Positive and negative selection on the human genome

An efficient and robust ABC approach to infer the rate and strength of adaptation

Inferring the effects of positive selection on genomes remains a critical step in characterizing the ultimate and proximate causes of adaptation across species, and quantifying positive selection remains a challenge due to the confounding effects of many other evolutionary processes. Robust and efficient approaches for adaptation inference could help characterize the rate and strength of adaptation in nonmodel species for which demographic history, mutational processes, and recombination patterns are not currently well-described. Here, we introduce an efficient and user-friendly extension of the McDonald-Kreitman test (ABC-MK) for quantifying long-term protein adaptation in specific lineages of interest. We characterize the performance of our approach with forward simulations and find that it is robust to many demographic perturbations and positive selection configurations, demonstrating its suitability for applications to nonmodel genomes. We apply ABC-MK to the human proteome and a set of known virus interacting proteins (VIPs) to test the long-term adaptation in genes interacting with viruses. We find substantially stronger signatures of positive selection on RNA-VIPs than DNA-VIPs, suggesting that RNA viruses may be an important driver of human adaptation over deep evolutionary time scales.

Evolutionary origin of germline pathogenic variants in human DNA mismatch repair genes

BACKGROUND

Mismatch repair (MMR) system is evolutionarily conserved for genome stability maintenance. Germline pathogenic variants (PVs) in MMR genes that lead to MMR functional deficiency are associated with high cancer risk. Knowing the evolutionary origin of germline PVs in human MMR genes will facilitate understanding the biological base of MMR deficiency in cancer. However, systematic knowledge is lacking to address the issue. In this study, we performed a comprehensive analysis to know the evolutionary origin of human MMR PVs.

METHODS

We retrieved MMR gene variants from the ClinVar database. The genomes of 100 vertebrates were collected from the UCSC genome browser and ancient human sequencing data were obtained through comprehensive data mining. Cross-species conservation analysis was performed based on the phylogenetic relationship among 100 vertebrates. Rescaled ancient sequencing data were used to perform variant calling for archeological analysis.

RESULTS

Using the phylogenetic approach, we traced the 3369 MMR PVs identified in modern humans in 99 non-human vertebrate genomes but found no evidence for cross-species conservation as the source for human MMR PVs. Using the archeological approach, we searched the human MMR PVs in over 5000 ancient human genomes dated from 45,045 to 100 years before present and identified a group of MMR PVs shared between modern and ancient humans mostly within 10,000 years with similar quantitative patterns.

CONCLUSION

Our study reveals that MMR PVs in modern humans were arisen within the recent human evolutionary history.

Comparative Population Transcriptomics Provide New Insight into the Evolutionary History and Adaptive Potential of World Ocean Krill

Genetic variation is instrumental for adaptation to changing environments but it is unclear how it is structured and contributes to adaptation in pelagic species lacking clear barriers to gene flow. Here, we applied comparative genomics to extensive transcriptome datasets from 20 krill species collected across the Atlantic, Indian, Pacific, and Southern Oceans. We compared genetic variation both within and between species to elucidate their evolutionary history and genomic bases of adaptation. We resolved phylogenetic interrelationships and uncovered genomic evidence to elevate the cryptic Euphausia similis var. armata into species. Levels of genetic variation and rates of adaptive protein evolution vary widely. Species endemic to the cold Southern Ocean, such as the Antarctic krill Euphausia superba, showed less genetic variation and lower evolutionary rates than other species. This could suggest a low adaptive potential to rapid climate change. We uncovered hundreds of candidate genes with signatures of adaptive evolution among Antarctic Euphausia but did not observe strong evidence of adaptive convergence with the predominantly Arctic Thysanoessa. We instead identified candidates for cold-adaptation that have also been detected in Antarctic fish, including genes that govern thermal reception such as TrpA1. Our results suggest parallel genetic responses to similar selection pressures across Antarctic taxa and provide new insights into the adaptive potential of important zooplankton already affected by climate change.

An efficient and robust ABC approach to infer the rate and strength of adaptation

Inferring the effects of positive selection on genomes remains a critical step in characterizing the ultimate and proximate causes of adaptation across species, and quantifying positive selection remains a challenge due to the confounding effects of many other evolutionary processes. Robust and efficient approaches for adaptation inference could help characterize the rate and strength of adaptation in non-model species for which demographic history, mutational processes, and recombination patterns are not currently well-described. Here, we introduce an efficient and user-friendly extension of the McDonald-Kreitman test (ABC-MK) for quantifying long-term protein adaptation in specific lineages of interest. We characterize the performance of our approach with forward simulations and find that it is robust to many demographic perturbations and positive selection configurations, demonstrating its suitability for applications to non-model genomes. We apply ABC-MK to the human proteome and a set of known Virus Interacting Proteins (VIPs) to test the long-term adaptation in genes interacting with viruses. We find substantially stronger signatures of positive selection on RNA-VIPs than DNA-VIPs, suggesting that RNA viruses may be an important driver of human adaptation over deep evolutionary time scales.

Intra- vs. Interhost Evolution of SARS-CoV-2 Driven by Uncorrelated Selection-The Evolution Thwarted

In viral evolution, a new mutation has to proliferate within the host (Stage I) in order to be transmitted and then compete in the host population (Stage II). We now analyze the intrahost single nucleotide variants (iSNVs) in a set of 79 SARS-CoV-2 infected patients with most transmissions tracked. Here, every mutation has two measures: 1) iSNV frequency within each individual host in Stage I; 2) occurrence among individuals ranging from 1 (private), 2-78 (public), to 79 (global) occurrences in Stage II. In Stage I, a small fraction of nonsynonymous iSNVs are sufficiently advantageous to rise to a high frequency, often 100%. However, such iSNVs usually fail to become public mutations. Thus, the selective forces in the two stages of evolution are uncorrelated and, possibly, antagonistic. For that reason, successful mutants, including many variants of concern, have to avoid being eliminated in Stage I when they first emerge. As a result, they may not have the transmission advantage to outcompete the dominant strains and, hence, are rare in the host population. Few of them could manage to slowly accumulate advantageous mutations to compete in Stage II. When they do, they would appear suddenly as in each of the six successive waves of SARS-CoV-2 strains. In conclusion, Stage I evolution, the gate-keeper, may contravene the long-term viral evolution and should be heeded in viral studies.

Perspective of artificial intelligence in healthcare data management: A journey towards precision medicine

Mounting evidence has highlighted the implementation of big data handling and management in the healthcare industry to improve the clinical services. Various private and public companies have generated, stored, and analyzed different types of big healthcare data, such as omics data, clinical data, electronic health records, personal health records, and sensing data with the aim to move in the direction of precision medicine. Additionally, with the advancement in technologies, researchers are curious to extract the potential involvement of artificial intelligence and machine learning on big healthcare data to enhance the quality of patient's lives. However, seeking solutions from big healthcare data requires proper management, storage, and analysis, which imposes hinderances associated with big data handling. Herein, we briefly discuss the implication of big data handling and the role of artificial intelligence in precision medicine. Further, we also highlighted the potential of artificial intelligence in integrating and analyzing the big data that offer personalized treatment. In addition, we briefly discuss the applications of artificial intelligence in personalized treatment, especially in neurological diseases. Lastly, we discuss the challenges and limitations imposed by artificial intelligence in big data management and analysis to hinder precision medicine.

