
0.4947 0.0243
0.2856 0.1642
0.08555 0.3078
Each cell is the regression slope of one line after 45 generations of mutation accumulation. Positive slopes indicate an increase in total offspring, while negative slopes indicate a drop in total progeny numbers.
Male progeny
The average number of male offspring produced per generation in MA lines did not significantly change over 45 generations of mutation accumulation (regression slope = -0.02842, t test P = 0.3396) (Appendix B:Fig. 4). MA lines produced an average of 29 (+/- 3.61) male offspring per line in the second generation, and an average of 28 (+/- 2.15) male offspring per 27 line in generation 45. Examining the number of male offspring produced in individual MA lines, two lines showed significant differences in the number of male progeny produced across 45 generations with one line decreasing significantly from 97 males in generation two to 18 males in generation 45 (regression slope = -0.369, t test P = 0.047) and the other producing significantly more male progeny from six males in generation two to 43 in generation 45
(regression slope = 0.323, t test P = 0.499). No significant changes in male offspring totals were observed among the remaining 24 MA lines.
In contrast to the MA lines, control lines exhibited a small non-significant increase in the average number of male offspring produced in all lines across 45 generations, from an average of
38 (+/- 2.88) males per line in generation two to an average of 42 (+/- 4.73) male progeny per line in generation 45 (regression slope = 0.0777, t test P = 0.328) (Appendix B:Fig. 4). One line did show a significant increase in the number of male offspring produced when control lines were independently evaluated, with the number of male progeny rising from 27 in the second generation to 46 in generation 45 (regression slope = 0.54, t test P = 0.0019).
Female progeny
Analyzing female offspring viability in MA lines, the average number of female progeny produced among all lines showed no significant change across 45 generations of mutation accumulation, going from an average of 20 (+/- 1.31) females produced per line in generation two to an average of 21 (+/- 1.51) females per line in generation 45 (regression slope = -0.00416, t test P = 0.832) (Appendix B:Fig. 5). Individual MA lines showed no significant change in the number of female progeny across 45 generations of mutation accumulation. 28
Control lines showed a small non-significant increase in the number of female progeny
produced across 45 generations, from an average of 24 (+/- 2.30) female offspring per line in
generation two, to 26 (+/- 3.03) females offspring per line in generation 45 (regression slope =
-0.0118, t test P = 0.827) (Appendix B:Fig. 5). Among individual control lines, no significant changes in female progeny numbers were observed in 45 generations.
Experimental and control sex ratios
MA lines showed no significant change in the average sex ratio (the ratio of male progeny to the total number of progeny produced per generation) across 45 generations, going from an average sex ratio of 55% (+/- 1.72%) male offspring among MA lines in generation two to 56%
(+/- 1.54%) male offspring in generation 45 (regression slope = -0.000058, t test P = 0.791)
(Appendix B:Fig. 6). When each MA line was independently evaluated, two lines showed a significant change in sex ratio following 45 generations of mutation accumulation. One line showed a significant decrease in sex ratio across 45 generations (regression slope = -0.0028, t test
P = 0.0231), while the second demonstrated a significant increase in sex ratios from 45% males to
67% males across 45 generations of mutation accumulation (regression slope = 0.0025, t test P =
0.0473).
In the control lines, the average sex ratio did not significantly change from the second
generation to generation 45, resulting in an average sex ratio of 62% (+/- 3.19%) male offspring
(regression slope = 0.00023, t test P = 0.631) (Appendix B:Fig. 7). When individual control lines were examined, two lines showed significant positive changes in sex ratio. One line increased from
59% males in generation two, to 65% male offspring in generation 45 (regression slope = 0.00234, 29 t test P = 0.0334), while the second line increased from 63% males in generation two to 81% males in generation 45 (regression slope = 0.00249, t test P = 0.0179).
Effects of mutation accumulation upon eclosion rate
The average time from mating of adults to eclosion of offspring (eclosion time) in MA lines was evaluated at three points: during the first generation, after 31 generations of mutation accumulation, and after 45 generations of mutation accumulation. Significant differences in eclosion times were observed over the course of 45 generations of mutation accumulation
(ANOVA P = 0.0016) (Table 4). Eclosion times in MA lines were observed to decrease significantly from generation one (16 days on average until eclosion) compared to generation 45
(14 days, Tuckey’s t test P = 0.0001) (Table 4). A smaller but still significant decrease in eclosion times was also observed between generation 31 (15 days) and generation 45 (Tuckey’s t test P =
0.0495) (Table 4, Appendix B:Fig. 8). No significant differences were seen in eclosion times between generation one and generation 31 (Tuckey’s t test P = 0.433) (Table 5).
