Stress-induced mutagenesis and complex adaptation

Because mutations are mostly deleterious, mutation rates should be reduced by natural selection. However, mutations also provide the raw material for adaptation. Therefore, evolutionary theory suggests that the mutation rate must balance between adaptability—the ability to adapt—and adaptedness—the ability to remain adapted. We model an asexual population crossing a fitness valley and analyse the rate of complex adaptation with and without stress-induced mutagenesis (SIM)—the increase of mutation rates in response to stress or maladaptation. We show that SIM increases the rate of complex adaptation without reducing the population mean fitness, thus breaking the evolutionary trade-off between adaptability and adaptedness. Our theoretical results support the hypothesis that SIM promotes adaptation and provide quantitative predictions of the rate of complex adaptation with different mutational strategies.     

From bad to good: Fitness reversals and the ascent of deleterious mutations

Deleterious mutations are considered a major impediment to adaptation, and there are straightforward expectations for the rate at which they accumulate as a function of population size and mutation rate. In a simulation model of an evolving population of asexually replicating RNA molecules, initially deleterious mutations accumulated at rates nearly equal to that of initially beneficial mutations, without impeding evolutionary progress. As the mutation rate was increased within a moderate range, deleterious mutation accumulation and mean fitness improvement both increased. The fixation rates were higher than predicted by many population-genetic models. This seemingly paradoxical result was resolved in part by the observation that, during the time to fixation, the selection coefficient (s) of initially deleterious mutations reversed to confer a selective advantage. Significantly, more than half of the fixations of initially deleterious mutations involved fitness reversals. These fitness reversals had a substantial effect on the total fitness of the genome and thus contributed to its success in the population. Despite the relative importance of fitness reversals, however, the probabilities of fixation for both initially beneficial and initially deleterious mutations were exceedingly small (on the order of 10⁻⁵ of all mutations).     

The Evolution of Selfing Is Accompanied by Reduced Efficacy of Selection and Purging of Deleterious Mutations

The transition from outcrossing to selfing is predicted to reduce the genome-wide efficacy of selection because of the lower effective population size (N_e) that accompanies this change in mating system. However, strongly recessive deleterious mutations exposed in the homozygous backgrounds of selfers should be under strong purifying selection. Here, we examine estimates of the distribution of fitness effects (DFE) and changes in the magnitude of effective selection coefficients (N_es) acting on mutations during the transition from outcrossing to selfing. Using forward simulations, we investigated the ability of a DFE inference approach to detect the joint influence of mating system and the dominance of deleterious mutations on selection efficacy. We investigated predictions from our simulations in the annual plant Eichhornia paniculata, in which selfing has evolved from outcrossing on multiple occasions. We used range-wide sampling to generate population genomic datasets and identified nonsynonymous and synonymous polymorphisms segregating in outcrossing and selfing populations. We found that the transition to selfing was accompanied by a change in the DFE, with a larger fraction of effectively neutral sites (N_es < 1), a result consistent with the effects of reduced N_e in selfers. Moreover, an increased proportion of sites in selfers were under strong purifying selection (N_es > 100), and simulations suggest that this is due to the exposure of recessive deleterious mutations. We conclude that the transition to selfing has been accompanied by the genome-wide influences of reduced N_e and strong purifying selection against deleterious recessive mutations, an example of purging at the molecular level.     

Deleterious Mutations Accumulate Faster in Allopolyploid Than Diploid Cotton (Gossypium) and Unequally between Subgenomes

Whole-genome duplication (polyploidization) is among the most dramatic mutational processes in nature, so understanding how natural selection differs in polyploids relative to diploids is an important goal. Population genetics theory predicts that recessive deleterious mutations accumulate faster in allopolyploids than diploids due to the masking effect of redundant gene copies, but this prediction is hitherto unconfirmed. Here, we use the cotton genus (Gossypium), which contains seven allopolyploids derived from a single polyploidization event 1–2 Million years ago, to investigate deleterious mutation accumulation. We use two methods of identifying deleterious mutations at the nucleotide and amino acid level, along with whole-genome resequencing of 43 individuals spanning six allopolyploid species and their two diploid progenitors, to demonstrate that deleterious mutations accumulate faster in allopolyploids than in their diploid progenitors. We find that, unlike what would be expected under models of demographic changes alone, strongly deleterious mutations show the biggest difference between ploidy levels, and this effect diminishes for moderately and mildly deleterious mutations. We further show that the proportion of nonsynonymous mutations that are deleterious differs between the two coresident subgenomes in the allopolyploids, suggesting that homoeologous masking acts unequally between subgenomes. Our results provide a genome-wide perspective on classic notions of the significance of gene duplication that likely are broadly applicable to allopolyploids, with implications for our understanding of the evolutionary fate of deleterious mutations. Finally, we note that some measures of selection (e.g., dN/dS, π_N/π_S) may be biased when species of different ploidy levels are compared.     

