Genetic diversity is the amount of variation observed between DNA sequences from distinct individuals of a given species. This pivotal concept of population genetics has implications for species health, domestication, management and conservation. Levels of genetic diversity seem to vary greatly in natural populations and species, but the determinants of this variation, and particularly the relative influences of species biology and ecology versus population history, are still largely mysterious. Here we show that the diversity of a species is predictable, and is determined in the first place by its ecological strategy. We investigated the genome-wide diversity of 76 non-model animal species by sequencing the transcriptome of two to ten individuals in each species. The distribution of genetic diversity between species revealed no detectable influence of geographic range or invasive status but was accurately predicted by key species traits related to parental investment: long-lived or low-fecundity species with brooding ability were genetically less diverse than short-lived or highly fecund ones. Our analysis demonstrates the influence of long-term life-history strategies on species response to short-term environmental perturbations, a result with immediate implications for conservation policies.

BackgroundThe morphological peculiarities of turtles have, for a long time, impeded their accurate placement in the phylogeny of amniotes. Molecular data used to address this major evolutionary question have so far been limited to a handful of markers and/or taxa. These studies have supported conflicting topologies, positioning turtles as either the sister group to all other reptiles, to lepidosaurs (tuatara, lizards and snakes), to archosaurs (birds and crocodiles), or to crocodilians. Genome-scale data have been shown to be useful in resolving other debated phylogenies, but no such adequate dataset is yet available for amniotes.ResultsIn this study, we used next-generation sequencing to obtain seven new transcriptomes from the blood, liver, or jaws of four turtles, a caiman, a lizard, and a lungfish. We used a phylogenomic dataset based on 248 nuclear genes (187,026 nucleotide sites) for 16 vertebrate taxa to resolve the origins of turtles. Maximum likelihood and Bayesian concatenation analyses and species tree approaches performed under the most realistic models of the nucleotide and amino acid substitution processes unambiguously support turtles as a sister group to birds and crocodiles. The use of more simplistic models of nucleotide substitution for both concatenation and species tree reconstruction methods leads to the artefactual grouping of turtles and crocodiles, most likely because of substitution saturation at third codon positions. Relaxed molecular clock methods estimate the divergence between turtles and archosaurs around 255 million years ago. The most recent common ancestor of living turtles, corresponding to the split between Pleurodira and Cryptodira, is estimated to have occurred around 157 million years ago, in the Upper Jurassic period. This is a more recent estimate than previously reported, and questions the interpretation of controversial Lower Jurassic fossils as being part of the extant turtles radiation.ConclusionsThese results provide a phylogenetic framework and timescale with which to interpret the evolution of the peculiar morphological, developmental, and molecular features of turtles within the amniotes.

In animals, the population genomic literature is dominated by two taxa, namely mammals and drosophilids, in which fully sequenced, well-annotated genomes have been available for years. Data from other metazoan phyla are scarce, probably because the vast majority of living species still lack a closely related reference genome. Here we achieve de novo, reference-free population genomic analysis from wild samples in five non-model animal species, based on next-generation sequencing transcriptome data. We introduce a pipe-line for cDNA assembly, read mapping, SNP/genotype calling, and data cleaning, with specific focus on the issue of hidden paralogy detection. In two species for which a reference genome is available, similar results were obtained whether the reference was used or not, demonstrating the robustness of our de novo inferences. The population genomic profile of a hare, a turtle, an oyster, a tunicate, and a termite were found to be intermediate between those of human and Drosophila, indicating that the discordant genomic diversity patterns that have been reported between these two species do not reflect a generalized vertebrate versus invertebrate gap. The genomic average diversity was generally higher in invertebrates than in vertebrates (with the notable exception of termite), in agreement with the notion that population size tends to be larger in the former than in the latter. The non-synonymous to synonymous ratio, however, did not differ significantly between vertebrates and invertebrates, even though it was negatively correlated with genetic diversity within each of the two groups. This study opens promising perspective regarding genome-wide population analyses of non-model organisms and the influence of population size on non-synonymous versus synonymous diversity.

Efficient algorithms and programs for the analysis of the ever-growing amount of biological sequence data are strongly needed in the genomics era. The pace at which new data and methodologies are generated calls for the use of pre-existing, optimized-yet extensible-code, typically distributed as libraries or packages. This motivated the Bio++ project, aiming at developing a set of C++ libraries for sequence analysis, phylogenetics, population genetics, and molecular evolution. The main attractiveness of Bio++ is the extensibility and reusability of its components through its object-oriented design, without compromising the computer-efficiency of the underlying methods. We present here the second major release of the libraries, which provides an extended set of classes and methods. These extensions notably provide built-in access to sequence databases and new data structures for handling and manipulating sequences from the omics era, such as multiple genome alignments and sequencing reads libraries. More complex models of sequence evolution, such as mixture models and generic n-tuples alphabets, are also included.

