Genetics and recent human evolution

Starting with "mitochondrial Eve" in 1987, genetics has played an increasingly important role in studies of the last two million years of human evolution. It initially appeared that genetic data resolved the basic models of recent human evolution in favor of the "out-of-Africa replacement" hypothesis in which anatomically modern humans evolved in Africa about 150,000 years ago, started to spread throughout the world about 100,000 years ago, and subsequently drove to complete genetic extinction (replacement) all other human populations in Eurasia. Unfortunately, many of the genetic studies on recent human evolution have suffered from scientific flaws, including misrepresenting the models of recent human evolution, focusing upon hypothesis compatibility rather than hypothesis testing, committing the ecological fallacy, and failing to consider a broader array of alternative hypotheses. Once these flaws are corrected, there is actually little genetic support for the out-of-Africa replacement hypothesis. Indeed, when genetic data are used in a hypothesis-testing framework, the out-of-Africa replacement hypothesis is strongly rejected. The model of recent human evolution that emerges from a statistical hypothesis-testing framework does not correspond to any of the traditional models of human evolution, but it is compatible with fossil and archaeological data. These studies also reveal that any one gene or DNA region captures only a small part of human evolutionary history, so multilocus studies are essential. As more and more loci became available, genetics will undoubtedly offer additional insights and resolutions of human evolution.     

Origin and differentiation of human mitochondrial DNA.

A recent study of mitochondrial DNA (mtDNA) polymorphism has generated much debate about modern human origins by proposing the existence of an "African Eve" living 200,000 years ago somewhere in Africa. In an attempt to synthesize information concerning human mtDNA genetic polymorphism, all available data on mtDNA RFLP have been gathered. A phylogeny of the mtDNA types found in 10 populations reveals that all types could have issued from a single common ancestral type. The distribution of shared types between continental groups indicates that caucasoid populations could be the closest to an ancestral population from which all other continental groups would have diverged. A partial phylogeny of the types found in five other populations also demonstrates that the myth of an African Eden was based on an incorrect "genealogical tree" of mtDNA types. Two measures of molecular diversity have been computed on all samples on the basis of mtDNA type frequencies, on one hand, and on the basis of the number of polymorphic sites in the samples, on the other. A large discrepancy is found between the two measures except in African populations; this suggests the existence of some differential selective mechanisms. The lapse of time necessary for creating the observed molecular diversity from an ancestral monomorphic population has been calculated and is found generally greater in Oriental and caucasoid populations. Implications concerning human mtDNA evolution are discussed.     

The evolutionary genomics of pathogen recombination

A pressing problem in studying the evolution of microbial pathogens is to determine the extent to which these genomes recombine. This information is essential for locating pathogenicity loci by using association studies or population genetic approaches. Recombination also complicates the use of phylogenetic approaches to estimate evolutionary parameters such as selection pressures. Reliable methods that detect and estimate the rate of recombination are, therefore, vital. This article reviews the approaches that are available for detecting and estimating recombination in microbial pathogens and how they can be used to understand pathogen evolution and to identify medically relevant loci.     

Genomics refutes an exclusively African origin of humans

Ten years ago, evidence from genetics gave strong support to the "recent African origin" view of the evolution of modern humans, which posits that Homo sapiens arose as a new species in Africa and subsequently spread, leading to the extinction of other archaic human species. Subsequent data from the nuclear genome not only fail to support this model, they do not support any simple model of human demographic history. In this paper, we study a process in which the modern human phenotype originates in Africa and then advances across the world by local demic diffusion, hybridization, and natural selection. While the multiregional model of human origins posits a number of independent single locus selective sweeps, and the "out of Africa" model posits a sweep of a new species, we study the intermediate case of a phenotypic sweep. Numerical simulations of this process replicate many of the seemingly contradictory features of the genetic data, and suggest that as much as 80% of nuclear loci have assimilated genetic material from non-African archaic humans.     

