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Evolutionary Applications
Article . 2016 . Peer-reviewed
License: CC BY
Data sources: Crossref
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Evolutionary Applications
Article
License: CC BY
Data sources: UnpayWall
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PubMed Central
Other literature type . 2016
Data sources: PubMed Central
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Genomics advances the study of inbreeding depression in the wild

Authors: Kardos, Marty; Taylor, Helen R.; Ellegren, Hans; Luikart, Gordon; Allendorf, Fred W.;

Genomics advances the study of inbreeding depression in the wild

Abstract

AbstractInbreeding depression (reduced fitness of individuals with related parents) has long been a major focus of ecology, evolution, and conservation biology. Despite decades of research, we still have a limited understanding of the strength, underlying genetic mechanisms, and demographic consequences of inbreeding depression in the wild. Studying inbreeding depression in natural populations has been hampered by the inability to precisely measure individual inbreeding. Fortunately, the rapidly increasing availability of high‐throughput sequencing data means it is now feasible to measure the inbreeding of any individual with high precision. Here, we review how genomic data are advancing our understanding of inbreeding depression in the wild. Recent results show that individual inbreeding and inbreeding depression can be measured more precisely with genomic data than via traditional pedigree analysis. Additionally, the availability of genomic data has made it possible to pinpoint loci with large effects contributing to inbreeding depression in wild populations, although this will continue to be a challenging task in many study systems due to low statistical power. Now that reliably measuring individual inbreeding is no longer a limitation, a major focus of future studies should be to more accurately quantify effects of inbreeding depression on population growth and viability.

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    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    250
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
250
Top 1%
Top 10%
Top 1%
Green
gold