Detecting positive selection within genomes: the problem of biased gene conversion

Half a Century of Controversy: The Neutralist/Selectionist Debate in Molecular Evolution

The neutral and nearly neutral theories, introduced more than 50 yr ago, have raised and still raise passionate discussion regarding the forces governing molecular evolution and their relative importance. The debate, initially focused on the amount of within-species polymorphism and constancy of the substitution rate, has spread, matured, and now underlies a wide range of topics and questions. The neutralist/selectionist controversy has structured the field and influences the way molecular evolutionary scientists conceive their research.

Evolution of the Mutation Spectrum Across a Mammalian Phylogeny

Although evolutionary biologists have long theorized that variation in DNA repair efficacy might explain some of the diversity of lifespan and cancer incidence across species, we have little data on the variability of normal germline mutagenesis outside of humans. Here, we shed light on the spectrum and etiology of mutagenesis across mammals by quantifying mutational sequence context biases using polymorphism data from thirteen species of mice, apes, bears, wolves, and cetaceans. After normalizing the mutation spectrum for reference genome accessibility and k-mer content, we use the Mantel test to deduce that mutation spectrum divergence is highly correlated with genetic divergence between species, whereas life history traits like reproductive age are weaker predictors of mutation spectrum divergence. Potential bioinformatic confounders are only weakly related to a small set of mutation spectrum features. We find that clock-like mutational signatures previously inferred from human cancers cannot explain the phylogenetic signal exhibited by the mammalian mutation spectrum, despite the ability of these signatures to fit each species' 3-mer spectrum with high cosine similarity. In contrast, parental aging signatures inferred from human de novo mutation data appear to explain much of the 1-mer spectrum's phylogenetic signal in combination with a novel mutational signature. We posit that future models purporting to explain the etiology of mammalian mutagenesis need to capture the fact that more closely related species have more similar mutation spectra; a model that fits each marginal spectrum with high cosine similarity is not guaranteed to capture this hierarchy of mutation spectrum variation among species.

GC-biased gene conversion drives accelerated evolution of ultraconserved elements in mammalian and avian genomes

Ultraconserved elements (UCEs) are the most conserved regions among the genomes of evolutionarily distant species and are thought to play critical biological functions. However, some UCEs rapidly evolved in specific lineages, and whether they contributed to adaptive evolution is still controversial. Here, using an increased number of sequenced genomes with high taxonomic coverage, we identified 2191 mammalian UCEs and 5938 avian UCEs from 95 mammal and 94 bird genomes, respectively. Our results show that these UCEs are functionally constrained and that their adjacent genes are prone to widespread expression with low expression diversity across tissues. Functional enrichment of mammalian and avian UCEs shows different trends indicating that UCEs may contribute to adaptive evolution of taxa. Focusing on lineage-specific accelerated evolution, we discover that the proportion of fast-evolving UCEs in nine mammalian and 10 avian test lineages range from 0.19% to 13.2%. Notably, up to 62.1% of fast-evolving UCEs in test lineages are much more likely to result from GC-biased gene conversion (gBGC). A single cervid-specific gBGC region embracing the uc.359 allele significantly alters the expression of Nova1 and other neural-related genes in the rat brain. Combined with the altered regulatory activity of ancient gBGC-induced fast-evolving UCEs in eutherians, our results provide evidence that synergy between gBGC and selection shaped lineage-specific substitution patterns, even in the most constrained regulatory elements. In summary, our results show that gBGC played an important role in facilitating lineage-specific accelerated evolution of UCEs, and further support the idea that a combination of multiple evolutionary forces shapes adaptive evolution.

The evolutionary maintenance of ancient recombining sex chromosomes in the ostrich

Sex chromosomes have evolved repeatedly across the tree of life and often exhibit extreme size dimorphism due to genetic degeneration of the sex-limited chromosome (e.g. the W chromosome of some birds and Y chromosome of mammals). However, in some lineages, ancient sex-limited chromosomes have escaped degeneration. Here, we study the evolutionary maintenance of sex chromosomes in the ostrich (Struthio camelus), where the W remains 65% the size of the Z chromosome, despite being more than 100 million years old. Using genome-wide resequencing data, we show that the population scaled recombination rate of the pseudoautosomal region (PAR) is higher than similar sized autosomes and is correlated with pedigree-based recombination rate in the heterogametic females, but not homogametic males. Genetic variation within the sex-linked region (SLR) (π = 0.001) was significantly lower than in the PAR, consistent with recombination cessation. Conversely, genetic variation across the PAR (π = 0.0016) was similar to that of autosomes and dependent on local recombination rates, GC content and to a lesser extent, gene density. In particular, the region close to the SLR was as genetically diverse as autosomes, likely due to high recombination rates around the PAR boundary restricting genetic linkage with the SLR to only ~50Kb. The potential for alleles with antagonistic fitness effects in males and females to drive chromosome degeneration is therefore limited. While some regions of the PAR had divergent male-female allele frequencies, suggestive of sexually antagonistic alleles, coalescent simulations showed this was broadly consistent with neutral genetic processes. Our results indicate that the degeneration of the large and ancient sex chromosomes of the ostrich may have been slowed by high recombination in the female PAR, reducing the scope for the accumulation of sexually antagonistic variation to generate selection for recombination cessation.

"Evolution of the mutation spectrum across a mammalian phylogeny"

Little is known about how the spectrum and etiology of germline mutagenesis might vary among mammalian species. To shed light on this mystery, we quantify variation in mutational sequence context biases using polymorphism data from thirteen species of mice, apes, bears, wolves, and cetaceans. After normalizing the mutation spectrum for reference genome accessibility and k -mer content, we use the Mantel test to deduce that mutation spectrum divergence is highly correlated with genetic divergence between species, whereas life history traits like reproductive age are weaker predictors of mutation spectrum divergence. Potential bioinformatic confounders are only weakly related to a small set of mutation spectrum features. We find that clocklike mutational signatures previously inferred from human cancers cannot explain the phylogenetic signal exhibited by the mammalian mutation spectrum, despite the ability of these clocklike signatures to fit each species' 3-mer spectrum with high cosine similarity. In contrast, parental aging signatures inferred from human de novo mutation data appear to explain much of the mutation spectrum's phylogenetic signal when fit to non-context-dependent mutation spectrum data in combination with a novel mutational signature. We posit that future models purporting to explain the etiology of mammalian mutagenesis need to capture the fact that more closely related species have more similar mutation spectra; a model that fits each marginal spectrum with high cosine similarity is not guaranteed to capture this hierarchy of mutation spectrum variation among species.

Beginner's Guide on the Use of PAML to Detect Positive Selection

The CODEML program in the PAML package has been widely used to analyze protein-coding gene sequences to estimate the synonymous and nonsynonymous rates (dS and dN) and to detect positive Darwinian selection driving protein evolution. For users not familiar with molecular evolutionary analysis, the program is known to have a steep learning curve. Here, we provide a step-by-step protocol to illustrate the commonly used tests available in the program, including the branch models, the site models, and the branch-site models, which can be used to detect positive selection driving adaptive protein evolution affecting particular lineages of the species phylogeny, affecting a subset of amino acid residues in the protein, and affecting a subset of sites along prespecified lineages, respectively. A data set of the myxovirus (Mx) genes from ten mammal and two bird species is used as an example. We discuss a new feature in CODEML that allows users to perform positive selection tests for multiple genes for the same set of taxa, as is common in modern genome-sequencing projects. The PAML package is distributed at https://github.com/abacus-gene/paml under the GNU license, with support provided at its discussion site (https://groups.google.com/g/pamlsoftware). Data files used in this protocol are available at https://github.com/abacus-gene/paml-tutorial.

