Selectome update: quality control and computational improvements to a database of positive selection

Responses to predation pressure involve similar sets of genes in two divergent species of Daphnia

Species that are not closely related can express similar inducible traits, but molecular mechanisms underlying the observed responses are often unknown, nor is it known if these mechanisms are shared between such species. Here, we compared transcriptional profiles of two Daphnia species (D. mitsukuri and D. sinensis) from different subgenera, at both juvenile and adult developmental stages. Both species were exposed to the same predation threat (fish kairomones), and both showed similar induced morphological changes (reduced body length). At the early developmental stage, response to predation risk resulted in similar changes in expression levels of 23 orthologues in both species. These orthologues, involved in 107 GO categories, changed in the same direction in both species (over- or underexpressed), in comparison to non-exposed controls. Several of these orthologues were associated with DNA replication, structural constituents of cuticle or innate immune response. In both species, the differentially expressed (DE) genes on average had higher ω (dN /dS ) values than non-DE genes, suggesting that these genes had experienced greater positive selection or lower purifying selection than non-DE genes. Overall, our results suggest that similar suites of genes, responding in similar ways to predation pressure, have been retained in Daphnia for many millions of years.

Harmonized cross-species cell atlases of trigeminal and dorsal root ganglia

Peripheral sensory neurons in the dorsal root ganglion (DRG) and trigeminal ganglion (TG) are specialized to detect and transduce diverse environmental stimuli including touch, temperature, and pain to the central nervous system. Recent advances in single-cell RNA-sequencing (scRNA-seq) have provided new insights into the diversity of sensory ganglia cell types in rodents, non-human primates, and humans, but it remains difficult to compare transcriptomically defined cell types across studies and species. Here, we built cross-species harmonized atlases of DRG and TG cell types that describe 18 neuronal and 11 non-neuronal cell types across 6 species and 19 studies. We then demonstrate the utility of this harmonized reference atlas by using it to annotate newly profiled DRG nuclei/cells from both human and the highly regenerative axolotl. We observe that the transcriptomic profiles of sensory neuron subtypes are broadly similar across vertebrates, but the expression of functionally important neuropeptides and channels can vary notably. The new resources and data presented here can guide future studies in comparative transcriptomics, simplify cell type nomenclature differences across studies, and help prioritize targets for future pain therapy development.

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.

Phospholipid Scramblase 4 (PLSCR4) Regulates Adipocyte Differentiation via PIP3-Mediated AKT Activation

Phospholipid scramblase 4 (PLSCR4) is a member of a conserved enzyme family with high relevance for the remodeling of phospholipid distribution in the plasma membrane and the regulation of cellular signaling. While PLSCR1 and -3 are involved in the regulation of adipose-tissue expansion, the role of PLSCR4 is so far unknown. PLSCR4 is significantly downregulated in an adipose-progenitor-cell model of deficiency for phosphatase and tensin homolog (PTEN). PTEN acts as a tumor suppressor and antagonist of the growth and survival signaling phosphoinositide 3-kinase (PI3K)/AKT cascade by dephosphorylating phosphatidylinositol-3,4,5-trisphosphate (PIP3). Patients with PTEN germline deletion frequently develop lipomas. The underlying mechanism for this aberrant adipose-tissue growth is incompletely understood. PLSCR4 is most highly expressed in human adipose tissue, compared with other phospholipid scramblases, suggesting a specific role of PLSCR4 in adipose-tissue biology. In cell and mouse models of lipid accumulation, we found PLSCR4 to be downregulated. We observed increased adipogenesis in PLSCR4-knockdown adipose progenitor cells, while PLSCR4 overexpression attenuated lipid accumulation. PLSCR4 knockdown was associated with increased PIP3 levels and the activation of AKT. Our results indicated that PLSCR4 is a regulator of PI3K/AKT signaling and adipogenesis and may play a role in PTEN-associated adipose-tissue overgrowth and lipoma formation.

Convergent consequences of parthenogenesis on stick insect genomes

The shift from sexual reproduction to parthenogenesis has occurred repeatedly in animals, but how the loss of sex affects genome evolution remains poorly understood. We generated reference genomes for five independently evolved parthenogenetic species in the stick insect genus Timema and their closest sexual relatives. Using these references and population genomic data, we show that parthenogenesis results in an extreme reduction of heterozygosity and often leads to genetically uniform populations. We also find evidence for less effective positive selection in parthenogenetic species, suggesting that sex is ubiquitous in natural populations because it facilitates fast rates of adaptation. Parthenogenetic species did not show increased transposable element (TE) accumulation, likely because there is little TE activity in the genus. By using replicated sexual-parthenogenetic comparisons, our study reveals how the absence of sex affects genome evolution in natural populations, providing empirical support for the negative consequences of parthenogenesis as predicted by theory.

Relative model selection of evolutionary substitution models can be sensitive to multiple sequence alignment uncertainty

BACKGROUND

Multiple sequence alignments (MSAs) represent the fundamental unit of data inputted to most comparative sequence analyses. In phylogenetic analyses in particular, errors in MSA construction have the potential to induce further errors in downstream analyses such as phylogenetic reconstruction itself, ancestral state reconstruction, and divergence time estimation. In addition to providing phylogenetic methods with an MSA to analyze, researchers must also specify a suitable evolutionary model for the given analysis. Most commonly, researchers apply relative model selection to select a model from candidate set and then provide both the MSA and the selected model as input to subsequent analyses. While the influence of MSA errors has been explored for most stages of phylogenetics pipelines, the potential effects of MSA uncertainty on the relative model selection procedure itself have not been explored.

RESULTS

We assessed the consistency of relative model selection when presented with multiple perturbed versions of a given MSA. We find that while relative model selection is mostly robust to MSA uncertainty, in a substantial proportion of circumstances, relative model selection identifies distinct best-fitting models from different MSAs created from the same set of sequences. We find that this issue is more pervasive for nucleotide data compared to amino-acid data. However, we also find that it is challenging to predict whether relative model selection will be robust or sensitive to uncertainty in a given MSA.

CONCLUSIONS

We find that that MSA uncertainty can affect virtually all steps of phylogenetic analysis pipelines to a greater extent than has previously been recognized, including relative model selection.

