Abstract
Population genomics is advancing our understanding of evolution, ecology, conservation, agriculture, forestry, and human health by allowing new and long-standing questions to be addressed with unprecedented power and accuracy. These advances result from plummeting costs for DNA sequencing, which makes genotyping feasible for hundreds to millions of individuals and loci, and also allows for the study of variation in gene expression, epigenetic variation, and proteins. The increased power also results from the development of innovative software, statistical approaches, and models to extract information from massive next-generation sequencing datasets. Among the most exciting developments are conceptually novel approaches that are advancing understanding about inbreeding and outbreeding depression, adaptive gene flow, population demographic history, and the genomic basis of local adaptation and speciation. Remaining challenges in applying genomics to natural and managed populations include the limited understanding and availability of validated bioinformatics pipelines for genotyping and analyzing genomic data. We also lack knowledge of best practices and general guidelines for filtering and genotyping genomic data including restriction site-associated DNA sequences (RAD), targeted DNA capture, and pooled sequencing. Finally, we emphasize the need for continued rigorous teaching of population genetics theory, so that the next generation of population genomicists can ask well-informed questions and interpret next-generation sequence datasets.
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Acknowledgments
We thank G. McKinney for helpful comments and information on linkage mapping and Fred Allendorf for discussions and ideas regarding population genomics concepts and definitions. GL, MK, and BKH were supported in part by funding from US National Science Foundation grants DEB-1258203 and DoB-1639014. Montana Fish Wildlife and Parks provided supported GL and MK through contract #199101903. GL and BKH were also supported in part by funding from NASA grant number NNX14AB84G. OPR received support from a Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Grant RGPIN 2017-04589. PAH received support from National Science Foundation grants DEB-1316549 and DEB-1655809.
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Luikart, G., Kardos, M., Hand, B.K., Rajora, O.P., Aitken, S.N., Hohenlohe, P.A. (2018). Population Genomics: Advancing Understanding of Nature. In: Rajora, O. (eds) Population Genomics. Population Genomics. Springer, Cham. https://doi.org/10.1007/13836_2018_60
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