The effective population sizes of the anthropoid ancestors of the human-chimpanzee lineage provide insights on the historical biogeography of the great apes

Temporal challenges in detecting balancing selection from population genomic data

The role of balancing selection in maintaining genetic variation remains an open question in population genetics. Recent years have seen numerous studies identifying candidate loci potentially experiencing balancing selection, most predominantly in human populations. There are however numerous alternative evolutionary processes that may leave similar patterns of variation, thereby potentially confounding inference, and the expected signatures of balancing selection additionally change in a temporal fashion. Here we use forward-in-time simulations to quantify expected statistical power to detect balancing selection using both site frequency spectrum- and linkage disequilibrium-based methods under a variety of evolutionarily realistic null models. We find that whilst site frequency spectrum-based methods have little power immediately after a balanced mutation begins segregating, power increases with time since the introduction of the balanced allele. Conversely, linkage disequilibrium-based methods have considerable power whilst the allele is young, and power dissipates rapidly as the time since introduction increases. Taken together, this suggests that site frequency spectrum-based methods are most effective at detecting long-term balancing selection (>25N generations since the introduction of the balanced allele) whilst linkage disequilibrium-based methods are effective over much shorter timescales (<1N generations), thereby leaving a large time frame over which current methods have little power to detect the action of balancing selection. Finally, we investigate the extent to which alternative evolutionary processes may mimic these patterns, and demonstrate the need for caution in attempting to distinguish the signatures of balancing selection from those of both neutral processes (e.g. population structure and admixture) as well as of alternative selective processes (e.g. partial selective sweeps).

Pervasive incomplete lineage sorting illuminates speciation and selection in primates

Incomplete lineage sorting (ILS) causes the phylogeny of some parts of the genome to differ from the species tree. In this work, we investigate the frequencies and determinants of ILS in 29 major ancestral nodes across the entire primate phylogeny. We find up to 64% of the genome affected by ILS at individual nodes. We exploit ILS to reconstruct speciation times and ancestral population sizes. Estimated speciation times are much more recent than genomic divergence times and are in good agreement with the fossil record. We show extensive variation of ILS along the genome, mainly driven by recombination but also by the distance to genes, highlighting a major impact of selection on variation along the genome. In many nodes, ILS is reduced more on the X chromosome compared with autosomes than expected under neutrality, which suggests higher impacts of natural selection on the X chromosome. Finally, we show an excess of ILS in genes with immune functions and a deficit of ILS in housekeeping genes. The extensive ILS in primates discovered in this study provides insights into the speciation times, ancestral population sizes, and patterns of natural selection that shape primate evolution.

OUP accepted manuscript

The rate of amino acid substitution has been shown to be correlated to a number of factors including the rate of recombination, the age of the gene, the length of the protein, mean expression level, and gene function. However, the extent to which these correlations are due to adaptive and nonadaptive evolution has not been studied in detail, at least not in hominids. We find that the rate of adaptive evolution is significantly positively correlated to the rate of recombination, protein length and gene expression level, and negatively correlated to gene age. These correlations remain significant when each factor is controlled for in turn, except when controlling for expression in an analysis of protein length; and they also generally remain significant when biased gene conversion is taken into account. However, the positive correlations could be an artifact of population size contraction. We also find that the rate of nonadaptive evolution is negatively correlated to each factor, and all these correlations survive controlling for each other and biased gene conversion. Finally, we examine the effect of gene function on rates of adaptive and nonadaptive evolution; we confirm that virus-interacting proteins (VIPs) have higher rates of adaptive and lower rates of nonadaptive evolution, but we also demonstrate that there is significant variation in the rate of adaptive and nonadaptive evolution between GO categories when removing VIPs. We estimate that the VIP/non-VIP axis explains about 5–8 fold more of the variance in evolutionary rate than GO categories.

OUP accepted manuscript

It is known that methods to estimate the rate of adaptive evolution, which are based on the McDonald–Kreitman test, can be biased by changes in effective population size. Here, we demonstrate theoretically that changes in population size can also generate an artifactual correlation between the rate of adaptive evolution and any factor that is correlated to the strength of selection acting against deleterious mutations. In this context, we have investigated whether several site-level factors influence the rate of adaptive evolution in the divergence of humans and chimpanzees, two species that have been inferred to have undergone population size contraction since they diverged. We find that the rate of adaptive evolution, relative to the rate of mutation, is higher for more exposed amino acids, lower for amino acid pairs that are more dissimilar in terms of their polarity, volume, and lower for amino acid pairs that are subject to stronger purifying selection, as measured by the ratio of the numbers of nonsynonymous to synonymous polymorphisms (p_N/p_S). All of these correlations are opposite to the artifactual correlations expected under contracting population size. We therefore conclude that these correlations are genuine.