Table 4 Results of One-way ANOVA on the effect of mutation accumulation on eclosion time. ANOVA table Sum of Squares DF MS F P value Generations of Mutation Accumulation 58.15 2 29.08 7.053 *** Residual (random) 309.2 75 4.123 Generations is a measure of how long the lines have been living under the conditions of mutation accumulation. Measurements of eclosion time were taken at generation one, generation 31, and at generation 45. 26 MA lines were analyzed, with no significant differences in the eclosion times seen between the individual lines. * = <0.05 p-value. ** = <0.01 p-value. *** = <0.001 p-value 30
Table 5 Tuckey’s post t-test with Bonferroni correction comparisons of eclosion times between different generations of mutation accumulation Comparison Mean 95% CI of diff. Adjusted P Diff. Value Beginning eclosion vs. Generation 31 eclosion 0.6923 -0.6808 to 2.065 0.4326 Beginning eclosion vs. Final eclosion 2.077 1.044 to 3.110 *** Generation 31 eclosion vs. Final eclosion 1.385 0.002420 to 2.767 * Comparison of eclosion times in MA experimental lines. Eclosion times were recorded and compared between a beginning, middle and end of experiment generation. * = <0.05 p-value. ** = <0.01 p-value. *** = <0.001 p-value
Control lines were also evaluated for changes in eclosion time, with days to eclosion
recorded at generation two (18 days until eclosion), 40 (16 days until eclosion), and 45 (16 days
until eclosion). No significant changes in control eclosion times were s een at any of the three tested
time points (ANOVA P = 0.133) (Table 6, 7) (Appendix B:Fig. 9)
Table 6 One-way ANOVA on the time of eclosion differences in control lines. ANOVA table Sum of Squares DF MS F P value Generations of Control 14.74 2 29.08 2.199 P=0.1328 Residual (random) 80.44 24 3.352 Generations is a measure of how long the lines have been living under the conditions of control lines. Measurements of eclosion time were taken at generation two, generation 40, and at generation 45. Nine control lines were analyzed, with no significant differences in the eclosion times seen between the individual lines.
Table 7 Tuckey’s post t-test with Bonferroni correction comparisons of eclosion times between different generations of control lines Comparison Mean Diff. 95% CI of diff. Adjusted P Value Generation two vs. Generation 40 1.667 -0.4886 to 3.822 0.1517 Generation two vs. Generation 45 1.444 -0.7108 to 3.600 0.2357 Generation 40 vs. Generation 45 -0.2222 -2.378 to 1.933 0.9642 Comparison of eclosion times in control lines. Eclosion times were recorded and compared between a beginning, middle and end of experiment generation.
Discussion
The accumulation of mutations on the haplo-X chromosome of male D. melanogaster and the diplo-X chromosomes of female D. melanogaster showed no significant population level 31
changes in fitness, measured as changes in offspring viability and sex ratios. Hence, our hypothesis
that, after 45 generations of mutation accumulation, haplo-X chromosome male D. melanogaster
would have greater offspring fitness when compared to diplo-X-chromosome females was not
supported. This lack of change in offspring fitness as deleterious mutations accumulated over time
indicates an evolutionary balance may exist between the effects of greater selection efficiency in
haplo-X chromosome males and the increased mutational loads experienced by diplo-X
chromosome females.
One possible explanation for this lack of significant changes in fitness, is that while beneficial mutations are known to be less common than neutral and deleterious mutations, some studies have shown they can have a significant effect on fitness (Peck 1994; Joseph and Hall 2004;
Zhang et al. 2011). In haplo-X males, a single de novo beneficial mutation may offset the fitness
losses from several deleterious mutations. This would result in males containing a rare recessive
beneficial mutation being more likely to pass that beneficial mutation on to future generations.
Males containing at least one beneficial X-chromosome mutation may be more likely to produce offspring when compared to males lacking that beneficial mutation, with the beneficial mutation possibly offsetting several deleterious mutations from previous generations (Peck 1994).
This mutation accumulation experiment was designed to negate the transfer of sex- chromosomes between genders, and to investigate the possibilities of a counter-point to the male- clearing house theory, that of a mutational collecting house. A collecting house, where de novo
rare recessive beneficial mutations could be selected for in haplo-X males, may result in fitness
increases in natural populations where males have a single X-chromosome and females have two
separate X-chromosomes. Beneficial mutations that occur in haplo-X males would return to the female genome with an increased chance of fixation in the next generation, increasing chances of 32
adaptation and survival of the population. Due to the rarity of beneficial mutations, de novo mildly
deleterious mutations arising after the fixation of a beneficial mutation in haplo-X males, could reduce or eliminate the fitness gain across several generations if the mutation was not preserved in the heterozygous state in diplo-X chromosome females (Pamilo et al. 1987; Peck 1994). In this study, D. melanogaster lines have patriclinous and matroclinous inheritance of the X- chromosome, meaning it is impossible for new beneficial mutations to move from the haplo male
X-chromosome to the diplo female X-chromosome. As mutations accumulate across generations in haplo-X males, male fitness would therefore increase whenever a rare recessive beneficial mutation occurred and then decline over several generations as deleterious mutations begin to offset the fitness increase.
