Population genomics of marine fishes: identifying adaptive variation in space and time.
Studies of adaptive evolution have experienced a recent revival in population genetics of natural populations and there is currently much focus on identifying genomic signatures of selection in space and time. Insights into local adaptation, adaptive response to global change and evolutionary consequences of selective harvesting can be generated through population genomics studies, allowing the separation of the effects invoked by neutral processes (drift-migration) from those due to selection. Such knowledge is important not only for improving our basic understanding of natural as well as human-induced evolutionary processes, but also for predicting future trajectories of biodiversity and for setting conservation priorities. Marine fishes possess a number of features rendering them well suited for providing general insights into adaptive genomic evolution in natural populations. These include well-described population structures, substantial and rapidly developing genomic resources and abundant archived samples enabling temporal studies. Furthermore, superior possibilities for conducting large-scale experiments under controlled conditions, due to the economic resources provided by the large and growing aquaculture industry, hold great promise for utilizing recent technological developments. Here, we review achievements in marine fish genomics to date and highlight potential avenues for future research, which will provide both general insights into evolution in high gene flow species, as well as specific knowledge which can lead to improved management of marine organisms.
Nielsen
Einar E
EE
Technical University of Denmark, National Institute of Aquatic Resources, Vejlsøvej 39, Silkeborg, Denmark. een@aqua.dtu.dk
Hemmer-Hansen
Jakob
J
Larsen
Peter Foged
PF
Bekkevold
Dorte
D
D000222:Adaptation, Physiological / Q000235:genetics; D000818:Animals; D019143:Evolution, Molecular; D005399:Fishes / Q000235:genetics*; D020869:Gene Expression Profiling; D014644:Genetic Variation; D005828:Genetics, Population; D023281:Genomics; D040641:Quantitative Trait Loci