Evolution is not Uniform Along Coding Sequences

Amino acids evolve at different speeds within protein sequences, because their functional and structural roles are different. Notably, amino acids located at the surface of proteins are known to evolve more rapidly than those in the core. In particular, amino acids at the N- and C-termini of protein sequences are likely to be more exposed than those at the core of the folded protein due to their location in the peptidic chain, and they are known to be less structured. Because of these reasons, we would expect that amino acids located at protein termini would evolve faster than residues located inside the chain. Here we test this hypothesis and found that amino acids evolve almost twice as fast at protein termini compared with those in the center, hinting at a strong topological bias along the sequence length. We further show that the distribution of solvent-accessible residues and functional domains in proteins readily explain how structural and functional constraints are weaker at their termini, leading to the observed excess of amino acid substitutions. Finally, we show that the specific evolutionary rates at protein termini may have direct consequences, notably misleading in silico methods used to infer sites under positive selection within genes. These results suggest that accounting for positional information should improve evolutionary models.

Evaluation of Methods to Detect Shifts in Directional Selection at the Genome Scale

Identifying the footprints of selection in coding sequences can inform about the importance and function of individual sites. Analyses of the ratio of nonsynonymous to synonymous substitutions (dN/dS) have been widely used to pinpoint changes in the intensity of selection, but cannot distinguish them from changes in the direction of selection, that is, changes in the fitness of specific amino acids at a given position. A few methods that rely on amino-acid profiles to detect changes in directional selection have been designed, but their performances have not been well characterized. In this paper, we investigate the performance of six of these methods. We evaluate them on simulations along empirical phylogenies in which transition events have been annotated and compare their ability to detect sites that have undergone changes in the direction or intensity of selection to that of a widely used dN/dS approach, codeml's branch-site model A. We show that all methods have reduced performance in the presence of biased gene conversion but not CpG hypermutability. The best profile method, Pelican, a new implementation of Tamuri AU, Hay AJ, Goldstein RA. (2009. Identifying changes in selective constraints: host shifts in influenza. PLoS Comput Biol. 5(11):e1000564), performs as well as codeml in a range of conditions except for detecting relaxations of selection, and performs better when tree length increases, or in the presence of persistent positive selection. It is fast, enabling genome-scale searches for site-wise changes in the direction of selection associated with phenotypic changes.

Positive selection-driven fixation of a hominin-specific amino acid mutation related to dephosphorylation in IRF9

The arms race between humans and pathogens drives the evolution of the human genome. It is thus expected that genes from the interferon-regulatory factors family (IRFs), a critical family for anti-viral immune response, should be undergoing episodes of positive selection. Herein, we tested this hypothesis and found multiple lines of evidence for positive selection on the amino acid site Val129 (NP_006075.3:p.Ser129Val) of human IRF9. Interestingly, the ancestral reconstruction and population distribution analyses revealed that the ancestral state (Ser129) is conserved among mammals, while the derived positively selected state (Val129) was fixed before the “out-of-Africa” event ~ 500,000 years ago. The motif analysis revealed that this young amino acid (Val129) may serve as a dephosphorylation site of IRF9. Structural parallelism between homologous genes further suggested the functional effects underlying the dephosphorylation that may affect the immune activity of IRF9. This study provides a model in which a strong positive Darwinian selection drives a recent fixation of a hominin-specific amino acid leading to molecular adaptation involving dephosphorylation in an immune-responsive gene.

Unusual mammalian usage of TGA stop codons reveals that sequence conservation need not imply purifying selection

The assumption that conservation of sequence implies the action of purifying selection is central to diverse methodologies to infer functional importance. GC-biased gene conversion (gBGC), a meiotic mismatch repair bias strongly favouring GC over AT, can in principle mimic the action of selection, this being thought to be especially important in mammals. As mutation is GC→AT biased, to demonstrate that gBGC does indeed cause false signals requires evidence that an AT-rich residue is selectively optimal compared to its more GC-rich allele, while showing also that the GC-rich alternative is conserved. We propose that mammalian stop codon evolution provides a robust test case. Although in most taxa TAA is the optimal stop codon, TGA is both abundant and conserved in mammalian genomes. We show that this mammalian exceptionalism is well explained by gBGC mimicking purifying selection and that TAA is the selectively optimal codon. Supportive of gBGC, we observe (i) TGA usage trends are consistent at the focal stop codon and elsewhere (in UTR sequences); (ii) that higher TGA usage and higher TAA→TGA substitution rates are predicted by a high recombination rate; and (iii) across species the difference in TAA <-> TGA substitution rates between GC-rich and GC-poor genes is largest in genomes that possess higher between-gene GC variation. TAA optimality is supported both by enrichment in highly expressed genes and trends associated with effective population size. High TGA usage and high TAA→TGA rates in mammals are thus consistent with gBGC’s predicted ability to “drive” deleterious mutations and supports the hypothesis that sequence conservation need not be indicative of purifying selection. A general trend for GC-rich trinucleotides to reside at frequencies far above their mutational equilibrium in high recombining domains supports the generality of these results.

Genome-wide analysis of sucrose synthase family in soybean and their expression in response to abiotic stress and seed development

The sucrose synthase (SS) is an important enzyme family which play a vital role in sugar metabolism to improve the fruit quality of the plants. In many plant species, the members of SS family have been investigated but the detailed information is not available in legumes particularly and Glycine max specifically. In the present study, we found thirteen SS members (GmSS1-GmSS13) in G. max genome. High conserved regions were present in the GmSS sequences that may due to the selection pressure during evolutionary events. The segmental duplication was the major factor to increase the number of GmSS family members. The identified thirteen GmSS genes were divided into Class I, Class II and Class III with variable numbers of genes in each class. The protein interaction of GmSS gave the co-expression of sucrose synthase with glucose-1-phosphate adenylyltransferase while SLAC and REL test found number of positive sites in the coding sequences of SS family members. All the GmSS family members except GmSS7 and few of class III members, were highly expressed in all the soybean tissues. The expression of the class I members decreased during seed development, whireas, the class II members expression increased during the seed developing, may involve in sugar metabolism during seed development. Solexa sequencing libraries of acidic condition (pH 4.2) stress samples showed that the expression of class I GmSS genes increased 1- to 2-folds in treated samples than control. The differential expression pattern was observed between the members of a paralogous. This study provides detailed genome-wide analysis of GmSS family in soybean that will provide new insights for future evolutionary and soybean breeding to improve the plant growth and development.

