Abstract
Current methods for studying the genetic basis of adaptation evaluate genetic associations with ecologically relevant traits or single environmental variables, under the implicit assumption that natural selection imposes correlations between phenotypes, environments and genotypes. In practice, observed trait and environmental data are manifestations of unknown selective forces and are only indirectly associated with adaptive genetic variation. In theory, improved estimation of these forces could enable more powerful detection of loci under selection. Here we present an approach in which we approximate adaptive variation by modeling phenotypes as a function of the environment and using the predicted trait in multivariate and univariate genome-wide association analysis (GWAS). Based on computer simulations and published flowering time data from the model plant Arabidopsis thaliana, we find that environmentally predicted traits lead to higher recovery of functional loci in multivariate GWAS and are more strongly correlated to allele frequencies at adaptive loci than individual environmental variables. Our results provide an example of the use of environmental data to obtain independent and meaningful information on adaptive genetic variation.
Highlights
The genetic basis of environmental adaptation in natural and agricultural populations is a topic of growing interest and urgency
Based on computer simulations and published flowering time data from the model plant Arabidopsis thaliana, we find that environmentally predicted traits lead to higher recovery of functional loci in multivariate genome-wide association analysis (GWAS) and are more strongly correlated to allele frequencies at adaptive loci than individual environmental variables
Researchers look for loci whose differences in allelic state correlate with differences in a particular trait or environmental variable such as temperature
Summary
The genetic basis of environmental adaptation in natural and agricultural populations is a topic of growing interest and urgency. The search for adaptive genes involves testing for associations of genomic markers with either ecologically relevant traits measured in common garden experiments [1] [2] [3] [4] or with environmental variables [5] [6] [7] [4] [8]. These two approaches reflect the assumption that traits, environment and genotype are correlated due to natural selection, as is expected under local adaptation [9] [10] [11]. The reliance on single variables means that this method cannot account for more complex relations between traits and the environment and makes limited use of the independent information provided by trait and environmental data
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
