An HMM-based Comparative Genomic Framework for Detecting Introgression in Eukaryotes

One outcome of interspecific hybridization and subsequent effects of evolutionary forces is introgression, which is the integration of genetic material from one species into the genome of an individual in another species. The evolution of several groups of eukaryotic species has involved hybridization, and cases of adaptation through introgression have been already established. In this work, we report on a new comparative genomic framework for detecting introgression in genomes, called PhyloNet-HMM, which combines phylogenetic networks, that capture reticulate evolutionary relationships among genomes, with hidden Markov models (HMMs), that capture dependencies within genomes. A novel aspect of our work is that it also accounts for incomplete lineage sorting and dependence across loci. Application of our model to variation data from chromosome 7 in the mouse (Mus musculus domesticus) genome detects a recently reported adaptive introgression event involving the rodent poison resistance gene Vkorc1, in addition to other newly detected introgression regions. Based on our analysis, it is estimated that about 12% of all sites withinchromosome 7 are of introgressive origin (these cover about 18 Mbp of chromosome 7, and over 300 genes). Further, our model detects no introgression in two negative control data sets. Our work provides a powerful framework for systematic analysis of introgression while simultaneously accounting for dependence across sites, point mutations, recombination, and ancestral polymorphism

Interpreting the genomic landscape of introgression.

Introgression, the transfer of genetic material between species through hybridisation, occurs in many taxa and has important consequences. Genomic studies allow us to characterise the landscape of introgression across the genome, shedding light on both its adaptive benefits and the incompatibilities that help to maintain species barriers. Studies taking a genome-wide view suggest that adaptive introgression may be common, but that introgressed variation between many species is selected against throughout much of the genome. Confounding factors can complicate interpretations from these data, and computational simulations have proved vital to illustrate expected patterns under different scenarios. Future developments will move beyond correlative evidence to explicit models that account for how selection and genetic drift influence introgressed variation

Population genomics of speciation and admixture

The application of population genomics to the understanding of speciation has led to the emerging field of speciation genomics. This has brought new insight into how divergence builds up within the genome during speciation and is also revealing the extent to which species can continue to exchange genetic material despite reproductive barriers. It is also providing powerful new approaches for linking genotype to phenotype in admixed populations. In this chapter, we give an overview of some of the methods that have been used and some of the novel insights gained. We also outline some of the pitfalls of the most commonly used methods and possible problems with interpretation of the results

Einkorn genomics sheds light on history of the oldest domesticated wheat

Einkorn (Triticum monococcum) was the first domesticated wheat species, and was central to the birth of agriculture and the Neolithic Revolution in the Fertile Crescent around 10,000 years ago$^{1,2}$. Here we generate and analyse 5.2-Gb genome assemblies for wild and domesticated einkorn, including completely assembled centromeres. Einkorn centromeres are highly dynamic, showing evidence of ancient and recent centromere shifts caused by structural rearrangements. Whole-genome sequencing analysis of a diversity panel uncovered the population structure and evolutionary history of einkorn, revealing complex patterns of hybridizations and introgressions after the dispersal of domesticated einkorn from the Fertile Crescent. We also show that around 1% of the modern bread wheat (Triticum aestivum) A subgenome originates from einkorn. These resources and findings highlight the history of einkorn evolution and provide a basis to accelerate the genomics-assisted improvement of einkorn and bread wheat

Analyse bioinformatique des événements de transferts horizontaux entre espèces de drosophiles et lien avec la régulation des éléments transposables

Transposable elements (TEs) are repeated DNA sequences that are able to move (transpose) within their host genome. To counteract the negative effects of their TEs, regulation mechanisms of the TE transposition are present in the host genome. Once a TE is regulated, the progressive accumulation of mutations in its sequence will inevitably lead to the definitive loss of its transposition capacity. My work during this thesis is was to better understand the succss and the maintaining of these peculiar repeated sequencest, with the study of horizontal transfers (HTs) of TEs enabling them to escape host regulation mechanisms, and the study of this regulation. The first part of my thesis concerns the study of HTs between two closely related drosophila species. I have developed a new bioinformatic method for the detection of HTs between two eukaryotic genomes. The development of this method brought me to work on the unilateral multiple testing problematic for which I have developed a new procedure to control the expected false discovery rate (FDR). The second part of my thesis focuses on the regulation of TEs by the small RNA pathway, an RNA interference mechanism. For this study, I have analyzed sequencing data of small RNAs and total RNAs. For this work, I have developed an analysis pipeline, to study differences of expression between repeated sequences. Some features of the small RNA dataset required the development of a new procedure to parse them. This procedure was extended and implemented in a software to be used for the quality control of next generation sequencing dataLes éléments transposable (ET) sont des séquences d'ADN qui ont la capacité de se déplacer au sein des génomes. Pour contrebalancer les effets négatifs liés à l'activité des ET, il existe chez leurs hôtes des mécanismes régulant l'activité de transposition. Une fois qu'un ET est régulé, l'accumulation progressive de mutations dans sa séquence conduit fatalement à la perte définitive de son activité de transposition. J'ai cherché au cours de cette thèse à mieux comprendre le succès et le maintien de ces séquences répétées, avec d'une part l'étude des transferts horizontaux (TH) d'ET, un moyen d'échapper aux mécanismes de régulation , et d'autre part l'étude de leur régulation. Dans la première partie de ma thèse, je me suis intéressé à l'étude des TH entre deux espèces proches de drosophiles. Dans cette étude, j'ai développé une nouvelle méthode bioinformatique permettant la détection de séquences transférées horizontalement entre deux génomes eucaryotes qui m'a permis détecter de nombreux TH d'ET. Ce travail m'a aussi conduit à développé une nouvelle méthode de contrôle du taux de faux positifs moyen applicable aux tests multiples unilatéraux. Dans la deuxième partie de ma thèse, j'ai étudié la régulation des ET par la voie des petits ARN, un mécanisme de l'ARN interférence. Dans cette étude, j'ai analysé des données de séquençage de petits ARN, ainsi que d'ARN totaux issues de différentes populations de D. simulans. Ce travail a conduit au développement d'un pipeline d'analyse permettant d'étudier des différences d'expression entre des séquences répétées ainsi que d'une nouvelle procédure de contrôle qualité de ce type de donné