An Improved Codon Modeling Approach for Accurate Estimation of the Mutation Bias

Phylogenetic codon models are routinely used to characterize selective regimes in coding sequences. Their parametric design, however, is still a matter of debate, in particular concerning the question of how to account for differing nucleotide frequencies and substitution rates. This problem relates to the fact that nucleotide composition in protein-coding sequences is the result of the interactions between mutation and selection. In particular, because of the structure of the genetic code, the nucleotide composition differs between the three coding positions, with the third position showing a more extreme composition. Yet, phylogenetic codon models do not correctly capture this phenomenon and instead predict that the nucleotide composition should be the same for all three positions. Alternatively, some models allow for different nucleotide rates at the three positions, an approach conflating the effects of mutation and selection on nucleotide composition. In practice, it results in inaccurate estimation of the strength of selection. Conceptually, the problem comes from the fact that phylogenetic codon models do not correctly capture the fixation bias acting against the mutational pressure at the mutation–selection equilibrium. To address this problem and to more accurately identify mutation rates and selection strength, we present an improved codon modeling approach where the fixation rate is not seen as a scalar, but as a tensor. This approach gives an accurate representation of how mutation and selection oppose each other at equilibrium and yields a reliable estimate of the mutational process, while disentangling the mean fixation probabilities prevailing in different mutational directions.

OUP accepted manuscript

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

OUP accepted manuscript

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

Variability in Codon Usage in Coronaviruses Is Mainly Driven by Mutational Bias and Selective Constraints on CpG Dinucleotide

The Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the third human-emerged virus of the 21st century from the Coronaviridae family, causing the ongoing coronavirus disease 2019 (COVID-19) pandemic. Due to the high zoonotic potential of coronaviruses, it is critical to unravel their evolutionary history of host species breadth, host-switch potential, adaptation and emergence, to identify viruses posing a pandemic risk in humans. We present here a comprehensive analysis of the composition and codon usage bias of the 82 Orthocoronavirinae members, infecting 47 different avian and mammalian hosts. Our results clearly establish that synonymous codon usage varies widely among viruses, is only weakly dependent on their primary host, and is dominated by mutational bias towards AU-enrichment and by CpG avoidance. Indeed, variation in GC3 explains around 34%, while variation in CpG frequency explains around 14% of total variation in codon usage bias. Further insight on the mutational equilibrium within Orthocoronavirinae revealed that most coronavirus genomes are close to their neutral equilibrium, the exception being the three recently infecting human coronaviruses, which lie further away from the mutational equilibrium than their endemic human coronavirus counterparts. Finally, our results suggest that, while replicating in humans, SARS-CoV-2 is slowly becoming AU-richer, likely until attaining a new mutational equilibrium.

A Bayesian Mutation-Selection Framework for Detecting Site-Specific Adaptive Evolution in Protein-Coding Genes

In recent years, codon substitution models based on the mutation–selection principle have been extended for the purpose of detecting signatures of adaptive evolution in protein-coding genes. However, the approaches used to date have either focused on detecting global signals of adaptive regimes—across the entire gene—or on contexts where experimentally derived, site-specific amino acid fitness profiles are available. Here, we present a Bayesian site-heterogeneous mutation–selection framework for site-specific detection of adaptive substitution regimes given a protein-coding DNA alignment. We offer implementations, briefly present simulation results, and apply the approach on a few real data sets. Our analyses suggest that the new approach shows greater sensitivity than traditional methods. However, more study is required to assess the impact of potential model violations on the method, and gain a greater empirical sense its behavior on a broader range of real data sets. We propose an outline of such a research program.

Hearing Sensitivity of Primates: Recurrent and Episodic Positive Selection in Hair Cells and Stereocilia Protein-Coding Genes

The large spectrum of hearing sensitivity observed in primates results from the impact of environmental and behavioral pressures to optimize sound perception and localization. Although evidence of positive selection in auditory genes has been detected in mammals including in Hominoids, selection has never been investigated in other primates. We analyzed 123 genes highly expressed in the inner ear of 27 primate species and tested to what extent positive selection may have shaped these genes in the order Primates tree. We combined both site and branch-site tests to obtain a comprehensive picture of the positively selected genes (PSGs) involved in hearing sensitivity, and drew a detailed description of the most affected branches in the tree. We chose a conservative approach, and thus focused on confounding factors potentially affecting PSG signals (alignment, GC-biased gene conversion, duplications, heterogeneous sequencing qualities). Using site tests, we showed that around 12% of these genes are PSGs, an α selection value consistent with average human genome estimates (10-15%). Using branch-site tests, we showed that the primate tree is heterogeneously affected by positive selection, with the black snub-nosed monkey, the bushbaby, and the orangutan, being the most impacted branches. A large proportion of these genes is inclined to shape hair cells and stereocilia, which are involved in the mechanotransduction process, known to influence frequency perception. Adaptive selection, and more specifically recurrent adaptive evolution, could have acted in parallel on a set of genes (ADGRV1, USH2A, PCDH15, PTPRQ, and ATP8A2) involved in stereocilia growth and the whole complex of bundle links connecting them, in species across different habitats, including high altitude and nocturnal environments.

Runaway GC Evolution in Gerbil Genomes

Recombination increases the local GC-content in genomic regions through GC-biased gene conversion (gBGC). The recent discovery of a large genomic region with extreme GC-content in the fat sand rat Psammomys obesus provides a model to study the effects of gBGC on chromosome evolution. Here, we compare the GC-content and GC-to-AT substitution patterns across protein-coding genes of four gerbil species and two murine rodents (mouse and rat). We find that the known high-GC region is present in all the gerbils, and is characterized by high substitution rates for all mutational categories (AT-to-GC, GC-to-AT, and GC-conservative) both at synonymous and nonsynonymous sites. A higher AT-to-GC than GC-to-AT rate is consistent with the high GC-content. Additionally, we find more than 300 genes outside the known region with outlying values of AT-to-GC synonymous substitution rates in gerbils. Of these, over 30% are organized into at least 17 large clusters observable at the megabase-scale. The unusual GC-skewed substitution pattern suggests the evolution of genomic regions with very high recombination rates in the gerbil lineage, which can lead to a runaway increase in GC-content. Our results imply that rapid evolution of GC-content is possible in mammals, with gerbil species providing a powerful model to study the mechanisms of gBGC.

Genetic Mechanisms Underlying Cortical Evolution in Mammals

The remarkable sensory, motor, and cognitive abilities of mammals mainly depend on the neocortex. Thus, the emergence of the six-layered neocortex in reptilian ancestors of mammals constitutes a fundamental evolutionary landmark. The mammalian cortex is a columnar epithelium of densely packed cells organized in layers where neurons are generated mainly in the subventricular zone in successive waves throughout development. Newborn cells move away from their site of neurogenesis through radial or tangential migration to reach their specific destination closer to the pial surface of the same or different cortical area. Interestingly, the genetic programs underlying neocortical development diversified in different mammalian lineages. In this work, I will review several recent studies that characterized how distinct transcriptional programs relate to the development and functional organization of the neocortex across diverse mammalian lineages. In some primates such as the anthropoids, the neocortex became extremely large, especially in humans where it comprises around 80% of the brain. It has been hypothesized that the massive expansion of the cortical surface and elaboration of its connections in the human lineage, has enabled our unique cognitive capacities including abstract thinking, long-term planning, verbal language and elaborated tool making capabilities. I will also analyze the lineage-specific genetic changes that could have led to the modification of key neurodevelopmental events, including regulation of cell number, neuronal migration, and differentiation into specific phenotypes, in order to shed light on the evolutionary mechanisms underlying the diversity of mammalian brains including the human brain.