Expression profiles of east-west highly differentiated genes in Uyghur genomes

It remains unknown and debatable how European-Asian-differentiated alleles affect individual phenotypes. Here, we made the first effort to analyze the expression profiles of highly differentiated genes with eastern and western origins in 90 Uyghurs using whole-genome (30× to 60×) and transcriptome data. We screened 921 872 east-west highly differentiated genetic variants, of which ∼4.32% were expression quantitative trait loci (eQTLs), ∼0.12% were alternative splicing quantitative trait loci (sQTLs), and ∼0.12% showed allele-specific expression (ASE). The 8305 highly differentiated eQTLs of strong effects appear to have undergone natural selection, associated with immunity and metabolism. European-origin alleles tend to be more biasedly expressed; highly differentiated ASEs were enriched in diabetes-associated genes, likely affecting the diabetes susceptibility in the Uyghurs. We proposed an admixture-induced expression model to dissect the highly differentiated expression profiles. We provide new insights into the genetic basis of phenotypic differentiation between Western and Eastern populations, advancing our understanding of the impact of genetic admixture.

Population Genomic Analysis of Diploid-Autopolyploid Species

This chapter outlines an empirical analysis of genome-wide single-nucleotide polymorphism (SNP) variation and its underlying drivers among multiple natural populations within a diploid-autopolyploid species. The aim is to reconstruct the genetic structure among natural populations of varying ploidy and infer footprints of selection in these populations, framed around specific questions that are typically encountered when analyzing a mixed-ploidy data set,e.g., addressing the relevance of natural whole-genome duplication for speciation and adaptation. We briefly review the options for the analysis of polyploid population genomic data involving variant calling, population structure, demographic history inference, and selection scanning approaches. Further, we provide suggestions for methods and associated software, possible caveats, and examples of their application to mixed-ploidy and autopolyploid data sets.

Multilocus phylogeography, population genetics and niche evolution of Australian brown and black-tailed treecreepers (Aves: Climacteris)

The Carpentarian barrier across north-eastern Australia is a major biogeographic barrier and a generator of biodiversity within the Australian Monsoonal Tropics. Here we present a continent-wide analysis of mitochondrial (control region) and autosomal (14 anonymous loci) sequence and indel variation and niche modelling of brown and black-tailed treecreepers (Climacteris picumnus and Climacteris melanurus), a clade with a classic distribution on either side of the Carpentarian barrier. mtDNA control region sequences exhibited reciprocal monophyly and strong differentiation (Fst = 0.91), and revealed a signature of a recent selective sweep in C. picumnus. A variety of tests support an isolation-with-migration model of divergence, albeit with low levels of gene flow across the Carpentarian barrier and a divergence time between species of ~1.7–2.8 Mya. Palaeoecological niche models show that both range size as measured by available habitat and estimated historical population sizes of both species declined in the past ~600 kyr and that the area of interspecific range overlap was never historically large, perhaps decreasing opportunities for extensive gene flow. The relatively long divergence time and low opportunity for gene flow may have facilitated speciation more so than in other co-distributed bird taxa across the Australian Monsoonal Tropics.

Genomic insights into inter- and intraspecific mating system shifts in Primulina

The mating system shift from outcrossing to selfing is one of the most frequent evolutionary trends in flowering plants. However, the genomic consequences of this shift remain poorly understood. Specifically, the relative importance of the demographic and genetic processes causing changes in genetic variation and selection efficacy associated with the evolution of selfing is unclear. Here we sequenced the genomes of two Primulina species with contrasting mating systems: P. eburnea (outcrossing) versus P. tabacum (outcrossing, mixed-mating and selfing populations). Whole-genome resequencing data were used to investigate the genomic consequences of mating system shifts within and between species. We found that highly selfing populations of P. tabacum display loss of genetic diversity, increased deleterious mutations, higher genomic burden and fewer adaptive substitutions. However, compared with outcrossing populations, mixed-mating populations did not display loss of genetic diversity and accumulation of genetic load. We find no evidence of population bottlenecks associated with the shift to selfing, which suggests that the genetic effects of selfing on N_e and possibly linked selection, rather than demographic history, are the primary drivers of diversity reduction in highly selfing populations. Our results highlight the importance of distinguishing the relative contribution of mating system and demography on the genomic consequences associated with mating system evolution in plants.

impMKT: the imputed McDonald and Kreitman test, a straightforward correction that significantly increases the evidence of positive selection of the McDonald and Kreitman test at the gene level

The McDonald and Kreitman test is one of the most powerful and widely used methods to detect and quantify recurrent natural selection in DNA sequence data. One of its main limitations is the underestimation of positive selection due to the presence of slightly deleterious variants segregating at low frequencies. Although several approaches have been developed to overcome this limitation, most of them work on gene pooled analyses. Here, we present the imputed McDonald and Kreitman test (impMKT), a new straightforward approach for the detection of positive selection and other selection components of the distribution of fitness effects at the gene level. We compare imputed McDonald and Kreitman test with other widely used McDonald and Kreitman test approaches considering both simulated and empirical data. By applying imputed McDonald and Kreitman test to humans and Drosophila data at the gene level, we substantially increase the statistical evidence of positive selection with respect to previous approaches (e.g. by 50% and 157% compared with the McDonald and Kreitman test in Drosophila and humans, respectively). Finally, we review the minimum number of genes required to obtain a reliable estimation of the proportion of adaptive substitution (α) in gene pooled analyses by using the imputed McDonald and Kreitman test compared with other McDonald and Kreitman test implementations. Because of its simplicity and increased power to detect recurrent positive selection on genes, we propose the imputed McDonald and Kreitman test as the first straightforward approach for testing specific evolutionary hypotheses at the gene level. The software implementation and population genomics data are available at the web-server imkt.uab.cat.