Evolution at a High Imposed Mutation Rate: Adaptation Obscures the Load in Phage T7

Evolution at high mutation rates is expected to reduce population fitness deterministically by the accumulation of deleterious mutations. A high enough rate should even cause extinction (lethal mutagenesis), a principle motivating the clinical use of mutagenic drugs to treat viral infections. The impact of a high mutation rate on long-term viral fitness was tested here. A large population of the DNA bacteriophage T7 was grown with a mutagen, producing a genomic rate of 4 nonlethal mutations per generation, two to three orders of magnitude above the baseline rate. Fitness—viral growth rate in the mutagenic environment—was predicted to decline substantially; after 200 generations, fitness had increased, rejecting the model. A high mutation load was nonetheless evident from (i) many low- to moderate-frequency mutations in the population (averaging 245 per genome) and (ii) an 80% drop in average burst size. Twenty-eight mutations reached high frequency and were thus presumably adaptive, clustered mostly in DNA metabolism genes, chiefly DNA polymerase. Yet blocking DNA polymerase evolution failed to yield a fitness decrease after 100 generations. Although mutagenic drugs have caused viral extinction in vitro under some conditions, this study is the first to match theory and fitness evolution at a high mutation rate. Failure of the theory challenges the quantitative basis of lethal mutagenesis and highlights the potential for adaptive evolution at high mutation rates.THE evolutionary consequences of a high mutation rate are mysterious. It is widely considered that mutations are essential for adaptation, but that the rate maximizing adaptation is far below what can be tolerated (e.g., Trobner and Piechocki 1984; Sniegowski 1997, 2001). In this “twilight zone” of higher-than-optimal mutation rates, the population experiences unique challenges. In one process, the “error catastrophe,” the best genotype is driven out of the population deterministically because the onslaught of viable, mutant genotypes simply overwhelms it (Eigen et al. 1988). With Muller''s ratchet, a phenomenon of finite asexual populations, high mutation rates and genetic drift combine to cause loss of the wild-type genome, and the absence of recombination blocks its recreation (Muller 1964); fitness gradually decays as mutations continue their stochastic accumulation. Yet another high mutation rate process is the straightforward, deterministic decline in population fitness as deleterious mutations accumulate (Kimura and Maruyama 1966), leading to extinction if fecundity is too low to compensate (Maynard Smith 1978; Bull et al. 2007).The problem with our understanding of evolution at a high mutation rate is that it is piecemeal. We do not yet know how to combine these different processes nor do we know their relative importance. For example, the fitness loss at a high mutation rate can be offset both by adaptation and by the error catastrophe, but for realistic models, there is no formal basis for predicting the magnitude of adaptation or even for recognizing an error catastrophe (Bull et al. 2005, 2007). Empirical studies are needed. Several studies of viruses have explored extinction through elevated mutation rate (lethal mutagenesis) (Domingo et al. 2001; Anderson et al. 2004; also see discussion), but they have not been tied to any quantitative model. The practical value of such work is that mutagenic drugs are sometimes used to treat viral infections, yet we do not know how the elevated mutation rate is affecting the virus.Here we develop an empirical system to enforce viral evolution at a high mutation rate and test theory developed for lethal mutagenesis. A mutagen is applied to the culture in which the DNA bacteriophage T7 is grown, the mutation input per generation is measured on a genomewide scale, and the system is used to observe both molecular and fitness evolution. Comparison of data and theory provides new insights into the process that underlies lethal mutagenesis. However, existing theory must also be modified to address some empirical properties of the system.

Theory of fitness evolution at high mutation rate:

