Molecular evolution of candidate male reproductive genes in the brown algal model Ectocarpus

Background: Evolutionary studies of genes that mediate recognition between sperm and egg contribute to our understanding of reproductive isolation and speciation. Surface receptors involved in fertilization are targets of sexual selection, reinforcement, and other evolutionary forces including positive selection. This observation was made across different lineages of the eukaryotic tree from land plants to mammals, and is particularly evident in free-spawning animals. Here we use the brown algal model species Ectocarpus (Phaeophyceae) to investigate the evolution of candidate gamete recognition proteins in a distant major phylogenetic group of eukaryotes. Results: Male gamete specific genes were identified by comparing transcriptome data covering different stages of the Ectocarpus life cycle and screened for characteristics expected from gamete recognition receptors. Selected genes were sequenced in a representative number of strains from distant geographical locations and varying stages of reproductive isolation, to search for signatures of adaptive evolution. One of the genes (Esi0130_0068) showed evidence of selective pressure. Interestingly, that gene displayed domain similarities to the receptor for egg jelly (REJ) protein involved in sperm-egg recognition in sea urchins. Conclusions: We have identified a male gamete specific gene with similarity to known gamete recognition receptors and signatures of adaptation. Altogether, this gene could contribute to gamete interaction during reproduction as well as reproductive isolation in Ectocarpus and is therefore a good candidate for further functional evaluation

Rewriting Human History and Empowering Indigenous Communities with Genome Editing Tools.

Appropriate empirical-based evidence and detailed theoretical considerations should be used for evolutionary explanations of phenotypic variation observed in the field of human population genetics (especially Indigenous populations). Investigators within the population genetics community frequently overlook the importance of these criteria when associating observed phenotypic variation with evolutionary explanations. A functional investigation of population-specific variation using cutting-edge genome editing tools has the potential to empower the population genetics community by holding "just-so" evolutionary explanations accountable. Here, we detail currently available precision genome editing tools and methods, with a particular emphasis on base editing, that can be applied to functionally investigate population-specific point mutations. We use the recent identification of thrifty mutations in the CREBRF gene as an example of the current dire need for an alliance between the fields of population genetics and genome editing

Detecting Selection on Noncoding Nucleotide Variation: Methods and Applications

There has been a long tradition in molecular evolution to study selective pressures operating at the amino-acid level. But protein-coding variation is not the only level on which molecular adaptations occur, and it is not clear what roles non-coding variation has played in evolutionary history, since they have not yet been systematically explored. In this dissertation I systematically explore several aspects of selective pressures of noncoding nucleotide variation: The first project (Chapter 2) describes research on the determinants of eukaryotic translation dynamics, which include selection on non-coding aspects of DNA variation. Deep sequencing of ribosome-protected mRNA fragments and polysome gradients in various eukaryotic organisms have revealed an intriguing pattern: shorter mRNAs tend to have a greater overall density of ribosomes than longer mRNAs. There is debate about the cause of this trend. To resolve this open question, I systematically analysed 5’ mRNA structure and codon usage patterns in short versus long genes across 100 sequenced eukaryotic genomes. My results showed that compared with longer ones, short genes initiate faster, and also elongate faster. Thus the higher ribosome density in short eukaryote genes cannot be explained by translation elongation. Rather it is the translation initiation rate that sets the pace for eukaryotic protein translation. This work was followed by modelling studies of translation dynamics in a yeast cell. Chapter 3 concerns detecting selective pressures on the viral RNA structures. Most previous research on RNA viruses has focused on identifying amino-acid residues under positive or purifying selection, whereas selection on RNA structures has received less attention. I developed algorithms to scan along the viral genome and identify regions that exhibit signals of purifying or diversifying selection on RNA structure, by comparing the structural distances between actual viral RNA sequences against an appropriate null distribution. Unlike other algorithms that identify structural constraints, my approach accounts for the phylogenetic relationships among viral sequences, as well the observed variation in amino-acid sequences. Applied to Influenza viruses, I found that a significant portion of influenza viral genomes have experienced purifying selection for RNA structure, in both the positive- and negative-sense RNA forms, over the past few decades; and I found the first evidence of positive selection on RNA structure in specific regions of these viral genomes. Overall, the projects presented in these chapters represent a systematic look at several novel aspects of selection on noncoding nucleotide variation. These projects should open up new directions in studying the molecular signatures of natural selection, including studies on interactions between different layers at which selection may operate simultaneously (e.g. RNA structure and protein sequence)

Coalescence 2.0: a multiple branching of recent theoretical developments and their applications