Spruce giga-genomes: structurally similar yet distinctive with differentially expanding gene families and rapidly evolving genes

Spruces (Picea spp.) are coniferous trees widespread in boreal and mountainous forests of the northern hemisphere, with large economic significance and enormous contributions to global carbon sequestration. Spruces harbor very large genomes with high repetitiveness, hampering their comparative analysis. Here, we present and compare the genomes of four different North American spruces: the genome assemblies for Engelmann spruce (Picea engelmannii) and Sitka spruce (Picea sitchensis) together with improved and more contiguous genome assemblies for white spruce (Picea glauca) and for a naturally occurring introgress of these three species known as interior spruce (P. engelmannii × glauca × sitchensis). The genomes were structurally similar, and a large part of scaffolds could be anchored to a genetic map. The composition of the interior spruce genome indicated asymmetric contributions from the three ancestral genomes. Phylogenetic analysis of the nuclear and organelle genomes revealed a topology indicative of ancient reticulation. Different patterns of expansion of gene families among genomes were observed and related with presumed diversifying ecological adaptations. We identified rapidly evolving genes that harbored high rates of non-synonymous polymorphisms relative to synonymous ones, indicative of positive selection and its hitchhiking effects. These gene sets were mostly distinct between the genomes of ecologically contrasted species, and signatures of convergent balancing selection were detected. Stress and stimulus response was identified as the most frequent function assigned to expanding gene families and rapidly evolving genes. These two aspects of genomic evolution were complementary in their contribution to divergent evolution of presumed adaptive nature. These more contiguous spruce giga-genome sequences should strengthen our understanding of conifer genome structure and evolution, as their comparison offers clues into the genetic basis of adaptation and ecology of conifers at the genomic level. They will also provide tools to better monitor natural genetic diversity and improve the management of conifer forests. The genomes of four closely related North American spruces indicate that their high similarity at the morphological level is paralleled by the high conservation of their physical genome structure. Yet, the evidence of divergent evolution is apparent in their rapidly evolving genomes, supported by differential expansion of key gene families and large sets of genes under positive selection, largely in relation to stimulus and environmental stress response.

A new test suggests hundreds of amino acid polymorphisms in humans are subject to balancing selection

The role that balancing selection plays in the maintenance of genetic diversity remains unresolved. Here, we introduce a new test, based on the McDonald–Kreitman test, in which the number of polymorphisms that are shared between populations is contrasted to those that are private at selected and neutral sites. We show that this simple test is robust to a variety of demographic changes, and that it can also give a direct estimate of the number of shared polymorphisms that are directly maintained by balancing selection. We apply our method to population genomic data from humans and provide some evidence that hundreds of nonsynonymous polymorphisms are subject to balancing selection.

Excessive replacement changes drive evolution of global sheep prion protein (PRNP) sequences

Sheep prion protein (PRNP) is the major host genetic factor responsible for susceptibility to scrapie. We aimed to understand the evolutionary history of sheep PRNP, and primarily focused on breeds from Turkey and Ethiopia, representing genome-wise ancient sheep populations. Population molecular genetic analyses are extended to European, South Asian, and East Asian populations, and for the first time to scrapie associated haplotypes. 1178 PRNP coding region nucleotide sequences were analyzed. High levels of nucleotide diversity driven by extensive low-frequency replacement changes are observed in all populations. Interspecific analyses were conducted using mouflon and domestic goat as outgroup species. Despite an abundance of silent and replacement changes, lack of silent or replacement fixations was observed. All scrapie-associated haplotype analyses from all populations also showed extensive low-frequency replacement changes. Neutrality tests did not indicate positive (directional), balancing or strong negative selection or population contraction for any of the haplotypes in any population. A simple negative selection history driven by prion disease susceptibility is not supported by the population and haplotype based analyses. Molecular function, biological process enrichment, and protein-protein interaction analyses suggested functioning of PRNP protein in multiple pathways, and possible other functional constraint selections. In conclusion, a complex selection history favoring excessive replacement changes together with weak purifying selection possibly driven by frequency-dependent selection is driving PRNP sequence evolution. Our results is not unique only to the Turkish and Ethiopian samples, but can be generalized to global sheep populations.

Epistatic selection on a selfish Segregation Distorter supergene - drive, recombination, and genetic load

Meiotic drive supergenes are complexes of alleles at linked loci that together subvert Mendelian segregation resulting in preferential transmission. In males, the most common mechanism of drive involves the disruption of sperm bearing one of a pair of alternative alleles. While at least two loci are important for male drive-the driver and the target-linked modifiers can enhance drive, creating selection pressure to suppress recombination. In this work, we investigate the evolution and genomic consequences of an autosomal, multilocus, male meiotic drive system, Segregation Distorter (SD) in the fruit fly, Drosophila melanogaster. In African populations, the predominant SD chromosome variant, SD-Mal, is characterized by two overlapping, paracentric inversions on chromosome arm 2R and nearly perfect (~100%) transmission. We study the SD-Mal system in detail, exploring its components, chromosomal structure, and evolutionary history. Our findings reveal a recent chromosome-scale selective sweep mediated by strong epistatic selection for haplotypes carrying Sd, the main driving allele, and one or more factors within the double inversion. While most SD-Mal chromosomes are homozygous lethal, SD-Mal haplotypes can recombine with other, complementing haplotypes via crossing over, and with wildtype chromosomes via gene conversion. SD-Mal chromosomes have nevertheless accumulated lethal mutations, excess non-synonymous mutations, and excess transposable element insertions. Therefore, SD-Mal haplotypes evolve as a small, semi-isolated subpopulation with a history of strong selection. These results may explain the evolutionary turnover of SD haplotypes in different populations around the world and have implications for supergene evolution broadly.

The relative fitness of the de novo variants in general Lithuanian population vs. in individuals with intellectual disability

The effect of a variant on an organism is always multifaceted and can be considered from multiple perspectives-biochemical, medical, or evolutionary. However, the relationship between the effects of amino acid substitution on protein activity, human health, and an individual's evolutionary fitness is not trivial. We uncover that the general Lithuanian population is characterized by a "mirror reflection" of the de novo variant fitness effect, confirming the theory of neutrality. Meanwhile, in the group of individuals with intellectual disability, compared with the reference exome de novo variants significantly changed the composition of the amino acid. Therefore, it predicts that, both in terms of the number of amino acids and changes in their relative fitness, the structure of the proteins encoded by the studied amino acids undergo significant changes following the de novo variant, leading to possible changes in protein function associated with phenotypic traits. These results suggest that the analysis of relative fitness of exome sequences with de novo variants can predict the future phenotype. Therefore even in those cases, then only a few of all functional prediction analysis tools predict a variant as damaging, the negative relative fitness or even adaptability of the genome variant should be carefully evaluated considering both its direct function and the global background of the possible disease-associated mechanism regardless of the phenotype being studied.

Molecular epidemiology of yellow fever virus in Africa: A perspective of the phylogeographic split between East/Central African and West African lineages

Yellow fever (YF) is a major public-health problem in Africa. Yellow fever virus (YFV), the etiological agent responsible for the disease, exhibits clear delineation of phylogeography between East/Central Africa and West Africa. In order to decipher the genetic nature of the YFV epidemic between these areas, we performed a genome-wide study on its African isolates using the McDonald-Kreitman (MK) test in combination with the type II functional divergence analysis. The results showed that adaptive genetic diversifications have occurred on viral nonstructural protein 1 (NS1) and NS5, which are essential for viral genome replication and immune antagonism, with the East/Central African-West African epidemic split. On both proteins, a number of amino acid replacements have been favored by functional divergence. These findings could help to bridge the gap between the phylogeographic delineation and niche adaptation underlying the YFV-epidemic across Africa and shed light on viral determinants of this process.

