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.     

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.     

How to Make a Rodent Giant: Genomic Basis and Tradeoffs of Gigantism in the Capybara,the World’s Largest Rodent

Gigantism results when one lineage within a clade evolves extremely large body size relative to its small-bodied ancestors, a common phenomenon in animals. Theory predicts that the evolution of giants should be constrained by two tradeoffs. First, because body size is negatively correlated with population size, purifying selection is expected to be less efficient in species of large body size, leading to increased mutational load. Second, gigantism is achieved through generating a higher number of cells along with higher rates of cell proliferation, thus increasing the likelihood of cancer. To explore the genetic basis of gigantism in rodents and uncover genomic signatures of gigantism-related tradeoffs, we assembled a draft genome of the capybara (Hydrochoerus hydrochaeris), the world’s largest living rodent. We found that the genome-wide ratio of nonsynonymous to synonymous mutations (ω) is elevated in the capybara relative to other rodents, likely caused by a generation-time effect and consistent with a nearly neutral model of molecular evolution. A genome-wide scan for adaptive protein evolution in the capybara highlighted several genes controlling postnatal bone growth regulation and musculoskeletal development, which are relevant to anatomical and developmental modifications for an increase in overall body size. Capybara-specific gene-family expansions included a putative novel anticancer adaptation that involves T-cell-mediated tumor suppression, offering a potential resolution to the increased cancer risk in this lineage. Our comparative genomic results uncovered the signature of an intragenomic conflict where the evolution of gigantism in the capybara involved selection on genes and pathways that are directly linked to cancer.     

Why Do More Divergent Sequences Produce Smaller Nonsynonymous/Synonymous Rate Ratios in Pairwise Sequence Comparisons?

Several studies have reported a negative correlation between estimates of the nonsynonymous to synonymous rate ratio (ω = d_N/d_S) and the sequence distance d in pairwise comparisons of the same gene from different species. That is, more divergent sequences produce smaller estimates of ω. Explanations for this negative correlation have included segregating nonsynonymous polymorphisms in closely related species and nonlinear dynamics of the ratio of two random variables. Here we study the statistical properties of the maximum-likelihood estimates of ω and d in pairwise alignments and explore the possibility that the negative correlation can be entirely explained by those properties. We show that the ω estimate is positively biased for small d and that the bias decreases with the increase of d. We also show that the estimates of ω and d are negatively correlated when ω < 1 and positively correlated when ω > 1. However, the bias in estimates of ω and the correlation between estimates of ω and d are not enough to explain the much stronger correlation observed in real data sets. We then explore the behavior of the estimates when the model is misspecified and suggest that the observed correlation may be due to protein-level selection that causes very different amino acids to be favored in different domains of the protein. Widely used models fail to account for such among-site heterogeneity and cause underestimation of the nonsynonymous rate and ω, with the bias being much stronger for distant sequences. We point out that tests of positive selection based on the ω ratio are invariant to the parameterization of the model and thus unaffected by bias in the ω estimates or the correlation between estimates of ω and d.     

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.     

Helicobacter pylori evolution: lineage- specific adaptations in homologs of eukaryotic Sel1-like genes

Geographic partitioning is postulated to foster divergence of Helicobacter pylori populations as an adaptive response to local differences in predominant host physiology. H. pylori's ability to establish persistent infection despite host inflammatory responses likely involves active management of host defenses using bacterial proteins that may themselves be targets for adaptive evolution. Sequenced H. pylori genomes encode a family of eight or nine secreted proteins containing repeat motifs that are characteristic of the eukaryotic Sel1 regulatory protein, whereas the related Campylobacter and Wolinella genomes each contain only one or two such “Sel1-like repeat” (SLR) genes (“slr genes”). Signatures of positive selection (ratio of nonsynonymous to synonymous mutations, d_N/d_S = ω > 1) were evident in the evolutionary history of H. pylori slr gene family expansion. Sequence analysis of six of these slr genes (hp0160, hp0211, hp0235, hp0519, hp0628, and hp1117) from representative East Asian, European, and African H. pylori strains revealed that all but hp0628 had undergone positive selection, with different amino acids often selected in different regions. Most striking was a divergence of Japanese and Korean alleles of hp0519, with Japanese alleles having undergone particularly strong positive selection (ω_J > 25), whereas alleles of other genes from these populations were intermingled. Homology-based structural modeling localized most residues under positive selection to SLR protein surfaces. Rapid evolution of certain slr genes in specific H. pylori lineages suggests a model of adaptive change driven by selection for fine-tuning of host responses, and facilitated by geographic isolation. Characterization of such local adaptations should help elucidate how H. pylori manages persistent infection, and potentially lead to interventions tailored to diverse human populations.     