Comparable Number of Genes Having Experienced Positive Selection among Great Ape Species

Simple Summary

It is of great interest to quantify adaptive evolution in human lineage by studying genes under positive selection, since these genes could reveal insights into our own adaptive evolutionary history compared to our closely related species and often these genes are functionally important. We used the great apes as the subjects to detect gene-level adaptive evolution signals in all the great ape lineages and investigated the evolutionary patterns and functional relevance of these adaptive evolution signals. Even the differences in population size among these closely related great apes have resulted in differences in their ability to remove deleterious alleles and to adapt to changing environments, we found that they experienced comparable numbers of positive selection. Notably, we identified several genes that offer insights into great ape and human evolution. For example, SOD1, a gene associated with aging in humans, experienced positive selection in the common ancestor of the great ape and this positive selection may contribute to the aging evolution in great apes. Overall, an updated list of positively selected genes reported by this study not only informs us of adaptive evolution during great ape evolution, but is also helpful to the further study of non-human primate models for disease and other fields.

Abstract

Alleles that cause advantageous phenotypes with positive selection contribute to adaptive evolution. Investigations of positive selection in protein-coding genes rely on the accuracy of orthology, models, the quality of assemblies, and alignment. Here, based on the latest genome assemblies and gene annotations, we present a comparative analysis on positive selection in four great ape species and identify 211 high-confidence positively selected genes (PSGs). Even the differences in population size among these closely related great apes have resulted in differences in their ability to remove deleterious alleles and to adapt to changing environments, we found that they experienced comparable numbers of positive selection. We also uncovered that more than half of multigene families exhibited signals of positive selection, suggesting that imbalanced positive selection resulted in the functional divergence of duplicates. Moreover, at the expression level, although positive selection led to a more non-uniform pattern across tissues, the correlation between positive selection and expression patterns is diverse. Overall, this updated list of PSGs is of great significance for the further study of the phenotypic evolution in great apes.

The Evolutionary History of Vertebrate Adhesion GPCRs and Its Implication on Their Classification

Adhesion G protein-coupled receptors (aGPCRs) form a structurally separate class of GPCRs with an unresolved evolutionary history and classification. Based on phylogenetic relations of human aGPCRs, nine families (A-G, L, V) were distinguished. Taking advantage of available genome data, we determined the aGPCR repertoires in all vertebrate classes. Although most aGPCR families show a high numerical stability in vertebrate genomes, the full repertoire of family E, F, and G members appeared only after the fish-tetrapod split. We did not find any evidence for new aGPCR families in vertebrates which are not present in the human genome. Based on ortholog sequence alignments, selection analysis clearly indicated two types of tetrapod aGPCRs: (i) aGPCR under strong purifying selection in tetrapod evolution (families A, B, D, L, V); and (ii) aGPCR with signatures of positive selection in some tetrapod linages (families C, E, G, F). The alignments of aGPCRs also allowed for a revised definition of reference positions within the seven-transmembrane-helix domain (relative position numbering scheme). Based on our phylogenetic cluster analysis, we suggest a revised nomenclature of aGPCRs including their transcript variants. Herein, the former families E and L are combined to one family (L) and GPR128/ADGRG7 forms a separate family (E). Furthermore, our analyses provide valuable information about the (patho)physiological relevance of individual aGPCR members.

ModelTeller: Model Selection for Optimal Phylogenetic Reconstruction Using Machine Learning

Statistical criteria have long been the standard for selecting the best model for phylogenetic reconstruction and downstream statistical inference. Although model selection is regarded as a fundamental step in phylogenetics, existing methods for this task consume computational resources for long processing time, they are not always feasible, and sometimes depend on preliminary assumptions which do not hold for sequence data. Moreover, although these methods are dedicated to revealing the processes that underlie the sequence data, they do not always produce the most accurate trees. Notably, phylogeny reconstruction consists of two related tasks, topology reconstruction and branch-length estimation. It was previously shown that in many cases the most complex model, GTR+I+G, leads to topologies that are as accurate as using existing model selection criteria, but overestimates branch lengths. Here, we present ModelTeller, a computational methodology for phylogenetic model selection, devised within the machine-learning framework, optimized to predict the most accurate nucleotide substitution model for branch-length estimation. We demonstrate that ModelTeller leads to more accurate branch-length inference than current model selection criteria on data sets simulated under realistic processes. ModelTeller relies on a readily implemented machine-learning model and thus the prediction according to features extracted from the sequence data results in a substantial decrease in running time compared with existing strategies. By harnessing the machine-learning framework, we distinguish between features that mostly contribute to branch-length optimization, concerning the extent of sequence divergence, and features that are related to estimates of the model parameters that are important for the selection made by current criteria.

Synonymous Site-to-Site Substitution Rate Variation Dramatically Inflates False Positive Rates of Selection Analyses: Ignore at Your Own Peril

Most molecular evolutionary studies of natural selection maintain the decades-old assumption that synonymous substitution rate variation (SRV) across sites within genes occurs at levels that are either nonexistent or negligible. However, numerous studies challenge this assumption from a biological perspective and show that SRV is comparable in magnitude to that of nonsynonymous substitution rate variation. We evaluated the impact of this assumption on methods for inferring selection at the molecular level by incorporating SRV into an existing method (BUSTED) for detecting signatures of episodic diversifying selection in genes. Using simulated data we found that failing to account for even moderate levels of SRV in selection testing is likely to produce intolerably high false positive rates. To evaluate the effect of the SRV assumption on actual inferences we compared results of tests with and without the assumption in an empirical analysis of over 13,000 Euteleostomi (bony vertebrate) gene alignments from the Selectome database. This exercise reveals that close to 50% of positive results (i.e., evidence for selection) in empirical analyses disappear when SRV is modeled as part of the statistical analysis and are thus candidates for being false positives. The results from this work add to a growing literature establishing that tests of selection are much more sensitive to certain model assumptions than previously believed.

