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Revisiting classic clines in Drosophila melanogaster in the age of genomics

  • Indiana University Bloomington

Research output: Contribution to journalReview articlepeer-review

122 Scopus citations

Abstract

Adaptation to spatially varying environments has been studied for decades, but advances in sequencing technology are now enabling researchers to investigate the landscape of genetic variation underlying this adaptation genome wide. In this review we highlight some of the decades-long research on local adaptation in Drosophila melanogaster from well-studied clines in North America and Australia. We explore the evidence for parallel adaptation and identify commonalities in the genes responding to clinal selection across continents as well as discussing instances where patterns differ among clines. We also investigate recent studies utilizing whole-genome data to identify clines in D. melanogaster and several other systems. Although connecting segregating genomic variation to variation in phenotypes and fitness remains challenging, clinal genomics is poised to increase our understanding of local adaptation and the selective pressures that drive the extensive phenotypic diversity observed in nature.

Original languageEnglish
Pages (from-to)434-444
Number of pages11
JournalTrends in Genetics
Volume31
Issue number8
DOIs
StatePublished - Aug 1 2015

Funding

The authors thank David Begun and Daniel Schrider for their helpful comments. Discussions with Alisa Sedghifar and Nicolas Svetec improved this review, as did comments from two anonymous reviewers. Funding for J.R.A. came from an Indiana University Genome, Cell, and Developmental Biology Training Grant from the National Institutes of Health (NIH) (T32-GM007757) and a National Science Foundation Graduate Research Fellowship (1342962). B.S.C. was supported by a National Research Service Award from the National Institute of Allergy and Infectious Diseases of the NIH (F32-AI114176).

Funder number
1342962
T32GM007757
F32-AI114176

    Keywords

    • Latitudinal cline
    • Local adaptation
    • Spatially varying selection

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