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dc.contributor.author
Luqman, Hirzi
dc.contributor.author
Widmer, Alex
dc.contributor.author
Fior, Simone
dc.contributor.author
Wegmann, Daniel
dc.date.accessioned
2021-07-20T15:47:42Z
dc.date.available
2021-07-15T10:26:24Z
dc.date.available
2021-07-20T15:47:42Z
dc.date.issued
2021
dc.identifier.issn
1755-098X
dc.identifier.issn
1471-8278
dc.identifier.issn
1755-0998
dc.identifier.issn
1471-8286
dc.identifier.issn
1755-0998 1471-8286
dc.identifier.other
10.1111/1755-0998.13415
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/494861
dc.description.abstract
Adaptive genetic variation is a function of both selective and neutral forces. To accurately identify adaptive loci, it is thus critical to account for demographic history. Theory suggests that signatures of selection can be inferred using the coalescent, following the premise that genealogies of selected loci deviate from neutral expectations. Here, we build on this theory to develop an analytical framework to identify loci under selection via explicit demographic models (LSD). Under this framework, signatures of selection are inferred through deviations in demographic parameters, rather than through summary statistics directly, and demographic history is accounted for explicitly. Leveraging the property of demographic models to incorporate directionality, we show that LSD can provide information on the environment in which selection acts on a population. This can prove useful in elucidating the selective processes underlying local adaptation, by characterizing genetic trade-offs and extending the concepts of antagonistic pleiotropy and conditional neutrality from ecological theory to practical application in genomic data. We implement LSD via approximate Bayesian computation and demonstrate, via simulations, that LSD (a) has high power to identify selected loci across a large range of demographic-selection regimes, (b) outperforms commonly applied genome-scan methods under complex demographies and (c) accurately infers the directionality of selection for identified candidates. Using the same simulations, we further characterize the behaviour of isolation-with-migration models conducive to the study of local adaptation under regimes of selection. Finally, we demonstrate an application of LSD by detecting loci and characterizing genetic trade-offs underlying flower colour in Antirrhinum majus.
en_US
dc.language.iso
en
en_US
dc.publisher
Wiley
en_US
dc.subject
approximate Bayesian computation
en_US
dc.subject
demography
en_US
dc.subject
genetic trade-offs
en_US
dc.subject
genome scan
en_US
dc.subject
local adaptation
en_US
dc.subject
selection
en_US
dc.title
Identifying loci under selection via explicit demographic models
en_US
dc.type
Journal Article
dc.date.published
2021-05-08
ethz.journal.title
Molecular Ecology Resources
ethz.journal.abbreviated
Mol. ecol. resour.
ethz.size
19 p.
en_US
ethz.grant
Genomics of adaptation in the context of a rapid plant radiation
en_US
ethz.grant
Ecological Genomics of Plant Adaptation
en_US
ethz.identifier.wos
ethz.publication.place
Chichester
en_US
ethz.publication.status
published
en_US
ethz.grant.agreementno
160123
ethz.grant.agreementno
182675
ethz.grant.fundername
SNF
ethz.grant.fundername
SNF
ethz.grant.funderDoi
10.13039/501100001711
ethz.grant.funderDoi
10.13039/501100001711
ethz.grant.program
Projektförderung in Biologie und Medizin (Abteilung III)
ethz.grant.program
Projektförderung in Biologie und Medizin (Abteilung III)
ethz.date.deposited
2021-07-15T10:27:34Z
ethz.source
WOS
ethz.eth
yes
en_US
ethz.availability
Metadata only
en_US
ethz.rosetta.exportRequired
true
ethz.COinS
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