The germline mutational process in rhesus macaque and its implications for phylogenetic dating

BACKGROUND

Understanding the rate and pattern of germline mutations is of fundamental importance for understanding evolutionary processes.

RESULTS

Here we analyzed 19 parent-offspring trios of rhesus macaques (Macaca mulatta) at high sequencing coverage of ∼76× per individual and estimated a mean rate of 0.77 × 10-8de novo mutations per site per generation (95% CI: 0.69 × 10-8 to 0.85 × 10-8). By phasing 50% of the mutations to parental origins, we found that the mutation rate is positively correlated with the paternal age. The paternal lineage contributed a mean of 81% of the de novo mutations, with a trend of an increasing male contribution for older fathers. Approximately 3.5% of de novo mutations were shared between siblings, with no parental bias, suggesting that they arose from early development (postzygotic) stages. Finally, the divergence times between closely related primates calculated on the basis of the yearly mutation rate of rhesus macaque generally reconcile with divergence estimated with molecular clock methods, except for the Cercopithecoidea/Hominoidea molecular divergence dated at 58 Mya using our new estimate of the yearly mutation rate.

CONCLUSIONS

When compared to the traditional molecular clock methods, new estimated rates from pedigree samples can provide insights into the evolution of well-studied groups such as primates.

Greater strength of selection and higher proportion of beneficial amino acid changing mutations in humans compared with mice and Drosophila melanogaster

Quantifying and comparing the amount of adaptive evolution among different species is key to understanding how evolution works. Previous studies have shown differences in adaptive evolution across species; however, their specific causes remain elusive. Here, we use improved modeling of weakly deleterious mutations and the demographic history of the outgroup species and ancestral population and estimate that at least 20% of nonsynonymous substitutions between humans and an outgroup species were fixed by positive selection. This estimate is much higher than previous estimates, which did not correct for the sizes of the outgroup species and ancestral population. Next, we jointly estimate the proportion and selection coefficient (p⁺ and s⁺, respectively) of newly arising beneficial nonsynonymous mutations in humans, mice, and Drosophila melanogaster by examining patterns of polymorphism and divergence. We develop a novel composite likelihood framework to test whether these parameters differ across species. Overall, we reject a model with the same p⁺ and s⁺ of beneficial mutations across species and estimate that humans have a higher p⁺s⁺ compared with that of D. melanogaster and mice. We show that this result cannot be caused by biased gene conversion or hypermutable CpG sites. We discuss possible biological explanations that could generate the observed differences in the amount of adaptive evolution across species.

Molecular dating for phylogenies containing a mix of populations and species by using Bayesian and RelTime approaches

Simultaneous molecular dating of population and species divergences is essential in many biological investigations, including phylogeography, phylodynamics and species delimitation studies. In these investigations, multiple sequence alignments consist of both intra- and interspecies samples (mixed samples). As a result, the phylogenetic trees contain interspecies, interpopulation and within-population divergences. Bayesian relaxed clock methods are often employed in these analyses, but they assume the same tree prior for both inter- and intraspecies branching processes and require specification of a clock model for branch rates (independent vs. autocorrelated rates models). We evaluated the impact of a single tree prior on Bayesian divergence time estimates by analysing computer-simulated data sets. We also examined the effect of the assumption of independence of evolutionary rate variation among branches when the branch rates are autocorrelated. Bayesian approach with coalescent tree priors generally produced excellent molecular dates and highest posterior densities with high coverage probabilities. We also evaluated the performance of a non-Bayesian method, RelTime, which does not require the specification of a tree prior or a clock model. RelTime's performance was similar to that of the Bayesian approach, suggesting that it is also suitable to analyse data sets containing both populations and species variation when its computational efficiency is needed.