This steady loss of fitness could then be further offset by the occurrence of a second beneficial mutation leading to a wave shaped pattern of fitness across multiple generations of mutation accumulation. If X-chromosomes are unable to move from males to females in each generation, this may result in the fitness of haplo-X male offspring declining from a beneficial mutation fitness peak as de novo deleterious mutations arise in the single X-chromosome. If this pattern occurs several times across multiple generations, the rise and fall of male fitness across those generations would likely be equivalent to Fisher’s principle that sex ratios will never vary far from a 1:1 ratio (Fisher 1930; Bull and Charnov 1988; Carvalho et al. 1998).
Such a wave-like pattern of male offspring fitness can also give a possible explanation for the findings in this study of significant differences in eclosion times among MA lines, while no such differences were seen in control lines raised under the same laboratory conditions. Selection rarely operates within a vacuum, with one mutation affecting a single trait. A common trade-off when selecting for greater fitness are genes affecting longevity, as the conditions that lead to 33
maximum lifespan may be different from those which maximize fertility (Smith 1958; Mockett and Sohal 2006; Travers et al. 2015). Under the antagonistic pleiotropy theory of senescence, selection for greater fitness early in life may carry a cost to fitness in old age, possibly leading for example to faster eclosion times but also earlier senescence (Smith 1958; Flatt 2011).
We also note that in the two instances of significant changes in sex ratios among MA lines, the number of female offspring produced each generation affected the sex ratio more than the number of male progeny produced. In the experimental and control lines where the sex ratio increased, the number of female progeny produced each generation decreased faster than the number of male progeny produced each generation (line 12 male regression slope = -0.030, line
12 female regression slope: -0.213). This greater decrease in fitness of female offspring lead to the
observed significant increase in male sex ratios, indicating that the fitness of female offspring
accumulating deleterious mutations on two X-chromosomes may ultimately affect sex ratios more
than male fitness. This also illustrates a possible explanation for results of increased male viability
observed in previous mutation accumulation studies (Woodruff and Balinski 2018).
Our experiments demonstrate the complexity of gender-specific fitness differences that may arise for new mutations in the haplo-X chromosome of males and the diplo-X chromosome of females. This lack of significant changes in average offspring fitness of males and females was unexpected. Germinal selection, faster-X effects, and beneficial mutations are some of the conditions that may lead to haplo-X-chromosome males being more fit than their diplo-X chromosome female siblings in any given generation. Yet, examining the two individual lines in this study that showed significant changes in sex ratios revealed that the number of mutations occurring in the sex chromosomes of diplo-X females may play a much greater role in gender- specific fitness. Future experiments are planned to investigate the effects that gender-specific 34 frequencies of mutation, due to differential sex-chromosome ploidy, have on responses to environmental stressors, continuing the work of this study using MA crosses where X- chromosomes are prevented from moving between genders. 35
CHAPTER IV: THE EVOLUTION OF GERM-CELL DEVELOPMENT AND GERMINAL
MOSAICS OF DELETERIOUS MUTATIONS
Preface This chapter was submitted to Genetica journal as a research article in 2015 (Woodruff et al
2015). The original article was formatted to meet requirements for a BGSU Dissertation.
Introduction
In many animals, such as Drosophila, nematodes, Xenopus, zebrafish and mice, a small number of primordial germ cells (PGCs) are set aside early in development. The functional significance for the early sequestration of these cells is not clear; however, mitosis and mitochondrial DNA syntheses are arrested, transcription is stopped or reduced, and the PGCs migrate later to the emerging gonads and become germ cells (Sonnenblick 1965; Nieuwkoop and
Sutasurya 1981; Michod 1997; Ikenishi 1998; Saffman and Lasko 1999; Wylie 1999; Matova and Cooley 2001; Coffman 2003; Extavour and Akam 2003; Molyneaux and Wylie 2004; Santos and Lehmann 2004; Seydoux and Braum 2006; Strome and Lehmann 2007; Cinalli et al. 2008;
Western et al. 2008; Richardson and Lehmann 2010; Wolpert et al. 2011; Saitou and Yamaji
2010; Pocha and Montell 2014). Hence, in species with germ lines, PGCs undergo fewer rounds of DNA replication and are less metabolically active than somatic cells during early development. For example, in Drosophila melanogaster the PGCs (thirty to forty pole cells derived from two to four nuclei after about 12 divisions) are the first cells to be formed at the posterior end of the embryo, and mitosis does not restart in these cells until 16 hours of development (Sonnenblick 1965; Underwood et al. 1980; Drost and Lee 1998). Similarly, in mice, mitosis is arrested in PGCs until they begin to migrate to the gonads (Saitou and Yamaji 36
2010). What could be the evolutionary advantage of sequestering non-dividing PGCs early in development?
