Evolutionary insight from whole-genome sequencing of experimentally evolved microbes

• Published in: Molecular ecology 2012-05, Vol.21 (9), p.2058-2077
• Main Authors: DETTMAN, JEREMY R., RODRIGUE, NICOLAS, MELNYK, ANITA H., WONG, ALEX, BAILEY, SUSAN F., KASSEN, REES
• Format: Article
• Language: English
• Subjects: adaptive evolution; Bacteria - genetics; Chromosome Mapping; Chromosomes, Bacterial; Chromosomes, Fungal; Directed Molecular Evolution; Evolution, Molecular; Evolutionary biology; evolutionary genomics; experimental evolution; Fungi - genetics; Genes; Genome, Bacterial; Genome, Fungal; Genomes; High-Throughput Nucleotide Sequencing; next-generation sequencing; Sequence Analysis, DNA
• ISSN: 0962-1083; 1365-294X
• DOI: 10.1111/j.1365-294X.2012.05484.x

Experimental evolution (EE) combined with whole‐genome sequencing (WGS) has become a compelling approach to study the fundamental mechanisms and processes that drive evolution. Most EE‐WGS studies published to date have used microbes, owing to their ease of propagation and manipulation in the laboratory and relatively small genome sizes. These experiments are particularly suited to answer long‐standing questions such as: How many mutations underlie adaptive evolution, and how are they distributed across the genome and through time? Are there general rules or principles governing which genes contribute to adaptation, and are certain kinds of genes more likely to be targets than others? How common is epistasis among adaptive mutations, and what does this reveal about the variety of genetic routes to adaptation? How common is parallel evolution, where the same mutations evolve repeatedly and independently in response to similar selective pressures? Here, we summarize the significant findings of this body of work, identify important emerging trends and propose promising directions for future research. We also outline an example of a computational pipeline for use in EE‐WGS studies, based on freely available bioinformatics tools.