Analysis of selection in protein-coding sequences accounting for common biases

The evolution of protein-coding genes is usually driven by selective processes, which favor some evolutionary trajectories over others, optimizing the subsequent protein stability and activity. The analysis of selection in this type of genetic data is broadly performed with the metric nonsynonymous/synonymous substitution rate ratio (dN/dS). However, most of the well-established methodologies to estimate this metric make crucial assumptions, such as lack of recombination or invariable codon frequencies along genes, which can bias the estimation. Here, we review the most relevant biases in the dN/dS estimation and provide a detailed guide to estimate this metric using state-of-the-art procedures that account for such biases, along with illustrative practical examples and recommendations. We also discuss the traditional interpretation of the estimated dN/dS emphasizing the importance of considering complementary biological information such as the role of the observed substitutions on the stability and function of proteins. This review is oriented to help evolutionary biologists that aim to accurately estimate selection in protein-coding sequences.

Genome-wide macroevolutionary signatures of key innovations in butterflies colonizing new host plants

The mega-diversity of herbivorous insects is attributed to their co-evolutionary associations with plants. Despite abundant studies on insect-plant interactions, we do not know whether host-plant shifts have impacted both genomic adaptation and species diversification over geological times. We show that the antagonistic insect-plant interaction between swallowtail butterflies and the highly toxic birthworts began 55 million years ago in Beringia, followed by several major ancient host-plant shifts. This evolutionary framework provides a valuable opportunity for repeated tests of genomic signatures of macroevolutionary changes and estimation of diversification rates across their phylogeny. We find that host-plant shifts in butterflies are associated with both genome-wide adaptive molecular evolution (more genes under positive selection) and repeated bursts of speciation rates, contributing to an increase in global diversification through time. Our study links ecological changes, genome-wide adaptations and macroevolutionary consequences, lending support to the importance of ecological interactions as evolutionary drivers over long time periods.

Characterization of an eutherian gene cluster generated after transposon domestication identifies Bex3 as relevant for advanced neurological functions

BACKGROUND

One of the most unusual sources of phylogenetically restricted genes is the molecular domestication of transposable elements into a host genome as functional genes. Although these kinds of events are sometimes at the core of key macroevolutionary changes, their origin and organismal function are generally poorly understood.

RESULTS

Here, we identify several previously unreported transposable element domestication events in the human and mouse genomes. Among them, we find a remarkable molecular domestication that gave rise to a multigenic family in placental mammals, the Bex/Tceal gene cluster. These genes, which act as hub proteins within diverse signaling pathways, have been associated with neurological features of human patients carrying genomic microdeletions in chromosome X. The Bex/Tceal genes display neural-enriched patterns and are differentially expressed in human neurological disorders, such as autism and schizophrenia. Two different murine alleles of the cluster member Bex3 display morphological and physiopathological brain modifications, such as reduced interneuron number and hippocampal electrophysiological imbalance, alterations that translate into distinct behavioral phenotypes.

CONCLUSIONS

We provide an in-depth understanding of the emergence of a gene cluster that originated by transposon domestication and gene duplication at the origin of placental mammals, an evolutionary process that transformed a non-functional transposon sequence into novel components of the eutherian genome. These genes were integrated into existing signaling pathways involved in the development, maintenance, and function of the CNS in eutherians. At least one of its members, Bex3, is relevant for higher brain functions in placental mammals and may be involved in human neurological disorders.

Biased Gene Conversion Constrains Adaptation in Arabidopsis thaliana

Reduction of fitness due to deleterious mutations imposes a limit to adaptive evolution. By characterizing features that influence this genetic load we may better understand constraints on responses to both natural and human-mediated selection. Here, using whole-genome, transcriptome, and methylome data from >600 Arabidopsis thaliana individuals, we set out to identify important features influencing selective constraint. Our analyses reveal that multiple factors underlie the accumulation of maladaptive mutations, including gene expression level, gene network connectivity, and gene-body methylation. We then focus on a feature with major effect, nucleotide composition. The ancestral vs. derived status of segregating alleles suggests that GC-biased gene conversion, a recombination-associated process that increases the frequency of G and C nucleotides regardless of their fitness effects, shapes sequence patterns in A. thaliana Through estimation of mutational effects, we present evidence that biased gene conversion hinders the purging of deleterious mutations and contributes to a genome-wide signal of decreased efficacy of selection. By comparing these results to two outcrossing relatives, Arabidopsis lyrata and Capsella grandiflora, we find that protein evolution in A. thaliana is as strongly affected by biased gene conversion as in the outcrossing species. Last, we perform simulations to show that natural levels of outcrossing in A. thaliana are sufficient to facilitate biased gene conversion despite increased homozygosity due to selfing. Together, our results show that even predominantly selfing taxa are susceptible to biased gene conversion, suggesting that it may constitute an important constraint to adaptation among plant 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.

A genome-wide approach to the comprehensive analysis of GASA gene family in Glycine max

A vital role of short amino acid gene family, gibberellic acid stimulated arabidopsis (GASA), has been reported in plant growth and development. Although, little information is available about these cysteine rich short proteins in different plant species and this is the first comprehensive approach to exploit available genomic data and to analyze the GASA family in G. max. The phylogenetic and sequence composition analysis distributed the 37 identified GmGASA genes into three groups. Further investigation of the tissue expression pattern, phylogenetic analysis, motif, gene structure, chromosome distributions, duplication patterns, positive-selection pressure and cis-element analysis of 37 GmGASA genes. A conserved GASA domain was found in all identified GmGASA genes and exhibited similar characteristics. The online gene expression profile based analysis of GmGASA genes reveled that these genes were highly expressed in almost all soybean parts and some have high expression in flower which indicates that GmGASA genes displayed special or distinct expression pattern among different tissues. The segmental duplication was found in five pairs from 37 GmGASA genes and was distributed on 15 different chromosomes. The Ka/Ks ratio of 5 pairs of segmentally duplicated gene indicated that after the occurrence of duplication events, the duplicated gene pairs were purified and selected after restrictive functional differentiation. This investigated study of GmGASA gene will useful to support the statement about GASA genes role during flower induction in flowering plants.

Large-Scale Comparative Analysis of Codon Models Accounting for Protein and Nucleotide Selection

There are numerous sources of variation in the rate of synonymous substitutions inside genes, such as direct selection on the nucleotide sequence, or mutation rate variation. Yet scans for positive selection rely on codon models which incorporate an assumption of effectively neutral synonymous substitution rate, constant between sites of each gene. Here we perform a large-scale comparison of approaches which incorporate codon substitution rate variation and propose our own simple yet effective modification of existing models. We find strong effects of substitution rate variation on positive selection inference. More than 70% of the genes detected by the classical branch-site model are presumably false positives caused by the incorrect assumption of uniform synonymous substitution rate. We propose a new model which is strongly favored by the data while remaining computationally tractable. With the new model we can capture signatures of nucleotide level selection acting on translation initiation and on splicing sites within the coding region. Finally, we show that rate variation is highest in the highly recombining regions, and we propose that recombination and mutation rate variation, such as high CpG mutation rate, are the two main sources of nucleotide rate variation. Although we detect fewer genes under positive selection in Drosophila than without rate variation, the genes which we detect contain a stronger signal of adaptation of dynein, which could be associated with Wolbachia infection. We provide software to perform positive selection analysis using the new model.