Several explanations have been provided for the arresting of PGCs during early animal development. One possible evolutionary advantage of setting the non-dividing PGCs aside and having them migrate to a new position in the embryo later in development is that there may be selection for the healthiest cells through differential survival during the cell migration process
(Wolpert et al. 2011). For example, about one half of PGCs of Drosophila have been shown to be lost during this migration, leaving about 50 PGCs in each of the female gonads and about 36
PGCs in each of the male gonads (Drake et al. 1998; Drost and Lee 1998; Coffman 2003). The cell environment, including transcription arrest, has also been shown to inhibit the differentiation of the PGCs into somatic cells (Dixon, 1994; Wylie, 1999; Hayashi et al. 2007). There are genes expressed in PGCs that are essential for the migration and fate maintenance of these cells, and there are genes that are repressed in PGCs by epigenetic changes (Coffman et al. 2002; Raz
2003; Deshpande et al. 2007; Hayashi et al. 2007; Hemberger et al. 2009; Richardson and
Lehmann 2010). In addition, mitotic inertness in PGCs may prevent the dilution of cytoplasmic maternal factors during cell divisions, which have been demonstrated to influence the developmental fate of cells (Matova and Cooley 2001).
A commonly cited advantage for the sequestration of PGCs is the protection of mitotically inactive germ line from new mutations that cause somatic cell evolution, including cancer and the expression of somatic differentiation genes (Buss 1987; Seydoux and Braun 2006;
Cinalli et al. 2008; Strome and Lehmann 2007; Frank 2010). For example, setting PGCs aside early as non-replicating cells would reduce the frequency of mutations that could convert PGCs to somatic cell development (Buss 1987; Michod 1997; Strome and Lehmann 2007). 37
Metabolically inactive cells may also have a lower rate of genetic damage in mitochondrial DNA
because of the reduction in respiration products, such as oxygen free radicals (Bechman and
Ames, 1997; Stewart and Larsson 2014).
Since the majority of mutations occur because of DNA replication errors, with fewer cell divisions (and DNA replication events) the sequestered PGCs should also have a lower number of deleterious mutations than the more rapidly dividing somatic cells during early development
(Buss 1987; Drake et al 1998; Bachvarova et al. 2009). In support of this hypothesis, germ cells have a lower mutation rate than somatic cells, partially because germinal selection reduces the load of deleterious mutations and promotes beneficial ones (Abrahamson et al. 1966; Drake et al.
1988; Otto and Hastings 1998; Walter et al. 1998; Frank 2010; Lynch 2010). Given the relatively low mutation rates reported for many genes (10-5 to 10-6), one could expect that a small reduction in the number of replication cycles would not have a significant effect on the transmission probability of mutant alleles across generations. This situation however would change if mutations tend to occur as premeiotic clusters.
Here, we propose that a significant evolutionary advantage for the sequestration of non- dividing PGCs early in development is the prevention of premeiotic clusters of mutations (i.e., germinal mosaics), which lead to the generation of multiple gametes with an identical new mutant allele within individual organisms. If a mutation occurs in a PGC, and if that cell survives migration to the gonads and germinal selection, it is expected that up to one half of the gametes from the PGC (if the mutation occurs in the first cell division) will contain the new mutation. As a consequence of these premeiotic mutations, the individual would often produce a cluster of gametes with an identical mutant allele, increasing the probability that mutations can be passed to multiple offspring (see references in Woodruff and Thompson 1992; Woodruff et al. 38
1996; Drost and Lee 1998; Selby 1998; Woodruff and Zhang 2009; Gao et al. 2011, 2014)
(Appendix C:Figure 1). If these germinal mosaics are not rare, and if the mutations are not limited to a few types (say base-pair changes), then over evolutionary time there should be selection to prevent the occurrence of clusters of deleterious mutant alleles. We propose that this may be one reason for the evolution of sequestered PGCs.
Evidence of germinal mosaics
The reports of germinal mosaics are not new. Some of the founders of modern genetics observed premeiotic clusters of mutation, including C. B. Bridges, Th. Dobzhansky, S. Wright,
R. A. Fisher, J. B. S. Haldane, H. J. Muller, T. H. Morgan, and W. E. Castle (see references in
Thompson et al. 1998). However, premeiotic clusters of mutation within individuals were usually considered as rare events. In fact, due to the low rates of mutations, many did not consider them as an important factor in evolution (Nei 2013). Furthermore, mutation studies were mainly aimed at detecting detrimental phenotypic effects rather than assessing the role of mutations in germ-line development. It was not until the early 1990s that the importance of premeiotic clusters and germinal mosaics was reassessed, particularly in relation to their potential role in evolution (Woodruff and Thompson 1992). Given the impact of germinal mosaics in increasing both the frequency of mutations in gametes and their potential transmission across generations, it was imperative to assess the prevalence of clusters of mutation across species.