The objective is to develop a theory for data that are readily obtained. The most basic theory requires one population property (the deleterious mutation rate) to predict another population property (mean fitness), but other properties are not predicted. In experimental systems, mean fitness is easily measured, and the deleterious mutation rate can be estimated within bounds. A fully comprehensive model of evolution at a high mutation rate, one predicting full distributions of genotypes, could be developed if mutation rates and fitness effects were known for each individual mutation and for combinations of mutations, including recombination frequencies. However, the full spectrum of mutations and their fitness effects is too vast to allow those measurements in any biological system, so the only applicable theory describes just mean fitness.If the fitness (e.g., viability) of the mutation-free genotype is assigned the value 1, the mean fitness of an infinite, asexual population at equilibrium is e^−U, where U is the genomic deleterious mutation rate (discrete generations) (Kimura and Maruyama 1966). By itself, this result does not indicate whether a population will survive or not, but one simple modification extends the model to address lethal mutagenesis: fecundity. For an asexual population to survive, a minimal condition is that each parent must produce at least one surviving offspring. In the case of a virus, if each infection produces b viable progeny (in the absence of mutation), the inequality be^−U < 1 ensures eventual extinction. When this inequality is met, the number of progeny in each generation starts out smaller than the number in the parent generation, so the population size declines (Bull et al. 2007).This decline in fitness is not due to stochastic effects in small populations; extinction in this model formally requires a finite population, but the effect of deleterious mutations is treated deterministically. Finite population size can contribute to extinction at mutation rates below the threshold (e.g., from Muller''s ratchet), but we limit ourselves to nearly infinite population sizes.A useful property of the model is that the fitness effects of deleterious mutations and their individual rates need not be known, only the overall rate. Yet this elegance of the Kimura–Maruyama result starts to fade when considering empirical reality. The model considers only deleterious mutations, including lethals; neutral mutations are allowed but ignored, and beneficial mutations are not even allowed. Maximum fitness is assigned to the starting, mutation-free genotype, so any mutation that elevates fitness is excluded. Compensatory mutations that ameliorate the effect of deleterious mutations, and thus are beneficial only within mutated genomes, are also not allowed.To consider a simple model with beneficial mutations, if the initial genotype does not have maximum possible fitness, but a fitness of W relative to the starting genotype is attainable by beneficial mutations (W > 1), then a modified equilibrium is simply We^−U relative to a starting fitness of 1.0. In a virus whose initial fitness is b progeny, adaptive evolution could be accommodated in the model by increasing fecundity to B. The extent to which B exceeds b represents the extent to which the initial (wild-type) virus is poorly adapted to the mutagenic environment, which is unknown. Furthermore, this threshold relaxation omits compensatory mutations that ameliorate specific deleterious mutations and neglects any interference of deleterious mutations on the ascent of beneficial ones.Two further empirical limitations of the Kimura–Maruyama model are evident. Following the onset of an increased mutation rate, the fitness equilibrium may require few or many generations to be approached closely and potentially could require more generations than would be experienced by any real population (Crow and Kimura 1970; Bull and Wilke 2008). The rate of approach depends on the details of the mutation rate and fitness effects, whereas the equilibrium mean fitness does not. We thus attempt to carry out experiments long enough to assume that fitness has neared equilibrium. Second, the Kimura–Maruyama model was developed explicitly for asexuals; the same equilibrium applies with free recombination and no epistasis, but not necessarily when either of these conditions is violated (Maynard Smith 1978; Kondrashov 1982, 1984; Keightley and Otto 2006).In the Kimura–Maruyama model (Kimura and Maruyama 1966), fitness is measured per discrete generation as relative number of surviving offspring. In our viral study, fitness is measured as a growth rate, essentially the log of fitness in the Kimura–Maruyama model. This discrepancy can be resolved by deriving new results for growth rate, again assuming asexuality. Neglecting viral loss from death and other causes, a model of viral growth rate (r) is given by(1)where C is cell (host) density, k is the adsorption rate of virus to cells, b is burst size (average number of progeny per infected cell), and L is lysis time in minutes (Bull 2006). Cell density is assumed to be constant, and cells always outnumber virus (a condition that can be enforced experimentally). r is an exponential or geometric growth rate: at equilibrium, the number of virus at time t, N_t, as a function of initial density, N₀, is given by N_t = e^rtN₀. This model is tailored to the conditions used here, and a model for treatment of a mammalian infection would need to contend with spatial structure and the possibility that the viral population had reached a dynamic equilibrium in which exponential growth no longer applied (see also Steinmeyer and Wilke 2009).With a deleterious, genomic mutation rate U per generation, the deterministic growth rate of the mutation-free class is simply(2)By assumption, all mutation classes in the population are derived ultimately from the mutation-free class and, because all mutations in U are deleterious (neutral mutations are allowed but not counted), all mutants have slower growth rates than the mutation-free genotype. Back mutations and other forms of beneficial mutations are not allowed. It follows that the growth rate of the entire population at mutation–selection equilibrium is given by (2). This result is convenient because the average population growth rate can be understood from the growth rate of the mutation-free class. It is important to emphasize that the solution to (2) [and (1)] is an equilibrium that may require thousands of generations to be reached. Thus, if the solution is negative (r < 0), implying that the population will ultimately decline, the population may go extinct before attaining approximate equilibrium.Equation 2 does not lend itself to an explicit solution, but it is easily solved numerically. Although the parameters in (2) are meant to apply across all mutation rates, the reality for any chemical mutagen or drug is that higher doses of mutagen will not only increase U but also directly reduce viral fitness, such as by reducing burst size. To address this issue, parameters should be estimated in the mutagenic environment. In turn, estimating parameters in the mutagenic environment creates the complication that lethal mutations kill progeny and reduce the apparent burst size (when burst size is determined by plaque counts). To overcome this latter problem, we partition the total deleterious mutation rate into the sum of the lethal rate (U_X) and the nonlethal rate (U_d), U = U_X + U_d, and rewrite Equation 2 as(3)where , the viable burst size. Now, the direct effect of mutagen on burst size is inseparable from the effects of lethal mutations.

Population variation:

An important but subtle implication of the theory is that, when the mutation rate is high, the population will be genetically heterogeneous for deleterious mutations maintained at low to moderate frequencies (Haldane 1927; Crow and Kimura 1970; Eigen et al. 1988). Although every genome may contain many deleterious mutations, different genomes have different sets of deleterious mutations. Only a small proportion of the population may be of the best genotype, in which case, most individuals sampled will have lower fitness than that characterizing the population''s growth (Rouzine et al. 2003, 2008). This heterogeneity has the effect of complicating one means of estimating population fitness. When fitness involves component life history parameters such as burst size and lysis time, a fitness calculation based on separate estimates of life history components appears to underestimate actual population fitness. We have observed this effect in unpublished simulations and suspect that it is a parallel to the principle that the average of a ratio is not the ratio of averages. The T7 system that we use here has the advantage that the intrinsic mutation rate of the virus is low. Thus the starting phage and isolates are genetically uniform and are not subject to this problem. Estimation of fitness directly (as population growth rate rather than from separate fitness components) avoids this problem as well.     

