Genomic Evidence for the Complex Evolutionary History of Macaques (Genus Macaca).

The genus Macaca is widely distributed, occupies a variety of habitats, shows diverse phenotypic characteristics, and is one of the best-studied genera of nonhuman primates. Here, we reported five re-sequencing Macaca genomes, including one M. cyclopis, one M. fuscata, one M. thibetana, one M. silenus, and one M. sylvanus. Together with published genomes of other macaque species, we combined 20 genome sequences of 10 macaque species to investigate the gene introgression and genetic differences among the species. The network analysis of the SNV-fragment trees indicates a reticular phylogeny of macaque species. Combining the results from various analytical methods, we identified extensive ancient introgression events among macaque species. The multiple introgression signals between different species groups were also observed, such as between fascicularis group species and silenus group species. However, gene flow signals between fascicularis and sinica group were not as strong as those between fascicularis group and silenus group. On the other hand, the unidirect gene flow in M. arctoides probably occurred between the progenitor of M. arctoides and the common ancestor of fascicularis group. Our study also shows that the genetic backgrounds and genetic diversity of different macaques vary dramatically among species, even among populations of the same species. In conclusion, using whole genome sequences and multiple methods, we have studied the evolutionary history of the genus Macaca and provided evidence for extensive introgression among the species.

Weak selection on synonymous codons substantially inflates dN/dS estimates in bacteria.

Synonymous codon substitutions are not always selectively neutral as revealed by several types of analyses, including studies of codon usage patterns among genes. We analyzed codon usage in 13 bacterial genomes sampled from across a large order of bacteria, Enterobacterales, and identified presumptively neutral and selected classes of synonymous substitutions. To estimate substitution rates, given a neutral/selected classification of synonymous substitutions, we developed a flexible [Formula: see text] substitution model that allows multiple classes of synonymous substitutions. Under this multiclass synonymous substitution (MSS) model, the denominator of [Formula: see text] includes only the strictly neutral class of synonymous substitutions. On average, the value of [Formula: see text] under the MSS model was 80% of that under the standard codon model in which all synonymous substitutions are assumed to be neutral. The indication is that conventional [Formula: see text] analyses overestimate these values and thus overestimate the frequency of positive diversifying selection and underestimate the strength of purifying selection. To quantify the strength of selection necessary to explain this reduction, we developed a model of selected compensatory codon substitutions. The reduction in synonymous substitution rate, and thus the contribution that selection makes to codon bias variation among genes, can be adequately explained by very weak selection, with a mean product of population size and selection coefficient, [Formula: see text].

The Pop-Gen Pipeline Platform: A Software Platform for Population Genomic Analyses.

The Pop-Gen Pipeline Platform (PPP) is a software platform for population genomic analyses. The PPP was designed as a collection of scripts that facilitate common population genomic workflows in a consistent and standardized Python environment. Functions were developed to encompass entire workflows, including input preparation, file format conversion, various population genomic analyses, and output generation. The platform has also been developed with reproducibility and extensibility of analyses in mind. The PPP is an open-source package that is available for download and use at https://ppp.readthedocs.io/en/latest/PPP_pages/install.html.

An estimator of first coalescent time reveals selection on young variants and large heterogeneity in rare allele ages among human populations.

Allele age has long been a focus of population genetic research, primarily because it can be an important clue to the fitness effects of an allele. By virtue of their effects on fitness, alleles under directional selection are expected to be younger than neutral alleles of the same frequency. We developed a new coalescent-based estimator of a close proxy for allele age, the time when a copy of an allele first shares common ancestry with other chromosomes in a sample not carrying that allele. The estimator performs well, including for the very rarest of alleles that occur just once in a sample, with a bias that is typically negative. The estimator is mostly insensitive to population demography and to factors that can arise in population genomic pipelines, including the statistical phasing of chromosomes. Applications to 1000 Genomes Data and UK10K genome data confirm predictions that singleton alleles that alter proteins are significantly younger than those that do not, with a greater difference in the larger UK10K dataset, as expected. The 1000 Genomes populations varied markedly in their distributions for singleton allele ages, suggesting that these distributions can be used to inform models of demographic history, including recent events that are only revealed by their impacts on the ages of very rare alleles.

Further resolution of the house mouse (Mus musculus) phylogeny by integration over isolation-with-migration histories.