GC content of vertebrate exome landscapes reveal areas of accelerated protein evolution

BACKGROUND

Rapid accumulation of vertebrate genome sequences render comparative genomics a powerful approach to study macro-evolutionary events. The assessment of phylogenic relationships between species routinely depends on the analysis of sequence homology at the nucleotide or protein level.

RESULTS

We analyzed mRNA GC content, codon usage and divergence of orthologous proteins in 55 vertebrate genomes. Data were visualized in genome-wide landscapes using a sliding window approach. Landscapes of GC content reveal both evolutionary conservation of clustered genes, and lineage-specific changes, so that it was possible to construct a phylogenetic tree that closely matched the classic "tree of life". Landscapes of GC content also strongly correlated to landscapes of amino acid usage: positive correlation with glycine, alanine, arginine and proline and negative correlation with phenylalanine, tyrosine, methionine, isoleucine, asparagine and lysine. Peaks of GC content correlated strongly with increased protein divergence.

CONCLUSIONS

Landscapes of base- and amino acid composition of the coding genome opens a new approach in comparative genomics, allowing identification of discrete regions in which protein evolution accelerated over deep evolutionary time. Insight in the evolution of genome structure may spur novel studies assessing the evolutionary benefit of genes in particular genomic regions.

Biased Inference of Selection Due to GC-Biased Gene Conversion and the Rate of Protein Evolution in Flycatchers When Accounting for It

The rate of recombination impacts on rates of protein evolution for at least two reasons: it affects the efficacy of selection due to linkage and influences sequence evolution through the process of GC-biased gene conversion (gBGC). We studied how recombination, via gBGC, affects inferences of selection in gene sequences using comparative genomic and population genomic data from the collared flycatcher (Ficedula albicollis). We separately analyzed different mutation categories (“strong”-to-“weak,” “weak-to-strong,” and GC-conservative changes) and found that gBGC impacts on the distribution of fitness effects of new mutations, and leads to that the rate of adaptive evolution and the proportion of adaptive mutations among nonsynonymous substitutions are underestimated by 22–33%. It also biases inferences of demographic history based on the site frequency spectrum. In light of this impact, we suggest that inferences of selection (and demography) in lineages with pronounced gBGC should be based on GC-conservative changes only. Doing so, we estimate that 10% of nonsynonymous mutations are effectively neutral and that 27% of nonsynonymous substitutions have been fixed by positive selection in the flycatcher lineage. We also find that gene expression level, sex-bias in expression, and the number of protein–protein interactions, but not Hill–Robertson interference (HRI), are strong determinants of selective constraint and rate of adaptation of collared flycatcher genes. This study therefore illustrates the importance of disentangling the effects of different evolutionary forces and genetic factors in interpretation of sequence data, and from that infer the role of natural selection in DNA sequence evolution.

A massively parallel 3' UTR reporter assay reveals relationships between nucleotide content, sequence conservation, and mRNA destabilization

Compared to coding sequences, untranslated regions of the transcriptome are not well conserved, and functional annotation of these sequences is challenging. Global relationships between nucleotide composition of 3′ UTR sequences and their sequence conservation have been appreciated since mammalian genomes were first sequenced, but the functional relevance of these patterns remain unknown. We systematically measured the effect on gene expression of the sequences of more than 25,000 RNA-binding protein (RBP) binding sites in primary mouse T cells using a massively parallel reporter assay. GC-rich sequences were destabilizing of reporter mRNAs and come from more rapidly evolving regions of the genome. These sequences were more likely to be folded in vivo and contain a number of structural motifs that reduced accumulation of a heterologous reporter protein. Comparison of full-length 3′ UTR sequences across vertebrate phylogeny revealed that strictly conserved 3′ UTRs were GC-poor and enriched in genes associated with organismal development. In contrast, rapidly evolving 3′ UTRs tended to be GC-rich and derived from genes involved in metabolism and immune responses. Cell-essential genes had lower GC content in their 3′ UTRs, suggesting a connection between unstructured mRNA noncoding sequences and optimal protein production. By reducing gene expression, GC-rich RBP-occupied sequences act as a rapidly evolving substrate for gene regulatory interactions.

Exploiting selection at linked sites to infer the rate and strength of adaptation

Genomic data encodes past evolutionary events and has the potential to reveal the strength, rate, and biological drivers of adaptation. However, jointly estimating adaptation rate (a) and adaptation strength remains challenging because evolutionary processes such as demography, linkage, and non-neutral polymorphism can confound inference. Here, we exploit the influence of background selection to reduce the fixation rate of weakly-beneficial alleles to jointly infer the strength and rate of adaptation. We develop an MK-based method (ABC-MK) to infer adaptation rate and strength, and estimate α = 0.135 in human protein-coding sequences, 72% of which is contributed by weakly-adaptive variants. We show that in this adaptation regime α is reduced ≈ 25% by linkage genome-wide. Moreover, we show that virus-interacting proteins (VIPs) undergo adaptation that is both stronger and nearly twice as frequent as the genome average (α = 0.224, 56% due to strongly-beneficial alleles). Our results suggest that while most adaptation in human proteins is weakly-beneficial, adaptation to viruses is often strongly-beneficial. Our method provides a robust framework for estimating adaptation rate and strength across species.

Evolutionary Analysis of Makorin Ring Finger Protein 3 Reveals Positive Selection in Mammals

Makorin ring finger proteins (MKRNs) are part the of ubiquitin-proteasome system; a complex system important for cell functions. Ubiquitin fate through proteolytic, non-proteolytic pathways varies, depending on covalent linkage between ubiquitin and protein substrates. Makorin ring finger protein 3 is an integral part of covalent linkage of ubiquitin to protein substrates. Similar to others imprinted genes, MKRN3 also evolve under positive selection; however, which codons are specifically selected in MKRN3 during evolution are needed to be explored. Different maximum-likelihood (ML) codon-based methodologies were used to ascertain positive selection signatures in 22 mammalian sequences of MKRN3 to probe an individual codon for positive selection signatures. By applying the HyPhy software package implemented in the Data Monkey Web Server and CODEML implemented in PAML, evolutionary analysis based on two Ml frameworks were conducted. The analysis was executed by comparing M1a against M2a, M7 against M8, and PAML models and 2∆Lnl (LRT) was resulted by likelihood logs. M1a contributed ω1 (dN/dS) with LRT value (∆Lnl) 12.01, and positive selection was found in M2a with ω3 = 2.23603. To further improve selection test, M8 was compared to M7 with 2∆Lnl (LRT) 30.17, and M8 showed positive selection with ω = 1.55759. The data were fit to M8 than M7, which suggests that M8 was the most significant model of selection. M8 was judged encouraging for this analysis and used to establish a positive selection of MKRN3 proteins. We found Gly312 as a positively selected amino acid in a zinc finger motif/Really Interesting New Gene (RING) finger motif; the former ones’ region is involved in RNA binding and the later ones in ubiquitin ligase activity of the protein, vital for protein function. Selection analyses of MKRNs might advance the developments in unique approaches that could lead to genetic progress over the selection of superior individuals with the breeding values higher for certain traits as ancestries to get the next generation.