After the early descriptions of premeiotic clusters, multiple studies have detected germinal mosaics in all tested organisms and in nature (see references in Woodruff and
Thompson, 1992; Bernards and Gusella 1994; Thompson et al. 1998; Campbell et al. 2014) and for every possible type of genetic change, including base-pair changes, lethal mutations, visible 39 mutations, allozyme mutations, chromosome rearrangements, nucleotide tandem repeats, indels, and aneuploidy (Chilcote et al. 1987; Hecht 1987; Edwards et al. 1992; Bunyan et al. 1994;
Cossee et al. 1997; Engel et al. 2001). To highlight the frequent occurrence of germinal mosaics, there have been over 330 reports of germinal mosaics and gonadal mosaics (germline and somatic mutations within an individual) in humans (RCW data base is available upon request), and over 20 percent of lethal and visible mutations in D. melanogaster were reported to occur in clusters (see references in Drost and Lee 1998). In addition, large germinal mosaics have been observed in numerous experimental organisms, including 96% of progeny from D. melanogaster
(69 out of 72 progeny tested), over 51% of progeny from mice (166 out of 297, and 416 out of
807 offspring), and 35% of progeny from guinea pigs (79 out of 228 progeny) (Woodruff et al.
1996). In humans, where progeny size is not large, several examples of identical mutant alleles have been reported in multiple offspring (4/4, 3/3, 3/4, 3/9, 4/7, and 4/8) (Woodruff and Zhang
2009). Furthermore, studies revealed that over 40% of sperm and oocytes from a human can have a new mutation (Edwards et al. 1992; Namikawa et al. 1995; Zhuang et al. 1996; Thompson et al. 1998; Sommer et al. 2001; Yoon et al. 2003; Woodruff and Zhang 2009).
Germinal mosaics have also been observed in silkworms, rabbits, cattle, nematodes, chickens, pigeons, barn swallows, salamanders, medaka fish, horses, pigs, honey bees, wasps, blowflies, and grasshoppers (see references in Drost and Lee 1998; Huai and Woodruff 1998;
Woodruff and Thompson 2005). In nature, large clusters of mutations have been detected in offspring of olive ridley sea turtles (9/140 progeny), green turtles (2/3 and 3/6), dollar sunfish
(11/45), pink salmon (9/50 and 4/48), pipefish (5/13, 2/33, 3/42, 2/59, and 2/9), knobbed whelks
(19/503), lizards (8/11), and mountain gorillas (2/5)(see references in Woodruff et al. 1996;
Woodruff and Zhang, 2009). To date, the evidence for the existence of germinal mosaics is 40 therefore abundant. It is clear that germinal mosaics are not rare events, they have been found for different types of genetic changes, and have been detected in all organisms tested.
Evolutionary significance of germinal mosaics
As germinal mosaics affect the relative frequency of newly emerging mutations and consequently their transmission across generations, their presence may influence both population and evolutionary theories that involve mutations. The presence of clusters can affect estimates of mutation rates and the probability of fixation of new mutant alleles (including underdominant ones), as the size of clusters influences their relative frequencies, both at the individual (size of the cluster) and population (mutation frequency) levels. Hence, several studies have now emphasized the potential role of premeiotic clusters in speciation, at least part of the overdispersed molecular clock, and the cost of natural selection (see references in Woodruff and
Zhang 2009).
One reason the significance of germinal mosaics is generally ignored is the incorrect assumption that new mutations always arise as single events. For example, the probability of fixation of new mutant alleles and the rate of base-pair substitutions usually assume that, in diploid species, a single mutant allele arises out of 2N total alleles, when it is actually c mutant alleles out of 2N total alleles, where c is the size of a cluster or the average size of clusters; c being clearly greater than one (Woodruff and Thompson 2005). Given the common nature of premeiotic clusters, all members of clusters must therefore be counted when determining mutation rates (see references in Thompson et al. 1998). This has been demonstrated theoretically by Fu and Huai (2003), who concluded that mutation rate estimates should consider the number and size of clusters. That is, multiple offspring with the same new mutant allele from one parent cannot be counted as a single mutant as suggested by Russell and Russell 41
(1996), or be ignored based on the assumption of technical artifacts (e.g., Venn et al. 2014). As an example, if three albino blue jays caused by identical mutant alleles at the base-pair level are observed in a nest, the three mutations must be counted, not just one, and certainly not zero. The chance that the three albino blue jays would have resulted from three independent base-pair changes in identical chromosomal locations is negligible. For example, Zhuang et al. (1996) observed three human siblings that had the same base-pair substitutions in the alpha1 chain of type I collagen, leading to osteogenesis imperfecta, a bone development disorder. These changes have been attributed to a germinal mosaic, since the probability that these substitutions originated from three independent mutations at the same nucleotide in these three siblings is very small, about 12 x 10-9 cubed (Kong et al. 2012).
From an evolutionary perspective, the prevention of germinal mosaics may have an important adaptive significance. As shown in Appendix C:Figure 1, the probability of inclusion of a new mutation in offspring is greatly increased if the mutation occurs before meiosis and gives rise to a cluster of gametes than if the genetic change, as usually assumed, occurs as a single event in a single gamete. If PGCs were not set-aside early in development, then there would be more deleterious mutations due to an increase in the number of cell replication cycles and, as a consequence, more germinal mosaics, reducing the evolutionary fitness of these mutant-bearing organisms. Hence, over time there would likely be selection for PGCs to be sequestered early in development.