The Estimated Pacemaker for Great Apes Supports the Hominoid Slowdown Hypothesis

The recent surge of genomic data has prompted the investigation of substitution rate variation across the genome, as well as among lineages. Evolutionary trees inferred from distinct genomic regions may display branch lengths that differ between loci by simple proportionality constants, indicating that rate variation follows a pacemaker model, which may be attributed to lineage effects. Analyses of genes from diverse biological clades produced contrasting results, supporting either this model or alternative scenarios where multiple pacemakers exist. So far, an evaluation of the pacemaker hypothesis for all great apes has never been carried out. In this work, we tested whether the evolutionary rates of hominids conform to pacemakers, which were inferred accounting for gene tree/species tree discordance. For higher precision, substitution rates in branches were estimated with a calibration-free approach, the relative rate framework. A predominant evolutionary trend in great apes was evidenced by the recovery of a large pacemaker, encompassing most hominid genomic regions. In addition, the majority of genes followed a pace of evolution that was closely related to the strict molecular clock. However, slight rate decreases were recovered in the internal branches leading to humans, corroborating the hominoid slowdown hypothesis. Our findings suggest that in great apes, life history traits were the major drivers of substitution rate variation across the genome.

Appropriate Assignment of Fossil Calibration Information Minimizes the Difference between Phylogenetic and Pedigree Mutation Rates in Humans

Studies that measured mutation rates in human populations using pedigrees have reported values that differ significantly from rates estimated from the phylogenetic comparison of humans and chimpanzees. Consequently, exchanges between mutation rate values across different timescales lead to conflicting divergence time estimates. It has been argued that this variation of mutation rate estimates across hominoid evolution is in part caused by incorrect assignment of calibration information to the mean coalescent time among loci, instead of the true genetic isolation (speciation) time between humans and chimpanzees. In this study, we investigated the feasibility of estimating the human pedigree mutation rate using phylogenetic data from the genomes of great apes. We found that, when calibration information was correctly assigned to the human⁻chimpanzee speciation time (and not to the coalescent time), estimates of phylogenetic mutation rates were statistically equivalent to the estimates previously reported using studies of human pedigrees. We conclude that, within the range of biologically realistic ancestral generation times, part of the difference between whole-genome phylogenetic and pedigree mutation rates is due to inappropriate assignment of fossil calibration information to the mean coalescent time instead of the speciation time. Although our results focus on the human⁻chimpanzee divergence, our findings are general, and relevant to the inference of the timescale of the tree of life.

Repeat associated mechanisms of genome evolution and function revealed by the Mus caroli and Mus pahari genomes

Understanding the mechanisms driving lineage-specific evolution in both primates and rodents has been hindered by the lack of sister clades with a similar phylogenetic structure having high-quality genome assemblies. Here, we have created chromosome-level assemblies of the Mus caroli and Mus pahari genomes. Together with the Mus musculus and Rattus norvegicus genomes, this set of rodent genomes is similar in divergence times to the Hominidae (human-chimpanzee-gorilla-orangutan). By comparing the evolutionary dynamics between the Muridae and Hominidae, we identified punctate events of chromosome reshuffling that shaped the ancestral karyotype of Mus musculus and Mus caroli between 3 and 6 million yr ago, but that are absent in the Hominidae. Hominidae show between four- and sevenfold lower rates of nucleotide change and feature turnover in both neutral and functional sequences, suggesting an underlying coherence to the Muridae acceleration. Our system of matched, high-quality genome assemblies revealed how specific classes of repeats can play lineage-specific roles in related species. Recent LINE activity has remodeled protein-coding loci to a greater extent across the Muridae than the Hominidae, with functional consequences at the species level such as reproductive isolation. Furthermore, we charted a Muridae-specific retrotransposon expansion at unprecedented resolution, revealing how a single nucleotide mutation transformed a specific SINE element into an active CTCF binding site carrier specifically in Mus caroli, which resulted in thousands of novel, species-specific CTCF binding sites. Our results show that the comparison of matched phylogenetic sets of genomes will be an increasingly powerful strategy for understanding mammalian biology.

Impact of long-term chromosomal shuffling on the multispecies coalescent analysis of two anthropoid primate lineages

Multispecies coalescent (MSC) theory assumes that gene trees inferred from individual loci are independent trials of the MSC process. As genes might be physically close in syntenic associations spanning along chromosome regions, these assumptions might be flawed in evolutionary lineages with substantial karyotypic shuffling. Neotropical primates (NP) represent an ideal case for assessing the performance of MSC methods in such scenarios because chromosome diploid number varies significantly in this lineage. To this end, we investigated the effect of sequence length on the theoretical expectations of MSC model, as well as the results of coalescent‐based tree inference methods. This was carried out by comparing NP with hominids, a lineage in which chromosome macrostructure has been stable for at least 15 million years. We found that departure from the MSC model in Neotropical primates decreased with smaller sequence fragments, where sites sharing the same evolutionary history were more frequently found than in longer fragments. This scenario probably resulted from extensive karyotypic rearrangement occurring during the radiation of NP, contrary to the comparatively stable chromosome evolution in hominids.