Trimeric autotransporter adhesins in Acinetobacter baumannii, coincidental evolution at work

Trimeric autotransporter (TAA), also known as type Vc secretion system, is expressed by many strains of Acinetobacter baumannii, an opportunistic pathogen, which is responsible for nosocomial infections worldwide. TAAs, are modular homotrimeric virulence factors, containing a signal peptide, complex stalk, and conserved membrane anchoring domain. The evolutionary mechanisms underlying the evolvement of these adhesins are not clear. Here, we showed that TAA genes were laterally acquired and underwent gene duplication and recombination. The heterogeneity of TAA nucleotide sequences, GC content, codon usage, and the probability of recombination and duplication events were assessed by MEGA7. Given the heterogeneity of sequences, we used all-against-all BLAST for clustering the TAAs. The pattern of distribution of TAAs are highly scattered; GC content and codon usage for these genes are variable. Multiple events of lateral gene transfer from the early history of Acinetobacter and the occurrence of gene duplication, gene loss, and recombination after acquiring the alien genes may explain the scattered pattern of distribution of TAAs. Additionally, this gene is not present in many clinical isolates of A. baumannii, thus is not a single virulence factor attributing to the infection. The advantage of harboring such genes might be adopting to different environments by developing the biofilm communities. We suggested that TAA genes were laterally acquired in the environmental context and incidentally provided some benefits at the infection site. Thus, coincidental evolution theory may be better suited for describing the evolution of TAA genes in A. baumannii genomes.

Codon Usage Bias in Animals: Disentangling the Effects of Natural Selection, Effective Population Size, and GC-Biased Gene Conversion

Selection on codon usage bias is well documented in a number of microorganisms. Whether codon usage is also generally shaped by natural selection in large organisms, despite their relatively small effective population size (Ne), is unclear. In animals, the population genetics of codon usage bias has only been studied in a handful of model organisms so far, and can be affected by confounding, nonadaptive processes such as GC-biased gene conversion and experimental artefacts. Using population transcriptomics data, we analyzed the relationship between codon usage, gene expression, allele frequency distribution, and recombination rate in 30 nonmodel species of animals, each from a different family, covering a wide range of effective population sizes. We disentangled the effects of translational selection and GC-biased gene conversion on codon usage by separately analyzing GC-conservative and GC-changing mutations. We report evidence for effective translational selection on codon usage in large-Ne species of animals, but not in small-Ne ones, in agreement with the nearly neutral theory of molecular evolution. C- and T-ending codons tend to be preferred over synonymous G- and A-ending ones, for reasons that remain to be determined. In contrast, we uncovered a conspicuous effect of GC-biased gene conversion, which is widespread in animals and the main force determining the fate of AT↔GC mutations. Intriguingly, the strength of its effect was uncorrelated with Ne.

Influence of Recombination and GC-biased Gene Conversion on the Adaptive and Nonadaptive Substitution Rate in Mammals versus Birds

Recombination is expected to affect functional sequence evolution in several ways. On the one hand, recombination is thought to improve the efficiency of multilocus selection by dissipating linkage disequilibrium. On the other hand, natural selection can be counteracted by recombination-associated transmission distorters such as GC-biased gene conversion (gBGC), which tends to promote G and C alleles irrespective of their fitness effect in high-recombining regions. It has been suggested that gBGC might impact coding sequence evolution in vertebrates, and particularly the ratio of nonsynonymous to synonymous substitution rates (dN/dS). However, distinctive gBGC patterns have been reported in mammals and birds, maybe reflecting the documented contrasts in evolutionary dynamics of recombination rate between these two taxa. Here, we explore how recombination and gBGC affect coding sequence evolution in mammals and birds by analyzing proteome-wide data in six species of Galloanserae (fowls) and six species of catarrhine primates. We estimated the dN/dS ratio and rates of adaptive and nonadaptive evolution in bins of genes of increasing recombination rate, separately analyzing AT → GC, GC → AT, and G ↔ C/A ↔ T mutations. We show that in both taxa, recombination and gBGC entail a decrease in dN/dS. Our analysis indicates that recombination enhances the efficiency of purifying selection by lowering Hill-Robertson effects, whereas gBGC leads to an overestimation of the adaptive rate of AT → GC mutations. Finally, we report a mutagenic effect of recombination, which is independent of gBGC.

GC-biased gene conversion conceals the prediction of the nearly neutral theory in avian genomes

BACKGROUND

The nearly neutral theory of molecular evolution predicts that the efficacy of natural selection increases with the effective population size. This prediction has been verified by independent observations in diverse taxa, which show that life-history traits are strongly correlated with measures of the efficacy of selection, such as the dN/dS ratio. Surprisingly, avian taxa are an exception to this theory because correlations between life-history traits and dN/dS are apparently absent. Here we explore the role of GC-biased gene conversion on estimates of substitution rates as a potential driver of these unexpected observations.

RESULTS

We analyze the relationship between dN/dS estimated from alignments of 47 avian genomes and several proxies for effective population size. To distinguish the impact of GC-biased gene conversion from selection, we use an approach that accounts for non-stationary base composition and estimate dN/dS separately for changes affected or unaffected by GC-biased gene conversion. This analysis shows that the impact of GC-biased gene conversion on substitution rates can explain the lack of correlations between life-history traits and dN/dS. Strong correlations between life-history traits and dN/dS are recovered after accounting for GC-biased gene conversion. The correlations are robust to variation in base composition and genomic location.

CONCLUSIONS

Our study shows that gene sequence evolution across a wide range of avian lineages meets the prediction of the nearly neutral theory, the efficacy of selection increases with effective population size. Moreover, our study illustrates that accounting for GC-biased gene conversion is important to correctly estimate the strength of selection.

Selection Acting on Genomes

Populations evolve as mutations arise in individual organisms and, through hereditary transmission, may become "fixed" (shared by all individuals) in the population. Most mutations are lethal or have negative fitness consequences for the organism. Others have essentially no effect on organismal fitness and can become fixed through the neutral stochastic process known as random drift. However, mutations may also produce a selective advantage that boosts their chances of reaching fixation. Regions of genomes where new mutations are beneficial, rather than neutral or deleterious, tend to evolve more rapidly due to positive selection. Genes involved in immunity and defense are a well-known example; rapid evolution in these genes presumably occurs because new mutations help organisms to prevail in evolutionary "arms races" with pathogens. In recent years genome-wide scans for selection have enlarged our understanding of the genome evolution of various species. In this chapter, we will focus on methods to detect selection on the genome. In particular, we will discuss probabilistic models and how they have changed with the advent of new genome-wide data now available.