Two decades of suspect evidence for adaptive molecular evolution – Negative selection confounding positive selection signals

There has been a large literature in the last two decades affirming adaptive DNA sequence evolution between species. The main lines of evidence are from (i) the McDonald-Kreitman (MK) test, which compares divergence and polymorphism data, and (ii) the phylogenetic analysis by maximum likelihood (PAML) test, which analyzes multispecies divergence data. Here, we apply these two tests concurrently to genomic data of Drosophila and Arabidopsis. To our surprise, the >100 genes identified by the two tests do not overlap beyond random expectation. Because the non-concordance could be due to low powers leading to high false negatives, we merge every 20–30 genes into a ‘supergene’. At the supergene level, the power of detection is large but the calls still do not overlap. We rule out methodological reasons for the non-concordance. In particular, extensive simulations fail to find scenarios whereby positive selection can only be detected by either MK or PAML, but not both. Since molecular evolution is governed by positive and negative selection concurrently, a fundamental assumption for estimating one of these (say, positive selection) is that the other is constant. However, in a broad survey of primates, birds, Drosophila and Arabidopsis, we found that negative selection rarely stays constant for long in evolution. As a consequence, the variation in negative selection is often misconstrued as a signal of positive selection. In conclusion, MK, PAML and any method that examines genomic sequence evolution has to explicitly address the variation in negative selection before estimating positive selection. In a companion study, we propose a possible path forward in two stages—first, by mapping out the changes in negative selection and then using this map to estimate positive selection. For now, the large literature on positive selection between species has to await reassessment.

Genomic and environmental influences on resilience in a cold-water fish near the edge of its range

Small, isolated populations present a challenge for conservation. The dueling effects of selection and drift in a limited pool of genetic diversity make the responses of small populations to environmental perturbations erratic and difficult to predict. This is particularly true at the edge of a species range, where populations often persist at the limits of their environmental tolerances. Populations of cisco, Coregonus artedi, in inland lakes have experienced numerous extirpations along the southern edge of their range in recent decades, which are thought to result from environmental degradation and loss of cold, well-oxygenated habitat as lakes warm. Yet, cisco extirpations do not show a clear latitudinal pattern, suggesting that local environmental factors and potentially local adaptation may influence resilience. Here, we used genomic tools to investigate the nature of this pattern of resilience. We used restriction site-associated DNA capture (Rapture) sequencing to survey genomic diversity and differentiation in southern inland lake cisco populations and compared the frequency of deleterious mutations that potentially influence fitness across lakes. We also examined haplotype diversity in a region of the major histocompatibility complex involved in stress and immune system response. We correlated these metrics to spatial and environmental factors including latitude, lake size, and measures of oxythermal habitat and found significant relationships between genetic metrics and broad and local factors. High levels of genetic differentiation among populations were punctuated by a phylogeographic break and residual patterns of isolation-by-distance. Although the prevalence of deleterious mutations and inbreeding coefficients was significantly correlated with latitude, neutral and non-neutral genetic diversity were most strongly correlated with lake surface area. Notably, differences among lakes in the availability of estimated oxythermal habitat left no clear population genomic signature. Our results shed light on the complex dynamics influencing these isolated populations and provide valuable information for their conservation.

Revisiting the notion of deleterious sweeps

It has previously been shown that, conditional on its fixation, the time to fixation of a semi-dominant deleterious autosomal mutation in a randomly mating population is the same as that of an advantageous mutation. This result implies that deleterious mutations could generate selective sweep-like effects. Although their fixation probabilities greatly differ, the much larger input of deleterious relative to beneficial mutations suggests that this phenomenon could be important. We here examine how the fixation of mildly deleterious mutations affects levels and patterns of polymorphism at linked sites-both in the presence and absence of interference amongst deleterious mutations-and how this class of sites may contribute to divergence between-populations and species. We find that, while deleterious fixations are unlikely to represent a significant proportion of outliers in polymorphism-based genomic scans within populations, minor shifts in the frequencies of deleterious mutations can influence the proportions of private variants and the value of FST after a recent population split. As sites subject to deleterious mutations are necessarily found in functional genomic regions, interpretations in terms of recurrent positive selection may require reconsideration.

Dissecting genomic determinants of positive selection with an evolution-guided regression model

In evolutionary genomics, it is fundamentally important to understand how characteristics of genomic sequences, such as gene expression level, determine the rate of adaptive evolution. While numerous statistical methods, such as the McDonald–Kreitman (MK) test, are available to examine the association between genomic features and the rate of adaptation, we currently lack a statistical approach to disentangle the independent effect of a genomic feature from the effects of other correlated genomic features. To address this problem, I present a novel statistical model, the MK regression, which augments the MK test with a generalized linear model. Analogous to the classical multiple regression model, the MK regression can analyze multiple genomic features simultaneously to infer the independent effect of a genomic feature, holding constant all other genomic features. Using the MK regression, I identify numerous genomic features driving positive selection in chimpanzees. These features include well-known ones, such as local mutation rate, residue exposure level, tissue specificity, and immune genes, as well as new features not previously reported, such as gene expression level and metabolic genes. In particular, I show that highly expressed genes may have a higher adaptation rate than their weakly expressed counterparts, even though a higher expression level may impose stronger negative selection. Also, I show that metabolic genes may have a higher adaptation rate than their nonmetabolic counterparts, possibly due to recent changes in diet in primate evolution. Overall, the MK regression is a powerful approach to elucidate the genomic basis of adaptation.

Evidence for a force favoring GC over AT at short intronic sites in Drosophila simulans and Drosophila melanogaster

Population genetics studies often make use of a class of nucleotide site free from selective pressures, in order to make inferences about population size changes or natural selection at other sites. If such neutral sites can be identified, they offer the opportunity to avoid any confounding effects of selection. Here, we investigate evolution at putatively neutrally evolving short intronic sites in natural populations of Drosophila melanogaster and Drosophila simulans, in order to understand the properties of spontaneous mutations and the extent of GC-biased gene conversion in these species. Use of data on the genetics of natural populations is advantageous because it integrates information from large numbers of individuals over long timescales. In agreement with direct evidence from observations of spontaneous mutations in Drosophila, we find a bias in the spectrum of mutations toward AT basepairs. In addition, we find that this bias is stronger in the D. melanogaster lineage than in the D. simulans lineage. The evidence for GC-biased gene conversion in Drosophila has been equivocal. Here, we provide evidence for a weak force favoring GC in both species, which is correlated with the GC content of introns and is stronger in D. simulans than in D. melanogaster.