Significance of Population Size on the Fixation of Nonsynonymous Mutations in Genes Under Varying Levels of Selection Pressure

Previous studies observed a higher ratio of divergences at nonsynonymous and synonymous sites (ω = d_N/d_S) in species with a small population size compared to that estimated for those with a large population size. Here we examined the theoretical relationship between ω, effective population size (N_e), and selection coefficient (s). Our analysis revealed that when purifying selection is high, ω of species with small N_e is much higher than that of species with large N_e. However the difference between the two ω reduces with the decline in selection pressure (s → 0). We examined this relationship using primate and rodent genes and found that the ω estimated for highly constrained genes of primates was up to 2.9 times higher than that obtained for their orthologous rodent genes. Conversely, for genes under weak purifying selection the ω of primates was only 17% higher than that of rodents. When tissue specificity was used as a proxy for selection pressure we found that the ω of broadly expressed genes of primates was up to 2.1-fold higher than that of their rodent counterparts and this difference was only 27% for tissue specific genes. Since most of the nonsynonymous mutations in constrained or broadly expressed genes are deleterious, fixation of these mutations is influenced by N_e. This results in a higher ω of these genes in primates compared to those from rodents. Conversely, the majority of nonsynonymous mutations in less-constrained or tissue-specific genes are neutral or nearly neutral and therefore fixation of them is largely independent of N_e, which leads to the similarity of ω in primates and rodents.     

Genomic Consequences of Long-Term Population Decline in Brown Eared Pheasant

Population genetic theory and empirical evidence indicate that deleterious alleles can be purged in small populations. However, this viewpoint remains controversial. It is unclear whether natural selection is powerful enough to purge deleterious mutations when wild populations continue to decline. Pheasants are terrestrial birds facing a long-term risk of extinction as a result of anthropogenic perturbations and exploitation. Nevertheless, there are scant genomics resources available for conservation management and planning. Here, we analyzed comparative population genomic data for the three extant isolated populations of Brown eared pheasant (Crossoptilon mantchuricum) in China. We showed that C. mantchuricum has low genome-wide diversity and a contracting effective population size because of persistent declines over the past 100,000 years. We compared genome-wide variation in C. mantchuricum with that of its closely related sister species, the Blue eared pheasant (C. auritum) for which the conservation concern is low. There were detrimental genetic consequences across all C. mantchuricum genomes including extended runs of homozygous sequences, slow rates of linkage disequilibrium decay, excessive loss-of-function mutations, and loss of adaptive genetic diversity at the major histocompatibility complex region. To the best of our knowledge, this study is the first to perform a comprehensive conservation genomic analysis on this threatened pheasant species. Moreover, we demonstrated that natural selection may not suffice to purge deleterious mutations in wild populations undergoing long-term decline. The findings of this study could facilitate conservation planning for threatened species and help recover their population size.     

The Fixation Probability of Rare Mutators in Finite Asexual Populations

A mutator is an allele that increases the mutation rate throughout the genome by disrupting some aspect of DNA replication or repair. Mutators that increase the mutation rate by the order of 100-fold have been observed to spontaneously emerge and achieve high frequencies in natural populations and in long-term laboratory evolution experiments with Escherichia coli. In principle, the fixation of mutator alleles is limited by (i) competition with mutations in wild-type backgrounds, (ii) additional deleterious mutational load, and (iii) random genetic drift. Using a multiple-locus model and employing both simulation and analytic methods, we investigate the effects of these three factors on the fixation probability P_fix of an initially rare mutator as a function of population size N, beneficial and deleterious mutation rates, and the strength of mutations s. Our diffusion-based approximation for P_fix successfully captures effects ii and iii when selection is fast compared to mutation (). This enables us to predict the conditions under which mutators will be evolutionarily favored. Surprisingly, our simulations show that effect i is typically small for strong-effect mutators. Our results agree semiquantitatively with existing laboratory evolution experiments and suggest future experimental directions.     

The accumulation of deleterious genes in a population—Muller's Ratchet

A quantitative study of the operation of Muller's Ratchet for the accumulation of deleterious genes in an asexually reproducing population is made. For a population of size N, in which deleterious mutations occur at rate λ/genome/ generation, and the relative fitness of an individual with k mutants is (1 ? s)^k, the most important parameter is $\text{n}{}_0\text{= Ne}{}^{\mathrm{?\theta }}\text{,}\text{where}\text{θ =}\text{λ}\text{s}$. If n₀ is large (?25), deleterious mutations will accumulate very slowly, and independently of each other; if n₀ is small (<1), the rate of accumulation of deleterious mutations will be greater than a natural population could plausibly bear; an estimate of the speed of the Ratchet for intermediate values of n₀ is made. It is pointed out that the frequency distribution for the numbers of individuals carrying k mutants will retain its shape, but will move bodily to the right at the same average speed as the Ratchet. When favourable mutations also occur, the frequency distributions can move right of left; an estimate of the probability that any particular step is right or left is made, and it is shown that, for a given net rate of arrisal of deleterious mutations, the greater the rate of beneficial mutation, the greater the chance that beneficial mutations will accumulate.     