Population genetics theory has laid the foundations for genomics analyses including the recent burst in genome scans for selection and statistical inference of past demographic events in many prokaryote, animal and plant species. Identifying SNPs under natural selection and underpinning species adaptation relies on disentangling the respective contribution of random processes (mutation, drift, migration) from that of selection on nucleotide variability. Most theory and statistical tests have been developed using the Kingman coalescent theory based on the Wright-Fisher population model. However, these theoretical models rely on biological and life-history assumptions which may be violated in many prokaryote, fungal, animal or plant species. Recent theoretical developments of the so called multiple merger coalescent models are reviewed here ({\Lambda}-coalescent, beta-coalescent, Bolthausen-Snitzman, {\Xi}-coalescent). We explicit how these new models take into account various pervasive ecological and biological characteristics, life history traits or life cycles which were not accounted in previous theories such as 1) the skew in offspring production typical of marine species, 2) fast adapting microparasites (virus, bacteria and fungi) exhibiting large variation in population sizes during epidemics, 3) the peculiar life cycles of fungi and bacteria alternating sexual and asexual cycles, and 4) the high rates of extinction-recolonization in spatially structured populations. We finally discuss the relevance of multiple merger models for the detection of SNPs under selection in these species, for population genomics of very large sample size and advocate to potentially examine the conclusion of previous population genetics studies.Comment: 3 Figure

A genomic map of the effects of linked selection in Drosophila

Natural selection at one site shapes patterns of genetic variation at linked sites. Quantifying the effects of 'linked selection' on levels of genetic diversity is key to making reliable inference about demography, building a null model in scans for targets of adaptation, and learning about the dynamics of natural selection. Here, we introduce the first method that jointly infers parameters of distinct modes of linked selection, notably background selection and selective sweeps, from genome-wide diversity data, functional annotations and genetic maps. The central idea is to calculate the probability that a neutral site is polymorphic given local annotations, substitution patterns, and recombination rates. Information is then combined across sites and samples using composite likelihood in order to estimate genome-wide parameters of distinct modes of selection. In addition to parameter estimation, this approach yields a map of the expected neutral diversity levels along the genome. To illustrate the utility of our approach, we apply it to genome-wide resequencing data from 125 lines in Drosophila melanogaster and reliably predict diversity levels at the 1Mb scale. Our results corroborate estimates of a high fraction of beneficial substitutions in proteins and untranslated regions (UTR). They allow us to distinguish between the contribution of sweeps and other modes of selection around amino acid substitutions and to uncover evidence for pervasive sweeps in untranslated regions (UTRs). Our inference further suggests a substantial effect of linked selection from non-classic sweeps. More generally, we demonstrate that linked selection has had a larger effect in reducing diversity levels and increasing their variance in D. melanogaster than previously appreciated

Selection and Demography Drive Range-Wide Patterns of Mhc Variation in Mule Deer (odocoileus Hemionus)

Variation at functional genes involved in immune response is of increasing concern as wildlife diseases continue to emerge and threaten populations. The amount of standing genetic variation in a population is directly associated with its potential for rapid adaptation to novel environments. For genes in the major histocompatibility complex (MHC), which are crucial in activating the immune response and which have extremely high levels of polymorphism, the genetic variation has been shown to be influenced by both parasite-mediated selection and historical population demography. To better understand the relative roles of parasite-mediated selection and demography on MHC evolution in large populations, I analyzed geographic patterns of variation at the MHC DRB class II locus in mule deer (Odocoileus hemionus). I identified 31 new MHC-DRB alleles which were phylogenetically similar to other cervid MHC alleles, and I found 1 allele that was shared with white-tailed deer (Odocoileus virginianus). I found evidence for selection on the MHC based on high dN/dS ratios, positive neutrality tests, deviations from Hardy-Weinberg Equilibrium (HWE) and greater isolation-by-distance (IBD) than expected under neutrality. However, I also saw evidence that historical demography is important in shaping variation at the MHC, in the similar variation structures between MHC and microsatellites and the lack of significant environmental drivers of variation at either locus. These results show that both natural selection and historical demography are important drivers in the evolution of the MHC in mule deer and may aid in predicting how future adaptation is shaped when this species is confronted with environmental challenges

Adaptive Evolution as a Predictor of Species-Specific Innate Immune Response

It has been proposed that positive selection may be associated with protein functional change. For example, human and macaque have different outcomes to HIV infection and it has been shown that residues under positive selection in the macaque TRIM5α receptor locate to the region known to influence species-specific response to HIV. In general, however, the relationship between sequence and function has proven difficult to fully elucidate, and it is the role of large-scale studies to help bridge this gap in our understanding by revealing major patterns in the data that correlate genotype with function or phenotype. In this study, we investigate the level of species-specific positive selection in innate immune genes from human and mouse. In total, we analyzed 456 innate immune genes using codon-based models of evolution, comparing human, mouse, and 19 other vertebrate species to identify putative species-specific positive selection. Then we used population genomic data from the recently completed Neanderthal genome project, the 1000 human genomes project, and the 17 laboratory mouse genomes project to determine whether the residues that were putatively positively selected are fixed or variable in these populations. We find evidence of species-specific positive selection on both the human and the mouse branches and we show that the classes of genes under positive selection cluster by function and by interaction. Data from this study provide us with targets to test the relationship between positive selection and protein function and ultimately to test the relationship between positive selection and discordant phenotypes