A simple model of linkage disequilibrium and genetic drift in human genomic SNPs: importance of demography and SNP age

We propose a simple model of evolution at a pair of SNP loci, under mutation, genetic drift and recombination. The developed model allows to consider evolution of SNPs under different demographic scenarios. We applied it to SNP data containing polymorphisms spanning 19 gene regions. We initially matched the linkage disequilibrium (LD) data only, and then we reconciled both LD and heterozygosity data. The imbalance between LD and heterozygosity data, observed for some of the analyzed genomic regions, may be a signature of selection acting in these regions. However, assuming neutrality, we obtain estimates of the age of population expansion of modern humans, which are consistent with the consensus estimates. In addition, we are able to estimate the ages of the polymorphisms observed in different genomic regions and we find that they vary widely with respect to their age. Polymorphisms at loci implicated in human disease, seem to be younger than average. Our results supplement the conclusions originally obtained by Reich and co-workers for the same set of data.     

Genetic variability in a genomic region with long-range linkage disequilibrium reveals traces of a bottleneck in the history of the European population

The inference of the demographic history of populations from genetic variability data is not only of academic interest. It also provides background information for the identification of genes which may have played a role in human evolution or in the aetiology of human disease. To obtain a clear picture of this background, it is necessary to compare data obtained from a number of genomic loci. Due to its very low recombination rate, the NF1 gene region can be regarded as a further suitable locus. A combined resequencing and SNP typing project in a European population disclosed the presence of only two well separated subgroups of NF1 sequences. Statistical analysis revealed a bimodal distribution of the pairwise differences, a positive value of Tajima’s D and a TMRCA of 700,000 years for the whole sample, and pairwise differences indicative for a growing population and TMRCAs of 130,000 to 150,000 years for the subgroups. Together, the data lead to a model that the recent European population went through a bottleneck during the last 150,000 years of its history. Regarding the given timeframe, this bottleneck could either reflect a speciation event which led to the anatomically modern human (AMH), or a severe reduction of the population size during the emigration of AMHs out of Africa or the immigration into Europe.     

The population genetics of Quechuas, the largest native South American group: autosomal sequences, SNPs, and microsatellites evidence high level of diversity

Elucidating the pattern of genetic diversity for non-European populations is necessary to make the benefits of human genetics research available to individuals from these groups. In the era of large human genomic initiatives, Native American populations have been neglected, in particular, the Quechua, the largest South Amerindian group settled along the Andes. We characterized the genetic diversity of a Quechua population in a global setting, using autosomal noncoding sequences (nine unlinked loci for a total of 16 kb), 351 unlinked SNPs and 678 microsatellites and tested predictions of the model of the evolution of Native Americans proposed by (Tarazona-Santos et al.: Am J Hum Genet 68 (2001) 1485-1496). European admixture is <5% and African ancestry is barely detectable in the studied population. The largest genetic distances were between African versus Quechua or Melanesian populations, which is concordant with the African origin of modern humans and the fact that South America was the last part of the world to be peopled. The diversity in the Quechua population is comparable with that of Eurasian populations, and the allele frequency spectrum based on resequencing data does not reflect a reduction in the proportion of rare alleles. Thus, the Quechua population is a large reservoir of common and rare genetic variants of South Amerindians. These results are consistent with and complement our evolutionary model of South Amerindians (Tarazona-Santos et al.: Am J Hum Genet 68 (2001) 1485-1496), proposed based on Y-chromosome data, which predicts high genomic diversity due to the high level of gene flow between Andean populations and their long-term effective population size.     

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.     

Reconstructing human origins in the genomic era

Analyses of recently acquired genomic sequence data are leading to important insights into the early evolution of anatomically modern humans, as well as into the more recent demographic processes that accompanied the global radiation of Homo sapiens. Some of the new results contradict early, but still influential, conclusions that were based on analyses of gene trees from mitochondrial DNA and Y-chromosome sequences. In this review, we discuss the different genetic and statistical methods that are available for studying human population history, and identify the most plausible models of human evolution that can accommodate the contrasting patterns observed at different loci throughout the genome.     