Evidence that Adaptation in Drosophila Is Not Limited by Mutation at Single Sites

Adaptation in eukaryotes is generally assumed to be mutation-limited because of small effective population sizes. This view is difficult to reconcile, however, with the observation that adaptation to anthropogenic changes, such as the introduction of pesticides, can occur very rapidly. Here we investigate adaptation at a key insecticide resistance locus (Ace) in Drosophila melanogaster and show that multiple simple and complex resistance alleles evolved quickly and repeatedly within individual populations. Our results imply that the current effective population size of modern D. melanogaster populations is likely to be substantially larger (≥100-fold) than commonly believed. This discrepancy arises because estimates of the effective population size are generally derived from levels of standing variation and thus reveal long-term population dynamics dominated by sharp—even if infrequent—bottlenecks. The short-term effective population sizes relevant for strong adaptation, on the other hand, might be much closer to census population sizes. Adaptation in Drosophila may therefore not be limited by waiting for mutations at single sites, and complex adaptive alleles can be generated quickly without fixation of intermediate states. Adaptive events should also commonly involve the simultaneous rise in frequency of independently generated adaptive mutations. These so-called soft sweeps have very distinct effects on the linked neutral polymorphisms compared to the standard hard sweeps in mutation-limited scenarios. Methods for the mapping of adaptive mutations or association mapping of evolutionarily relevant mutations may thus need to be reconsidered.     

Direct estimation of the mitochondrial DNA mutation rate in Drosophila melanogaster

Mitochondrial DNA (mtDNA) variants are widely used in evolutionary genetics as markers for population history and to estimate divergence times among taxa. Inferences of species history are generally based on phylogenetic comparisons, which assume that molecular evolution is clock-like. Between-species comparisons have also been used to estimate the mutation rate, using sites that are thought to evolve neutrally. We directly estimated the mtDNA mutation rate by scanning the mitochondrial genome of Drosophila melanogaster lines that had undergone approximately 200 generations of spontaneous mutation accumulation (MA). We detected a total of 28 point mutations and eight insertion-deletion (indel) mutations, yielding an estimate for the single-nucleotide mutation rate of 6.2 × 10⁻⁸ per site per fly generation. Most mutations were heteroplasmic within a line, and their frequency distribution suggests that the effective number of mitochondrial genomes transmitted per female per generation is about 30. We observed repeated occurrences of some indel mutations, suggesting that indel mutational hotspots are common. Among the point mutations, there is a large excess of G→A mutations on the major strand (the sense strand for the majority of mitochondrial genes). These mutations tend to occur at nonsynonymous sites of protein-coding genes, and they are expected to be deleterious, so do not become fixed between species. The overall mtDNA mutation rate per base pair per fly generation in Drosophila is estimated to be about 10× higher than the nuclear mutation rate, but the mitochondrial major strand G→A mutation rate is about 70× higher than the nuclear rate. Silent sites are substantially more strongly biased towards A and T than nonsynonymous sites, consistent with the extreme mutation bias towards A+T. Strand-asymmetric mutation bias, coupled with selection to maintain specific nonsynonymous bases, therefore provides an explanation for the extreme base composition of the mitochondrial genome of Drosophila.     

Purging deleterious mutations under self fertilization: paradoxical recovery in fitness with increasing mutation rate in Caenorhabditis elegans

Background

The accumulation of deleterious mutations can drastically reduce population mean fitness. Self-fertilization is thought to be an effective means of purging deleterious mutations. However, widespread linkage disequilibrium generated and maintained by self-fertilization is predicted to reduce the efficacy of purging when mutations are present at multiple loci.

Methodology/Principal Findings

We tested the ability of self-fertilizing populations to purge deleterious mutations at multiple loci by exposing obligately self-fertilizing populations of Caenorhabditis elegans to a range of elevated mutation rates and found that mutations accumulated, as evidenced by a reduction in mean fitness, in each population. Therefore, purging in obligate selfing populations is overwhelmed by an increase in mutation rate. Surprisingly, we also found that obligate and predominantly self-fertilizing populations exposed to very high mutation rates exhibited consistently greater fitness than those subject to lesser increases in mutation rate, which contradicts the assumption that increases in mutation rate are negatively correlated with fitness. The high levels of genetic linkage inherent in self-fertilization could drive this fitness increase.

Conclusions

Compensatory mutations can be more frequent under high mutation rates and may alleviate a portion of the fitness lost due to the accumulation of deleterious mutations through epistatic interactions with deleterious mutations. The prolonged maintenance of tightly linked compensatory and deleterious mutations facilitated by self-fertilization may be responsible for the fitness increase as linkage disequilibrium between the compensatory and deleterious mutations preserves their epistatic interaction.     

What Use Is Population Genetics?

The Genetic Society of America’s Thomas Hunt Morgan Medal is awarded to an individual GSA member for lifetime achievement in the field of genetics. For over 40 years, 2015 recipient Brian Charlesworth has been a leader in both theoretical and empirical evolutionary genetics, making substantial contributions to our understanding of how evolution acts on genetic variation. Some of the areas in which Charlesworth’s research has been most influential are the evolution of sex chromosomes, transposable elements, deleterious mutations, sexual reproduction, and life history. He also developed the influential theory of background selection, whereby the recurrent elimination of deleterious mutations reduces variation at linked sites, providing a general explanation for the correlation between recombination rate and genetic variation.Open in a separate windowI am grateful to the Genetics Society of America for honoring me with the Thomas Hunt Morgan Medal and for inviting me to contribute this essay. I have spent nearly 50 years doing research in population genetics. This branch of genetics uses knowledge of the rules of inheritance to predict how the genetic composition of a population will change under the forces of evolution and compares the predictions to relevant data. As our knowledge of how genomes are organized and function has increased, so has the range of problems confronted by population geneticists. We are, however, a relatively small part of the genetics community, and sometimes it seems that our field is regarded as less important than those branches of genetics concerned with the properties of cells and individual organisms.I will take this opportunity to explain why I believe that population genetics is useful to a broad range of biologists. The fundamental importance of population genetics is the basic insights it provides into the mechanisms of evolution, some of which are far from intuitively obvious. Many of these insights came from the work of the first generation of population geneticists, notably Fisher, Haldane, and Wright. Their mathematical models showed that, contrary to what was believed by the majority of biologists in the 1920s, natural selection operating on Mendelian variation can cause evolutionary change at rates sufficient to explain historical patterns of evolution. This led to the modern synthesis of evolution (Provine 1971). No one can claim to understand how evolution works without some basic understanding of classical population genetics; those who do run the risk of making mistakes such as asserting that rapid evolutionary change is most likely to occur in small founder populations (Mayr 1954).

