Understanding the origin of species with genome-scale data: modelling gene flow

• Published in: Nature reviews. Genetics Vol. 14; no. 6; pp. 404 - 414
• Main Authors: Sousa, Vitor, Hey, Jody
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 01.06.2013; Nature Publishing Group
• Subjects: Agriculture; Animal Genetics and Genomics; Animals; Biogeography; Biomedicine; Cancer Research; Datasets; Divergent evolution; Evolution, Molecular; Evolutionary biology; Gene Flow; Gene Frequency; Gene Function; Genes; Genetic Speciation; Genome, Human; Genomes; Genomics; Human Genetics; Humans; Likelihood Functions; Linkage Disequilibrium; Mitochondrial DNA; Models, Genetic; Origin of species; Polymorphism, Genetic; review-article; United States > US; New Jersey
• ISSN: 1471-0056; 1471-0064
• DOI: 10.1038/nrg3446

Key Points One of the great debates in evolution is about how one species separates into two. The now classical allopatric speciation model has started to be questioned by recent findings that point to divergence in the presence of gene flow. Gene flow is expected to reduce the overall levels of differentiation across the genome. Divergence in the face of gene flow results from the interaction of the opposing forces of gene flow and diversifying selection and the action of recombination. Today, next-generation sequencing (NGS) technologies and assembly tools make it possible to obtain genome-scale data affordably from multiple individuals from closely related populations and/or species, offering the promise of disentangling the complex interplay between selection, gene flow and recombination. One common approach to learn about divergence is to scan the genome using indicators of population differentiation, such as F ST . Examples of statistics that are sensitive only to certain aspects of divergence include the ABBA and BABA test ( D statistic) for detecting and estimating unidirectional admixture (introgression). Isolation with migration models provide a general theoretical framework for studying speciation. Alternative modes of divergence can be described by alternative isolation with migration models, such as models with no gene flow, secondary contact and migration followed by isolation. A full portrait of the divergence processes can be obtained via the likelihood of a given divergence model. Currently, there are two main families of likelihood-based approaches to studying divergence: allele frequency spectrum (AFS) and genealogy-based approaches. One of the major limitations of current likelihood methods arises when trying to model intermediate levels of recombination explicitly, thus great advances in population genomic inference could be achieved with a comprehensive model of recombination and population divergence. These areas are already undergoing active research, especially in the quest for finding good approximations for the likelihoods of complex demographic models. Genome-wide data hold the key to answering long-standing questions about the mechanisms of speciation, including the role of gene flow. Here, the authors discuss recently developed methods to analyse genome-wide data and consider emerging results from their recent application. As it becomes easier to sequence multiple genomes from closely related species, evolutionary biologists working on speciation are struggling to get the most out of very large population genomic data sets. Such data hold the potential to resolve long-standing questions in evolutionary biology about the role of gene exchange in species formation. In principle, the new population genomic data can be used to disentangle the conflicting roles of natural selection and gene flow during the divergence process. However, there are great challenges in taking full advantage of such data, especially with regard to including recombination in genetic models of the divergence process. Current data, models, methods and the potential pitfalls in using them will be considered here.