SINEs of speciation: tracking lineages with retroposons

The value of short interspersed elements (SINEs) for diagnosing common ancestry is being expanded to examine the differential sorting of lineages through the course of speciation events. Because most SINEs are neutral markers of identical descent, are not precisely excised from the genome and have a known ancestral condition, they are advantageous for reconciling gene trees and species trees with minimal phylogenetic error. A population perspective on SINE evolution combined with coalescence theory provides a context for investigating the phenomenon of ancestral polymorphism and its role in producing incongruent SINE insertion patterns among multiple loci. Studies of human Alu repeats demonstrate the value of young polymorphic SINEs for assessing human genomic diversity and tracking ancient demographics of human populations, whereas incongruent insertion patterns revealed by older fixed SINE loci, such as those in African cichlid fishes, contain information that might help identify ancient radiations that are otherwise obscured by accumulated mutations in sequence data. Here, we review the utility of retroposons for inferring common ancestry, discuss limits to the method, and clarify confusion by providing examples from the literature that illustrate how discordant multi-locus insertion patterns of retroelements can indicate lineage-sorting events that should not be misinterpreted as phylogenetic noise.     

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.     

Model of the Complex of the Human Glycyl-tRNA Synthetase Anticodon-Binding Domain with IRES I Fragment

The currently available structural information is insufficient for a detailed analysis of interactions between human glycyl-tRNA synthetase (GARS) and enterovirus IRESs. At the same time, this information is required in order to understand how this IRES trans-acting factor (ITAF) functions during viral mRNA translation, which is in turn crucial for the development of direct-action antiviral agents. In this paper, a theoretical model of the complex between a cadicivirus A IRES fragment and the anticodon-binding domain of human GARS is constructed using molecular dynamics simulation based on all of the available structural and biochemical data. The proposed model enables the structural interpretation of the previously obtained biochemical data.     

Integrated sequence-structure motifs suffice to identify microRNA precursors

Background

Upwards of 1200 miRNA loci have hitherto been annotated in the human genome. The specific features defining a miRNA precursor and deciding its recognition and subsequent processing are not yet exhaustively described and miRNA loci can thus not be computationally identified with sufficient confidence.

Results

We rendered pre-miRNA and non-pre-miRNA hairpins as strings of integrated sequence-structure information, and used the software Teiresias to identify sequence-structure motifs (ss-motifs) of variable length in these data sets. Using only ss-motifs as features in a Support Vector Machine (SVM) algorithm for pre-miRNA identification achieved 99.2% specificity and 97.6% sensitivity on a human test data set, which is comparable to previously published algorithms employing combinations of sequence-structure and additional features. Further analysis of the ss-motif information contents revealed strongly significant deviations from those of the respective training sets, revealing important potential clues as to how the sequence and structural information of RNA hairpins are utilized by the miRNA processing apparatus.

Conclusion

Integrated sequence-structure motifs of variable length apparently capture nearly all information required to distinguish miRNA precursors from other stem-loop structures.     

Understanding the overdispersed molecular clock

Rates of molecular evolution at some protein-encoding loci are more irregular than expected under a simple neutral model of molecular evolution. This pattern of excessive irregularity in protein substitutions is often called the "overdispersed molecular clock" and is characterized by an index of dispersion, R(T) > 1. Assuming infinite sites, no recombination model of the gene R(T) is given for a general stationary model of molecular evolution. R(T) is shown to be affected by only three things: fluctuations that occur on a very slow time scale, advantageous or deleterious mutations, and interactions between mutations. In the absence of interactions, advantageous mutations are shown to lower R(T); deleterious mutations are shown to raise it. Previously described models for the overdispersed molecular clock are analyzed in terms of this work as are a few very simple new models. A model of deleterious mutations is shown to be sufficient to explain the observed values of R(T). Our current best estimates of R(T) suggest that either most mutations are deleterious or some key population parameter changes on a very slow time scale. No other interpretations seem plausible. Finally, a comment is made on how R(T) might be used to distinguish selective sweeps from background selection.     