Harnessing machine learning to guide phylogenetic-tree search algorithms

Inferring a phylogenetic tree is a fundamental challenge in evolutionary studies. Current paradigms for phylogenetic tree reconstruction rely on performing costly likelihood optimizations. With the aim of making tree inference feasible for problems involving more than a handful of sequences, inference under the maximum-likelihood paradigm integrates heuristic approaches to evaluate only a subset of all potential trees. Consequently, existing methods suffer from the known tradeoff between accuracy and running time. In this proof-of-concept study, we train a machine-learning algorithm over an extensive cohort of empirical data to predict the neighboring trees that increase the likelihood, without actually computing their likelihood. This provides means to safely discard a large set of the search space, thus potentially accelerating heuristic tree searches without losing accuracy. Our analyses suggest that machine learning can guide tree-search methodologies towards the most promising candidate trees.

Extra base hits: Widespread empirical support for instantaneous multiple-nucleotide changes

Despite many attempts to introduce evolutionary models that permit substitutions to instantly alter more than one nucleotide in a codon, the prevailing wisdom remains that such changes are rare and generally negligible or are reflective of non-biological artifacts, such as alignment errors. Codon models continue to posit that only single nucleotide change have non-zero rates. Here, we develop and test a simple hierarchy of codon-substitution models with non-zero evolutionary rates for only one-nucleotide (1H), one- and two-nucleotide (2H), or any (3H) codon substitutions. Using over 42, 000 empirical alignments, we find widespread statistical support for multiple hits: 61% of alignments prefer models with 2H allowed, and 23%-with 3H allowed. Analyses of simulated data suggest that these results are not likely to be due to simple artifacts such as model misspecification or alignment errors. Further modeling reveals that synonymous codon island jumping among codons encoding serine, especially along short branches, contributes significantly to this 3H signal. While serine codons were prominently involved in multiple-hit substitutions, there were other common exchanges contributing to better model fit. It appears that a small subset of sites in most alignments have unusual evolutionary dynamics not well explained by existing model formalisms, and that commonly estimated quantities, such as dN/dS ratios may be biased by model misspecification. Our findings highlight the need for continued evaluation of assumptions underlying workhorse evolutionary models and subsequent evolutionary inference techniques. We provide a software implementation for evolutionary biologists to assess the potential impact of extra base hits in their data in the HyPhy package and in the Datamonkey.org server.

Gene Duplication and Gain in the Trematode Atriophallophorus winterbourni Contributes to Adaptation to Parasitism

Gene duplications and novel genes have been shown to play a major role in helminth adaptation to a parasitic lifestyle because they provide the novelty necessary for adaptation to a changing environment, such as living in multiple hosts. Here we present the de novo sequenced and annotated genome of the parasitic trematode Atriophallophorus winterbourni and its comparative genomic analysis to other major parasitic trematodes. First, we reconstructed the species phylogeny, and dated the split of A. winterbourni from the Opisthorchiata suborder to approximately 237.4 Ma (±120.4 Myr). We then addressed the question of which expanded gene families and gained genes are potentially involved in adaptation to parasitism. To do this, we used hierarchical orthologous groups to reconstruct three ancestral genomes on the phylogeny leading to A. winterbourni and performed a GO (Gene Ontology) enrichment analysis of the gene composition of each ancestral genome, allowing us to characterize the subsequent genomic changes. Out of the 11,499 genes in the A. winterbourni genome, as much as 24% have arisen through duplication events since the speciation of A. winterbourni from the Opisthorchiata, and as much as 31.9% appear to be novel, that is, newly acquired. We found 13 gene families in A. winterbourni to have had more than ten genes arising through these recent duplications; all of which have functions potentially relating to host behavioral manipulation, host tissue penetration, and hiding from host immunity through antigen presentation. We identified several families with genes evolving under positive selection. Our results provide a valuable resource for future studies on the genomic basis of adaptation to parasitism and point to specific candidate genes putatively involved in antagonistic host-parasite adaptation.

Directional divergence of Ep300 duplicates in teleosts and its implications

Background

EP300 is a conserved protein in vertebrates, which serves as a key mediator of cellular homeostasis. Mutations and dysregulation of EP300 give rise to severe human developmental disorders and malignancy. Danio rerio is a promising model organism to study EP300 related diseases and drugs; however, the effect of EP300 duplicates derived from teleost-specific whole genome duplication should not just be neglected.

Results

In this study, we obtained EP300 protein sequences of representative teleosts, mammals and sauropsids, with which we inferred a highly supported maximum likelihood tree. We observed that Ep300 duplicates (Ep300a and Ep300b) were widely retained in teleosts and universally expressed in a variety of tissues. Consensus sequences of Ep300a and Ep300b had exactly the same distribution of conserved domains, suggesting that their functions should still be largely overlapped. We analyzed the molecular evolution of Ep300 duplicates in teleosts, using branch-site models, clade models and site models. The results showed that both duplicates were subject to strong positive selection; however, for an extant species, generally at most one copy was under positive selection. At the clade level, there were evident positive correlations between evolutionary rates, the number of positively selected sites and gene expression levels. In Ostariophysi, Ep300a were under stronger positive selection than Ep300b; in Neoteleostei, another species-rich teleost clade, the contrary was the case. We also modeled 3D structures of zf-TAZ domain and its flanking regions of Ep300a and Ep300b of D. rerio and Oryzias latipes and found that in either species the faster evolving copy had more short helixes.

Conclusions

Collectively, the two copies of Ep300 have undoubtedly experienced directional divergence in main teleost clades. The divergence of EP300 between teleosts and mammals should be greater than the divergence between different teleost clades. Further studies are needed to clarify to what extent the EP300 involved regulatory network has diverged between teleosts and mammals, which would also help explain the huge success of teleosts.