The Trouble with Sliding Windows and the Selective Pressure in BRCA1

Sliding-window analysis has widely been used to uncover synonymous (silent, d_S) and nonsynonymous (replacement, d_N) rate variation along the protein sequence and to detect regions of a protein under selective constraint (indicated by d_N<d_S) or positive selection (indicated by d_N>d_S). The approach compares two or more protein-coding genes and plots estimates dˆ _S and dˆ _N from each sliding window along the sequence. Here we demonstrate that the approach produces artifactual trends of synonymous and nonsynonymous rate variation, with greater variation in dˆ _S than in dˆ _N. Such trends are generated even if the true d_S and d_N are constant along the whole protein and different codons are evolving independently. Many published tests of negative and positive selection using sliding windows that we have examined appear to be invalid because they fail to correct for multiple testing. Instead, likelihood ratio tests provide a more rigorous framework for detecting signals of natural selection affecting protein evolution. We demonstrate that a previous finding that a particular region of the BRCA1 gene experienced a synonymous rate reduction driven by purifying selection is likely an artifact of the sliding window analysis. We evaluate various sliding-window analyses in molecular evolution, population genetics, and comparative genomics, and argue that the approach is not generally valid if it is not known a priori that a trend exists and if no correction for multiple testing is applied.     

High genetic diversity at the extreme range edge: nucleotide variation at nuclear loci in Scots pine (Pinus sylvestris L.) in Scotland

Nucleotide polymorphism at 12 nuclear loci was studied in Scots pine populations across an environmental gradient in Scotland, to evaluate the impacts of demographic history and selection on genetic diversity. At eight loci, diversity patterns were compared between Scottish and continental European populations. At these loci, a similar level of diversity (θ_sil=∼0.01) was found in Scottish vs mainland European populations, contrary to expectations for recent colonization, however, less rapid decay of linkage disequilibrium was observed in the former (ρ=0.0086±0.0009, ρ=0.0245±0.0022, respectively). Scottish populations also showed a deficit of rare nucleotide variants (multi-locus Tajima''s D=0.316 vs D=−0.379) and differed significantly from mainland populations in allelic frequency and/or haplotype structure at several loci. Within Scotland, western populations showed slightly reduced nucleotide diversity (π_tot=0.0068) compared with those from the south and east (0.0079 and 0.0083, respectively) and about three times higher recombination to diversity ratio (ρ/θ=0.71 vs 0.15 and 0.18, respectively). By comparison with results from coalescent simulations, the observed allelic frequency spectrum in the western populations was compatible with a relatively recent bottleneck (0.00175 × 4N_e generations) that reduced the population to about 2% of the present size. However, heterogeneity in the allelic frequency distribution among geographical regions in Scotland suggests that subsequent admixture of populations with different demographic histories may also have played a role.     

A century-long genetic record reveals that protist effective population sizes are comparable to those of macroscopic species

Effective population size (N_e) determines the rate of genetic drift and the relative influence of selection over random genetic changes. While free-living protist populations characteristically consist of huge numbers of cells (N), the absence of any estimates of contemporary N_e raises the question whether protist effective population sizes are comparably large. Using microsatellite genotype data of strains derived from revived cysts of the marine dinoflagellate Pentapharsodinium dalei from sections of a sediment record that spanned some 100 years, we present the first estimates of contemporary N_e for a local population in a free-living protist. The estimates of N_e are relatively small, of the order of a few 100 individuals, and thus are similar in magnitude to values of N_e reported for multicellular animals: the implications are that N_e of P. dalei is of many orders of magnitude lower than the number of cells present (N_e/N ∼ 10⁻¹²) and that stochastic genetic processes may be more prevalent in protist populations than previously anticipated.     