How many more divisions, and mutations, would occur if PGCs were not sequestered early in development? Previous developmental studies in D. melanogaster allow us to estimate this number. In Drosophila there are about 12 nuclear divisions before PGCs are formed, and about 35 to 36 total divisions from zygote to sperm and 32 to 37 total divisions from zygote to 42 eggs (Sonnenblick 1965; Underwood et al. 1980; Drost and Lee 1998). Hence, there are about
20 to 25 divisions from PGC formation to gametes. As comparisons, in mice the number of divisions from zygote to sperm is 62 and the number to eggs is 25, whereas in humans it is 36 in a human male of age 13 and 24 in females (Crow 1995; Drost and Lee 1998). If a small number of extra divisions occurs in Drosophila, say three to four, and if PGCs are not sequestered early in development, there would be about a 16 percent increase in divisions between PGCs and gametes or about 10 percent increase in total cell divisions from zygote to gametes. A 10 to 16 percent increase in deleterious mutations associated with DNA replications would be a significant increase in the mutational load if PGCs were not sequestered early in development, particularly considering that it has been estimated that at least one mutation occurs per mitotic division in some higher organisms (Campbell et al. 2014).
Evolutionary role of premeiotic clusters on PGC sequestration
Given the documented prevalence of germinal mosaics, and their consequent effects on both the rates of mutations in gametes and the potential transmission of mutations across generations, we propose the hypothesis that premeiotic clusters of mutations represent an important evolutionary cost that promotes selection for the early sequestration of PGCs during development. The proposed hypothesis provides a series of predictions regarding the number and size of clusters observed in species with different number of cell divisions from zygote to gamete formation, as well as the number of clusters observed in males and females. At least four predictions can be made:
1. The average number of clusters would be correlated with the number of cell divisions
from zygote to gamete formation. That is, species with higher number of cell divisions 43
will tend to have more clusters, given that there are more opportunities for premeiotic
mutations to arise (i.e., higher number of replication events).
2. The average size of clusters would also be correlated with the number of cell divisions
from zygote to gametes, as mutations arising during earlier cycles of cell replication
would lead to larger clusters (see Appendix C:Figure 1).
3. The number of cell divisions from zygote to gametes would also be expected to differ
between males and females, since the cost (in terms of deleterious mutations) that clusters
may impose to each sex will depend on the relative investment of each sex in the
production of gametes/offspring (Trivers and Willard 1973). For example, in mammals,
since females have a greater investment than males in the production of gametes and
offspring, they would be expected to have lower number of cell divisions from zygote to
gametes than males, as detrimental mutations would impose a relatively higher fitness
cost. These differences would be less prominent in species with similar male/female
investment (e.g., in species with external fertilization like fish or Xenopus).
4. In species where sexes do differ in the number of cell divisions from zygote to gametes,
we predict that there would be corresponding differences in the number and size of 44
premeiotic clusters, since the number of replication cycles would increase the probability
of having more and larger clusters of mutation.
The existence of germinal mosaics and their documented prevalence in most species raise additional questions of evolutionary relevance. For example, it seems clear that this process is mainly relevant in species with germ-line development (i.e., metazoans), where sequestration of
PGCs decreases the probability of mutations being transmitted across generations. In
multicellular species where specialized germ cells are not set aside, such as plants, clusters may
still be present (e.g., somatic mutational mosaics have been reported in many plant species; Gill
et al. 1995). However, in these cases the transmission of deleterious mutations across
generations will likely be driven through natural selection operating at the organismal level; i.e.,
through differential survival of offspring carrying the mutations. Another question of
evolutionary relevance relates to the idea that the prevalence of germinal mosaics may likely be
dependent on the actual effects of mutations on fitness. The evolution of PGC sequestration is
based on the documented fact that most mutations tend to be deleterious; thus, from an
evolutionary perspective, decreasing the presence of clusters has a clear adaptive value. Neutral
mutations (with little or no effect on fitness) would have no effect on the evolution of PGC
sequestration; however, these mutations would probably be more prevalent in clusters since they
are less likely to be subjected to differential cell survival during germ-line development.
To our knowledge, no studies have yet been done to explore the correlation between the
relative frequency of premeiotic clusters and the number of divisions from zygote to gametes
among different species with germ-line development (i.e., studies related to Predictions 1 and 2).