Ancient Evolutionary Origin of Intrinsically Disordered Cancer Risk Regions

Cancer is a heterogeneous genetic disease that alters the proper functioning of proteins involved in key regulatory processes such as cell cycle, DNA repair, survival, or apoptosis. Mutations often accumulate in hot-spots regions, highlighting critical functional modules within these proteins that need to be altered, amplified, or abolished for tumor formation. Recent evidence suggests that these mutational hotspots can correspond not only to globular domains, but also to intrinsically disordered regions (IDRs), which play a significant role in a subset of cancer types. IDRs have distinct functional properties that originate from their inherent flexibility. Generally, they correspond to more recent evolutionary inventions and show larger sequence variations across species. In this work, we analyzed the evolutionary origin of disordered regions that are specifically targeted in cancer. Surprisingly, the majority of these disordered cancer risk regions showed remarkable conservation with ancient evolutionary origin, stemming from the earliest multicellular animals or even beyond. Nevertheless, we encountered several examples where the mutated region emerged at a later stage compared with the origin of the gene family. We also showed the cancer risk regions become quickly fixated after their emergence, but evolution continues to tinker with their genes with novel regulatory elements introduced even at the level of humans. Our concise analysis provides a much clearer picture of the emergence of key regulatory elements in proteins and highlights the importance of taking into account the modular organisation of proteins for the analyses of evolutionary origin.

CoevDB: a database of intramolecular coevolution among protein-coding genes of the bony vertebrates

The study of molecular coevolution, due to its potential to identify gene regions under functional or structural constraints, has recently been subject to numerous scientific inquiries. Particular efforts have been conducted to develop methods predicting the presence of coevolution in molecular sequences. Among these methods, a few aim to model the underlying evolutionary process of coevolution, which enable to differentiate the shared history of genes to coevolution and thus improve their accuracy. However, the usage of such methods remains sparse due to their expensive computational cost and the lack of resources alleviating this issue. Here we present CoevDB (http://phylodb.unil.ch/CoevDB), a database containing the result of a large-scale analysis of intramolecular coevolution of 8201 protein-coding genes of bony vertebrates. The web interface of CoevDB gives access to the results to 800 millions of statistical tests corresponding to all the pairs of sites analyzed. Several type of queries enable users to explore the database by either targeting specific genes or by discovering genes having promising estimations of coevolution.

Equiprobable discrete models of site-specific substitution rates underestimate the extent of rate variability

It is standard practice to model site-to-site variability of substitution rates by discretizing a continuous distribution into a small number, K, of equiprobable rate categories. We demonstrate that the variance of this discretized distribution has an upper bound determined solely by the choice of K and the mean of the distribution. This bound can introduce biases into statistical inference, especially when estimating parameters governing site-to-site variability of substitution rates. Applications to two large collections of sequence alignments demonstrate that this upper bound is often reached in analyses of real data. When parameter estimation is of primary interest, additional rate categories or more flexible modeling methods should be considered.

Characterizing lineage-specific evolution and the processes driving genomic diversification in chordates

Background

Understanding the origins of genome content has long been a goal of molecular evolution and comparative genomics. By examining genome evolution through the guise of lineage-specific evolution, it is possible to make inferences about the evolutionary events that have given rise to species-specific diversification. Here we characterize the evolutionary trends found in chordate species using The Adaptive Evolution Database (TAED). TAED is a database of phylogenetically indexed gene families designed to detect episodes of directional or diversifying selection across chordates. Gene families within the database have been assessed for lineage-specific estimates of dN/dS and have been reconciled to the chordate species to identify retained duplicates. Gene families have also been mapped to the functional pathways and amino acid changes which occurred on high dN/dS lineages have been mapped to protein structures.

Results

An analysis of this exhaustive database has enabled a characterization of the processes of lineage-specific diversification in chordates. A pathway level enrichment analysis of TAED determined that pathways most commonly found to have elevated rates of evolution included those involved in metabolism, immunity, and cell signaling. An analysis of protein fold presence on proteins, after normalizing for frequency in the database, found common folds such as Rossmann folds, Jelly Roll folds, and TIM barrels were overrepresented on proteins most likely to undergo directional selection. A set of gene families which experience increased numbers of duplications within short evolutionary times are associated with pathways involved in metabolism, olfactory reception, and signaling. An analysis of protein secondary structure indicated more relaxed constraint in β-sheets and stronger constraint on alpha Helices, amidst a general preference for substitutions at exposed sites. Lastly a detailed analysis of the ornithine decarboxylase gene family, a key enzyme in the pathway for polyamine synthesis, revealed lineage-specific evolution along the lineage leading to Cetacea through rapid sequence evolution in a duplicate gene with amino acid substitutions causing active site rearrangement.

Conclusion

Episodes of lineage-specific evolution are frequent throughout chordate species. Both duplication and directional selection have played large roles in the evolution of the phylum. TAED is a powerful tool for facilitating this understanding of lineage-specific evolution.

Molecular footprint of Medawar's mutation accumulation process in mammalian aging

Medawar's mutation accumulation hypothesis explains aging by the declining force of natural selection with age: Slightly deleterious germline mutations expressed in old age can drift to fixation and thereby lead to aging‐related phenotypes. Although widely cited, empirical evidence for this hypothesis has remained limited. Here, we test one of its predictions that genes relatively highly expressed in old adults should be under weaker purifying selection than genes relatively highly expressed in young adults. Combining 66 transcriptome datasets (including 16 tissues from five mammalian species) with sequence conservation estimates across mammals, here we report that the overall conservation level of expressed genes is lower at old age compared to young adulthood. This age‐related decrease in transcriptome conservation (ADICT) is systematically observed in diverse mammalian tissues, including the brain, liver, lung, and artery, but not in others, most notably in the muscle and heart. Where observed, ADICT is driven partly by poorly conserved genes being up‐regulated during aging. In general, the more often a gene is found up‐regulated with age among tissues and species, the lower its evolutionary conservation. Poorly conserved and up‐regulated genes have overlapping functional properties that include responses to age‐associated tissue damage, such as apoptosis and inflammation. Meanwhile, these genes do not appear to be under positive selection. Hence, genes contributing to old age phenotypes are found to harbor an excess of slightly deleterious alleles, at least in certain tissues. This supports the notion that genetic drift shapes aging in multicellular organisms, consistent with Medawar's mutation accumulation hypothesis.

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.

