Bayes estimation of species divergence times and ancestral population sizes using DNA sequences from multiple loci

The effective population sizes of ancestral as well as modern species are important parameters in models of population genetics and human evolution. The commonly used method for estimating ancestral population sizes, based on counting mismatches between the species tree and the inferred gene trees, is highly biased as it ignores uncertainties in gene tree reconstruction. In this article, we develop a Bayes method for simultaneous estimation of the species divergence times and current and ancestral population sizes. The method uses DNA sequence data from multiple loci and extracts information about conflicts among gene tree topologies and coalescent times to estimate ancestral population sizes. The topology of the species tree is assumed known. A Markov chain Monte Carlo algorithm is implemented to integrate over uncertain gene trees and branch lengths (or coalescence times) at each locus as well as species divergence times. The method can handle any species tree and allows different numbers of sequences at different loci. We apply the method to published noncoding DNA sequences from the human and the great apes. There are strong correlations between posterior estimates of speciation times and ancestral population sizes. With the use of an informative prior for the human-chimpanzee divergence date, the population size of the common ancestor of the two species is estimated to be approximately 20,000, with a 95% credibility interval (8000, 40,000). Our estimates, however, are affected by model assumptions as well as data quality. We suggest that reliable estimates have yet to await more data and more realistic models.     

Estimation of hominoid ancestral population sizes under bayesian coalescent models incorporating mutation rate variation and sequencing errors

Estimation of population parameters for the common ancestors of humans and the great apes is important in understanding our evolutionary history. In particular, inference of population size for the human-chimpanzee common ancestor may shed light on the process by which the 2 species separated and on whether the human population experienced a severe size reduction in its early evolutionary history. In this study, the Bayesian method of ancestral inference of Rannala and Yang (2003. Bayes estimation of species divergence times and ancestral population sizes using DNA sequences from multiple loci. Genetics. 164:1645-1656) was extended to accommodate variable mutation rates among loci and random species-specific sequencing errors. The model was applied to analyze a genome-wide data set of approximately 15,000 neutral loci (7.4 Mb) aligned for human, chimpanzee, gorilla, orangutan, and macaque. We obtained robust and precise estimates for effective population sizes along the hominoid lineage extending back approximately 30 Myr to the cercopithecoid divergence. The results showed that ancestral populations were 5-10 times larger than modern humans along the entire hominoid lineage. The estimates were robust to the priors used and to model assumptions about recombination. The unusually low X chromosome divergence between human and chimpanzee could not be explained by variation in the male mutation bias or by current models of hybridization and introgression. Instead, our parameter estimates were consistent with a simple instantaneous process for human-chimpanzee speciation but showed a major reduction in X chromosome effective population size peculiar to the human-chimpanzee common ancestor, possibly due to selective sweeps on the X prior to separation of the 2 species.     

On the estimation of ancestral population sizes of modern humans

The theory developed by Takahata and colleagues for estimating the effective population size of ancestral species using homologous sequences from closely related extant species was extended to take account of variation of evolutionary rates among loci. Nuclear sequence data related to the evolution of modern humans were reanalysed and computer simulations were performed to examine the effect of rate variation on estimation of ancestral population sizes. It is found that the among-locus rate variation does not have a significant effect on estimation of the current population size when sequences from multiple loci are sampled from the same species, but does have a significant effect on estimation of the ancestral population size using sequences from different species. The effects of ancestral population size, species divergence time and among-locus rate variation are found to be highly correlated, and to achieve reliable estimates of the ancestral population size, effects of the other two factors should be estimated independently.     

Likelihood and Bayes estimation of ancestral population sizes in hominoids using data from multiple loci

Polymorphisms in an ancestral population can cause conflicts between gene trees and the species tree. Such conflicts can be used to estimate ancestral population sizes when data from multiple loci are available. In this article I extend previous work for estimating ancestral population sizes to analyze sequence data from three species under a finite-site nucleotide substitution model. Both maximum-likelihood (ML) and Bayes methods are implemented for joint estimation of the two speciation dates and the two population size parameters. Both methods account for uncertainties in the gene tree due to few informative sites at each locus and make an efficient use of information in the data. The Bayes algorithm using Markov chain Monte Carlo (MCMC) enjoys a computational advantage over ML and also provides a framework for incorporating prior information about the parameters. The methods are applied to a data set of 53 nuclear noncoding contigs from human, chimpanzee, and gorilla published by Chen and Li. Estimates of the effective population size for the common ancestor of humans and chimpanzees by both ML and Bayes methods are approximately 12,000-21,000, comparable to estimates for modern humans, and do not support the notion of a dramatic size reduction in early human populations. Estimates published previously from the same data are several times larger and appear to be biased due to methodological deficiency. The divergence between humans and chimpanzees is dated at approximately 5.2 million years ago and the gorilla divergence 1.1-1.7 million years earlier. The analysis suggests that typical data sets contain useful information about the ancestral population sizes and that it is advantageous to analyze data of several species simultaneously.     