Simulation-Based Evaluation of Hybridization Network Reconstruction Methods in the Presence of Incomplete Lineage Sorting

Hybridization events generate reticulate species relationships, giving rise to species networks rather than species trees. We report a comparative study of consensus, maximum parsimony, and maximum likelihood methods of species network reconstruction using gene trees simulated assuming a known species history. We evaluate the role of the divergence time between species involved in a hybridization event, the relative contributions of the hybridizing species, and the error in gene tree estimation. When gene tree discordance is mostly due to hybridization and not due to incomplete lineage sorting (ILS), most of the methods can detect even highly skewed hybridization events between highly divergent species. For recent divergences between hybridizing species, when the influence of ILS is sufficiently high, likelihood methods outperform parsimony and consensus methods, which erroneously identify extra hybridizations. The more sophisticated likelihood methods, however, are affected by gene tree errors to a greater extent than are consensus and parsimony.

Emerging Concepts of Data Integration in Pathogen Phylodynamics

Phylodynamics has become an increasingly popular statistical framework to extract evolutionary and epidemiological information from pathogen genomes. By harnessing such information, epidemiologists aim to shed light on the spatio-temporal patterns of spread and to test hypotheses about the underlying interaction of evolutionary and ecological dynamics in pathogen populations. Although the field has witnessed a rich development of statistical inference tools with increasing levels of sophistication, these tools initially focused on sequences as their sole primary data source. Integrating various sources of information, however, promises to deliver more precise insights in infectious diseases and to increase opportunities for statistical hypothesis testing. Here, we review how the emerging concept of data integration is stimulating new advances in Bayesian evolutionary inference methodology which formalize a marriage of statistical thinking and evolutionary biology. These approaches include connecting sequence to trait evolution, such as for host, phenotypic and geographic sampling information, but also the incorporation of covariates of evolutionary and epidemic processes in the reconstruction procedures. We highlight how a full Bayesian approach to covariate modeling and testing can generate further insights into sequence evolution, trait evolution, and population dynamics in pathogen populations. Specific examples demonstrate how such approaches can be used to test the impact of host on rabies and HIV evolutionary rates, to identify the drivers of influenza dispersal as well as the determinants of rabies cross-species transmissions, and to quantify the evolutionary dynamics of influenza antigenicity. Finally, we briefly discuss how data integration is now also permeating through the inference of transmission dynamics, leading to novel insights into tree-generative processes and detailed reconstructions of transmission trees. [Bayesian inference; birth–death models; coalescent models; continuous trait evolution; covariates; data integration; discrete trait evolution; pathogen phylodynamics.

An analytical upper bound on the number of loci required for all splits of a species tree to appear in a set of gene trees

Background

Many methods for species tree inference require data from a sufficiently large sample of genomic loci in order to produce accurate estimates. However, few studies have attempted to use analytical theory to quantify “sufficiently large”.

Results

Using the multispecies coalescent model, we report a general analytical upper bound on the number of gene trees n required such that with probability q, each bipartition of a species tree is represented at least once in a set of n random gene trees. This bound employs a formula that is straightforward to compute, depends only on the minimum internal branch length of the species tree and the number of taxa, and applies irrespective of the species tree topology. Using simulations, we investigate numerical properties of the bound as well as its accuracy under the multispecies coalescent.

Conclusions

Our results are helpful for conservatively bounding the number of gene trees required by the ASTRAL inference method, and the approach has potential to be extended to bound other properties of gene tree sets under the model.

In silico phylogenomics using complete genomes: a case study on the evolution of hominoids

The increasing availability of complete genome data is facilitating the acquisition of phylogenomic data sets, but the process of obtaining orthologous sequences from other genomes and assembling multiple sequence alignments remains piecemeal and arduous. We designed software that performs these tasks and outputs anonymous loci (AL) or anchored enrichment/ultraconserved element loci (AE/UCE) data sets in ready-to-analyze formats. We demonstrate our program by applying it to the hominoids. Starting with human, chimpanzee, gorilla, and orangutan genomes, our software generated an exhaustive data set of 292 ALs (∼1 kb each) in ∼3 h. Not only did analyses of our AL data set validate the program by yielding a portrait of hominoid evolution in agreement with previous studies, but the accuracy and precision of our estimated ancestral effective population sizes and speciation times represent improvements. We also used our program with a published set of 512 vertebrate-wide AE "probe" sequences to generate data sets consisting of 171 and 242 independent loci (∼1 kb each) in 11 and 13 min, respectively. The former data set consisted of flanking sequences 500 bp from adjacent AEs, while the latter contained sequences bordering AEs. Although our AE data sets produced the expected hominoid species tree, coalescent-based estimates of ancestral population sizes and speciation times based on these data were considerably lower than estimates from our AL data set and previous studies. Accordingly, we suggest that loci subjected to direct or indirect selection may not be appropriate for coalescent-based methods. Complete in silico approaches, combined with the burgeoning genome databases, will accelerate the pace of phylogenomics.