Recombination facilitates adaptive evolution in rhizobial soil bacteria

Homologous recombination is expected to increase natural selection efficacy by decoupling the fate of beneficial and deleterious mutations and by readily creating new combinations of beneficial alleles. Here, we investigate how the proportion of amino acid substitutions fixed by adaptive evolution (α) depends on the recombination rate in bacteria. We analyze 3,086 core protein-coding sequences from 196 genomes belonging to five closely related species of the genus Rhizobium. These genes are found in all species and do not display any signs of introgression between species. We estimate α using the site frequency spectrum (SFS) and divergence data for all pairs of species. We evaluate the impact of recombination within each species by dividing genes into three equally sized recombination classes based on their average level of intragenic linkage disequilibrium. We find that α varies from 0.07 to 0.39 across species and is positively correlated with the level of recombination. This is both due to a higher estimated rate of adaptive evolution and a lower estimated rate of nonadaptive evolution, suggesting that recombination both increases the fixation probability of advantageous variants and decreases the probability of fixation of deleterious variants. Our results demonstrate that homologous recombination facilitates adaptive evolution measured by α in the core genome of prokaryote species in agreement with studies in eukaryotes.

Molecular population genetics of Sex-lethal (Sxl) in the Drosophila melanogaster species group: a locus that genetically interacts with Wolbachia pipientis in Drosophila melanogaster

Sex-lethal (Sxl) is the sex determination switch in Drosophila, and also plays a critical role in germ-line stem cell daughter differentiation in Drosophila melanogaster. Three female-sterile alleles at Sxl in D. melanogaster were previously shown to genetically interact to varying degrees with the maternally inherited endosymbiont Wolbachia pipientis. Given this genetic interaction and W. pipientis’ ability to manipulate reproduction in Drosophila, we carried out a careful study of both the population genetics (within four Drosophila species) and molecular evolutionary analysis (across 20 Drosophila species) of Sxl. Consistent with earlier studies, we find that selective constraint has played a prominent role in Sxl’s molecular evolution within Drosophila, but we also observe patterns that suggest both episodic bursts of protein evolution and recent positive selection at Sxl. The episodic nature of Sxl’s protein evolution is discussed in light of its genetic interaction with W. pipientis.

An actin-related protein that is most highly expressed in Drosophila testes is critical for embryonic development

Most actin-related proteins (Arps) are highly conserved and carry out well-defined cellular functions in eukaryotes. However, many lineages like Drosophila and mammals encode divergent non-canonical Arps whose roles remain unknown. To elucidate the function of non-canonical Arps, we focus on Arp53D, which is highly expressed in testes and retained throughout Drosophila evolution. We show that Arp53D localizes to fusomes and actin cones, two germline-specific actin structures critical for sperm maturation, via a unique N-terminal tail. Surprisingly, we find that male fertility is not impaired upon Arp53D loss, yet population cage experiments reveal that Arp53D is required for optimal fitness in Drosophila melanogaster. To reconcile these findings, we focus on Arp53D function in ovaries and embryos where it is only weakly expressed. We find that under heat stress Arp53D-knockout (KO) females lay embryos with reduced nuclear integrity and lower viability; these defects are further exacerbated in Arp53D-KO embryos. Thus, despite its relatively recent evolution and primarily testis-specific expression, non-canonical Arp53D is required for optimal embryonic development in Drosophila.

De Novo Mutation and Rapid Protein (Co-)evolution during Meiotic Adaptation in Arabidopsis arenosa

A sudden shift in environment or cellular context necessitates rapid adaptation. A dramatic example is genome duplication, which leads to polyploidy. In such situations, the waiting time for new mutations might be prohibitive; theoretical and empirical studies suggest that rapid adaptation will largely rely on standing variation already present in source populations. Here, we investigate the evolution of meiosis proteins in Arabidopsis arenosa, some of which were previously implicated in adaptation to polyploidy, and in a diploid, habitat. A striking and unexplained feature of prior results was the large number of amino acid changes in multiple interacting proteins, especially in the relatively young tetraploid. Here, we investigate whether selection on meiosis genes is found in other lineages, how the polyploid may have accumulated so many differences, and whether derived variants were selected from standing variation. We use a range-wide sample of 145 resequenced genomes of diploid and tetraploid A. arenosa, with new genome assemblies. We confirmed signals of positive selection in the polyploid and diploid lineages they were previously reported in and find additional meiosis genes with evidence of selection. We show that the polyploid lineage stands out both qualitatively and quantitatively. Compared with diploids, meiosis proteins in the polyploid have more amino acid changes and a higher proportion affecting more strongly conserved sites. We find evidence that in tetraploids, positive selection may have commonly acted on de novo mutations. Several tests provide hints that coevolution, and in some cases, multinucleotide mutations, might contribute to rapid accumulation of changes in meiotic proteins.

Positive Selection in Gene Regulatory Factors Suggests Adaptive Pleiotropic Changes During Human Evolution

Gene regulatory factors (GRFs), such as transcription factors, co-factors and histone-modifying enzymes, play many important roles in modifying gene expression in biological processes. They have also been proposed to underlie speciation and adaptation. To investigate potential contributions of GRFs to primate evolution, we analyzed GRF genes in 27 publicly available primate genomes. Genes coding for zinc finger (ZNF) proteins, especially ZNFs with a Krüppel-associated box (KRAB) domain were the most abundant TFs in all genomes. Gene numbers per TF family differed between all species. To detect signs of positive selection in GRF genes we investigated more than 3,000 human GRFs with their more than 70,000 orthologs in 26 non-human primates. We implemented two independent tests for positive selection, the branch-site-model of the PAML suite and aBSREL of the HyPhy suite, focusing on the human and great ape branch. Our workflow included rigorous procedures to reduce the number of false positives: excluding distantly similar orthologs, manual corrections of alignments, and considering only genes and sites detected by both tests for positive selection. Furthermore, we verified the candidate sites for selection by investigating their variation within human and non-human great ape population data. In order to approximately assign a date to positively selected sites in the human lineage, we analyzed archaic human genomes. Our work revealed with high confidence five GRFs that have been positively selected on the human lineage and one GRF that has been positively selected on the great ape lineage. These GRFs are scattered on different chromosomes and have been previously linked to diverse functions. For some of them a role in speciation and/or adaptation can be proposed based on the expression pattern or association with human diseases, but it seems that they all contributed independently to human evolution. Four of the positively selected GRFs are KRAB-ZNF proteins, that induce changes in target genes co-expression and/or through arms race with transposable elements. Since each positively selected GRF contains several sites with evidence for positive selection, we suggest that these GRFs participated pleiotropically to phenotypic adaptations in humans.

A novel family of secreted insect proteins linked to plant gall development

In an elaborate form of inter-species exploitation, many insects hijack plant development to induce novel plant organs called galls that provide the insect with a source of nutrition and a temporary home. Galls result from dramatic reprogramming of plant cell biology driven by insect molecules, but the roles of specific insect molecules in gall development have not yet been determined. Here, we study the aphid Hormaphis cornu, which makes distinctive "cone" galls on leaves of witch hazel Hamamelis virginiana. We found that derived genetic variants in the aphid gene determinant of gall color (dgc) are associated with strong downregulation of dgc transcription in aphid salivary glands, upregulation in galls of seven genes involved in anthocyanin synthesis, and deposition of two red anthocyanins in galls. We hypothesize that aphids inject DGC protein into galls and that this results in differential expression of a small number of plant genes. dgc is a member of a large, diverse family of novel predicted secreted proteins characterized by a pair of widely spaced cysteine-tyrosine-cysteine (CYC) residues, which we named BICYCLE proteins. bicycle genes are most strongly expressed in the salivary glands specifically of galling aphid generations, suggesting that they may regulate many aspects of gall development. bicycle genes have experienced unusually frequent diversifying selection, consistent with their potential role controlling gall development in a molecular arms race between aphids and their host plants.

