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 (Ne) 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 Ne. 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

Biased gene conversion : origin, dynamics and intensity of the fourth evolutionary force of eucaryotic genomes

En génomique comparative, on considère classiquement trois forces déterminant l'évolution des séquences : la mutation, la sélection et la dérive génétique. Récemment, lors de l'étude de l'origine évolutive des variations de la composition en base des génomes, un quatrième agent a été identifié : la conversion génique biaisée (BGC). Le BGC est intimement lié à la recombinaison méiotique et semble présent chez la plupart des eucaryotes. Ce phénomène introduit une surreprésentation de certains allèles dans les produits méiotiques aboutissant à une augmentation de la fréquence de ces variants dans la population. Ce processus est capable de mimer et d'interférer avec la sélection naturelle. Il est donc important de le caractériser afin de pouvoir le distinguer efficacement de la sélection dans l'étude de l'adaptation à l'échelle moléculaire. C'est ce que nous nous attachons à faire dans le cadre de ce travail. Pour cela nous utilisons deux espèces modèles. Premièrement la levure Saccharomyces cerevisiae pour laquelle une carte de recombinaison haute résolution permettant l'analyse du processus de conversion, est disponible. L'étude approfondie de cette carte nous a permis de lever le voile sur les mécanismes moléculaires qui sous-tendent le BGC. Deuxièmement, grâce à des découvertes récentes sur la détermination des patrons de recombinaison via la protéine PRDM9 chez les mammifères, nous avons quantifié la dynamique et l'intensité de ce processus dans l'histoire évolutive récente de l'homme. Ces résultats nous ont permis de confirmer la place du BGC comme quatrième force d'évolution moléculaire, mais aussi de discuter de l'origine évolutive de ce phénomèneUsually, three main forces are considered when studying sequences evolution in comparative genomics : mutation, selection and genetic drift. Recently, a fourth process has been identified during the study of base composition landscapes in genomes : biased gene conversion (BGC). This phenomenon introduces an overrepresentation of certain alleles in meiosis products (gametes or spores) leading to an increase of the frequency of those variants in the population. Thus, it is able to mimic and interfere with natural selection. Hence, it is important to describe this phenomenon in order to be able to trustfully distinguish BGC and selection in the study of adaptation at the molecular scale. So, the main goal of this work is to analyze the molecular origin, the intensity and the dynamics of BGC. To do so, we use two model species. First, we use the yeast Saccharomyces cerevisiae because, for this specie, a high-resolution recombination map is available which allows a fine study of the conversion process. Analyzing this map led us to shed the light on the molecular mechanisms of BGC. Secondly, recent discoveries on the role of the PRDM9 protein in the determination of recombination landscapes in mammals allowed us to quantify the dynamics and intensity of BGC in the recent human history. Thanks to those two studies, we first confirmed that BGC is the fourth force of molecular evolution and we also provided hypotheses about the evolutionary origin of this proces

La conversion génique biaisée : origine, dynamique et intensité de la quatrième force d’évolution des génomes eucaryotes

Usually, three main forces are considered when studying sequences evolution in comparative genomics : mutation, selection and genetic drift. Recently, a fourth process has been identified during the study of base composition landscapes in genomes : biased gene conversion (BGC). This phenomenon introduces an overrepresentation of certain alleles in meiosis products (gametes or spores) leading to an increase of the frequency of those variants in the population. Thus, it is able to mimic and interfere with natural selection. Hence, it is important to describe this phenomenon in order to be able to trustfully distinguish BGC and selection in the study of adaptation at the molecular scale. So, the main goal of this work is to analyze the molecular origin, the intensity and the dynamics of BGC. To do so, we use two model species. First, we use the yeast Saccharomyces cerevisiae because, for this specie, a high-resolution recombination map is available which allows a fine study of the conversion process. Analyzing this map led us to shed the light on the molecular mechanisms of BGC. Secondly, recent discoveries on the role of the PRDM9 protein in the determination of recombination landscapes in mammals allowed us to quantify the dynamics and intensity of BGC in the recent human history. Thanks to those two studies, we first confirmed that BGC is the fourth force of molecular evolution and we also provided hypotheses about the evolutionary origin of this processEn génomique comparative, on considère classiquement trois forces déterminant l'évolution des séquences : la mutation, la sélection et la dérive génétique. Récemment, lors de l'étude de l'origine évolutive des variations de la composition en base des génomes, un quatrième agent a été identifié : la conversion génique biaisée (BGC). Le BGC est intimement lié à la recombinaison méiotique et semble présent chez la plupart des eucaryotes. Ce phénomène introduit une surreprésentation de certains allèles dans les produits méiotiques aboutissant à une augmentation de la fréquence de ces variants dans la population. Ce processus est capable de mimer et d'interférer avec la sélection naturelle. Il est donc important de le caractériser afin de pouvoir le distinguer efficacement de la sélection dans l'étude de l'adaptation à l'échelle moléculaire. C'est ce que nous nous attachons à faire dans le cadre de ce travail. Pour cela nous utilisons deux espèces modèles. Premièrement la levure Saccharomyces cerevisiae pour laquelle une carte de recombinaison haute résolution permettant l'analyse du processus de conversion, est disponible. L'étude approfondie de cette carte nous a permis de lever le voile sur les mécanismes moléculaires qui sous-tendent le BGC. Deuxièmement, grâce à des découvertes récentes sur la détermination des patrons de recombinaison via la protéine PRDM9 chez les mammifères, nous avons quantifié la dynamique et l'intensité de ce processus dans l'histoire évolutive récente de l'homme. Ces résultats nous ont permis de confirmer la place du BGC comme quatrième force d'évolution moléculaire, mais aussi de discuter de l'origine évolutive de ce phénomèn