Estimating divergence time and ancestral effective population size of Bornean and Sumatran orangutan subspecies using a coalescent hidden Markov model

Due to genetic variation in the ancestor of two populations or two species, the divergence time for DNA sequences from two populations is variable along the genome. Within genomic segments all bases will share the same divergence-because they share a most recent common ancestor-when no recombination event has occurred to split them apart. The size of these segments of constant divergence depends on the recombination rate, but also on the speciation time, the effective population size of the ancestral population, as well as demographic effects and selection. Thus, inference of these parameters may be possible if we can decode the divergence times along a genomic alignment. Here, we present a new hidden Markov model that infers the changing divergence (coalescence) times along the genome alignment using a coalescent framework, in order to estimate the speciation time, the recombination rate, and the ancestral effective population size. The model is efficient enough to allow inference on whole-genome data sets. We first investigate the power and consistency of the model with coalescent simulations and then apply it to the whole-genome sequences of the two orangutan sub-species, Bornean (P. p. pygmaeus) and Sumatran (P. p. abelii) orangutans from the Orangutan Genome Project. We estimate the speciation time between the two sub-species to be thousand years ago and the effective population size of the ancestral orangutan species to be , consistent with recent results based on smaller data sets. We also report a negative correlation between chromosome size and ancestral effective population size, which we interpret as a signature of recombination increasing the efficacy of selection.     

Speciational history of Australian grass finches (Poephila) inferred from thirty gene trees

Multilocus genealogical approaches are still uncommon in phylogeography and historical demography, fields which have been dominated by microsatellite markers and mitochondrial DNA, particularly for vertebrates. Using 30 newly developed anonymous nuclear loci, we estimated population divergence times and ancestral population sizes of three closely related species of Australian grass finches (Poephila) distributed across two barriers in northern Australia. We verified that substitution rates were generally constant both among lineages and among loci, and that intralocus recombination was uncommon in our dataset, thereby satisfying two assumptions of our multilocus analysis. The reconstructed gene trees exhibited all three possible tree topologies and displayed considerable variation in coalescent times, yet this information provided the raw data for maximum likelihood and Bayesian estimation of population divergence times and ancestral population sizes. Estimates of these parameters were in close agreement with each other regardless of statistical approach and our Bayesian estimates were robust to prior assumptions. Our results suggest that black-throated finches (Poephila cincta) diverged from long-tailed finches (P. acuticauda and P. hecki) across the Carpentarian Barrier in northeastern Australia around 0.6 million years ago (mya), and that P. acuticauda diverged from P. hecki across the Kimberley Plateau-Arnhem Land Barrier in northwestern Australia approximately 0.3 mya. Bayesian 95% credibility intervals around these estimates strongly support Pleistocene timing for both speciation events, despite the fact that many gene divergences across the Carpentarian region clearly predated the Pleistocene. Estimates of ancestral effective population sizes for the basal ancestor and long-tailed finch ancestor were large (about 521,000 and about 384,000, respectively). Although the errors around the population size parameter estimates are considerable, they are the first for birds taking into account multiple sources of variance.     

