Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

In the presence of population structure: From genomics to candidate genes underlying local adaptation

Nicholas Price, Lua Lopez, Adrian E. Platts, Jesse R. Lasky, John K. McKay
doi: https://doi.org/10.1101/642306
Nicholas Price
Department of Bioagricultural Sciences & Pest Management, Colorado State University, Fort Collins, CO 80523, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: price4890@gmail.com
Lua Lopez
Department of Biology, Binghamton University (State University of New York), Binghamton, NY 13902, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Adrian E. Platts
Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USACenter for Genomics and Systems Biology, Department of Biology, New York University, New York 10003
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jesse R. Lasky
Department of Biology, Pennsylvania State University, University Park, PA 16802, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
John K. McKay
Department of Bioagricultural Sciences & Pest Management, Colorado State University, Fort Collins, CO 80523, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Preview PDF
Loading

Abstract

Understanding the genomic signatures, genes, and traits underlying local adaptation of organisms to heterogeneous environments is of central importance to the field evolutionary biology. Mixed linear models that identify allele associations to environment, while controlling for genome-wide variation at other loci, have emerged as the method of choice when studying local adaptation. Despite their importance, it is unclear whether this approach performs better than identifying environmentally-associated SNPs without accounting for population structure. To examine this, we first use the mixed linear model GEMMA, and simple Spearman correlations, to identify SNPs showing significant associations to climate with and without accounting for population structure. Subsequently, using Italy and Sweden populations, we compare evidence of allele frequency differentiation (FST), linkage disequilibrium Embedded Image, fitness variation, and functional constraint, underlying these SNPs. Using a lenient cut-off for significance, we find that SNPs identified by both approaches, and SNPs uniquely identified by Spearman correlations, were enriched at sites showing genomic evidence of local adaptation and function but were limited across Quantitative Trait Loci (QTL) explaining fitness variation. SNPs uniquely identified by GEMMA, showed no direct or indirect evidence of local adaptation, and no enrichment along putative functional sites. Finally, SNPs that showed significantly high FST and LD, were enriched along fitness QTL peaks and cis-regulatory/nonsynonymous sites showing significant functional constraint. Using these SNPs, we identify genes underlying fitness QTL, and genes linking flowering time to local adaptation. These include a negative regulator of abscisic-acid (FLDH) and flowering time genes PIF3, FIO1, and COL5.

Footnotes

  • author name correction

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
Back to top
PreviousNext
Posted May 21, 2019.
Download PDF

Supplementary Material

Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
In the presence of population structure: From genomics to candidate genes underlying local adaptation
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
Share
In the presence of population structure: From genomics to candidate genes underlying local adaptation
Nicholas Price, Lua Lopez, Adrian E. Platts, Jesse R. Lasky, John K. McKay
bioRxiv 642306; doi: https://doi.org/10.1101/642306
Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
Citation Tools
In the presence of population structure: From genomics to candidate genes underlying local adaptation
Nicholas Price, Lua Lopez, Adrian E. Platts, Jesse R. Lasky, John K. McKay
bioRxiv 642306; doi: https://doi.org/10.1101/642306

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Evolutionary Biology
Subject Areas
All Articles
  • Animal Behavior and Cognition (1544)
  • Biochemistry (2500)
  • Bioengineering (1757)
  • Bioinformatics (9727)
  • Biophysics (3928)
  • Cancer Biology (2990)
  • Cell Biology (4235)
  • Clinical Trials (135)
  • Developmental Biology (2653)
  • Ecology (4129)
  • Epidemiology (2033)
  • Evolutionary Biology (6931)
  • Genetics (5243)
  • Genomics (6531)
  • Immunology (2207)
  • Microbiology (7012)
  • Molecular Biology (2782)
  • Neuroscience (17410)
  • Paleontology (127)
  • Pathology (432)
  • Pharmacology and Toxicology (712)
  • Physiology (1068)
  • Plant Biology (2515)
  • Scientific Communication and Education (647)
  • Synthetic Biology (835)
  • Systems Biology (2698)
  • Zoology (439)