Determinants of the Efficacy of Natural Selection on Coding and Noncoding Variability in Two Passerine Species

Population genetic theory predicts that selection should be more effective when the effective population size (N_e) is larger, and that the efficacy of selection should correlate positively with recombination rate. Here, we analyzed the genomes of ten great tits and ten zebra finches. Nucleotide diversity at 4-fold degenerate sites indicates that zebra finches have a 2.83-fold larger N_e. We obtained clear evidence that purifying selection is more effective in zebra finches. The proportion of substitutions at 0-fold degenerate sites fixed by positive selection (α) is high in both species (great tit 48%; zebra finch 64%) and is significantly higher in zebra finches. When α was estimated on GC-conservative changes (i.e., between A and T and between G and C), the estimates reduced in both species (great tit 22%; zebra finch 53%). A theoretical model presented herein suggests that failing to control for the effects of GC-biased gene conversion (gBGC) is potentially a contributor to the overestimation of α, and that this effect cannot be alleviated by first fitting a demographic model to neutral variants. We present the first estimates in birds for α in the untranslated regions, and found evidence for substantial adaptive changes. Finally, although purifying selection is stronger in high-recombination regions, we obtained mixed evidence for α increasing with recombination rate, especially after accounting for gBGC. These results highlight that it is important to consider the potential confounding effects of gBGC when quantifying selection and that our understanding of what determines the efficacy of selection is incomplete.

Background selection and biased gene conversion affect more than 95% of the human genome and bias demographic inferences

Disentangling the effect on genomic diversity of natural selection from that of demography is notoriously difficult, but necessary to properly reconstruct the history of species. Here, we use high-quality human genomic data to show that purifying selection at linked sites (i.e. background selection, BGS) and GC-biased gene conversion (gBGC) together affect as much as 95% of the variants of our genome. We find that the magnitude and relative importance of BGS and gBGC are largely determined by variation in recombination rate and base composition. Importantly, synonymous sites and non-transcribed regions are also affected, albeit to different degrees. Their use for demographic inference can lead to strong biases. However, by conditioning on genomic regions with recombination rates above 1.5 cM/Mb and mutation types (C↔G, A↔T), we identify a set of SNPs that is mostly unaffected by BGS or gBGC, and that avoids these biases in the reconstruction of human history.

Adaptive Landscape of Protein Variation in Human Exomes

The human genome contains hundreds of thousands of missense mutations. However, only a handful of these variants are known to be adaptive, which implies that adaptation through protein sequence change is an extremely rare phenomenon in human evolution. Alternatively, existing methods may lack the power to pinpoint adaptive variation. We have developed and applied an Evolutionary Probability Approach (EPA) to discover candidate adaptive polymorphisms (CAPs) through the discordance between allelic evolutionary probabilities and their observed frequencies in human populations. EPA reveals thousands of missense CAPs, which suggest that a large number of previously optimal alleles experienced a reversal of fortune in the human lineage. We explored nonadaptive mechanisms to explain CAPs, including the effects of demography, mutation rate variability, and negative and positive selective pressures in modern humans. Many nonadaptive hypotheses were tested, but failed to explain the data, which suggests that a large proportion of CAP alleles have increased in frequency due to beneficial selection. This suggestion is supported by the fact that a vast majority of adaptive missense variants discovered previously in humans are CAPs, and hundreds of CAP alleles are protective in genotype-phenotype association data. Our integrated phylogenomic and population genetic EPA approach predicts the existence of thousands of nonneutral candidate variants in the human proteome. We expect this collection to be enriched in beneficial variation. The EPA approach can be applied to discover candidate adaptive variation in any protein, population, or species for which allele frequency data and reliable multispecies alignments are available.

Faster-X evolution: Theory and evidence from Drosophila

A faster rate of adaptive evolution of X-linked genes compared with autosomal genes can be caused by the fixation of recessive or partially recessive advantageous mutations, due to the full expression of X-linked mutations in hemizygous males. Other processes, including recombination rate and mutation rate differences between X chromosomes and autosomes, may also cause faster evolution of X-linked genes. We review population genetics theory concerning the expected relative values of variability and rates of evolution of X-linked and autosomal DNA sequences. The theoretical predictions are compared with data from population genomic studies of several species of Drosophila. We conclude that there is evidence for adaptive faster-X evolution of several classes of functionally significant nucleotides. We also find evidence for potential differences in mutation rates between X-linked and autosomal genes, due to differences in mutational bias towards GC to AT mutations. Many aspects of the data are consistent with the male hemizygosity model, although not all possible confounding factors can be excluded.

Codon usage and codon pair patterns in non-grass monocot genomes

BACKGROUND AND AIMS

Studies on codon usage in monocots have focused on grasses, and observed patterns of this taxon were generalized to all monocot species. Here, non-grass monocot species were analysed to investigate the differences between grass and non-grass monocots.

METHODS

First, studies of codon usage in monocots were reviewed. The current information was then extended regarding codon usage, as well as codon-pair context bias, using four completely sequenced non-grass monocot genomes (Musa acuminata, Musa balbisiana, Phoenix dactylifera and Spirodela polyrhiza) for which comparable transcriptome datasets are available. Measurements were taken regarding relative synonymous codon usage, effective number of codons, derived optimal codon and GC content and then the relationships investigated to infer the underlying evolutionary forces.

KEY RESULTS

The research identified optimal codons, rare codons and preferred codon-pair context in the non-grass monocot species studied. In contrast to the bimodal distribution of GC3 (GC content in third codon position) in grasses, non-grass monocots showed a unimodal distribution. Disproportionate use of G and C (and of A and T) in two- and four-codon amino acids detected in the analysis rules out the mutational bias hypothesis as an explanation of genomic variation in GC content. There was found to be a positive relationship between CAI (codon adaptation index; predicts the level of expression of a gene) and GC3. In addition, a strong correlation was observed between coding and genomic GC content and negative correlation of GC3 with gene length, indicating a strong impact of GC-biased gene conversion (gBGC) in shaping codon usage and nucleotide composition in non-grass monocots.

CONCLUSION

Optimal codons in these non-grass monocots show a preference for G/C in the third codon position. These results support the concept that codon usage and nucleotide composition in non-grass monocots are mainly driven by gBGC.

Genome-scale detection of positive selection in nine primates predicts human-virus evolutionary conflicts

Hotspots of rapid genome evolution hold clues about human adaptation. We present a comparative analysis of nine whole-genome sequenced primates to identify high-confidence targets of positive selection. We find strong statistical evidence for positive selection in 331 protein-coding genes (3%), pinpointing 934 adaptively evolving codons (0.014%). Our new procedure is stringent and reveals substantial artefacts (20% of initial predictions) that have inflated previous estimates. The final 331 positively selected genes (PSG) are strongly enriched for innate and adaptive immunity, secreted and cell membrane proteins (e.g. pattern recognition, complement, cytokines, immune receptors, MHC, Siglecs). We also find evidence for positive selection in reproduction and chromosome segregation (e.g. centromere-associated CENPO, CENPT), apolipoproteins, smell/taste receptors and mitochondrial proteins. Focusing on the virus–host interaction, we retrieve most evolutionary conflicts known to influence antiviral activity (e.g. TRIM5, MAVS, SAMHD1, tetherin) and predict 70 novel cases through integration with virus–human interaction data. Protein structure analysis further identifies positive selection in the interaction interfaces between viruses and their cellular receptors (CD4-HIV; CD46-measles, adenoviruses; CD55-picornaviruses). Finally, primate PSG consistently show high sequence variation in human exomes, suggesting ongoing evolution. Our curated dataset of positive selection is a rich source for studying the genetics underlying human (antiviral) phenotypes. Procedures and data are available at https://github.com/robinvanderlee/positive-selection.