Species trees from gene trees: reconstructing Bayesian posterior distributions of a species phylogeny using estimated gene tree distributions

The desire to infer the evolutionary history of a group of species should be more viable now that a considerable amount of multilocus molecular data is available. However, the current molecular phylogenetic paradigm still reconstructs gene trees to represent the species tree. Further, commonly used methods of combining data, such as the concatenation method, are known to be inconsistent in some circumstances. In this paper, we propose a Bayesian hierarchical model to estimate the phylogeny of a group of species using multiple estimated gene tree distributions, such as those that arise in a Bayesian analysis of DNA sequence data. Our model employs substitution models used in traditional phylogenetics but also uses coalescent theory to explain genealogical signals from species trees to gene trees and from gene trees to sequence data, thereby forming a complete stochastic model to estimate gene trees, species trees, ancestral population sizes, and species divergence times simultaneously. Our model is founded on the assumption that gene trees, even of unlinked loci, are correlated due to being derived from a single species tree and therefore should be estimated jointly. We apply the method to two multilocus data sets of DNA sequences. The estimates of the species tree topology and divergence times appear to be robust to the prior of the population size, whereas the estimates of effective population sizes are sensitive to the prior used in the analysis. These analyses also suggest that the model is superior to the concatenation method in fitting these data sets and thus provides a more realistic assessment of the variability in the distribution of the species tree that may have produced the molecular information at hand. Future improvements of our model and algorithm should include consideration of other factors that can cause discordance of gene trees and species trees, such as horizontal transfer or gene duplication.     

Disentangling linkage disequilibrium and linkage from dense single-nucleotide polymorphism trio data

Parent-offspring trios are widely collected for disease gene-mapping studies and are being extensively genotyped as part of the International HapMap Project. With dense maps of markers on trios, the effects of LD and linkage can be separated, allowing estimation of recombination rates in a model-free setting. Here we define a model-free multipoint method on the basis of dense sequence polymorphism data from parent-offspring trios to estimate intermarker recombination rates. We use simulations to show that this method has up to 92% power to detect recombination hotspots of intensity 25 times background over a region of size 10 kb typed at density 1 marker per 2.5 kb and almost 100% power to detect large hotspots of intensity >125 times background over regions of size 10 kb typed with just 1 marker per 5 kb (alpha = 0.05). We found strong agreement at megabase scales between estimates from our method applied to HapMap trio data and estimates from the genetic map. At finer scales, using Centre d'Etude du Polymorphisme Humain (CEPH) pedigree data across a 10-Mb region of chromosome 20, a comparison of population recombination rate estimates obtained from our method with estimates obtained using a coalescent-based approximate-likelihood method implemented in PHASE 2.0 shows detection of the same coldspots and most hotspots: The Spearman rank correlation between the estimates from our method and those from PHASE is 0.58 (p < 2.2(-16)).     

Maximum-likelihood estimation of admixture proportions from genetic data

For an admixed population, an important question is how much genetic contribution comes from each parental population. Several methods have been developed to estimate such admixture proportions, using data on genetic markers sampled from parental and admixed populations. In this study, I propose a likelihood method to estimate jointly the admixture proportions, the genetic drift that occurred to the admixed population and each parental population during the period between the hybridization and sampling events, and the genetic drift in each ancestral population within the interval between their split and hybridization. The results from extensive simulations using various combinations of relevant parameter values show that in general much more accurate and precise estimates of admixture proportions are obtained from the likelihood method than from previous methods. The likelihood method also yields reasonable estimates of genetic drift that occurred to each population, which translate into relative effective sizes (N(e)) or absolute average N(e)'s if the times when the relevant events (such as population split, admixture, and sampling) occurred are known. The proposed likelihood method also has features such as relatively low computational requirement compared with previous ones, flexibility for admixture models, and marker types. In particular, it allows for missing data from a contributing parental population. The method is applied to a human data set and a wolflike canids data set, and the results obtained are discussed in comparison with those from other estimators and from previous studies.     

Genomic divergences between humans and other hominoids and the effective population size of the common ancestor of humans and chimpanzees