Adaptive Evolution of Animal Proteins over Development: Support for the Darwin Selection Opportunity Hypothesis of Evo-Devo

A driving hypothesis of evolutionary developmental biology is that animal morphological diversity is shaped both by adaptation and by developmental constraints. Here, we have tested Darwin’s “selection opportunity” hypothesis, according to which high evolutionary divergence in late development is due to strong positive selection. We contrasted it to a “developmental constraint” hypothesis, according to which late development is under relaxed negative selection. Indeed, the highest divergence between species, both at the morphological and molecular levels, is observed late in embryogenesis and postembryonically. To distinguish between adaptation and relaxation hypotheses, we investigated the evidence of positive selection on protein-coding genes in relation to their expression over development, in fly Drosophila melanogaster, zebrafish Danio rerio, and mouse Mus musculus. First, we found that genes specifically expressed in late development have stronger signals of positive selection. Second, over the full transcriptome, genes with evidence for positive selection trend to be expressed in late development. Finally, genes involved in pathways with cumulative evidence of positive selection have higher expression in late development. Overall, there is a consistent signal that positive selection mainly affects genes and pathways expressed in late embryonic development and in adult. Our results imply that the evolution of embryogenesis is mostly conservative, with most adaptive evolution affecting some stages of postembryonic gene expression, and thus postembryonic phenotypes. This is consistent with the diversity of environmental challenges to which juveniles and adults are exposed.

Insights into the Genomics of Clownfish Adaptive Radiation: Genetic Basis of the Mutualism with Sea Anemones

Clownfishes are an iconic group of coral reef fishes, especially known for their mutualism with sea anemones. This mutualism is particularly interesting as it likely acted as the key innovation that triggered clownfish adaptive radiation. Indeed, after the acquisition of the mutualism, clownfishes diversified into multiple ecological niches linked with host and habitat use. However, despite the importance of this mutualism, the genetic mechanisms allowing clownfishes to interact with sea anemones are still unclear. Here, we used a comparative genomics and molecular evolutionary analyses to investigate the genetic basis of clownfish mutualism with sea anemones. We assembled and annotated the genome of nine clownfish species and one closely related outgroup. Orthologous genes inferred between these species and additional publicly available teleost genomes resulted in almost 16,000 genes that were tested for positively selected substitutions potentially involved in the adaptation of clownfishes to live in sea anemones. We identified 17 genes with a signal of positive selection at the origin of clownfish radiation. Two of them (Versican core protein and Protein O-GlcNAse) show particularly interesting functions associated with N-acetylated sugars, which are known to be involved in sea anemone discharge of toxins. This study provides the first insights into the genetic mechanisms of clownfish mutualism with sea anemones. Indeed, we identified the first candidate genes likely to be associated with clownfish protection form sea anemones, and thus the evolution of their mutualism. Additionally, the genomic resources acquired represent a valuable resource for further investigation of the genomic basis of clownfish adaptive radiation.

Simultaneous Bayesian inference of phylogeny and molecular coevolution

Patterns of molecular coevolution can reveal structural and functional constraints within or among organic molecules. These patterns are better understood when considering the underlying evolutionary process, which enables us to disentangle the signal of the dependent evolution of sites (coevolution) from the effects of shared ancestry of genes. Conversely, disregarding the dependent evolution of sites when studying the history of genes negatively impacts the accuracy of the inferred phylogenetic trees. Although molecular coevolution and phylogenetic history are interdependent, analyses of the two processes are conducted separately, a choice dictated by computational convenience, but at the expense of accuracy. We present a Bayesian method and associated software to infer how many and which sites of an alignment evolve according to an independent or a pairwise dependent evolutionary process, and to simultaneously estimate the phylogenetic relationships among sequences. We validate our method on synthetic datasets and challenge our predictions of coevolution on the 16S rRNA molecule by comparing them with its known molecular structure. Finally, we assess the accuracy of phylogenetic trees inferred under the assumption of independence among sites using synthetic datasets, the 16S rRNA molecule and 10 additional alignments of protein-coding genes of eukaryotes. Our results demonstrate that inferring phylogenetic trees while accounting for dependent site evolution significantly impacts the estimates of the phylogeny and the evolutionary process.

Model selection may not be a mandatory step for phylogeny reconstruction

Determining the most suitable model for phylogeny reconstruction constitutes a fundamental step in numerous evolutionary studies. Over the years, various criteria for model selection have been proposed, leading to debate over which criterion is preferable. However, the necessity of this procedure has not been questioned to date. Here, we demonstrate that although incongruency regarding the selected model is frequent over empirical and simulated data, all criteria lead to very similar inferences. When topologies and ancestral sequence reconstruction are the desired output, choosing one criterion over another is not crucial. Moreover, skipping model selection and using instead the most parameter-rich model, GTR+I+G, leads to similar inferences, thus rendering this time-consuming step nonessential, at least under current strategies of model selection.

Developmental Constraints on Genome Evolution in Four Bilaterian Model Species

Developmental constraints on genome evolution have been suggested to follow either an early conservation model or an "hourglass" model. Both models agree that late development strongly diverges between species, but debate on which developmental period is the most conserved. Here, based on a modified "Transcriptome Age Index" approach, that is, weighting trait measures by expression level, we analyzed the constraints acting on three evolutionary traits of protein coding genes (strength of purifying selection on protein sequences, phyletic age, and duplicability) in four species: Nematode worm Caenorhabditis elegans, fly Drosophila melanogaster, zebrafish Danio rerio, and mouse Mus musculus. In general, we found that both models can be supported by different genomic properties. Sequence evolution follows an hourglass model, but the evolution of phyletic age and of duplicability follow an early conservation model. Further analyses indicate that stronger purifying selection on sequences in the middle development are driven by temporal pleiotropy of these genes. In addition, we report evidence that expression in late development is enriched with retrogenes, which usually lack efficient regulatory elements. This implies that expression in late development could facilitate transcription of new genes, and provide opportunities for acquisition of function. Finally, in C. elegans, we suggest that dosage imbalance could be one of the main factors that cause depleted expression of high duplicability genes in early development.

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.

State aggregation for fast likelihood computations in molecular evolution

Motivation

Codon models are widely used to identify the signature of selection at the molecular level and to test for changes in selective pressure during the evolution of genes encoding proteins. The large size of the state space of the Markov processes used to model codon evolution makes it difficult to use these models with large biological datasets. We propose here to use state aggregation to reduce the state space of codon models and, thus, improve the computational performance of likelihood estimation on these models.