However, a few studies on germ-line development in experimental species are consistent with 45
some of the predictions listed above. For example, developmental studies in mice and humans
revealed significant differences in the number of cell divisions from zygote to gametes in different sexes (Crow 1995; Drost and Lee 1998), as suggested by Prediction 3. Furthermore, the number of cell divisions from zygote to gametes was found to be consistently smaller in the females (25 cell divisions from zygote to egg versus 62 from zygote to sperm in mice; 24 from zygote to egg versus 36 to sperm in humans), as predicted by the differential investments of each sex in the production of gametes (also consistent with Prediction 3). Interestingly, in
Drosophila, where males and females have considerably smaller differential investment between sexes than mammals, the number of cell divisions from zygote to gametes has been shown to be similar between sexes (35-36 from zygote to sperm versus 32-37 from zygote to egg).
The limited number of empirical studies on germ-line development makes the testing of the proposed hypothesis unattainable at this time. However, future research on the overall frequency and size of germinal mosaics in multiple species will allow the assessment of the proposed predictions and, thus, an evaluation of the role that premeiotic clusters of mutations have played in the evolution of PGC sequestration. Given the common nature of premeiotic clusters of mutations during germ-line development, it seems clear that the sequestration of
PGCs reduces the number of DNA replication events and thus the number of deleterious
mutations that end up as germinal mosaics in gametes. This may be one reason why the
sequestration of PGCs early in development has evolved in animals. 46
CHAPTER V: CONCLUSIONS
These studies sought to address deficiencies in mutational accumulation theory by evaluating how the accumulation of mildly deleterious mutations in non-autosomal chromosome locations, and at different points in organismal development, changes the expected fitness of the population as mutations occur. General predictions can be made about the effects of mildly deleterious mutations accumulating within the autosomes of multicellular diploids, though many questions still need to be addressed. This work has attempted to investigate some of these questions, exploring the complications introduced by new mutations arising in differential ploidy of haplo-diplo sex chromosomes and the potential of new clusters of mutations arising in PGCs.
These complications make identifying how the effects of accumulating mutations alter population fitness across multiple generations difficult to decipher. As mutations arise in the haplo-diplo sex chromosomes their expression and selective effect are affected by the ploidy of the sex chromosome. As these differences can accumulate as new mutations occur, we see that the pattern of fitness change in that gender is ploidy dependent, meaning that gender can have significant effects on the fitness of a population. Results from these studies demonstrate that while overall fitness of males compared to females across generations generally averages out at a one to one ratio, significant gender-based differences in population fitness can be observed across the experimental period.
It is important to address that differential sex chromosome ploidy is not the only source of significant unexpected variations in population fitness due to de novo mutations. Cluster mutations tend to arise when a mutation occurs during a significant point in the cell cycle, as opposed to occurring in a significant location (such as the haploid male sex chromosome), and as a result, the unusual fitness changes observed when cluster mutations occur differ from when 47 mildly deleterious mutations accumulate in the number of mutations that have occurred. Cluster mutations generally consist of the same mutation occurring in multiple descendants of the organism the mutation first arose in. It can be proposed therefore, that while cluster mutations can spread through a population much faster than would be expected, they are in some ways, a more straightforward fitness change than ones that result from the accumulation of mutations in chromosomes with differential ploidy.
One of the most important aspects to take away from these studies are the differences in how mutations occurring in haplo-diplo sex chromosomes and cluster mutations are affected by selection. When a cluster mutation first appears, all progeny that inherit the mutation are likely to respond the same way to selective pressures, as the affected offspring affected by a cluster mutation all carry the same mutation. It is possible that several generations may pass before variation begins to appear among these offspring in response to the mutation, and until that happens, the mutation is very likely to change in its frequency among the population. Especially as the cluster mutation results in a large pool of offspring all carrying the relevant mutation as a heterozygote. Cluster mutations may ultimately move to fixation or elimination faster than any single mutation would be able to in a population depending upon the number of offspring that inherit a copy of the mutation from the cluster.
The fate of mutations that arise within haplo-diplo sex chromosomes, however, depends entirely upon the gender that they first appear in. If a mutation occurs within the haploid sex- chromosome then selection will be able to immediately act upon it, allowing for rapid removal of deleterious mutations, and fixation of rare beneficial mutations. When these mutations arise in a diploid sex-chromosome, then the mutation will be hidden in the heterozygous state, resulting in the potential for multiple mutations to accumulate over time in the sex chromosomes. While we 48
could reasonably expect that each of these mutations has little individual effect on population
fitness, the increasing mutation load from many mildly deleterious mutations (or even from rare
recessive beneficial mutations) will gradually result in a loss of fitness among the population.
Our studies show how the haploid sex-chromosome might act to ofe fset the ffects of mutation
accumulation in the diploid sex-chromosome, both through the selection for beneficial
mutations, and against deleterious mutants as they move between the two genders each
generation.