To study the genomic divergences among hominoids and to estimate the effective population size of the common ancestor of humans and chimpanzees, we selected 53 autosomal intergenic nonrepetitive DNA segments from the human genome and sequenced them in a human, a chimpanzee, a gorilla, and an orangutan. The average sequence divergence was only 1.24% +/- 0.07% for the human-chimpanzee pair, 1.62% +/- 0.08% for the human-gorilla pair, and 1.63% +/- 0.08% for the chimpanzee-gorilla pair. These estimates, which were confirmed by additional data from GenBank, are substantially lower than previous ones, which included repetitive sequences and might have been based on less-accurate sequence data. The average sequence divergences between orangutans and humans, chimpanzees, and gorillas were 3.08% +/- 0.11%, 3.12% +/- 0.11%, and 3.09% +/- 0.11%, respectively, which also are substantially lower than previous estimates. The sequence divergences in other regions between hominoids were estimated from extensive data in GenBank and the literature, and Alus showed the highest divergence, followed in order by Y-linked noncoding regions, pseudogenes, autosomal intergenic regions, X-linked noncoding regions, synonymous sites, introns, and nonsynonymous sites. The neighbor-joining tree derived from the concatenated sequence of the 53 segments--24,234 bp in length--supports the Homo-Pan clade with a 100% bootstrap value. However, when each segment is analyzed separately, 22 of the 53 segments (approximately 42%) give a tree that is incongruent with the species tree, suggesting a large effective population size (N(e)) of the common ancestor of Homo and Pan. Indeed, a parsimony analysis of the 53 segments and 37 protein-coding genes leads to an estimate of N(e) = 52,000 to 96,000. As this estimate is 5 to 9 times larger than the long-term effective population size of humans (approximately 10,000) estimated from various genetic polymorphism data, the human lineage apparently had experienced a large reduction in effective population size after its separation from the chimpanzee lineage. Our analysis assumes a molecular clock, which is in fact supported by the sequence data used. Taking the orangutan speciation date as 12 to 16 million years ago, we obtain an estimate of 4.6 to 6.2 million years for the Homo-Pan divergence and an estimate of 6.2 to 8.4 million years for the gorilla speciation date, suggesting that the gorilla lineage branched off 1.6 to 2.2 million years earlier than did the human-chimpanzee divergence.     

Ancestral Population Sizes and Species Divergence Times in the Primate Lineage on the Basis of Intron and BAC End Sequences

The effective sizes of ancestral populations and species divergence times of six primate species (humans, chimpanzees, gorillas, orangutans, and representatives of Old World monkeys and New World monkeys) are estimated by applying the two-species maximum likelihood (ML) method to intron sequences of 20 different loci. Examination of rate heterogeneity of nucleotide substitutions and intragenic recombination identifies five outrageous loci (ODC1, GHR, HBE, INS, and HBG). The estimated ancestral polymorphism ranges from 0.21 to 0.96% at major divergences in primate evolution. One exceptionally low polymorphism occurs when African and Asian apes diverged. However, taking into consideration the possible short generation times in primate ancestors, it is concluded that the ancestral population size in the primate lineage was no smaller than that of extant humans. Furthermore, under the assumption of 6 million years (myr) divergence between humans and chimpanzees, the divergence time of humans from gorillas, orangutans, Old World monkeys, and New World monkeys is estimated as 7.2, 18, 34, and 65 myr ago, respectively, which are generally older than traditional estimates. Beside the intron sequences, three other data sets of orthologous sequences are used between the human and the chimpanzee comparison. The ML application to these data sets including 58,156 random BAC end sequences (BES) shows that the nucleotide substitution rate is as low as 0.6–0.8 × 10^–9 per site per year and the extent of ancestral polymorphism is 0.33–0.51%. With such a low substitution rate and short generation time, the relatively high extent of polymorphism suggests a fairly large effective population size in the ancestral lineage common to humans and chimpanzees.[Reviewing Editor: Dr. Magnus Nordborg]     

Perspective: gene divergence, population divergence, and the variance in coalescence time in phylogeographic studies

