Join us for the 4th session of the ERGA BioGenome Analyis & Applications Seminars!
Wednesday, December 20th - 12:00 CEST
Inferring demographic history with population genomics: the challenges of Pool-Seq data
The study of natural populations has been revolutionised by Next Generation Sequencing (NGS), which enables us to obtain genome-wide resequencing data from multiple individuals and populations. Such data hold the potential to resolve questions about the evolutionary history of a given species. However, even though we are facing a flood of genomic data, we currently lack tools to analyse such large datasets. We will illustrate how model-based approaches can be useful to reconstruct the past evolutionary history of populations. Given its cost efficiency, resequencing of pooled samples (Pool-seq) is becoming a popular method to assess genome-wide diversity patterns in natural populations. However, Pool-seq is associated with specific sources of noise, such as unequal individual contributions. Consequently, using Pool-seq for the reconstruction of evolutionary history has remained underexplored. We will describe how such specific sources of error can be explicitly modelled to simulate Pool-seq datasets. We will show how simulations of SNPs under different scenarios can be used to aid researchers in defining the sampling design and sequencing effort, as well as estimate relevant demographic history parameters using Approximate Bayesian Computation (ABC). By jointly modelling Pool-seq data, demographic history and the effects of selection due to barrier loci, we illustrate that it is possible to infer demographic history parameters accounting for technical errors associated with Pool-seq. Our simulation study results indicate Pool-seq data allows distinction between general scenarios of ecotype formation (single versus parallel origin), and to infer relevant demographic parameters (e.g., effective sizes, split times). We exemplify the application of our method to Pool-seq data from the rocky-shore gastropod Littorina saxatilis, which became a model system in speciation genetics and ecotype formation. Our results indicate that demographic modelling and inference can be successful based on pool-sequencing using ABC.
Bridging the gap between Pool-Seq data and demographic history inference
Vitor C. Sousa
I conducted my Ph.D. at the Gulbenkian Science Institute (IGC, Oeiras, Portugal) and received my degree from the University of Lisbon in 2010, supervised by Lounès Chikhi and Manuela Coelho. I was then a postdoctoral researcher in Jody Hey’s lab (Rutgers University, New Jersey, USA) from 2010 to 2013, and in Laurent Excoffier’s lab (University of Bern and Swiss Institute of Bioinformatics, Switzerland) from 2013 to 2016. Since 2016 I have been a researcher at cE3c, first as an invited researcher, and from 2017 to 2018 as a Marie Sklodowska-Curie fellow. Since 2020 I am an Assistant Professor at the Department of Animal Biology, University of Lisbon. My research aims at characterising the interplay between demographic processes (e.g. gene flow, bottlenecks, population expansions) and natural selection in the structure and divergence of populations. I am the group leader of the Evolutionary Genetics group at cE3c, working on population genomics, and its applications to speciation, conservation, molecular ecology, and human genetics.
I am a master in Evolutionary and Developmental Biology from the University of Lisbon and I am currently finishing a PhD in Biodiversity, Genetics & Evolution, supervised by Vítor C. Sousa of the Evolutionary Genetics group at cE3c and co-supervised by Dr Rui Faria and Dr. Roger Butlin. During my PhD I developed new tools to model and simulate Pool-seq data and combined those tools with an approximate Bayesian computation framework to investigate scenarios of ecotype formation.