Introduction to population genomics methods
Résumé
High-throughput sequencing technologies have provided an unprecedented opportunity to study the different evolutionary forces that have shaped present-day patterns of genetic diversity, with important implications for many directions in plant biology research. To manage such massive quantities of sequencing data, biologists however need new additional skills in informatics and statistics. In this chapter, our objective is to introduce population genomics methods to beginners following a learning-by-doing strategy in order to help the reader to analyze the sequencing data by themselves. Conducted analyses cover several main area of evolutionary biology, such as an initial description of the evolutionary history of a given species or the identification of genes targeted by natural or artificial selection. In addition to the practical advices, we performed re-analyses of two cases studies with different kind of data: a domesticated cereal (African rice) and a non-domesticated tree species (sessile oak). All the code needed to replicate this work is publicly available on github (https://github.com/ThibaultLeroyFr/Intro2PopGenomics/).
Mots clés
Whole-genome sequencing Pool-seq Nucleotide diversity Molecular evolution genome scans population structure individual artificial and natural selection bioinformatics perseverance
Whole-genome sequencing
Pool-seq
Nucleotide diversity
Molecular evolution
genome scans
population structure
individual
artificial and natural selection
bioinformatics
perseverance