Next-generation sequencing (NGS) technologies offer the opportunity for population genomic study of non-model organisms sampled in the wild. The transcriptome is a convenient and popular target for such purposes. However, designing genetic markers from NGS transcriptome data requires assembling gene-coding sequences out of short reads. This is a complex task owing to gene duplications, genetic polymorphism, alternative splicing and transcription noise. Typical assembling programmes return thousands of predicted contigs, whose connection to the species true gene content is unclear, and from which SNP definition is uneasy. Here, the transcriptomes of five diverse non-model animal species (hare, turtle, ant, oyster and tunicate) were assembled from newly generated 454 and Illumina sequence reads. In two species for which a reference genome is available, a new procedure was introduced to annotate each predicted contig as either a full-length cDNA, fragment, chimera, allele, paralogue, genomic sequence or other, based on the number of, and overlap between, blast hits to the appropriate reference. Analyses showed that (i) the highest quality assemblies are obtained when 454 and Illumina data are combined, (ii) typical de novo assemblies include a majority of irrelevant cDNA predictions and (iii) assemblies can be appropriately cleaned by filtering contigs based on length and coverage. We conclude that robust, reference-free assembly of thousands of genes from transcriptomic NGS data is possible, opening promising perspectives for transcriptome-based population genomics in animals. A Galaxy pipeline implementing our best-performing assembling strategy is provided.

Phylogenomics has revealed the existence of fast-evolving animal phyla in which the amino acid substitution rate, averaged across many proteins, is consistently higher than in other lineages. The reasons for such differences in proteome-wide evolutionary rates are still unknown, largely because only a handful of species offer within-species genomic data from which molecular evolutionary processes can be deduced. In this study, we use next-generation sequencing technologies and individual whole-transcriptome sequencing to gather extensive polymorphism sequence data sets from Ciona intestinalis. Ciona is probably the best-characterized member of the fast-evolving Urochordata group (tunicates), which was recently identified as the sister group of the slow-evolving vertebrates. We introduce and validate a maximum-likelihood framework for single-nucleotide polymorphism and genotype calling, based on high-throughput short-read typing. We report that the C. intestinalis proteome is characterized by a high level of within-species diversity, efficient purifying selection, and a substantial percentage of adaptive amino acid substitutions. We conclude that the increased rate of amino acid sequence evolution in tunicates, when compared with vertebrates, is the consequence of both a 2–6 times higher per-year mutation rate and prevalent adaptive evolution.

Mitochondrial dysfunction plays critical roles in cancer development and related therapeutic response; however, exact molecular mechanisms remain unclear. Recently, alongside the discovery of mitochondrial-specific DNA methyltransferases, global and site-specific methylation of the mitochondrial genome has been described. Investigation of any functional consequences however remains unclear and debated due to insufficient evidence of the quantitative degree and frequency of mitochondrial DNA (mtDNA) methylation. This study uses WGBS to provide the first quantitative report of mtDNA methylation at single base pair resolution. The data show that mitochondrial genomes are extensively methylated predominantly at non-CpG sites. Importantly, these methylation patterns display notable differences between normal and cancer cells. Furthermore, knockdown of DNA methyltransferase enzymes resulted in a marked global reduction of mtDNA methylation levels, indicating these enzymes may be associated with the establishment and/or maintenance of mtDNA methylation. DNMT3B knockdown cells displayed a comparatively pronounced global reduction in mtDNA methylation with concomitant increases in gene expression, suggesting a potential functional link between methylation and gene expression. Together these results demonstrate reproducible, non-random methylation patterns of mtDNA and challenge the notion that mtDNA is lowly methylated. This study discusses key differences in methodology that suggest future investigations must allow for techniques that assess both CpG and non-CpG methylation.

The evolution of reproductive division of labour and social life in social insects has lead to the emergence of several life-history traits and adaptations typical of larger organisms: social insect colonies can reach masses of several kilograms, they start reproducing only when they are several years old, and can live for decades. These features and the monopolization of reproduction by only one or few individuals in a colony should affect molecular evolution by reducing the effective population size. We tested this prediction by analysing genome-wide patterns of coding sequence polymorphism and divergence in eusocial vs. noneusocial insects based on newly generated RNA-seq data. We report very low amounts of genetic polymorphism and an elevated ratio of nonsynonymous to synonymous changes -a marker of the effective population size -in four distinct species of eusocial insects, which were more similar to vertebrates than to solitary insects regarding molecular evolutionary processes. Moreover, the ratio of nonsynonymous to synonymous substitutions was positively correlated with the level of social complexity across ant species. These results are fully consistent with the hypothesis of a reduced effective population size and an increased genetic load in eusocial insects, indicating that the evolution of social life has important consequences at both the genomic and population levels.