Does Gene Tree Discordance Explain the Mismatch between Macroevolutionary Models and Empirical Patterns of Tree Shape and Branching Times?

Classic null models for speciation and extinction give rise to phylogenies that differ in distribution from empirical phylogenies. In particular, empirical phylogenies are less balanced and have branching times closer to the root compared to phylogenies predicted by common null models. This difference might be due to null models of the speciation and extinction process being too simplistic, or due to the empirical datasets not being representative of random phylogenies. A third possibility arises because phylogenetic reconstruction methods often infer gene trees rather than species trees, producing an incongruity between models that predict species tree patterns and empirical analyses that consider gene trees. We investigate the extent to which the difference between gene trees and species trees under a combined birth-death and multispecies coalescent model can explain the difference in empirical trees and birth-death species trees. We simulate gene trees embedded in simulated species trees and investigate their difference with respect to tree balance and branching times. We observe that the gene trees are less balanced and typically have branching times closer to the root than the species trees. Empirical trees from TreeBase are also less balanced than our simulated species trees, and model gene trees can explain an imbalance increase of up to 8% compared to species trees. However, we see a much larger imbalance increase in empirical trees, about 100%, meaning that additional features must also be causing imbalance in empirical trees. This simulation study highlights the necessity of revisiting the assumptions made in phylogenetic analyses, as these assumptions, such as equating the gene tree with the species tree, might lead to a biased conclusion.

Multispecies coalescent analysis of the early diversification of neotropical primates: phylogenetic inference under strong gene trees/species tree conflict

Neotropical primates (NP) are presently distributed in the New World from Mexico to northern Argentina, comprising three large families, Cebidae, Atelidae, and Pitheciidae, consequently to their diversification following their separation from Old World anthropoids near the Eocene/Oligocene boundary, some 40 Ma. The evolution of NP has been intensively investigated in the last decade by studies focusing on their phylogeny and timescale. However, despite major efforts, the phylogenetic relationship between these three major clades and the age of their last common ancestor are still controversial because these inferences were based on limited numbers of loci and dating analyses that did not consider the evolutionary variation associated with the distribution of gene trees within the proposed phylogenies. We show, by multispecies coalescent analyses of selected genome segments, spanning along 92,496,904 bp that the early diversification of extant NP was marked by a 2-fold increase of their effective population size and that Atelids and Cebids are more closely related respective to Pitheciids. The molecular phylogeny of NP has been difficult to solve because of population-level phenomena at the early evolution of the lineage. The association of evolutionary variation with the distribution of gene trees within proposed phylogenies is crucial for distinguishing the mean genetic divergence between species (the mean coalescent time between loci) from speciation time. This approach, based on extensive genomic data provided by new generation DNA sequencing, provides more accurate reconstructions of phylogenies and timescales for all organisms.

Estimation of the ancestral effective population sizes of African great apes under different selection regimes

Reliable estimates of ancestral effective population sizes are necessary to unveil the population-level phenomena that shaped the phylogeny and molecular evolution of the African great apes. Although several methods have previously been applied to infer ancestral effective population sizes, an analysis of the influence of the selective regime on the estimates of ancestral demography has not been thoroughly conducted. In this study, three independent data sets under different selective regimes were used were composed to tackle this issue. The results showed that selection had a significant impact on the estimates of ancestral effective population sizes of the African great apes. The inference of the ancestral demography of African great apes was affected by the selection regime. The effects, however, were not homogeneous along the ancestral populations of great apes. The effective population size of the ancestor of humans and chimpanzees was more impacted by the selection regime when compared to the same parameter in the ancestor of humans, chimpanzees and gorillas. Because the selection regime influenced the estimates of ancestral effective population size, it is reasonable to assume that a portion of the discrepancy found in previous studies that inferred the ancestral effective population size may be attributable to the differential action of selection on the genes sampled.