Detecting Adaptive Differentiation in Structured Populations with Genomic Data and Common Gardens

Area of Science:

• Evolutionary genetics
• Quantitative genetics
• Genomics

Background:

• Polygenic adaptation, driven by allele frequency shifts at numerous loci, is a key evolutionary process.
• Existing methods for detecting polygenic adaptation are primarily focused on human populations, limiting applications in other systems.
• There is a need for novel methodologies to identify important quantitative traits for adaptation using genomic and phenotypic data.

Purpose of the Study:

• To develop and validate new statistical methods for detecting polygenic adaptation.
• To identify specific quantitative traits contributing to adaptation in maize.
• To assess the importance of polygenic adaptation in shaping trait variation across species.

Main Methods:

• Utilized principal components of the relatedness matrix to detect divergence indicative of polygenic adaptation.
• Employed a conditional test to account for and mitigate confounding effects of population structure.
• Applied the developed methods to genomic and common garden trait data from maize lines and landraces.

Main Results:

• Successfully detected patterns of excess divergence consistent with polygenic adaptation in maize.
• Identified specific quantitative traits under selection in the studied maize populations.
• Demonstrated the utility of the new methods in a non-human system.

Conclusions:

• The developed methods provide a robust framework for detecting polygenic adaptation in diverse species.
• These tools can enhance our understanding of the genetic basis of adaptation and the role of polygenic adaptation.
• Future applications can broaden the scope of polygenic adaptation studies in both wild and domesticated species.