A novel family of secreted insect proteins linked to plant gall development

In an elaborate form of inter-species exploitation, many insects hijack plant development to induce novel plant organs called galls that provide the insect with a source of nutrition and a temporary home. Galls result from dramatic reprogramming of plant cell biology driven by insect molecules, but the roles of specific insect molecules in gall development have not yet been determined. Here we study the aphidHormaphis cornu, which makes distinctive “cone” galls on leaves of witch hazelHamamelis virginiana. We found that derived genetic variants in the aphid genedeterminant of gall color(dgc) are associated with strong downregulation ofdgctranscription in aphid salivary glands, upregulation in galls of seven genes involved in anthocyanin synthesis, and deposition of two red anthocyanins in galls. We hypothesize that aphids inject DGC protein into galls, and that this results in differential expression of a small number of plant genes.Dgcis a member of a large, diverse family of novel predicted secreted proteins characterized by a pair of widely spaced cysteine-tyrosine-cysteine (CYC) residues, which we named BICYCLE proteins.Bicyclegenes are most strongly expressed in the salivary glands specifically of galling aphid generations, suggesting that they may regulate many aspects of gall development.Bicyclegenes have experienced unusually frequent diversifying selection, consistent with their potential role controlling gall development in a molecular arms race between aphids and their host plants.

One Sentence Summary

Aphidbicyclegenes, which encode diverse secreted proteins, contribute to plant gall development.

The genetic architecture of human complex phenotypes is modulated by linkage disequilibrium and heterozygosity

We propose an extended Gaussian mixture model for the distribution of causal effects of common single nucleotide polymorphisms (SNPs) for human complex phenotypes that depends on linkage disequilibrium (LD) and heterozygosity (H), while also allowing for independent components for small and large effects. Using a precise methodology showing how genome-wide association studies (GWASs) summary statistics (z-scores) arise through LD with underlying causal SNPs, we applied the model to GWAS of multiple human phenotypes. Our findings indicated that causal effects are distributed with dependence on total LD and H, whereby SNPs with lower total LD and H are more likely to be causal with larger effects; this dependence is consistent with models of the influence of negative pressure from natural selection. Compared with the basic Gaussian mixture model it is built on, the extended model-primarily through quantification of selection pressure-reproduces with greater accuracy the empirical distributions of z-scores, thus providing better estimates of genetic quantities, such as polygenicity and heritability, that arise from the distribution of causal effects.

VERSO: A comprehensive framework for the inference of robust phylogenies and the quantification of intra-host genomic diversity of viral samples

We introduce VERSO, a two-step framework for the characterization of viral evolution from sequencing data of viral genomes, which is an improvement on phylogenomic approaches for consensus sequences. VERSO exploits an efficient algorithmic strategy to return robust phylogenies from clonal variant profiles, also in conditions of sampling limitations. It then leverages variant frequency patterns to characterize the intra-host genomic diversity of samples, revealing undetected infection chains and pinpointing variants likely involved in homoplasies. On simulations, VERSO outperforms state-of-the-art tools for phylogenetic inference. Notably, the application to 6,726 amplicon and RNA sequencing samples refines the estimation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) evolution, while co-occurrence patterns of minor variants unveil undetected infection paths, which are validated with contact tracing data. Finally, the analysis of SARS-CoV-2 mutational landscape uncovers a temporal increase of overall genomic diversity and highlights variants transiting from minor to clonal state and homoplastic variants, some of which fall on the spike gene. Available at: https://github.com/BIMIB-DISCo/VERSO.

The evolutionary genetics of personality

Genetic influences on personality differences are ubiquitous, but their nature is not well understood. A theoretical framework might help, and can be provided by evolutionary genetics. We assess three evolutionary genetic mechanisms that could explain genetic variance in personality differences: selective neutrality, mutation‐selection balance, and balancing selection. Based on evolutionary genetic theory and empirical results from behaviour genetics and personality psychology, we conclude that selective neutrality is largely irrelevant, that mutation‐selection balance seems best at explaining genetic variance in intelligence, and that balancing selection by environmental heterogeneity seems best at explaining genetic variance in personality traits. We propose a general model of heritable personality differences that conceptualises intelligence as fitness components and personality traits as individual reaction norms of genotypes across environments, with different fitness consequences in different environmental niches. We also discuss the place of mental health in the model. This evolutionary genetic framework highlights the role of gene‐environment interactions in the study of personality, yields new insight into the person‐situation‐debate and the structure of personality, and has practical implications for both quantitative and molecular genetic studies of personality. Copyright © 2007 John Wiley & Sons, Ltd.

Inferring the molecular and phenotypic impact of amino acid variants with MutPred2

Identifying pathogenic variants and underlying functional alterations is challenging. To this end, we introduce MutPred2, a tool that improves the prioritization of pathogenic amino acid substitutions over existing methods, generates molecular mechanisms potentially causative of disease, and returns interpretable pathogenicity score distributions on individual genomes. Whilst its prioritization performance is state-of-the-art, a distinguishing feature of MutPred2 is the probabilistic modeling of variant impact on specific aspects of protein structure and function that can serve to guide experimental studies of phenotype-altering variants. We demonstrate the utility of MutPred2 in the identification of the structural and functional mutational signatures relevant to Mendelian disorders and the prioritization of de novo mutations associated with complex neurodevelopmental disorders. We then experimentally validate the functional impact of several variants identified in patients with such disorders. We argue that mechanism-driven studies of human inherited disease have the potential to significantly accelerate the discovery of clinically actionable variants.

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.

Demographic Processes Linked to Genetic Diversity and Positive Selection across a Species' Range

Demography determines the strength of genetic drift, which generally reduces genetic variation and the efficacy of selection. Here, we disentangled the importance of demographic processes at a local scale (census size and mating system) and at a species-range scale (old split between population clusters, recolonization after the last glaciation cycle, and admixture) in determining within-population genomic diversity and genomic signatures of positive selection. Analyses were based on re-sequence data from 52 populations of North American Arabidopsis lyrata collected across its entire distribution. The mating system and range dynamics since the last glaciation cycle explained around 60% of the variation in genomic diversity among populations and 52% of the variation in the signature of positive selection. Diversity was lowest in selfing compared with outcrossing populations and in areas further away from glacial refugia. In parallel, reduced positive selection was found in selfing populations and in populations with a longer route of postglacial range expansion. The signature of positive selection was also reduced in populations without admixture. We conclude that recent range expansion can have a profound influence on diversity in coding and non-coding DNA, similar in magnitude to the shift toward selfing. Distribution limits may in fact be caused by reduced effective population size and compromised positive selection in recently colonized parts of the range.

