Genetic signatures of natural selection in a model invasive ascidian
Genetic signatures of natural selection in a model invasive ascidian
Invasive species represent promising models to study species’ responses to rapidly changing environments. Although local adaptation frequently occurs during contemporary range expansion, the associated genetic signatures at both population and genomic levels remain largely unknown. Here, we use genome-wide gene-associated microsatellites to investigate genetic signatures of natural selection in a model invasive ascidian, Ciona robusta. Population genetic analyses of 150 individuals sampled in Korea, New Zealand, South Africa and Spain showed significant genetic differentiation among populations. Based on outlier tests, we found high incidence of signatures of directional selection at 19 loci. Hitchhiking mapping analyses identified 12 directional selective sweep regions, and all selective sweep windows on chromosomes were narrow (~8.9 kb). Further analyses indentified 132 candidate genes under selection. When we compared our genetic data and six crucial environmental variables, 16 putatively selected loci showed significant correlation with these environmental variables. This suggests that the local environmental conditions have left significant signatures of selection at both population and genomic levels. Finally, we identified “plastic” genomic regions and genes that are promising regions to investigate evolutionary responses to rapid environmental change in C. robusta.
Lin, Yaping
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Chen, Yiyong
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Yi, Changho
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Fong, Jonathan J.
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Kim, Won
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Rius, Marc
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Zhan, Aibin
85979af1-e6a9-477d-8b59-252ea3528730
7 March 2017
Lin, Yaping
dc06f4b2-d223-408a-8e4d-b1c9f858ed04
Chen, Yiyong
dc9bb800-55e6-41c1-8066-3401ca9eebfb
Yi, Changho
8d5febbe-28d0-4bef-95f1-d13c38527b26
Fong, Jonathan J.
0810c8e5-e778-49ec-add6-6b49c4c01bea
Kim, Won
e529b4ac-fc75-40c6-a778-ba37dcea83ae
Rius, Marc
c4e88345-4b4e-4428-b4b2-37229155f68d
Zhan, Aibin
85979af1-e6a9-477d-8b59-252ea3528730
Lin, Yaping, Chen, Yiyong, Yi, Changho, Fong, Jonathan J., Kim, Won, Rius, Marc and Zhan, Aibin
(2017)
Genetic signatures of natural selection in a model invasive ascidian.
Scientific Reports, 7, [44080].
(doi:10.1038/srep44080).
Abstract
Invasive species represent promising models to study species’ responses to rapidly changing environments. Although local adaptation frequently occurs during contemporary range expansion, the associated genetic signatures at both population and genomic levels remain largely unknown. Here, we use genome-wide gene-associated microsatellites to investigate genetic signatures of natural selection in a model invasive ascidian, Ciona robusta. Population genetic analyses of 150 individuals sampled in Korea, New Zealand, South Africa and Spain showed significant genetic differentiation among populations. Based on outlier tests, we found high incidence of signatures of directional selection at 19 loci. Hitchhiking mapping analyses identified 12 directional selective sweep regions, and all selective sweep windows on chromosomes were narrow (~8.9 kb). Further analyses indentified 132 candidate genes under selection. When we compared our genetic data and six crucial environmental variables, 16 putatively selected loci showed significant correlation with these environmental variables. This suggests that the local environmental conditions have left significant signatures of selection at both population and genomic levels. Finally, we identified “plastic” genomic regions and genes that are promising regions to investigate evolutionary responses to rapid environmental change in C. robusta.
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srep44080
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Accepted/In Press date: 7 February 2017
e-pub ahead of print date: 7 March 2017
Published date: 7 March 2017
Organisations:
Marine Biology & Ecology
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Local EPrints ID: 406836
URI: http://eprints.soton.ac.uk/id/eprint/406836
ISSN: 2045-2322
PURE UUID: e7271c7a-f870-4eb0-b0fb-9d7aef6853d0
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Date deposited: 24 Mar 2017 02:02
Last modified: 15 Mar 2024 12:54
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Author:
Yaping Lin
Author:
Yiyong Chen
Author:
Changho Yi
Author:
Jonathan J. Fong
Author:
Won Kim
Author:
Aibin Zhan
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