Plant adaptation and speciation studied by population genomic approaches.

Autor: Bamba M; Department of Biology (Frontier Science Program), Graduate School of Science and Engineering, Chiba University, Chiba, Japan., Kawaguchi YW; Department of Biology (Frontier Science Program), Graduate School of Science and Engineering, Chiba University, Chiba, Japan., Tsuchimatsu T; Department of Biology, Graduate School of Science, Chiba University, Chiba, Japan.
Jazyk: angličtina
Zdroj: Development, growth & differentiation [Dev Growth Differ] 2019 Jan; Vol. 61 (1), pp. 12-24. Date of Electronic Publication: 2018 Nov 25.
DOI: 10.1111/dgd.12578
Abstrakt: Ever since Darwin, one of the major challenges in evolutionary biology is to unravel the process and mechanisms of adaptation and speciation. Population genomics-the analysis of whole-genome polymorphism data from large population samples-is a critical approach to study adaptation and speciation, as population genomics datasets enable us to: (1) perform genome-wide association studies (GWAS) to find genes underlying adaptive phenotypic variations; (2) scan the footprints of selection across the genome to pinpoint loci under selection; and (3) infer the structure and demographic history of populations. Here, we review recent studies of plants using population genomics, covering those focusing on interactions with other organisms, adaptations to local climatic conditions, and the genomic causes and consequences of reproductive isolation. Integrative studies involving GWAS, selection scans, functional studies, and fitness measurements in the field have successfully identified loci for adaptation, revealed the molecular basis of genetic trade-offs, and shown that fitness can be predicted by polygenic effects of a number of loci associated with local climate. We highlight the importance of the measurement of fitness and phenotypes in the field, which can be powerful tools when combined with population genomic analyses.
(© 2018 Japanese Society of Developmental Biologists.)
Databáze: MEDLINE
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