BACKGROUND: The three main subspecies of house mice, Mus musculus castaneus, Mus musculus domesticus, and Mus musculus musculus, are estimated to have diverged ~ 350-500KYA. Resolution of the details of their evolutionary history is complicated by their relatively recent divergence, ongoing gene flow among the subspecies, and complex demographic histories. Previous studies have been limited to some extent by the number of loci surveyed and/or by the scope of the method used. Here, we apply a method (IMa3) that provides an estimate of a population phylogeny while allowing for complex histories of gene exchange. RESULTS: Results strongly support a topology with M. m. domesticus as sister to M. m. castaneus and M. m. musculus. In addition, we find evidence of gene flow between all pairs of subspecies, but that gene flow is most restricted from M. m. musculus into M. m. domesticus. Estimates of other key parameters are dependent on assumptions regarding generation time and mutation rate in house mice. Nevertheless, our results support previous findings that the effective population size, Ne, of M. m. castaneus is larger than that of the other two subspecies, that the three subspecies began diverging ~ 130 - 420KYA, and that the time between divergence events was short. CONCLUSIONS: Joint demographic and phylogenetic analyses of genomic data provide a clearer picture of the history of divergence in house mice.

Emerging Frontiers in the Study of Molecular Evolution.

A collection of the editors of Journal of Molecular Evolution have gotten together to pose a set of key challenges and future directions for the field of molecular evolution. Topics include challenges and new directions in prebiotic chemistry and the RNA world, reconstruction of early cellular genomes and proteins, macromolecular and functional evolution, evolutionary cell biology, genome evolution, molecular evolutionary ecology, viral phylodynamics, theoretical population genomics, somatic cell molecular evolution, and directed evolution. While our effort is not meant to be exhaustive, it reflects research questions and problems in the field of molecular evolution that are exciting to our editors.

Phylogeny Estimation by Integration over Isolation with Migration Models.

Phylogeny estimation is difficult for closely related populations and species, especially if they have been exchanging genes. We present a hierarchical Bayesian, Markov-chain Monte Carlo method with a state space that includes all possible phylogenies in a full Isolation-with-Migration model framework. The method is based on a new type of genealogy augmentation called a "hidden genealogy" that enables efficient updating of the phylogeny. This is the first likelihood-based method to fully incorporate directional gene flow and genetic drift for estimation of a species or population phylogeny. Application to human hunter-gatherer populations from Africa revealed a clear phylogenetic history, with strong support for gene exchange with an unsampled ghost population, and relatively ancient divergence between a ghost population and modern human populations, consistent with human/archaic divergence. In contrast, a study of five chimpanzee populations reveals a clear phylogeny with several pairs of populations having exchanged DNA, but does not support a history with an unsampled ghost population.

Understanding the origin of species with genome-scale data: modelling gene flow.

As it becomes easier to sequence multiple genomes from closely related species, evolutionary biologists working on speciation are struggling to get the most out of very large population genomic data sets. Such data hold the potential to resolve long-standing questions in evolutionary biology about the role of gene exchange in species formation. In principle, the new population genomic data can be used to disentangle the conflicting roles of natural selection and gene flow during the divergence process. However, there are great challenges in taking full advantage of such data, especially with regard to including recombination in genetic models of the divergence process. Current data, models, methods and the potential pitfalls in using them will be considered here.

Bayesian Analysis of Evolutionary Divergence with Genomic Data under Diverse Demographic Models.

We present a new Bayesian method for estimating demographic and phylogenetic history using population genomic data. Several key innovations are introduced that allow the study of diverse models within an Isolation-with-Migration framework. The new method implements a 2-step analysis, with an initial Markov chain Monte Carlo (MCMC) phase that samples simple coalescent trees, followed by the calculation of the joint posterior density for the parameters of a demographic model. In step 1, the MCMC sampling phase, the method uses a reduced state space, consisting of coalescent trees without migration paths, and a simple importance sampling distribution without the demography of interest. Once obtained, a single sample of trees can be used in step 2 to calculate the joint posterior density for model parameters under multiple diverse demographic models, without having to repeat MCMC runs. Because migration paths are not included in the state space of the MCMC phase, but rather are handled by analytic integration in step 2 of the analysis, the method is scalable to a large number of loci with excellent MCMC mixing properties. With an implementation of the new method in the computer program MIST, we demonstrate the method's accuracy, scalability, and other advantages using simulated data and DNA sequences of two common chimpanzee subspecies: Pan troglodytes (P. t.) troglodytes and P. t. verus.