Multiregional, not multiple origins

Multiregional evolution is a model to account for the pattern of human evolution in the Pleistocene. The underlying hypothesis is that a worldwide network of genic exchanges, between evolving human populations that continually divide and reticulate, provides a frame of population interconnections that allows both species-wide evolutionary change and local distinctions and differentiation. "Multiregional" does not mean independent multiple origins, ancient divergence of modern populations, simultaneous appearance of adaptive characters in different regions, or parallel evolution. A valid understanding of multiregional evolution would go a long way toward reducing the modern human origins controversy.     

Pairwise difference analysis in modern human origins research

Pairwise difference analysis is a phenetic method that groups taxa on the basis of the number of differences they exhibit. Recently, pairwise difference analysis has been used to investigate the phylogenetic relationships of hominid fossils at the centre of the modern human origins debate. It has been argued that the results of these analyses disprove the African replacement model of modern human origins, and support instead its competitor, the multiregional evolution model. However, this inference is problematic because the ability of pairwise difference analysis to recover phylogenetic information from morphological data has not been demonstrated. With this in mind, we conducted pairwise difference analyses of craniodental and soft tissue evidence from a group of extant primates for which a reliable molecular phylogeny is available, the hominoids. We found that the phylogenies yielded by the pairwise difference analyses were incompatible with the molecular phylogeny for the group. Given the robustness of the molecular phylogeny, these results suggest that pairwise difference analysis cannot be relied on to generate reliable estimates of primate phylogeny from morphological data. The corollary of this is that the results of published pairwise difference analyses of hominid fossils are not informative regarding the origin of modern humans.     

The evolutionary epidemiology of multilocus drug resistance

The evolution of resistance to drugs is a major public health concern as it erodes the efficacy of our therapeutic arsenal against bacterial, viral, and fungal pathogens. Increasingly, it is recognized that the evolution of resistance involves genetic changes at more than one locus, both in cases where multiple changes are required to obtain high-level resistance, and where compensatory changes at secondary loci ameliorate the costs of resistance. Similarly, multiple loci are often involved in the evolution of multidrug resistance. There has been widespread interest recently in understanding the evolutionary consequences of multilocus resistance, with many empirical studies documenting extensive patterns of genetic interactions (i.e., epistasis) among the loci involved. Currently, however, there are few general theoretical results available that bridge the gap between classical multilocus population genetics and mathematical epidemiology. Here, such theory is developed to shed new light on these previous studies, and to provide further guidance on the type of data required to predict the evolution of pathogens in response to drug pressure. Our results reveal the importance of feedbacks between the epidemiological and evolutionary dynamics, and illustrate how these feedbacks can be exploited to control resistance. In particular, we show how interventions such as social distancing and isolation can influence rates of recombination, and how this then can slow the spread of multilocus resistance and increase the likelihood of reversion to drug sensitivity once drug therapy has ceased.     

Estimating changes in mutational mechanisms of evolution

By considering three DNA sequences simultaneously there is sufficient information to recover a full Markov model with three transition matrices from the root to each of the sequences. It is necessary to have relatively long sequences because, for nucleotides, the full model requires 39 parameters that are estimated from 63 observable values. This triplet Markov method is evaluated for the protein coding genes of mammalian vertebrate mitochondrial genomes, and, in addition, version for two-state-characters (such as R/Y coding) is implemented. A key finding is that some changes in mutational mechanism differentially affect the mutation rate between pairs of nucleotides: there does not appear to be a universal change in "rate" of evolution. It remains to be explored whether detecting changes in certain nucleotide interchanges can be localized to a particular part of the DNA replication/repair system. In order to estimate divergence dates it may eventually be advantageous to use the nucleotide interchanges that show little rate change.