As our knowledge of how genomes are organized and function has increased, so has the range of problems confronted by population geneticists. We are, however, a relatively small part of the genetics community, and sometimes it seems that our field is regarded as less important than those branches of genetics concerned with the properties of cells and individual organisms.—B.C.

The modern synthesis is getting on for 80 years old, so this argument will probably not convince skeptical molecular geneticists that population genetics has a lot to offer the modern biologist. I provide two examples of the useful role that population genetic studies can play. First, one of the most notable discoveries of the past 40 years was the finding that the genomes of most species contain families of transposable elements (TEs) with the capacity to make new copies that insert elsewhere in the genome (Shapiro 1983). This led to two schools of thought about why they are present in the genome. One claimed that TEs are maintained because they confer benefits on the host by producing adaptively useful mutations (Syvanen 1984); the other believed that they are parasites, maintained by their ability to replicate within the genome despite potentially deleterious fitness effects of TE insertions (Doolittle and Sapienza 1980; Orgel and Crick 1980).The second hypothesis can be tested by comparing population genetic predictions with the results of TE surveys within populations. In the early 1980s, Chuck Langley, myself and several collaborators tried to do just this, using populations of Drosophila melanogaster (Charlesworth and Langley 1989). The models predicted that most Drosophila TEs should be found at low population frequencies at their insertion sites. This is so because D. melanogaster populations have large effective sizes (N_e). N_e is essentially the number of individuals that genetically contribute to the next generation. Large N_e means that a very small selection pressure can keep deleterious elements at low frequencies. This is a consequence of one of the most important findings of classical population genetics—the fate of a variant in a population is the product of N_e and the strength of selection (Fisher 1930; Kimura 1962). If, for example, N_e is 1000, a mutation that reduces fitness relative to wild type by 0.001 will be eliminated from the population with near certainty.Using the crude tools then available (restriction mapping of cloned genomic regions and in situ hybridization of labeled TE probes to polytene chromosomes), we found that nearly all TEs are indeed present at low frequencies in the population (Charlesworth and Langley 1989). Most of the exceptions to this rule were found in genomic regions in which little crossing over occurs (Maside et al. 2005). This is consistent with Chuck’s proposal that a major contributor to the removal of TEs from the population is selection against aneuploid progeny created by crossing over among homologous TEs at different locations in the genome (Langley et al. 1988). It is now a familiar finding that nonrecombining genomes or genomic regions tend to be full of TEs and other kinds of repetitive sequences; the population genetic reasons for this, discussed by Charlesworth et al. (1994), are perhaps not so familiar.Modern genomic methods provide much more powerful means for identifying TE insertions. Recent population surveys using these methods have confirmed the older findings: most TEs in Drosophila are present at low frequencies, and there is statistical evidence for selection against insertions (Barron et al. 2014). This is consistent with the existence of elaborate molecular mechanisms for repressing TE activity, such as the Piwi-interacting RNA (piRNA) pathway of animals (Senti and Brennecke 2010); there would be no reason to evolve such mechanisms if TEs were harmless. In a few cases, TEs have swept to high frequencies or fixation, and there is convincing evidence that at least some of these events are associated with increased fitness caused by the TE insertions themselves (Barron et al. 2014). These cases do not contradict the intragenomic parasite hypothesis for the maintenance of TEs; favorable mutations induced by TEs are too rare to outweigh the elimination of deleterious insertions unless new insertions continually replace those that are lost.

From the theory of aging, to the degeneration of Y chromosomes, to the dynamics of transposable elements, our understanding of the genetic basis of evolution is deeper and richer as a result of Charlesworth’s many contributions to the field. —Charles Langley, University of California, Davis