Molecular methods as applied to the biogeography of single species (phylogeography) or multiple codistributed species (comparative phylogeography) have been productively and extensively used to elucidate common historical features in the diversification of the Earth's biota. However, only recently have methods for estimating population divergence times or their confidence limits while taking into account the critical effects of genetic polymorphism in ancestral species become available, and earlier methods for doing so are underutilized. We review models that address the crucial distinction between the gene divergence, the parameter that is typically recovered in molecular phylogeographic studies, and the population divergence, which is in most cases the parameter of interest and will almost always postdate the gene divergence. Assuming that population sizes of ancestral species are distributed similarly to those of extant species, we show that phylogeographic studies in vertebrates suggest that divergence of alleles in ancestral species can comprise from less than 10% to over 50% of the total divergence between sister species, suggesting that the problem of ancestral polymorphism in dating population divergence can be substantial. The variance in the number of substitutions (among loci for a given species or among species for a given gene) resulting from the stochastic nature of DNA change is generally smaller than the variance due to substitutions along allelic lines whose coalescence times vary due to genetic drift in the ancestral population. Whereas the former variance can be reduced by further DNA sequencing at a single locus, the latter cannot. Contrary to phylogeographic intuition, dating population divergence times when allelic lines have achieved reciprocal monophyly is in some ways more challenging than when allelic lines have not achieved monophyly, because in the former case critical data on ancestral population size provided by residual ancestral polymorphism is lost. In the former case differences in coalescence time between species pairs can in principle be explained entirely by differences in ancestral population size without resorting to explanations involving differences in divergence time. Furthermore, the confidence limits on population divergence times are severely underestimated when those for number of substitutions per site in the DNA sequences examined are used as a proxy. This uncertainty highlights the importance of multilocus data in estimating population divergence times; multilocus data can in principle distinguish differences in coalescence time (T) resulting from differences in population divergence time and differences in T due to differences in ancestral population sizes and will reduce the confidence limits on the estimates. We analyze the contribution of ancestral population size (theta) to T and the effect of uncertainty in theta on estimates of population divergence (tau) for single loci under reciprocal monophyly using a simple Bayesian extension of Takahata and Satta's and Yang's recent coalescent methods. The confidence limits on tau decrease when the range over which ancestral population size theta is assumed to be distributed decreases and when tau increases; they generally exclude zero when tau/(4Ne) > 1. We also apply a maximum-likelihood method to several single and multilocus data sets. With multilocus data, the criterion for excluding tau = 0 is roughly that l tau/(4Ne) > 1, where l is the number of loci. Our analyses corroborate recent suggestions that increasing the number of loci is critical to decreasing the uncertainty in estimates of population divergence time.     

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.     

Genomic relationships and speciation times of human, chimpanzee, and gorilla inferred from a coalescent hidden Markov model

The genealogical relationship of human, chimpanzee, and gorilla varies along the genome. We develop a hidden Markov model (HMM) that incorporates this variation and relate the model parameters to population genetics quantities such as speciation times and ancestral population sizes. Our HMM is an analytically tractable approximation to the coalescent process with recombination, and in simulations we see no apparent bias in the HMM estimates. We apply the HMM to four autosomal contiguous human–chimp–gorilla–orangutan alignments comprising a total of 1.9 million base pairs. We find a very recent speciation time of human–chimp (4.1 ± 0.4 million years), and fairly large ancestral effective population sizes (65,000 ± 30,000 for the human–chimp ancestor and 45,000 ± 10,000 for the human–chimp–gorilla ancestor). Furthermore, around 50% of the human genome coalesces with chimpanzee after speciation with gorilla. We also consider 250,000 base pairs of X-chromosome alignments and find an effective population size much smaller than 75% of the autosomal effective population sizes. Finally, we find that the rate of transitions between different genealogies correlates well with the region-wide present-day human recombination rate, but does not correlate with the fine-scale recombination rates and recombination hot spots, suggesting that the latter are evolutionarily transient.     

Bayesian inference of fine-scale recombination rates using population genomic data

Recently, several statistical methods for estimating fine-scale recombination rates using population samples have been developed. However, currently available methods that can be applied to large-scale data are limited to approximated likelihoods. Here, we developed a full-likelihood Markov chain Monte Carlo method for estimating recombination rate under a Bayesian framework. Genealogies underlying a sampling of chromosomes are effectively modelled by using marginal individual single nucleotide polymorphism genealogies related through an ancestral recombination graph. The method is compared with two existing composite-likelihood methods using simulated data.Simulation studies show that our method performs well for different simulation scenarios. The method is applied to two human population genetic variation datasets that have been studied by sperm typing. Our results are consistent with the estimates from sperm crossover analysis.     