IMGui-A Desktop GUI Application for Isolation with Migration Analyses.

The Isolation with Migration (IM) programs (e.g., IMa2) have been utilized extensively by evolutionary biologists for model-based inference of demographic parameters including effective population sizes, migration rates, and divergence times. Here, we describe a graphical user interface for the latest IM program. IMGui provides a comprehensive set of tools for performing demographic analyses, tracking progress of runs, and visualizing results. Developed using node. js and the Electron framework, IMGui is an application that runs on any desktop operating system, and is available for download at https://github.com/jaredgk/IMgui-electron-packages.

Inferring Very Recent Population Growth Rate from Population-Scale Sequencing Data: Using a Large-Sample Coalescent Estimator.

Large-sample or population-level sequencing data provide unprecedented opportunities for inferring detailed population histories, especially recent demographic histories. On the other hand, it challenges most existing population genetic methods: Simulation-based approaches require intensive computation, and analytical approaches are often numerically intractable when the sample size is large. We propose a computationally efficient method for simultaneous estimation of population size, the rate, and onset time of population growth in the very recent history, using the pattern of the total number of segregating sites as a function of sample size. Coalescent simulation shows that it can accurately and efficiently estimate the parameters of recent population growth from large-scale data. This approach has the flexibility to model population history with multiple growth stages or other epochs, and it is robust when the sample size is very large or at the population scale, for which the Kingman's coalescent assumption is not valid. This approach is applied to recently published data and estimates the recent population growth rate in the European population to be 1.49% with the onset time 7.26 ka, and the rate in the African population to be 0.735% with the onset time 10.01 ka.

On the occurrence of false positives in tests of migration under an isolation-with-migration model.

The population genetic study of divergence is often carried out using a Bayesian genealogy sampler, like those implemented in ima2 and related programs, and these analyses frequently include a likelihood ratio test of the null hypothesis of no migration between populations. Cruickshank and Hahn (2014, Molecular Ecology, 23, 3133-3157) recently reported a high rate of false-positive test results with ima2 for data simulated with small numbers of loci under models with no migration and recent splitting times. We confirm these findings and discover that they are caused by a failure of the assumptions underlying likelihood ratio tests that arises when using marginal likelihoods for a subset of model parameters. We also show that for small data sets, with little divergence between samples from two populations, an excellent fit can often be found by a model with a low migration rate and recent splitting time and a model with a high migration rate and a deep splitting time.

A hidden Markov model for investigating recent positive selection through haplotype structure.

Recent positive selection can increase the frequency of an advantageous mutant rapidly enough that a relatively long ancestral haplotype will be remained intact around it. We present a hidden Markov model (HMM) to identify such haplotype structures. With HMM identified haplotype structures, a population genetic model for the extent of ancestral haplotypes is then adopted for parameter inference of the selection intensity and the allele age. Simulations show that this method can detect selection under a wide range of conditions and has higher power than the existing frequency spectrum-based method. In addition, it provides good estimate of the selection coefficients and allele ages for strong selection. The method analyzes large data sets in a reasonable amount of running time. This method is applied to HapMap III data for a genome scan, and identifies a list of candidate regions putatively under recent positive selection. It is also applied to several genes known to be under recent positive selection, including the LCT, KITLG and TYRP1 genes in Northern Europeans, and OCA2 in East Asians, to estimate their allele ages and selection coefficients.

Origins of shared genetic variation in African cichlids.

Cichlid fishes have evolved tremendous morphological and behavioral diversity in the waters of East Africa. Within each of the Great Lakes Tanganyika, Malawi, and Victoria, the phenomena of hybridization and retention of ancestral polymorphism explain allele sharing across species. Here, we explore the sharing of single nucleotide polymorphisms (SNPs) between the major East African cichlid assemblages. A set of approximately 200 genic and nongenic SNPs was ascertained in five Lake Malawi species and genotyped in a diverse collection of ~160 species from across Africa. We observed segregating polymorphism outside of the Malawi lineage for more than 50% of these loci; this holds similarly for genic versus nongenic SNPs, as well as for SNPs at putative CpG versus non-CpG sites. Bayesian and principal component analyses of genetic structure in the data demonstrate that the Lake Malawi endemic flock is not monophyletic and that river species have likely contributed significantly to Malawi genomes. Coalescent simulations support the hypothesis that river cichlids have transported polymorphism between lake assemblages. We observed strong genetic differentiation between Malawi lineages for approximately 8% of loci, with contributions from both genic and nongenic SNPs. Notably, more than half of these outlier loci between Malawi groups are polymorphic outside of the lake. Cichlid fishes have evolved diversity in Lake Malawi as new mutations combined with standing genetic variation shared across East Africa.