Formation and diversification of a paradigm biosynthetic gene cluster in plants

Numerous examples of biosynthetic gene clusters (BGCs), including for compounds of agricultural and medicinal importance, have now been discovered in plant genomes. However, little is known about how these complex traits are assembled and diversified. Here, we examine a large number of variants within and between species for a paradigm BGC (the thalianol cluster), which has evolved recently in a common ancestor of the Arabidopsis genus. Comparisons at the species level reveal differences in BGC organization and involvement of auxiliary genes, resulting in production of species-specific triterpenes. Within species, the thalianol cluster is primarily fixed, showing a low frequency of deleterious haplotypes. We further identify chromosomal inversion as a molecular mechanism that may shuffle more distant genes into the cluster, so enabling cluster compaction. Antagonistic natural selection pressures are likely involved in shaping the occurrence and maintenance of this BGC. Our work sheds light on the birth, life and death of complex genetic and metabolic traits in plants.

Mining and evolution analysis of lateral organ boundaries domain (LBD) genes in Chinese white pear (Pyrus bretschneideri)

BACKGROUND

The lateral organ boundaries domain (LBD) gene is a plant-specific transcription factor that plays a critical role in diverse biological processes. However, the evolution and functional divergence of the LBD gene family has not yet been characterized for the Chinese White Pear.

RESULTS

In our study, a total of 60 PbrLBDs were identified in the pear genome. The PbrLBD gene family was divided into two classes based on gene structure and phylogenetic analysis: class I (53) and class II (7). Cis-acting element analysis results suggested that PbrLBDs may participate in various biological processes, such as flavonoid biosynthetic and stress response. Synteny analysis results indicated that segmental duplication played a key role in the expansion of the PbrLBD gene family. The mean Ks and 4DTv values showed that the PbrLBD gene family had undergone only one recent whole-genome duplication event occurring at 30-45 MYA. Purifying selection was a primary force during the PbrLBD gene family evolution process. Transcriptome data analysis revealed that 10 PbrLBDs were expressed in all six examined tissues, and 73.33% of members in the PbrLBD gene family were expressed in pear sepal. qRT-PCR was conducted to verify the expression levels of 11 PbrLBDs in these six tissues. Specifically, PbrLBD20, PbrLBD35 and PbrLBD53 genes were down-regulated when anthocyanin concentrations were high, whereas PbrLBD33 was significantly up-regulated in pear when anthocyanin concentrations were high. Furthermore, PbrLBD20, one of the candidate genes related to anthocyanins was localized in the nucleus.

CONCLUSIONS

Our analysis provides valuable information for understanding the evolution of the PbrLBD gene family, and provides new insights into the regulation of pear pigment metabolism and lays a foundation for the future disclosure of the molecular mechanism of LBD gene regulating flavonoid metabolism.

Survival in the Tropics despite isolation, inbreeding and asexual reproduction: insights from the genome of the world's southernmost poplar (Populus ilicifolia)

Species are becoming extinct at unprecedented rates as a consequence of human activity. Hence it is important to understand the evolutionary dynamics of species with already small population sizes. Populus ilicifolia is a vulnerable poplar species that is isolated from other poplar species and is uniquely adapted to the Tropics. It has a very limited size, reproduces partly clonally and is therefore an excellent case study for conservation genomics. We present here the first annotated draft genome of P. ilicifolia, characterize genome-wide patterns of polymorphisms and compare those to other poplar species with larger natural ranges. P. ilicifolia experienced a more prolonged and severe decline of effective population size (N_e ) and signs of genetic erosion than any other poplar species with which it was compared. At present, the species has the lowest genome-wide genetic diversity, the highest abundance of long runs of homozygosity, high inbreeding levels as well as a high overall accumulation of deleterious variants. However, more effective purging of severely deleterious variants and adaptation to the Tropics may have contributed to its survival. Hence, in spite of its limited genetic variation, it is certainly worth pursuing the conservation efforts of this unique species.

iMKT: the integrative McDonald and Kreitman test

The McDonald and Kreitman test (MKT) is one of the most powerful and widely used methods to detect and quantify recurrent natural selection using DNA sequence data. Here we present iMKT (acronym for integrative McDonald and Kreitman test), a novel web-based service performing four distinct MKT types. It allows the detection and estimation of four different selection regimes −adaptive, neutral, strongly deleterious and weakly deleterious− acting on any genomic sequence. iMKT can analyze both user's own population genomic data and pre-loaded Drosophila melanogaster and human sequences of protein-coding genes obtained from the largest population genomic datasets to date. Advanced options in the website allow testing complex hypotheses such as the application example showed here: do genes located in high recombination regions undergo higher rates of adaptation? We aim that iMKT will become a reference site tool for the study of evolutionary adaptation in massive population genomics datasets, especially in Drosophila and humans. iMKT is a free resource online at https://imkt.uab.cat.

Invasion Rate Versus Diversity in Population Dynamics with Catastrophes

A key question in the current diversity crisis is how diversity has been maintained throughout evolution and how to preserve it. Modern coexistence theories suggest that a high invasion rate of rare new types is directly related to diversity. We show that adding almost any mechanism of catastrophes to a stochastic birth, death, and mutation process with limited carrying capacity induces a novel phase transition characterized by a positive invasion rate but a low diversity. In this phase, new types emerge and grow rapidly, but the resulting growth of very large types decreases diversity. This model also resolves two major drawbacks of neutral evolution models: their failure to explain balancing selection without resorting to fitness differences and the unrealistic time required for the creation of the observed large types. We test this model on a classical case of genetic polymorphism: the HLA locus.

Adaptive genetic diversification of Lassa virus associated with the epidemic split of north-central Nigerian and non-Nigerian lineages

Lassa fever (LF) is a viral hemorrhagic fever that causes high morbidity and severe mortality annually. The disease is endemic to two geographically separate areas within tropical West Africa, one in Nigeria and the second predominantly in Sierra Leone-Guinea-Liberia-Mali. Lassa virus (LASV), the causative agent of the disease, exhibits clear delineation of phylogeography between the endemic areas. In order to characterize the genetic nature of Nigerian-non-Nigerian epidemic split, we performed molecular epidemiological analyses on non-Nigerian isolates (lineage IV as well as lineage V) and their sister group from north-central Nigeria (lineage III). The results showed that adaptive genetic diversification has occurred between these currently circulating clusters in the spread process, and a number of replacement divergences have been fixed between these clusters on the viral RNA-dependent RNA polymerase (L protein). This study highlights the viral L protein could be a determinant factor for the epidemic split.

Admixture-enabled selection for rapid adaptive evolution in the Americas

BACKGROUND

Admixture occurs when previously isolated populations come together and exchange genetic material. We hypothesize that admixture can enable rapid adaptive evolution in human populations by introducing novel genetic variants (haplotypes) at intermediate frequencies, and we test this hypothesis through the analysis of whole genome sequences sampled from admixed Latin American populations in Colombia, Mexico, Peru, and Puerto Rico.