Ultimately the role of newly occurring mutations in evolution is still evolving in
complexity, as while we can make general predictions of how a single mutation is likely to affect
both organismal and population fitness, much work in understanding how these predictions can
be modified still needs to be done. When mutations arise before sequestration and germinal
selection in PGC’s and within sex-chromosomes with gender-based differences in iplo dy
important and multilayered changes in how the mutation(s) will affect the f itness of the organism and the population as a hole need to be expected and accounted for. As environments continue to
rapidly change as a result of anthropogenic activities, a greater understanding of expected fitness changes due to de novo mutations arising in these different contexts will be essential 49
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APPENDIX A: FIGURES FOR CHAPTER II
Fig. 1 The mating scheme that allowed for the accumulation of new mutations on the male X chromosome. Since Drosophila melanogaster XXY flies are females and XY lies are males, the C(1)DX, y f/Y G2 progeny, and subsequent generation progeny, are matroclinous females that receive their attached-X chromosome from their G1 mothers and the w1118 /Y male G2 progeny, and subsequent generation progeny, are patroclinous males that receive their X chromosome from their fathers. Hence, the single w1118 marked X chromosomes are inherited each generation only through haplo-X males. We measured the influence of new w1118 X-chromosome mutations on the fitness of males over 28 generations in 59 lines 70
Fig. 2 The mean number of males for the 59 lines for 28 generations. The P value is from a two-tail, one sample, t test comparing the mean of the sample of 59 slopes to the expectation of zero 71
Fig. 3 The mean number of females for the 59 lines for 28 generations. The P value is from a two-tail, one sample, t-test comparing the mean of the sample of 59 slopes to the expectation of zero 72
APPENDIX B: FIGURES FOR CHAPTER III
Mutation accumulation 30 lines established Generation 1: C(1)DX, y f/Y female X w1118/Y male (1 male X 1 female)
1 sibling female 1 sibling male
Mutation accumulation Generation 2: C(1)DX, y f/Y female X w1118/Y male
Continued for 45 generations, recording the # of eclosed males and females each generation Fig. 1 X-chromosome mutation accumulation breeding scheme. Each of the 30 lines established at the start of the experiment were taken from a laboratory stock (C(1)DX, y f/Y x w1118/Y), which was highly inbred for over 200 generations. This ensured that these brother/sister matings did not differ in their autosomes, while the compound-X and the Y chromosome in female D. melanogaster prevented recombination events and ensured patriclinous and matroclinous inheritance of the sex chromosomes 73
9 lines established Control 1118 Generation 1: 7 random C(1)DX, y f/Y X 7 random w /Y males (7 males X 7 females females)
Control Generation 2: 7 random C(1)DX, y f/Y X 7 random w1118/Y females males
Continued for 45 generations, recording the # of eclosed males and females each generation Fig. 2 Breeding scheme for control lines. Each line consists of seven randomly selected males and females from a laboratory stock (C(1)DX, y f/Y x w1118/Y), allowing selective pressures to play out, with more fit offspring (likely suffering from fewer mutations) being more likely to be selected. Males and females experienced the same matroclinous and patriclinous sex-chromosome inheritance patterns as MA lines, however the selective pressures in play among the larger population serves to slow the accumulation of deleterious X-chromosome mutations 74
Fig. 3 Mean number of progeny produced each generation in MA and control populations across 45 generations. Lines indicate regression analysis of how each population changed across 45
75
Fig. 4 Mean number of male progeny produced each generation in MA and control populations across 45 generations. Lines indicate regression analysis of how each population changed across 45 generations 76
Fig. 5 Mean number of female progeny produced each generation in MA and control populations over 45 generations. Lines indicate regression analysis of how the number of progeny produced in each population changed across 45 generations 77
Fig. 6 Mean sex ratio (males/total number of offspring) for MA population over 45 generations of mutation accumulation. The solid line models the best fit slope determined by regression analysis of how sex ratios changed across the 45 generations. No significant difference was observed in the mean sex ratio of the MA lines 78
Fig. 7 Mean sex ratio (males/total offspring) for control population across 45 generations. The solid line models the best fit slope determined by regression analysis of how the sex ratio changed in this population across the 45 generations. No significant difference was observed in the mean sex ratio of the control lines 79
Fig. 8 Average eclosion times for MA population measured at three time points. Eclosion times were measured as the time from oviposition until first eclosion and were measured at three time points: generations one, 31, 45. Significant difference in eclosion times were observed between generations one and 31, between generations one and 45, and between generations 31 and 45. ANOVA findings are detailed in tables 3 and 4. 80
Fig. 9 Average eclosion times for control populations measured at three time points. Eclosion times were measured as the time from oviposition until first eclosion and were measured at three time points: generations two, 41, 45. No significant differences were observed in eclosion times of control lines at the three examined generations 81
APPENDIX C: FIGURES FOR CHAPTER IV
Fig. 1 The consequence of mutation occurring during different stages of germ-cell development. A: A post-meiotic mutation gives rise to a single mutant gamete (A0; no cluster). B: A premeiotic mutation (A0) can give rise to a cluster of identical mutant gametes (in this case a premeiotic cluster of four A0 gametes). PGCs are primordial germ cells, some of which are lost during migration to the gonads through differential survival. Adapted from Woodruff and Thompson (2005) 82
APPENDIX D: LETTERS OF CONSENT