Recent relaxation of purifying selection on the tandem-repetitive early-stage histone H3 gene in brooding sea stars

Patterns of nucleotide substitution differ between marine species that have a pelagic feeding (planktotrophic) larval stage and related species that lack such a stage, for both adaptive and non-adaptive reasons. Here, patterns of nucleotide and inferred amino acid substitution are analyzed for the tandem-repetitive early-stage histone H3 gene in 36 sea star species of the order Forcipulatida with documented larval habitat. The relative rate of nonsynonymous substitution (expressed as ω = d_N/d_S) was significantly higher in lineages with a brooded non-feeding (lecithotrophic) larval form than in lineages with a planktotrophic larval form. There was also a significant excess of conservative over radical substitutions. The increase in ω for brooders as compared to non-brooders was much greater than for previously analyzed mitochondrial sequences in echinoderms. These data are consistent with the hypothesis that purifying selection on this gene has been relaxed in brooding lineages compared to non-brooding lineages. The hypotheses of adaptive or neutral evolution are less plausible, although recent pseudogenization following a period of relaxed purifying selection could also explain the results.     

An evolutionary maximum principle for density-dependent population dynamics in a fluctuating environment

The evolution of population dynamics in a stochastic environment is analysed under a general form of density-dependence with genetic variation in r and K, the intrinsic rate of increase and carrying capacity in the average environment, and in σ_e², the environmental variance of population growth rate. The continuous-time model assumes a large population size and a stationary distribution of environments with no autocorrelation. For a given population density, N, and genotype frequency, p, the expected selection gradient is always towards an increased population growth rate, and the expected fitness of a genotype is its Malthusian fitness in the average environment minus the covariance of its growth rate with that of the population. Long-term evolution maximizes the expected value of the density-dependence function, averaged over the stationary distribution of N. In the θ-logistic model, where density dependence of population growth is a function of N^θ, long-term evolution maximizes E[N^θ]=[1−σ_e²/(2r)]K^θ. While σ_e² is always selected to decrease, r and K are always selected to increase, implying a genetic trade-off among them. By contrast, given the other parameters, θ has an intermediate optimum between 1.781 and 2 corresponding to the limits of high or low stochasticity.     

The Effects of Demography and Long-Term Selection on the Accuracy of Genomic Prediction with Sequence Data

The use of dense SNPs to predict the genetic value of an individual for a complex trait is often referred to as “genomic selection” in livestock and crops, but is also relevant to human genetics to predict, for example, complex genetic disease risk. The accuracy of prediction depends on the strength of linkage disequilibrium (LD) between SNPs and causal mutations. If sequence data were used instead of dense SNPs, accuracy should increase because causal mutations are present, but demographic history and long-term negative selection also influence accuracy. We therefore evaluated genomic prediction, using simulated sequence in two contrasting populations: one reducing from an ancestrally large effective population size (N_e) to a small one, with high LD common in domestic livestock, while the second had a large constant-sized N_e with low LD similar to that in some human or outbred plant populations. There were two scenarios in each population; causal variants were either neutral or under long-term negative selection. For large N_e, sequence data led to a 22% increase in accuracy relative to ∼600K SNP chip data with a Bayesian analysis and a more modest advantage with a BLUP analysis. This advantage increased when causal variants were influenced by negative selection, and accuracy persisted when 10 generations separated reference and validation populations. However, in the reducing N_e population, there was little advantage for sequence even with negative selection. This study demonstrates the joint influence of demography and selection on accuracy of prediction and improves our understanding of how best to exploit sequence for genomic prediction.     

Selective constraints in cold‐region wild boars may defuse the effects of small effective population size on molecular evolution of mitogenomes

Spatial range expansion during population colonization is characterized by demographic events that may have significant effects on the efficiency of natural selection. Population genetics suggests that genetic drift brought by small effective population size (N_e) may undermine the efficiency of selection, leading to a faster accumulation of nonsynonymous mutations. However, it is still unknown whether this effect might be balanced or even reversed by strong selective constraints. Here, we used wild boars and local domestic pigs from tropical (Vietnam) and subarctic region (Siberia) as animal model to evaluate the effects of functional constraints and genetic drift on shaping molecular evolution. The likelihood‐ratio test revealed that Siberian clade evolved significantly different from Vietnamese clades. Different datasets consistently showed that Siberian wild boars had lower Ka/Ks ratios than Vietnamese samples. The potential role of positive selection for branches with higher Ka/Ks was evaluated using branch‐site model comparison. No signal of positive selection was found for the higher Ka/Ks in Vietnamese clades, suggesting the interclade difference was mainly due to the reduction in Ka/Ks for Siberian samples. This conclusion was further confirmed by the result from a larger sample size, among which wild boars from northern Asia (subarctic and nearby region) had lower Ka/Ks than those from southern Asia (temperate and tropical region). The lower Ka/Ks might be due to either stronger functional constraints, which prevent nonsynonymous mutations from accumulating in subarctic wild boars, or larger N_e in Siberian wild boars, which can boost the efficacy of purifying selection to remove functional mutations. The latter possibility was further ruled out by the Bayesian skyline plot analysis, which revealed that historical N_e of Siberian wild boars was smaller than that of Vietnamese wild boars. Altogether, these results suggest stronger functional constraints acting on mitogenomes of subarctic wild boars, which may provide new insights into their local adaptation of cold resistance.     