My other example is a population genetics discovery about a fundamental biological process: the PRDM9 protein involved in establishing recombination hot spots in humans. This was enabled by the revolution in population genetics brought about by coalescence theory (Hudson 1990), which is a powerful tool for looking at the statistical properties of a sample from a population under the hypothesis of selective neutrality. The basic idea is simple: if we sample two homologous, nonrecombining haploid genomes (e.g., mitochondrial DNA) from a large population, there is a probability of 1/(2N_e) that they are derived from the same parental genome in the preceding generation; i.e., they coalesce (N_e is the effective population size for the genome region in question). If they fail to coalesce in that generation, there is a probability of 1/(2N_e) that they coalesce one generation further back, and so on. If n genomes are sampled, there is a bifurcating tree connecting them back to their common ancestor. The size and shape of this tree are highly random, so genetically independent components of the genome experience different trees, even if they share the same N_e. The properties of sequence variability in the sample can be modeled by throwing mutations at random onto the tree (Hudson 1990).Recombination causes different sites in the genome to experience different trees, but closely linked sites have much more similar trees than independent sites. At the level of sequence variability, close linkage results in nonrandom associations between neutral variants—linkage disequilibrium (LD). The extent of LD among neutral variants at different sites is determined by the product of N_e and the frequency of recombination between them c (Ohta and Kimura 1971; McVean 2002). Richard Hudson proposed a statistical method for estimating N_ec from data on variants at multiple sites across the genome (Hudson 2001) that was implemented in a widely used computer program LDhat by Gil McVean and colleagues (McVean et al. 2002). Applications to large data sets on human sequence variability showed that the genome is full of recombination hot spots and cold spots, consistent with previous molecular genetic studies of specific loci (Myers et al. 2005). Most recombination occurs in hot spots and very little in between them, accounting for the fact that there is almost complete LD over tens or even hundreds of kilobases in humans. The identification of a large number of hot spots led to the discovery of a sequence motif bound by a zinc finger protein, PRDM9, at about the same time that mouse geneticists also discovered that PRDM9 promotes recombination (McVean and Myers 2010; Baudat et al. 2014). These discoveries have led to many interesting observations, such as associations between PRDM9 variants in humans and individual variation in recombination rates, generating an ongoing research program of great scientific interest (Baudat et al. 2014).With the ever-increasing use of genomic data, I am confident that many more such fruitful interactions between molecular and population genetics will take place. A take-home message is that more needs to be done to integrate training in population, molecular, and computational approaches to provide the next generation of researchers with the broad range of knowledge they will need.     

CTCF cis-Regulates Trinucleotide Repeat Instability in an Epigenetic Manner: A Novel Basis for Mutational Hot Spot Determination

At least 25 inherited disorders in humans result from microsatellite repeat expansion. Dramatic variation in repeat instability occurs at different disease loci and between different tissues; however, cis-elements and trans-factors regulating the instability process remain undefined. Genomic fragments from the human spinocerebellar ataxia type 7 (SCA7) locus, containing a highly unstable CAG tract, were previously introduced into mice to localize cis-acting “instability elements,” and revealed that genomic context is required for repeat instability. The critical instability-inducing region contained binding sites for CTCF—a regulatory factor implicated in genomic imprinting, chromatin remodeling, and DNA conformation change. To evaluate the role of CTCF in repeat instability, we derived transgenic mice carrying SCA7 genomic fragments with CTCF binding-site mutations. We found that CTCF binding-site mutation promotes triplet repeat instability both in the germ line and in somatic tissues, and that CpG methylation of CTCF binding sites can further destabilize triplet repeat expansions. As CTCF binding sites are associated with a number of highly unstable repeat loci, our findings suggest a novel basis for demarcation and regulation of mutational hot spots and implicate CTCF in the modulation of genetic repeat instability.     

The rate of adaptation in asexuals

I study the population genetics of adaptation in asexuals. I show that the rate of adaptive substitution in an asexual species or nonrecombining chromosome region is a bell-shaped function of the mutation rate: at some point, increasing the mutation rate decreases the rate of substitution. Curiously, the mutation rate that maximizes the rate of adaptation depends solely on the strength of selection against deleterious mutations. In particular, adaptation is fastest when the genomic rate of mutation, U, equals the harmonic mean of selection coefficients against deleterious mutations, where we assume that selection for favorable alleles is milder than that against deleterious ones. This simple result is independent of the shape of the distribution of effects among favorable and deleterious mutations, population size, and the action of clonal interference. In the course of this work, I derive an approximation to the probability of fixation of a favorable mutation in an asexual genome or nonrecombining chromosome region in which both favorable and deleterious mutations occur.     

The Effect of Deleterious Mutations on Neutral Molecular Variation

Selection against deleterious alleles maintained by mutation may cause a reduction in the amount of genetic variability at linked neutral sites. This is because a new neutral variant can only remain in a large population for a long period of time if it is maintained in gametes that are free of deleterious alleles, and hence are not destined for rapid elimination from the population by selection. Approximate formulas are derived for the reduction below classical neutral values resulting from such background selection against deleterious mutations, for the mean times to fixation and loss of new mutations, nucleotide site diversity, and number of segregating sites. These formulas apply to random-mating populations with no genetic recombination, and to populations reproducing exclusively asexually or by self-fertilization. For a given selection regime and mating system, the reduction is an exponential function of the total mutation rate to deleterious mutations for the section of the genome involved. Simulations show that the effect decreases rapidly with increasing recombination frequency or rate of outcrossing. The mean time to loss of new neutral mutations and the total number of segregating neutral sites are less sensitive to background selection than the other statistics, unless the population size is of the order of a hundred thousand or more. The stationary distribution of allele frequencies at the neutral sites is correspondingly skewed in favor of rare alleles, compared with the classical neutral result. Observed reductions in molecular variation in low recombination genomic regions of sufficiently large size, for instance in the centromere-proximal regions of Drosophila autosomes or in highly selfing plant populations, may be partly due to background selection against deleterious mutations.     

