Evolutionary insight from whole-genome sequencing of experimentally evolved microbes

被引:115
|
作者
Dettman, Jeremy R. [1 ,2 ]
Rodrigue, Nicolas [3 ]
Melnyk, Anita H. [1 ,2 ]
Wong, Alex [4 ]
Bailey, Susan F. [1 ,2 ]
Kassen, Rees [1 ,2 ]
机构
[1] Univ Ottawa, Dept Biol, Ottawa, ON K1N 6N5, Canada
[2] Univ Ottawa, Ctr Adv Res Environm Genom, Ottawa, ON K1N 6N5, Canada
[3] Agr & Agri Food Canada, Eastern Cereal & Oilseeds Res Ctr, Ottawa, ON K1A 0C6, Canada
[4] Carleton Univ, Dept Biol, Ottawa, ON K1S 5B6, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
adaptive evolution; evolutionary genomics; experimental evolution; next-generation sequencing; TERM EXPERIMENTAL EVOLUTION; VIVO FLUOROQUINOLONE CONCENTRATIONS; ESCHERICHIA-COLI POPULATIONS; IN-VITRO SELECTION; SACCHAROMYCES-CEREVISIAE; ADAPTIVE EVOLUTION; BENEFICIAL MUTATIONS; ASEXUAL POPULATIONS; NUCLEOTIDE RESOLUTION; REGULATORY MUTATIONS;
D O I
10.1111/j.1365-294X.2012.05484.x
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
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.
引用
收藏
页码:2058 / 2077
页数:20
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