Inferring Demographic History from a Spectrum of Shared Haplotype Lengths

There has been much recent excitement about the use of genetics to elucidate ancestral history and demography. Whole genome data from humans and other species are revealing complex stories of divergence and admixture that were left undiscovered by previous smaller data sets. A central challenge is to estimate the timing of past admixture and divergence events, for example the time at which Neanderthals exchanged genetic material with humans and the time at which modern humans left Africa. Here, we present a method for using sequence data to jointly estimate the timing and magnitude of past admixture events, along with population divergence times and changes in effective population size. We infer demography from a collection of pairwise sequence alignments by summarizing their length distribution of tracts of identity by state (IBS) and maximizing an analytic composite likelihood derived from a Markovian coalescent approximation. Recent gene flow between populations leaves behind long tracts of identity by descent (IBD), and these tracts give our method power by influencing the distribution of shared IBS tracts. In simulated data, we accurately infer the timing and strength of admixture events, population size changes, and divergence times over a variety of ancient and recent time scales. Using the same technique, we analyze deeply sequenced trio parents from the 1000 Genomes project. The data show evidence of extensive gene flow between Africa and Europe after the time of divergence as well as substructure and gene flow among ancestral hominids. In particular, we infer that recent African-European gene flow and ancient ghost admixture into Europe are both necessary to explain the spectrum of IBS sharing in the trios, rejecting simpler models that contain less population structure.     

A robust measure of HIV-1 population turnover within chronically infected individuals

A simple nonparameteric test for population structure was applied to temporally spaced samples of HIV-1 sequences from the gag-pol region within two chronically infected individuals. The results show that temporal structure can be detected for samples separated by about 22 months or more. The performance of the method, which was originally proposed to detect geographic structure, was tested for temporally spaced samples using neutral coalescent simulations. Simulations showed that the method is robust to variation in samples sizes and mutation rates, to the presence/absence of recombination, and that the power to detect temporal structure is high. By comparing levels of temporal structure in simulations to the levels observed in real data, we estimate the effective intra-individual population size of HIV-1 to be between 10(3) and 10(4) viruses, which is in agreement with some previous estimates. Using this estimate and a simple measure of sequence diversity, we estimate an effective neutral mutation rate of about 5 x 10(-6) per site per generation in the gag-pol region. The definition and interpretation of estimates of such "effective" population parameters are discussed.     

On the Number of Ancestors to a DNA Sequence

If homologous sequences in a population are not subject to recombination, they can all be traced back to one ancestral sequence. However, the rest of our genome is subject to recombination and will be spread out on a series of individuals. The distribution of ancestral material to an extant chromosome is here investigated by the coalescent with recombination, and the results are discussed relative to humans. In an ancestral population of actual size 1.3 million a minority of <6.4% will carry material ancestral to any present human. The estimated actual population size can be even higher, 5 million, reducing the percentage to 1.7%.     

Modern African ape populations as genetic and demographic models of the last common ancestor of humans, chimpanzees, and gorillas

In order to fully understand human evolutionary history through the use of molecular data, it is essential to include our closest relatives as a comparison. We provide here estimates of nucleotide diversity and effective population size of modern African ape species using data from several independent noncoding nuclear loci, and use these estimates to make predictions about the nature of the ancestral population that eventually gave rise to the living species of African apes, including humans. Chimpanzees, bonobos, and gorillas possess two to three times more nucleotide diversity than modern humans. We hypothesize that the last common ancestor (LCA) of these species had an effective population size more similar to modern apes than modern humans. In addition, estimated dates for the divergence of the Homo, Pan, and Gorilla lineages suggest that the LCA may have had stronger geographic structuring to its mtDNA than its nuclear DNA, perhaps indicative of strong female philopatry or a dispersal system analogous to gorillas, where females disperse only short distances from their natal group. Synthesizing different classes of data, and the inferences drawn from them, allows us to predict some of the genetic and demographic properties of the LCA of humans, chimpanzees, and gorillas.     

Effective population size is positively correlated with levels of adaptive divergence among annual sunflowers

The role of adaptation in the divergence of lineages has long been a central question in evolutionary biology, and as multilocus sequence data sets have become available for a wide range of taxa, empirical estimates of levels of adaptive molecular evolution are increasingly common. Estimates vary widely among taxa, with high levels of adaptive evolution in Drosophila, bacteria, and viruses but very little evidence of widespread adaptive evolution in hominids. Although estimates in plants are more limited, some recent work has suggested that rates of adaptive evolution in a range of plant taxa are surprisingly low and that there is little association between adaptive evolution and effective population size in contrast to patterns seen in other taxa. Here, we analyze data from 35 loci for six sunflower species that vary dramatically in effective population size. We find that rates of adaptive evolution are positively correlated with effective population size in these species, with a significant fraction of amino acid substitutions driven by positive selection in the species with the largest effective population sizes but little or no evidence of adaptive evolution in species with smaller effective population sizes. Although other factors likely contribute as well, in sunflowers effective population size appears to be an important determinant of rates of adaptive evolution.