RESULTS

Our screen for admixture-enabled selection relies on the identification of loci that contain more or less ancestry from a given source population than would be expected given the genome-wide ancestry frequencies. We employ a combined evidence approach to evaluate levels of ancestry enrichment at single loci across multiple populations and multiple loci that function together to encode polygenic traits. We find cross-population signals of African ancestry enrichment at the major histocompatibility locus on chromosome 6, consistent with admixture-enabled selection for enhanced adaptive immune response. Several of the human leukocyte antigen genes at this locus, such as HLA-A, HLA-DRB51, and HLA-DRB5, show independent evidence of positive selection prior to admixture, based on extended haplotype homozygosity in African populations. A number of traits related to inflammation, blood metabolites, and both the innate and adaptive immune system show evidence of admixture-enabled polygenic selection in Latin American populations.

CONCLUSIONS

The results reported here, considered together with the ubiquity of admixture in human evolution, suggest that admixture serves as a fundamental mechanism that drives rapid adaptive evolution in human populations.

The Genome of the Endangered Dryas Monkey Provides New Insights into the Evolutionary History of the Vervets

Genomic data can be a powerful tool for inferring ecology, behavior, and conservation needs of highly elusive species, particularly, when other sources of information are hard to come by. Here, we focus on the Dryas monkey (Cercopithecus dryas), an endangered primate endemic to the Congo Basin with cryptic behavior and possibly <250 remaining adult individuals. Using whole-genome sequencing data, we show that the Dryas monkey represents a sister lineage to the vervets (Chlorocebus sp.) and has diverged from them ∼1.4 Ma with additional bidirectional gene flow ∼750,000–∼500,000 years ago that has likely involved the crossing of the Congo River. Together with evidence of gene flow across the Congo River in bonobos and okapis, our results suggest that the fluvial topology of the Congo River might have been more dynamic than previously recognized. Despite the presence of several homozygous loss-of-function mutations in genes associated with sperm mobility and immunity, we find high genetic diversity and low levels of inbreeding and genetic load in the studied Dryas monkey individual. This suggests that the current population carries sufficient genetic variability for long-term survival and might be larger than currently recognized. We thus provide an example of how genomic data can directly improve our understanding of highly elusive species.

Polymorphism Data Assist Estimation of the Nonsynonymous over Synonymous Fixation Rate Ratio ω for Closely Related Species

The ratio of nonsynonymous over synonymous sequence divergence, dN/dS, is a widely used estimate of the nonsynonymous over synonymous fixation rate ratio ω, which measures the extent to which natural selection modulates protein sequence evolution. Its computation is based on a phylogenetic approach and computes sequence divergence of protein-coding DNA between species, traditionally using a single representative DNA sequence per species. This approach ignores the presence of polymorphisms and relies on the indirect assumption that new mutations fix instantaneously, an assumption which is generally violated and reasonable only for distantly related species. The violation of the underlying assumption leads to a time-dependence of sequence divergence, and biased estimates of ω in particular for closely related species, where the contribution of ancestral and lineage-specific polymorphisms to sequence divergence is substantial. We here use a time-dependent Poisson random field model to derive an analytical expression of dN/dS as a function of divergence time and sample size. We then extend our framework to the estimation of the proportion of adaptive protein evolution α. This mathematical treatment enables us to show that the joint usage of polymorphism and divergence data can assist the inference of selection for closely related species. Moreover, our analytical results provide the basis for a protocol for the estimation of ω and α for closely related species. We illustrate the performance of this protocol by studying a population data set of four corvid species, which involves the estimation of ω and α at different time-scales and for several choices of sample sizes.

Integrative analysis reveals RNA G-quadruplexes in UTRs are selectively constrained and enriched for functional associations

G-quadruplex (G4) sequences are abundant in untranslated regions (UTRs) of human messenger RNAs, but their functional importance remains unclear. By integrating multiple sources of genetic and genomic data, we show that putative G-quadruplex forming sequences (pG4) in 5' and 3' UTRs are selectively constrained, and enriched for cis-eQTLs and RNA-binding protein (RBP) interactions. Using over 15,000 whole-genome sequences, we find that negative selection acting on central guanines of UTR pG4s is comparable to that of missense variation in protein-coding sequences. At multiple GWAS-implicated SNPs within pG4 UTR sequences, we find robust allelic imbalance in gene expression across diverse tissue contexts in GTEx, suggesting that variants affecting G-quadruplex formation within UTRs may also contribute to phenotypic variation. Our results establish UTR G4s as important cis-regulatory elements and point to a link between disruption of UTR pG4 and disease.

Molecular Evolution in Large Steps-Codon Substitutions under Positive Selection

Molecular evolution is believed to proceed in small steps. The step size can be defined by a distance reflecting physico-chemical disparities between amino acid (AA) pairs that can be exchanged by single 1-bp mutations. We show that AA substitution rates are strongly and negatively correlated with this distance but only when positive selection is relatively weak. We use the McDonald and Kreitman test to separate the influences of positive and negative selection. While negative selection is indeed stronger on AA substitutions generating larger changes in chemical properties of AAs, positive selection operates by different rules. For 65 of the 75 possible pairs, positive selection is comparable in strength regardless of AA distance. However, the ten pairs under the strongest positive selection all exhibit large leaps in chemical properties. Five of the ten pairs are shared between Drosophila and Hominoids, thus hinting at a common but modest biochemical basis of adaptation across taxa. The hypothesis that adaptive changes often take large functional steps will need to be extensively tested. If validated, molecular models will need to better integrate positive and negative selection in the search for adaptive signal.

The Impact of Protein Architecture on Adaptive Evolution

Adaptive mutations play an important role in molecular evolution. However, the frequency and nature of these mutations at the intramolecular level are poorly understood. To address this, we analyzed the impact of protein architecture on the rate of adaptive substitutions, aiming to understand how protein biophysics influences fitness and adaptation. Using Drosophila melanogaster and Arabidopsis thaliana population genomics data, we fitted models of distribution of fitness effects and estimated the rate of adaptive amino-acid substitutions both at the protein and amino-acid residue level. We performed a comprehensive analysis covering genome, gene, and protein structure, by exploring a multitude of factors with a plausible impact on the rate of adaptive evolution, such as intron number, protein length, secondary structure, relative solvent accessibility, intrinsic protein disorder, chaperone affinity, gene expression, protein function, and protein-protein interactions. We found that the relative solvent accessibility is a major determinant of adaptive evolution, with most adaptive mutations occurring at the surface of proteins. Moreover, we observe that the rate of adaptive substitutions differs between protein functional classes, with genes encoding for protein biosynthesis and degradation signaling exhibiting the fastest rates of protein adaptation. Overall, our results suggest that adaptive evolution in proteins is mainly driven by intermolecular interactions, with host-pathogen coevolution likely playing a major role.