Results

We show that this heuristic speeds up the computations of the M0 and branch-site models up to 6.8 times. We also show through simulations that state aggregation does not introduce a detectable bias. We analyzed a real dataset and show that aggregation provides highly correlated predictions compared to the full likelihood computations. Finally, state aggregation is a very general approach and can be applied to any continuous-time Markov process-based model with large state space, such as amino acid and coevolution models. We therefore discuss different ways to apply state aggregation to Markov models used in phylogenetics.

Availability and Implementation

The heuristic is implemented in the godon package (https://bitbucket.org/Davydov/godon) and in a version of FastCodeML (https://gitlab.isb-sib.ch/phylo/fastcodeml).

Contact

nicolas.salamin@unil.ch

Supplementary Information

Supplementary data are available at Bioinformatics online.

A comprehensive transcriptional map of primate brain development

The transcriptional underpinnings of brain development remain poorly understood, particularly in humans and closely related non-human primates. We describe a high-resolution transcriptional atlas of rhesus monkey (Macaca mulatta) brain development that combines dense temporal sampling of prenatal and postnatal periods with fine anatomical division of cortical and subcortical regions associated with human neuropsychiatric disease. Gene expression changes more rapidly before birth, both in progenitor cells and maturing neurons. Cortical layers and areas acquire adult-like molecular profiles surprisingly late in postnatal development. Disparate cell populations exhibit distinct developmental timing of gene expression, but also unexpected synchrony of processes underlying neural circuit construction including cell projection and adhesion. Candidate risk genes for neurodevelopmental disorders including primary microcephaly, autism spectrum disorder, intellectual disability, and schizophrenia show disease-specific spatiotemporal enrichment within developing neocortex. Human developmental expression trajectories are more similar to monkey than rodent, although approximately 9% of genes show human-specific regulation with evidence for prolonged maturation or neoteny compared to monkey.

Extracting functional trends from whole genome duplication events using comparative genomics

Background

The number of species with completed genomes, including those with evidence for recent whole genome duplication events has exploded. The recently sequenced Atlantic salmon genome has been through two rounds of whole genome duplication since the divergence of teleost fish from the lineage that led to amniotes. This quadrupoling of the number of potential genes has led to complex patterns of retention and loss among gene families.

Results

Methods have been developed to characterize the interplay of duplicate gene retention processes across both whole genome duplication events and additional smaller scale duplication events. Further, gene expression divergence data has become available as well for Atlantic salmon and the closely related, pre-whole genome duplication pike and methods to describe expression divergence are also presented. These methods for the characterization of duplicate gene retention and gene expression divergence that have been applied to salmon are described.

Conclusions

With the growth in available genomic and functional data, the opportunities to extract functional inference from large scale duplicates using comparative methods have expanded dramatically. Recently developed methods that further this inference for duplicated genes have been described.

Electronic supplementary material

The online version of this article (doi:10.1186/s12575-016-0041-2) contains supplementary material, which is available to authorized users.

Alternative splicing modulated by genetic variants demonstrates accelerated evolution regulated by highly conserved proteins

Identification of functional genetic variants and elucidation of their regulatory mechanisms represent significant challenges of the post-genomic era. A poorly understood topic is the involvement of genetic variants in mediating post-transcriptional RNA processing, including alternative splicing. Thus far, little is known about the genomic, evolutionary, and regulatory features of genetically modulated alternative splicing (GMAS). Here, we systematically identified intronic tag variants for genetic modulation of alternative splicing using RNA-seq data specific to cellular compartments. Combined with our previous method that identifies exonic tags for GMAS, this study yielded 622 GMAS exons. We observed that GMAS events are highly cell type independent, indicating that splicing-altering genetic variants could have widespread function across cell types. Interestingly, GMAS genes, exons, and single-nucleotide variants (SNVs) all demonstrated positive selection or accelerated evolution in primates. We predicted that GMAS SNVs often alter binding of splicing factors, with SRSF1 affecting the most GMAS events and demonstrating global allelic binding bias. However, in contrast to their GMAS targets, the predicted splicing factors are more conserved than expected, suggesting that cis-regulatory variation is the major driving force of splicing evolution. Moreover, GMAS-related splicing factors had stronger consensus motifs than expected, consistent with their susceptibility to SNV disruption. Intriguingly, GMAS SNVs in general do not alter the strongest consensus position of the splicing factor motif, except the more than 100 GMAS SNVs in linkage disequilibrium with polymorphisms reported by genome-wide association studies. Our study reports many GMAS events and enables a better understanding of the evolutionary and regulatory features of this phenomenon.

Evolutionary genomics and HIV restriction factors

PURPOSE OF REVIEW

To provide updated insights into innate antiviral immunity and highlight prototypical evolutionary features of well characterized HIV restriction factors.

RECENT FINDINGS

Recently, a new HIV restriction factor, Myxovirus resistance 2, has been discovered and the region/residue responsible for its activity identified using an evolutionary approach. Furthermore, IFI16, an innate immunity protein known to sense several viruses, has been shown to contribute to the defense to HIV-1 by causing cell death upon sensing HIV-1 DNA.

SUMMARY

Restriction factors against HIV show characteristic signatures of positive selection. Different patterns of accelerated sequence evolution can distinguish antiviral strategies--offense or defence--as well as the level of specificity of the antiviral properties. Sequence analysis of primate orthologs of restriction factors serves to localize functional domains and sites responsible for antiviral action. We use recent discoveries to illustrate how evolutionary genomic analyses help identify new antiviral genes and their mechanisms of action.

POTION: an end-to-end pipeline for positive Darwinian selection detection in genome-scale data through phylogenetic comparison of protein-coding genes

Background

Detection of genes evolving under positive Darwinian evolution in genome-scale data is nowadays a prevailing strategy in comparative genomics studies to identify genes potentially involved in adaptation processes. Despite the large number of studies aiming to detect and contextualize such gene sets, there is virtually no software available to perform this task in a general, automatic, large-scale and reliable manner. This certainly occurs due to the computational challenges involved in this task, such as the appropriate modeling of data under analysis, the computation time to perform several of the required steps when dealing with genome-scale data and the highly error-prone nature of the sequence and alignment data structures needed for genome-wide positive selection detection.