Allele age estimators designed for whole genome datasets show only a modest decrease in accuracy when applied to whole exome datasets.

Personalized genomics in the healthcare system is becoming increasingly accessible as the costs of sequencing decreases. With the increase in number of genomes, larger numbers of rare variants are being discovered and much work is being done to identify their functional impacts in relation to disease phenotypes. One way to characterize these variants is to estimate the time the mutation entered the population. However, allele age estimators such as Relate, Genealogical Estimator of Variant Age, and time of coalescence, were developed based on the assumption that datasets include the entire genome. We examined the performance of each of these estimators on simulated exome data under a neutral constant population size model and found that each provides usable estimates of allele age from whole-exome datasets. To test the robustness of these methods, analyses were undertaken to simulate data under a population expansion model and background selection. Relate performs the best amongst all three estimators with Pearson coefficients of 0.64 and 0.68 (neutral constant and expansion population model) with a 17 percent and 15 percent drop in accuracy between whole genome and whole exome estimations. Of the three estimators, Relate is best able to parallelize to yield quick results with little resources, however even Relate is only able to scale to thousands of samples making it unable to match the hundreds of thousands of samples being currently released. While more work is needed to expand the capabilities of current methods of estimating allele age, these methods estimate the age of mutations with a modest decrease in performance.

Diverse captive non-human primates with phytanic acid-deficient diets rich in plant products have substantial phytanic acid levels in their red blood cells.

BACKGROUND: Humans and rodents with impaired phytanic acid (PA) metabolism can accumulate toxic stores of PA that have deleterious effects on multiple organ systems. Ruminants and certain fish obtain PA from the microbial degradation of dietary chlorophyll and/or through chlorophyll-derived precursors. In contrast, humans cannot derive PA from chlorophyll and instead normally obtain it only from meat, dairy, and fish products. RESULTS: Captive apes and Old world monkeys had significantly higher red blood cell (RBC) PA levels relative to humans when all subjects were fed PA-deficient diets. Given the adverse health effects resulting from PA over accumulation, we investigated the molecular evolution of thirteen PA metabolism genes in apes, Old world monkeys, and New world monkeys. All non-human primate (NHP) orthologs are predicted to encode full-length proteins with the marmoset Phyh gene containing a rare, but functional, GA splice donor dinucleotide. Acox2, Scp2, and Pecr sequences had amino acid positions with accelerated substitution rates while Amacr had significant variation in evolutionary rates in apes relative to other primates. CONCLUSIONS: Unlike humans, diverse captive NHPs with PA-deficient diets rich in plant products have substantial RBC PA levels. The favored hypothesis is that NHPs can derive significant amounts of PA from the degradation of ingested chlorophyll through gut fermentation. If correct, this raises the possibility that RBC PA levels could serve as a biomarker for evaluating the digestive health of captive NHPs. Furthermore, the evolutionary rates of the several genes relevant to PA metabolism provide candidate genetic adaptations to NHP diets.

Analyses of allele age and fitness impact reveal human beneficial alleles to be older than neutral controls.

A classic population genetic prediction is that alleles experiencing directional selection should swiftly traverse allele frequency space, leaving detectable reductions in genetic variation in linked regions. However, despite this expectation, identifying clear footprints of beneficial allele passage has proven to be surprisingly challenging. We addressed the basic premise underlying this expectation by estimating the ages of large numbers of beneficial and deleterious alleles in a human population genomic data set. Deleterious alleles were found to be young, on average, given their allele frequency. However, beneficial alleles were older on average than non-coding, non-regulatory alleles of the same frequency. This finding is not consistent with directional selection and instead indicates some type of balancing selection. Among derived beneficial alleles, those fixed in the population show higher local recombination rates than those still segregating, consistent with a model in which new beneficial alleles experience an initial period of balancing selection due to linkage disequilibrium with deleterious recessive alleles. Alleles that ultimately fix following a period of balancing selection will leave a modest 'soft' sweep impact on the local variation, consistent with the overall paucity of species-wide 'hard' sweeps in human genomes.