Tempo of Degeneration Across Independently Evolved Nonrecombining Regions

Recombination is beneficial over the long term, allowing more effective selection. Despite long-term advantages of recombination, local recombination suppression can evolve and lead to genomic degeneration, in particular on sex chromosomes. Here, we investigated the tempo of degeneration in nonrecombining regions, that is, the function curve for the accumulation of deleterious mutations over time, leveraging on 22 independent events of recombination suppression identified on mating-type chromosomes of anther-smut fungi, including newly identified ones. Using previously available and newly generated high-quality genome assemblies of alternative mating types of 13 Microbotryum species, we estimated degeneration levels in terms of accumulation of nonoptimal codons and nonsynonymous substitutions in nonrecombining regions. We found a reduced frequency of optimal codons in the nonrecombining regions compared with autosomes, that was not due to less frequent GC-biased gene conversion or lower ancestral expression levels compared with recombining regions. The frequency of optimal codons rapidly decreased following recombination suppression and reached an asymptote after ca. 3 Ma. The strength of purifying selection remained virtually constant at d_N/d_S = 0.55, that is, at an intermediate level between purifying selection and neutral evolution. Accordingly, nonsynonymous differences between mating-type chromosomes increased linearly with stratum age, at a rate of 0.015 per My. We thus develop a method for disentangling effects of reduced selection efficacy from GC-biased gene conversion in the evolution of codon usage and we quantify the tempo of degeneration in nonrecombining regions, which is important for our knowledge on genomic evolution and on the maintenance of regions without recombination.     

Effective population size does not predict codon usage bias in mammals

Synonymous codons are not used at equal frequency throughout the genome, a phenomenon termed codon usage bias (CUB). It is often assumed that interspecific variation in the intensity of CUB is related to species differences in effective population sizes (N_e), with selection on CUB operating less efficiently in species with small N_e. Here, we specifically ask whether variation in N_e predicts differences in CUB in mammals and report two main findings. First, across 41 mammalian genomes, CUB was not correlated with two indirect proxies of N_e (body mass and generation time), even though there was statistically significant evidence of selection shaping CUB across all species. Interestingly, autosomal genes showed higher codon usage bias compared to X‐linked genes, and high‐recombination genes showed higher codon usage bias compared to low recombination genes, suggesting intraspecific variation in N_e predicts variation in CUB. Second, across six mammalian species with genetic estimates of N_e (human, chimpanzee, rabbit, and three mouse species: Mus musculus, M. domesticus, and M. castaneus), N_e and CUB were weakly and inconsistently correlated. At least in mammals, interspecific divergence in N_e does not strongly predict variation in CUB. One hypothesis is that each species responds to a unique distribution of selection coefficients, confounding any straightforward link between N_e and CUB.     

Rapid Evolution of the Ribonuclease A Superfamily: Adaptive Expansion of Independent Gene Clusters in Rats and Mice

The two eosinophil ribonucleases, eosinophil-derived neurotoxin (EDN/RNase 2) and eosinophil cationic protein (ECP/RNase 3), are among the most rapidly evolving coding sequences known among primates. The eight mouse genes identified as orthologs of EDN and ECP form a highly divergent, species-limited cluster. We present here the rat ribonuclease cluster, a group of eight distinct ribonuclease A superfamily genes that are more closely related to one another than they are to their murine counterparts. The existence of independent gene clusters suggests that numerous duplications and diversification events have occurred at these loci recently, sometime after the divergence of these two rodent species (∼10–15 million years ago). Nonsynonymous substitutions per site (d _N) calculated for the 64 mouse/rat gene pairs indicate that these ribonucleases are incorporating nonsilent mutations at accelerated rates, and comparisons of nonsynonymous to synonymous substitution (d _N / d _S) suggest that diversity in the mouse ribonuclease cluster is promoted by positive (Darwinian) selection. Although the pressures promoting similar but clearly independent styles of rapid diversification among these primate and rodent genes remain uncertain, our recent findings regarding the function of human EDN suggest a role for these ribonucleases in antiviral host defense. Received: 8 April 1999 / Accepted: 22 June 1999