Results

We present POTION, an open source, modular and end-to-end software for genome-scale detection of positive Darwinian selection in groups of homologous coding sequences. Our software represents a key step towards genome-scale, automated detection of positive selection, from predicted coding sequences and their homology relationships to high-quality groups of positively selected genes. POTION reduces false positives through several sophisticated sequence and group filters based on numeric, phylogenetic, quality and conservation criteria to remove spurious data and through multiple hypothesis corrections, and considerably reduces computation time thanks to a parallelized design. Our software achieved a high classification performance when used to evaluate a curated dataset of Trypanosoma brucei paralogs previously surveyed for positive selection. When used to analyze predicted groups of homologous genes of 19 strains of Mycobacterium tuberculosis as a case study we demonstrated the filters implemented in POTION to remove sources of errors that commonly inflate errors in positive selection detection. A thorough literature review found no other software similar to POTION in terms of customization, scale and automation.

Conclusion

To the best of our knowledge, POTION is the first tool to allow users to construct and check hypotheses regarding the occurrence of site-based evidence of positive selection in non-curated, genome-scale data within a feasible time frame and with no human intervention after initial configuration. POTION is available at http://www.lmb.cnptia.embrapa.br/share/POTION/.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1765-0) contains supplementary material, which is available to authorized users.

Understanding the functional difference between growth arrest-specific protein 6 and protein S: an evolutionary approach

Although protein S (PROS1) and growth arrest-specific protein 6 (GAS6) proteins are homologous with a high degree of structural similarity, they are functionally different. The objectives of this study were to identify the evolutionary origins from which these functional differences arose. Bioinformatics methods were used to estimate the evolutionary divergence time and to detect the amino acid residues under functional divergence between GAS6 and PROS1. The properties of these residues were analysed in the light of their three-dimensional structures, such as their stability effects, the identification of electrostatic patches and the identification potential protein-protein interaction. The divergence between GAS6 and PROS1 probably occurred during the whole-genome duplications in vertebrates. A total of 78 amino acid sites were identified to be under functional divergence. One of these sites, Asn463, is involved in N-glycosylation in GAS6, but is mutated in PROS1, preventing this post-translational modification. Sites experiencing functional divergence tend to express a greater diversity of stabilizing/destabilizing effects than sites that do not experience such functional divergence. Three electrostatic patches in the LG1/LG2 domains were found to differ between GAS6 and PROS1. Finally, a surface responsible for protein-protein interactions was identified. These results may help researchers to analyse disease-causing mutations in the light of evolutionary and structural constraints, and link genetic pathology to clinical phenotypes.

Tissue-Specific Evolution of Protein Coding Genes in Human and Mouse

Protein-coding genes evolve at different rates, and the influence of different parameters, from gene size to expression level, has been extensively studied. While in yeast gene expression level is the major causal factor of gene evolutionary rate, the situation is more complex in animals. Here we investigate these relations further, especially taking in account gene expression in different organs as well as indirect correlations between parameters. We used RNA-seq data from two large datasets, covering 22 mouse tissues and 27 human tissues. Over all tissues, evolutionary rate only correlates weakly with levels and breadth of expression. The strongest explanatory factors of purifying selection are GC content, expression in many developmental stages, and expression in brain tissues. While the main component of evolutionary rate is purifying selection, we also find tissue-specific patterns for sites under neutral evolution and for positive selection. We observe fast evolution of genes expressed in testis, but also in other tissues, notably liver, which are explained by weak purifying selection rather than by positive selection.

Less is more: an adaptive branch-site random effects model for efficient detection of episodic diversifying selection

Over the past two decades, comparative sequence analysis using codon-substitution models has been honed into a powerful and popular approach for detecting signatures of natural selection from molecular data. A substantial body of work has focused on developing a class of "branch-site" models which permit selective pressures on sequences, quantified by the ω ratio, to vary among both codon sites and individual branches in the phylogeny. We develop and present a method in this class, adaptive branch-site random effects likelihood (aBSREL), whose key innovation is variable parametric complexity chosen with an information theoretic criterion. By applying models of different complexity to different branches in the phylogeny, aBSREL delivers statistical performance matching or exceeding best-in-class existing approaches, while running an order of magnitude faster. Based on simulated data analysis, we offer guidelines for what extent and strength of diversifying positive selection can be detected reliably and suggest that there is a natural limit on the optimal parametric complexity for "branch-site" models. An aBSREL analysis of 8,893 Euteleostomes gene alignments demonstrates that over 80% of branches in typical gene phylogenies can be adequately modeled with a single ω ratio model, that is, current models are unnecessarily complicated. However, there are a relatively small number of key branches, whose identities are derived from the data using a model selection procedure, for which it is essential to accurately model evolutionary complexity.

Gene-wide identification of episodic selection

We present BUSTED, a new approach to identifying gene-wide evidence of episodic positive selection, where the non-synonymous substitution rate is transiently greater than the synonymous rate. BUSTED can be used either on an entire phylogeny (without requiring an a priori hypothesis regarding which branches are under positive selection) or on a pre-specified subset of foreground lineages (if a suitable a priori hypothesis is available). Selection is modeled as varying stochastically over branches and sites, and we propose a computationally inexpensive evidence metric for identifying sites subject to episodic positive selection on any foreground branches. We compare BUSTED with existing models on simulated and empirical data. An implementation is available on www.datamonkey.org/busted, with a widget allowing the interactive specification of foreground branches.

Extensive copy-number variation of young genes across stickleback populations

Duplicate genes emerge as copy-number variations (CNVs) at the population level, and remain copy-number polymorphic until they are fixed or lost. The successful establishment of such structural polymorphisms in the genome plays an important role in evolution by promoting genetic diversity, complexity and innovation. To characterize the early evolutionary stages of duplicate genes and their potential adaptive benefits, we combine comparative genomics with population genomics analyses to evaluate the distribution and impact of CNVs across natural populations of an eco-genomic model, the three-spined stickleback. With whole genome sequences of 66 individuals from populations inhabiting three distinct habitats, we find that CNVs generally occur at low frequencies and are often only found in one of the 11 populations surveyed. A subset of CNVs, however, displays copy-number differentiation between populations, showing elevated within-population frequencies consistent with local adaptation. By comparing teleost genomes to identify lineage-specific genes and duplications in sticklebacks, we highlight rampant gene content differences among individuals in which over 30% of young duplicate genes are CNVs. These CNV genes are evolving rapidly at the molecular level and are enriched with functional categories associated with environmental interactions, depicting the dynamic early copy-number polymorphic stage of genes during population differentiation.