Detection of Pathways Affected by Positive Selection in Primate Lineages Ancestral to Humans

Gene set enrichment approaches have been increasingly successful in finding signals of recent polygenic selection in the human genome. In this study, we aim at detecting biological pathways affected by positive selection in more ancient human evolutionary history. Focusing on four branches of the primate tree that lead to modern humans, we tested all available protein coding gene trees of the Primates clade for signals of adaptation in these branches, using the likelihood-based branch site test of positive selection. The results of these locus-specific tests were then used as input for a gene set enrichment test, where whole pathways are globally scored for a signal of positive selection, instead of focusing only on outlier "significant" genes. We identified signals of positive selection in several pathways that are mainly involved in immune response, sensory perception, metabolism, and energy production. These pathway-level results are highly significant, even though there is no functional enrichment when only focusing on top scoring genes. Interestingly, several gene sets are found significant at multiple levels in the phylogeny, but different genes are responsible for the selection signal in the different branches. This suggests that the same function has been optimized in different ways at different times in primate evolution.

Maximum-likelihood approaches reveal signatures of positive selection in BMP15 and GDF9 genes modulating ovarian function in mammalian female fertility

Bone morphogenetic proteins (BMPs) and the growth factors (GDFs) play an important role in ovarian folliculogenesis and essential regulator of processes of numerous granulosa cells. BMP15 gene variations linked to various ovarian phenotypic consequences subject to the species, from infertility to improved prolificacy in sheep, primary ovarian insufficiency in women or associated with minor subfertility in mouse. To study the evolving role of BMP15 and GDF9, a phylogenetic analysis was performed. To find out the candidate gene associated with prolificacy in mammals, the nucleotide sequence of BMP15 and GDF9 genes was recognized under positive selection in various mammalian species. Maximum‐likelihood approaches used on BMP15 and GDF9 genes exhibited a robust divergence and a prompted evolution as compared to other TGFβ family members. Furthermore, among 32 mammalian species, we identified positive selection signals in the hominidae clade resulting to 132D, 147E, 163Y, 191W, and 236P codon sites of BMP15 and 162F, 188K, 206R, 240A, 244L, 246H, 248S, 251D, 253L, 254F and other codon sites of GDF9. The positively selected amino acid sites such as Alanine, Lucien, Arginine, and lysine are important for signaling. In conclusion, this study evidences that GDF9 and BMP15 genes have rapid evolution than other TGFß family members and was subjected to positive selection in the mammalian clade. Selected sites under the positive selection are of remarkable significance for the particular functioning of the protein and consequently for female fertility.

Genome sequence of a diabetes-prone rodent reveals a mutation hotspot around the ParaHox gene cluster

The sand rat Psammomys obesus is a gerbil species native to deserts of North Africa and the Middle East, and is constrained in its ecology because high carbohydrate diets induce obesity and type II diabetes that, in extreme cases, can lead to pancreatic failure and death. We report the sequencing of the sand rat genome and discovery of an unusual, extensive, and mutationally biased GC-rich genomic domain. This highly divergent genomic region encompasses several functionally essential genes, and spans the ParaHox cluster which includes the insulin-regulating homeobox gene Pdx1. The sequence of sand rat Pdx1 has been grossly affected by GC-biased mutation, leading to the highest divergence observed for this gene across the Bilateria. In addition to genomic insights into restricted caloric intake in a desert species, the discovery of a localized chromosomal region subject to elevated mutation suggests that mutational heterogeneity within genomes could influence the course of evolution.

Evolutionary forces affecting synonymous variations in plant genomes

Base composition is highly variable among and within plant genomes, especially at third codon positions, ranging from GC-poor and homogeneous species to GC-rich and highly heterogeneous ones (particularly Monocots). Consequently, synonymous codon usage is biased in most species, even when base composition is relatively homogeneous. The causes of these variations are still under debate, with three main forces being possibly involved: mutational bias, selection and GC-biased gene conversion (gBGC). So far, both selection and gBGC have been detected in some species but how their relative strength varies among and within species remains unclear. Population genetics approaches allow to jointly estimating the intensity of selection, gBGC and mutational bias. We extended a recently developed method and applied it to a large population genomic dataset based on transcriptome sequencing of 11 angiosperm species spread across the phylogeny. We found that at synonymous positions, base composition is far from mutation-drift equilibrium in most genomes and that gBGC is a widespread and stronger process than selection. gBGC could strongly contribute to base composition variation among plant species, implying that it should be taken into account in plant genome analyses, especially for GC-rich ones.

In protein coding genes, base composition strongly varies within and among plant genomes, especially at positions where changes do not alter the coded protein (synonymous variations). Some species, such as the model plant Arabidopsis thaliana, are relatively GC-poor and homogeneous while others, such as grasses, are highly heterogeneous and GC-rich. The causes of these variations are still debated: are they mainly due to selective or neutral processes? Answering to this question is important to correctly infer whether variations in base composition may have functional roles or not. We extended a population genetics method to jointly estimate the different forces that may affect synonymous variations and applied it to genomic datasets in 11 flowering plant species. We found that GC-biased gene conversion, a neutral process associated with recombination that mimics selection by favouring G and C bases, is a widespread and stronger process than selection and that it could explain the large variation in base composition observed in plant genomes. Our results bear implications for analysing plant genomes and for correctly interpreting what could be functional or not.

Analytical Biases Associated with GC-Content in Molecular Evolution

Molecular evolution is being revolutionized by high-throughput sequencing allowing an increased amount of genome-wide data available for multiple species. While base composition summarized by GC-content is one of the first metrics measured in genomes, its genomic distribution is a frequently neglected feature in downstream analyses based on DNA sequence comparisons. Here, we show how base composition heterogeneity among loci and taxa can bias common molecular evolution analyses such as phylogenetic tree reconstruction, detection of natural selection and estimation of codon usage. We then discuss the biological, technical and methodological causes of these GC-associated biases and suggest approaches to overcome them.

SENCA: A Multilayered Codon Model to Study the Origins and Dynamics of Codon Usage

Gene sequences are the target of evolution operating at different levels, including the nucleotide, codon, and amino acid levels. Disentangling the impact of those different levels on gene sequences requires developing a probabilistic model with three layers. Here we present SENCA (site evolution of nucleotides, codons, and amino acids), a codon substitution model that separately describes 1) nucleotide processes which apply on all sites of a sequence such as the mutational bias, 2) preferences between synonymous codons, and 3) preferences among amino acids. We argue that most synonymous substitutions are not neutral and that SENCA provides more accurate estimates of selection compared with more classical codon sequence models. We study the forces that drive the genomic content evolution, intraspecifically in the core genome of 21 prokaryotes and interspecifically for five Enterobacteria. We retrieve the existence of a universal mutational bias toward AT, and that taking into account selection on synonymous codon usage has consequences on the measurement of selection on nonsynonymous substitutions. We also confirm that codon usage bias is mostly driven by selection on preferred codons. We propose new summary statistics to measure the relative importance of the different evolutionary processes acting on sequences.