Evolutionary Inference from Admixed Genomes: Implications of Hybridization for Biodiversity Dynamics and Conservation

Hybridization as a macroevolutionary mechanism has been historically underappreciated among vertebrate biologists. Yet, the advent and subsequent proliferation of next-generation sequencing methods has increasingly shown hybridization to be a pervasive agent influencing evolution in many branches of the Tree of Life (to include ancestral hominids). Despite this, the dynamics of hybridization with regards to speciation and extinction remain poorly understood. To this end, I here examine the role of hybridization in the context of historical divergence and contemporary decline of several threatened and endangered North American taxa, with the goal to illuminate implications of hybridization for promoting—or impeding—population persistence in a shifting adaptive landscape. Chapter I employed population genomic approaches to examine potential effects of habitat modification on species boundary stability in co-occurring endemic fishes of the Colorado River basin (Gila robusta and G. cypha). Results showed how one potential outcome of hybridization might drive species decline: via a breakdown in selection against interspecific heterozygotes and subsequent genetic erosion of parental species. Chapter II explored long-term contributions of hybridization in an evolutionarily recent species complex (Gila) using a combination of phylogenomic and phylogeographic modelling approaches. Massively parallel computational methods were developed (and so deployed) to categorize sources of phylogenetic discordance as drivers of systematic bias among a panel of species tree inference algorithms. Contrary to past evidence, we found that hypotheses of hybrid origin (excluding one notable example) were instead explained by gene-tree discordance driven by a rapid radiation. Chapter III examined patterns of local ancestry in the endangered red wolf genome (Canis rufus) – a controversial taxon of a long-standing debate about the origin of the species. Analyses show how pervasive autosomal introgression served to mask signatures of prior isolation—in turn misleading analyses that led the species to be interpreted as of recent hybrid origin. Analyses also showed how recombination interacts with selection to create a non-random, structured genomic landscape of ancestries with, in the case of the red wolf, the ‘original’ species tree being retained only in low-recombination ‘refugia’ of the X chromosome. The final three chapters present bioinformatic software that I developed for my dissertation research to facilitate molecular approaches and analyses presented in Chapters I–III. Chapter IV details an in-silico method for optimizing similar genomic methods as used herein (RADseq of reduced representation libraries) for other non-model organisms. Chapter V describes a method for parsing genomic datasets for elements of interest, either as a filtering mechanism for downstream analysis, or as a precursor to targeted-enrichment reduced-representation genomic sequencing. Chapter VI presents a rapid algorithm for the definition of a ‘most parsimonious’ set of recombinational breakpoints in genomic datasets, as a method promoting local ancestry analyses as utilized in Chapter III. My three case studies and accompanying software promote three trajectories in modern hybridization research: How does hybridization impact short-term population persistence? How does hybridization drive macroevolutionary trends? and How do outcomes of hybridization vary in the genome? In so doing, my research promotes a deeper understanding of the role that hybridization has and will continue to play in governing the evolutionary fates of lineages at both contemporary and historic timescales

Evolutionary genomics : statistical and computational methods

This open access book addresses the challenge of analyzing and understanding the evolutionary dynamics of complex biological systems at the genomic level, and elaborates on some promising strategies that would bring us closer to uncovering of the vital relationships between genotype and phenotype. After a few educational primers, the book continues with sections on sequence homology and alignment, phylogenetic methods to study genome evolution, methodologies for evaluating selective pressures on genomic sequences as well as genomic evolution in light of protein domain architecture and transposable elements, population genomics and other omics, and discussions of current bottlenecks in handling and analyzing genomic data. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of detail and expert implementation advice that lead to the best results. Authoritative and comprehensive, Evolutionary Genomics: Statistical and Computational Methods, Second Edition aims to serve both novices in biology with strong statistics and computational skills, and molecular biologists with a good grasp of standard mathematical concepts, in moving this important field of study forward