Slow Recovery from Inbreeding Depression Generated by the Complex Genetic Architecture of Segregating Deleterious Mutations

The deleterious effects of inbreeding have been of extreme importance to evolutionary biology, but it has been difficult to characterize the complex interactions between genetic constraints and selection that lead to fitness loss and recovery after inbreeding. Haploid organisms and selfing organisms like the nematode Caenorhabditis elegans are capable of rapid recovery from the fixation of novel deleterious mutation; however, the potential for recovery and genomic consequences of inbreeding in diploid, outcrossing organisms are not well understood. We sought to answer two questions: 1) Can a diploid, outcrossing population recover from inbreeding via standing genetic variation and new mutation? and 2) How does allelic diversity change during recovery? We inbred C. remanei, an outcrossing relative of C. elegans, through brother-sister mating for 30 generations followed by recovery at large population size. Inbreeding reduced fitness but, surprisingly, recovery from inbreeding at large populations sizes generated only very moderate fitness recovery after 300 generations. We found that 65% of ancestral single nucleotide polymorphisms (SNPs) were fixed in the inbred population, far fewer than the theoretical expectation of ∼99%. Under recovery, 36 SNPs across 30 genes involved in alimentary, muscular, nervous, and reproductive systems changed reproducibly across replicates, indicating that strong selection for fitness recovery does exist. Our results indicate that recovery from inbreeding depression via standing genetic variation and mutation is likely to be constrained by the large number of segregating deleterious variants present in natural populations, limiting the capacity for recovery of small populations.     

The Molecular Clock of Neutral Evolution Can Be Accelerated or Slowed by Asymmetric Spatial Structure

Over time, a population acquires neutral genetic substitutions as a consequence of random drift. A famous result in population genetics asserts that the rate, K, at which these substitutions accumulate in the population coincides with the mutation rate, u, at which they arise in individuals: K = u. This identity enables genetic sequence data to be used as a “molecular clock” to estimate the timing of evolutionary events. While the molecular clock is known to be perturbed by selection, it is thought that K = u holds very generally for neutral evolution. Here we show that asymmetric spatial population structure can alter the molecular clock rate for neutral mutations, leading to either K<u or K>u. Our results apply to a general class of haploid, asexually reproducing, spatially structured populations. Deviations from K = u occur because mutations arise unequally at different sites and have different probabilities of fixation depending on where they arise. If birth rates are uniform across sites, then K ≤ u. In general, K can take any value between 0 and Nu. Our model can be applied to a variety of population structures. In one example, we investigate the accumulation of genetic mutations in the small intestine. In another application, we analyze over 900 Twitter networks to study the effect of network topology on the fixation of neutral innovations in social evolution.     

Population dynamics of GC-changing mutations in humans and great apes

The nucleotide composition of the genome is a balance between the origin and fixation rates of different mutations. For example, it is well-known that transitions occur more frequently than transversions, particularly at CpG sites. Differences in fixation rates of mutation types are less explored. Specifically, recombination-associated GC-biased gene conversion (gBGC) may differentially impact GC-changing mutations, due to differences in their genomic distributions and efficiency of mismatch repair mechanisms. Given that recombination evolves rapidly across species, we explore gBGC of different mutation types across human populations and great ape species. We report a stronger correlation between segregating GC frequency and recombination for transitions than for transversions. Notably, CpG transitions are most strongly affected by gBGC in humans and chimpanzees. We show that the overall strength of gBGC is generally correlated with effective population sizes in humans, with some notable exceptions, such as a stronger effect of gBGC on non-CpG transitions in populations of European descent. Furthermore, species of the Gorilla and Pongo genus have a greatly reduced gBGC effect on CpG sites. We also study the dependence of gBGC dynamics on flanking nucleotides and show that some mutation types evolve in opposition to the gBGC expectation, likely due to the hypermutability of specific nucleotide contexts. Our results highlight the importance of different gBGC dynamics experienced by GC-changing mutations and their impact on nucleotide composition evolution.     

The Genomic Selfing Syndrome Accompanies the Evolutionary Breakdown of Heterostyly

The evolutionary transition from outcrossing to selfing can have important genomic consequences. Decreased effective population size and the reduced efficacy of selection are predicted to play an important role in the molecular evolution of the genomes of selfing species. We investigated evidence for molecular signatures of the genomic selfing syndrome using 66 species of Primula including distylous (outcrossing) and derived homostylous (selfing) taxa. We complemented our comparative analysis with a microevolutionary study of P. chungensis, which is polymorphic for mating system and consists of both distylous and homostylous populations. We generated chloroplast and nuclear genomic data sets for distylous, homostylous, and distylous–homostylous species and identified patterns of nonsynonymous to synonymous divergence (d_N/d_S) and polymorphism (π_N/π_S) in species or lineages with contrasting mating systems. Our analysis of coding sequence divergence and polymorphism detected strongly reduced genetic diversity and heterozygosity, decreased efficacy of purifying selection, purging of large-effect deleterious mutations, and lower rates of adaptive evolution in samples from homostylous compared with distylous populations, consistent with theoretical expectations of the genomic selfing syndrome. Our results demonstrate that self-fertilization is a major driver of molecular evolutionary processes with genomic signatures of selfing evident in both old and relatively young homostylous populations.