After a locus is duplicated in a genome, individuals from a population instantaneously differ in the number of copies of this locus producing a copy-number variation (CNV). Over time, the joint effects of selection and other evolutionary forces will act to either eliminate the extra genetic copy or retain it. Depending on this evolutionary interplay, young duplications, including newly duplicated genes, can persist for millions of years as CNVs. CNVs may especially be prevalent between populations that have colonized and adapted to disparate environments in which selective pressures differ. Using whole genome sequences from several populations of three-spined sticklebacks that inhabit different environments, we find that a third of young duplicated genes are CNVs. These young CNV genes are enriched with environmental response functions and evolving rapidly at the molecular level, making them promising candidates for a role in the rapid ecological adaptation to novel environments.

A generalized mechanistic codon model

Models of codon evolution have attracted particular interest because of their unique capabilities to detect selection forces and their high fit when applied to sequence evolution. We described here a novel approach for modeling codon evolution, which is based on Kronecker product of matrices. The 61 × 61 codon substitution rate matrix is created using Kronecker product of three 4 × 4 nucleotide substitution matrices, the equilibrium frequency of codons, and the selection rate parameter. The entities of the nucleotide substitution matrices and selection rate are considered as parameters of the model, which are optimized by maximum likelihood. Our fully mechanistic model allows the instantaneous substitution matrix between codons to be fully estimated with only 19 parameters instead of 3,721, by using the biological interdependence existing between positions within codons. We illustrate the properties of our models using computer simulations and assessed its relevance by comparing the AICc measures of our model and other models of codon evolution on simulations and a large range of empirical data sets. We show that our model fits most biological data better compared with the current codon models. Furthermore, the parameters in our model can be interpreted in a similar way as the exchangeability rates found in empirical codon models.

Positive selection during the evolution of the blood coagulation factors in the context of their disease-causing mutations

Blood coagulation occurs through a cascade of enzymes and cofactors that produces a fibrin clot, while otherwise maintaining hemostasis. The 11 human coagulation factors (FG, FII–FXIII) have been identified across all vertebrates, suggesting that they emerged with the first vertebrates around 500 Ma. Human FVIII, FIX, and FXI are associated with thousands of disease-causing mutations. Here, we evaluated the strength of selective pressures on the 14 genes coding for the 11 factors during vertebrate evolution, and compared these with human mutations in FVIII, FIX, and FXI. Positive selection was identified for fibrinogen (FG), FIII, FVIII, FIX, and FX in the mammalian Primates and Laurasiatheria and the Sauropsida (reptiles and birds). This showed that the coagulation system in vertebrates was under strong selective pressures, perhaps to adapt against blood-invading pathogens. The comparison of these results with disease-causing mutations reported in FVIII, FIX, and FXI showed that the number of disease-causing mutations, and the probability of positive selection were inversely related to each other. It was concluded that when a site was under positive selection, it was less likely to be associated with disease-causing mutations. In contrast, sites under negative selection were more likely to be associated with disease-causing mutations and be destabilizing. A residue-by-residue comparison of the FVIII, FIX, and FXI sequence alignments confirmed this. This improved understanding of evolutionary changes in FVIII, FIX, and FXI provided greater insight into disease-causing mutations, and better assessments of the codon sites that may be mutated in applications of gene therapy.

Uncovering adaptive evolution in the human lineage

BACKGROUND

The recent increase in human polymorphism data, together with the availability of genome sequences from several primate species, provides an unprecedented opportunity to investigate how natural selection has shaped human evolution.

RESULTS

We compared human branch-specific substitutions with variation data in the current human population to measure the impact of adaptive evolution on human protein coding genes. The use of single nucleotide polymorphisms (SNPs) with high derived allele frequencies (DAFs) minimized the influence of segregating slightly deleterious mutations and improved the estimation of the number of adaptive sites. Using DAF ≥ 60% we showed that the proportion of adaptive substitutions is 0.2% in the complete gene set. However, the percentage rose to 40% when we focused on genes that are specifically accelerated in the human branch with respect to the chimpanzee branch, or on genes that show signatures of adaptive selection at the codon level by the maximum likelihood based branch-site test. In general, neural genes are enriched in positive selection signatures. Genes with multiple lines of evidence of positive selection include taxilin beta, which is involved in motor nerve regeneration and syntabulin, and is required for the formation of new presynaptic boutons.

CONCLUSIONS

We combined several methods to detect adaptive evolution in human coding sequences at a genome-wide level. The use of variation data, in addition to sequence divergence information, uncovered previously undetected positive selection signatures in neural genes.

Patterns of positive selection in seven ant genomes

The evolution of ants is marked by remarkable adaptations that allowed the development of very complex social systems. To identify how ant-specific adaptations are associated with patterns of molecular evolution, we searched for signs of positive selection on amino-acid changes in proteins. We identified 24 functional categories of genes which were enriched for positively selected genes in the ant lineage. We also reanalyzed genome-wide data sets in bees and flies with the same methodology to check whether positive selection was specific to ants or also present in other insects. Notably, genes implicated in immunity were enriched for positively selected genes in the three lineages, ruling out the hypothesis that the evolution of hygienic behaviors in social insects caused a major relaxation of selective pressure on immune genes. Our scan also indicated that genes implicated in neurogenesis and olfaction started to undergo increased positive selection before the evolution of sociality in Hymenoptera. Finally, the comparison between these three lineages allowed us to pinpoint molecular evolution patterns that were specific to the ant lineage. In particular, there was ant-specific recurrent positive selection on genes with mitochondrial functions, suggesting that mitochondrial activity was improved during the evolution of this lineage. This might have been an important step toward the evolution of extreme lifespan that is a hallmark of ants.