Combining population genomics and fitness QTLs to identify the genetics of local adaptation in Arabidopsis thaliana

Nicholas Price, Brook T. Moyers, Lua Lopez, Jesse R. Lasky, J. Grey Monroe, Jack L. Mullen, Christopher G. Oakley, Junjiang Lin, Jon Ågren, Daniel R. Schrider, Andrew D. Kern, John K. McKay

Research output: Contribution to journalArticlepeer-review

19 Scopus citations

Abstract

Evidence for adaptation to different climates in the model species Arabidopsis thaliana is seen in reciprocal transplant experiments, but the genetic basis of this adaptation remains poorly understood. Field-based quantitative trait locus (QTL) studies provide direct but low-resolution evidence for the genetic basis of local adaptation. Using high-resolution population genomic approaches, we examine local adaptation along previously identified genetic trade-off (GT) and conditionally neutral (CN) QTLs for fitness between locally adapted Italian and Swedish A. thaliana populations [Ågren J, et al. (2013) Proc Natl Acad Sci USA 110:21077–21082]. We find that genomic regions enriched in high FST SNPs colocalize with GT QTL peaks. Many of these high FST regions also colocalize with regions enriched for SNPs significantly correlated to climate in Eurasia and evidence of recent selective sweeps in Sweden. Examining unfolded site frequency spectra across genes containing high FST SNPs suggests GTs may be due to more recent adaptation in Sweden than Italy. Finally, we collapse a list of thousands of genes spanning GT QTLs to 42 genes that likely underlie the observed GTs and explore potential biological processes driving these tradeoffs, from protein phosphorylation, to seed dormancy and longevity. Our analyses link population genomic analyses and field-based QTL studies of local adaptation, and emphasize that GTs play an important role in the process of local adaptation.

Original languageEnglish (US)
Pages (from-to)5028-5033
Number of pages6
JournalProceedings of the National Academy of Sciences of the United States of America
Volume115
Issue number19
DOIs
StatePublished - May 8 2018

All Science Journal Classification (ASJC) codes

  • General

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