GC-Biased Gene Conversion in Yeast Is Specifically Associated with Crossovers: Molecular Mechanisms and Evolutionary Significance

GC-biased gene conversion (gBGC) is a process associated with recombination that favors the transmission of GC alleles over AT alleles during meiosis. gBGC plays a major role in genome evolution in many eukaryotes. However, the molecular mechanisms of gBGC are still unknown. Different steps of the recombination process could potentially cause gBGC: the formation of double-strand breaks (DSBs), the invasion of the homologous or sister chromatid, and the repair of mismatches in heteroduplexes. To investigate these models, we analyzed a genome-wide data set of crossovers (COs) and noncrossovers (NCOs) in Saccharomyces cerevisiae. We demonstrate that the overtransmission of GC alleles is specific to COs and that it occurs among conversion tracts in which all alleles are converted from the same donor haplotype. Thus, gBGC results from a process that leads to long-patch repair. We show that gBGC is associated with longer tracts and that it is driven by the nature (GC or AT) of the alleles located at the extremities of the tract. These observations invalidate the hypotheses that gBGC is due to the base excision repair machinery or to a bias in DSB formation and suggest that in S. cerevisiae, gBGC is caused by the mismatch repair (MMR) system. We propose that the presence of nicks on both DNA strands during CO resolution could be the cause of the bias in MMR activity. Our observations are consistent with the hypothesis that gBGC is a nonadaptive consequence of a selective pressure to limit the mutation rate in mitotic cells

The Red Queen Model of Recombination Hotspots Evolution in the Light of Archaic and Modern Human Genomes

International audienceRecombination is an essential process in eukaryotes, which increases diversity by disrupting genetic linkage between loci and ensures the proper segregation of chromosomes during meiosis. In the human genome, recombination events are clustered in hotspots, whose location is determined by the PRDM9 protein. There is evidence that the location of hotspots evolves rapidly, as a consequence of changes in PRDM9 DNA-binding domain. However, the reasons for these changes and the rate at which they occur are not known. In this study, we investigated the evolution of human hotspot loci and of PRDM9 target motifs, both in modern and archaic human lineages (Denisovan) to quantify the dynamic of hotspot turnover during the recent period of human evolution. We show that present-day human hotspots are young: they have been active only during the last 10% of the time since the divergence from chimpanzee, starting to be operating shortly before the split between Denisovans and modern humans. Surprisingly, however, our analyses indicate that Denisovan recombination hotspots did not overlap with modern human ones, despite sharing similar PRDM9 target motifs. We further show that high-affinity PRDM9 target motifs are subject to a strong self-destructive drive, known as biased gene conversion (BGC), which should lead to the loss of the majority of them in the next 3 MYR. This depletion of PRDM9 genomic targets is expected to decrease fitness, and thereby to favor new PRDM9 alleles binding different motifs. Our refined estimates of the age and life expectancy of human hotspots provide empirical evidence in support of the Red Queen hypothesis of recombination hotspots evolution

A resolution of the mutation load paradox in humans

Current information on the rate of mutation and the fraction of sites in the genome that are subject to selection suggests that each human has received, on average, at least two new harmful mutations from it’s parents. These mutations were subsequently removed by natural selection through reduced survival or fertility. It has been argued that the mutation load, the proportional reduction in population mean fitness relative to the fitness of an idealized mutation-free individual, allows a theoretical prediction of the proportion of individuals in the population that fail to reproduce as a consequence of these harmful mutations. Application of this theory to humans implies that at least 88% of individuals should fail to reproduce, and that each female would need to have more than 16 offspring to maintain population size. This prediction is clearly at odds with the low reproductive excess of human populations. Here, we derive expressions for the fraction of individuals that fail to reproduce as a consequence of recurrent deleterious mutation (φ) for a model in which selection occurs via differences in relative fitness, such as would occur through competition between individuals. We show that φ is much smaller than the value predicted by comparing fitness to that of a mutation-free genotype. Under the relative fitness model, we show that φ depends jointly on U and the selective effects of new deleterious mutations, and that a species could tolerate 10s or even 100s of new deleterious mutations per genome each generatio

Recombination rates and strength of dBGC on HM motifs in the human genome.

<p>(A) Distribution of human historical recombination rates (cM/Mb), measured over a 2 kb window centered on HM motifs from human autosomes (hg19 assembly; no filter). Red: motifs located within historical recombination hotspots. Blue: motifs located outside hotspots. (B) Distribution of estimated population-scaled dBGC coefficient (<i>G</i>) on HM motifs located in recombination hotspots in the human genome. Median  = 57.5.</p

HM motifs loss rates within <i>versus</i> outside THE1 elements.

a<p>Intact motif count at ancestral edge of the branch (cf. <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004790#pgen-1004790-g001" target="_blank">Figure 1</a>).</p>b<p>Motif loss rate along the branch.</p>c<p>P-value of proportion test comparing HM loss rates within <i>vs.</i> outside THE1 elements along the branch.</p><p>HM motifs loss rates within <i>versus</i> outside THE1 elements.</p