Enrichment of mRNA-like noncoding RNAs in the divergence of Drosophila males.

With the advent of transcriptome data, it has become clear that mRNA-like noncoding RNAs (mlncRNAs) are widespread in eukaryotes. Although their functions are poorly understood, these transcripts may play an important role in development and could thus be involved in determining developmental complexity and phenotypic diversification. However, few studies have assessed their potential roles in the divergence of closely related species. Here, we identify and study patterns of sequence and expression divergence in ten novel candidate mlncRNAs from Drosophila pseudoobscura and its close relative D. persimilis. The candidate mlncRNAs were identified by randomly sequencing a group of 734 cDNA clones from a microarray that showed either no difference in expression (187 clones) or differential expression (547 clones) in comparisons between D. pseudoobscura and D. persimilis and between these two species and their F(1) hybrids. Candidate mlncRNAs are overrepresented among differentially expressed transcripts between males of D. pseudoobscura and D. persimilis, and although they have high sequence conservation between these two species, seven of them have no putative homologs in any of the other ten Drosophila species whose genomes have been sequenced. Expression of eight of the ten candidate mlncRNAs was detected either in whole bodies (adults) or testes using a custom-designed oligonucleotide microarray. Three of the ten candidate mlncRNAs are highly expressed (in the top 4% of the male transcriptome), differentially expressed between species, and show extreme levels of sex-bias, with one transcript having the highest level of male bias in the whole transcriptome. Proteomic data from testes show no traces of any predicted peptides from the candidate mlncRNAs. Our results suggest that these mlncRNAs may be important in male-specific processes related to sexual dimorphism and species divergence in this species group.

Vicariance divergence and gene flow among islet populations of an endemic lizard.

Allopatry and allopatric speciation can arise through two different mechanisms: vicariance or colonization through dispersal. Distinguishing between these different allopatric mechanisms is difficult and one of the major challenges in biogeographical research. Here, we address whether allopatric isolation in an endemic island lizard is the result of vicariance or dispersal. We estimated the amount and direction of gene flow during the divergence of isolated islet populations and subspecies of the endemic Skyros wall lizard Podarcis gaigeae, a phenotypically variable species that inhabits a major island and small islets in the Greek archipelago. We applied isolation-with-migration models to estimate population divergence times, population sizes and gene flow between islet-mainland population pairs. Divergence times were significantly correlated with independently estimated geological divergence times. This correlation strongly supports a vicariance scenario where islet populations have sequentially become isolated from the major island. We did not find evidence for significant gene flow within P. g. gaigeae. However, gene-flow estimates from the islet to the mainland populations were positively affected by islet area and negatively by distance between the islet and mainland. We also found evidence for gene flow from one subspecies (P. g. weigandi) into another (P. g. gaigeae), but not in the other direction. Ongoing gene flow between the subspecies suggests that even in this geographically allopatric scenario with the sea posing a strong barrier to dispersal, divergence with some gene flow is still feasible.

Divergence time estimation using ddRAD data and an isolation-with-migration model applied to water vole populations of Arvicola.

Molecular dating methods of population splits are crucial in evolutionary biology, but they present important difficulties due to the complexity of the genealogical relationships of genes and past migrations between populations. Using the double digest restriction-site associated DNA (ddRAD) technique and an isolation-with-migration (IM) model, we studied the evolutionary history of water vole populations of the genus Arvicola, a group of complex evolution with fossorial and semi-aquatic ecotypes. To do this, we first estimated mutation rates of ddRAD loci using a phylogenetic approach. An IM model was then used to estimate split times and other relevant demographic parameters. A set of 300 ddRAD loci that included 85 calibrated loci resulted in good mixing and model convergence. The results showed that the two populations of A. scherman present in the Iberian Peninsula split 34 thousand years ago, during the last glaciation. In addition, the much greater divergence from its sister species, A. amphibius, may help to clarify the controversial taxonomy of the genus. We conclude that this approach, based on ddRAD data and an IM model, is highly useful for analyzing the origin of populations and species.