Work

Finding the genetic basis of adaptation: reducing complexity to improve trait mapping

Year: 2026

Type: review

Abstract: Genome-wide association studies (GWAS) have advanced our understanding of trait variation, yet persistent challenges limit their effectiveness in mapping adaptive traits. Population structure, allelic heterogeneity, trait complexity, and structural variation obscure true causal relationships. However, these factors can often be addressed through strategic simplification. Here, we review factors limiting GWAS success in natural populations and show that reducing complexity improves mapping outcomes. We examine how local population mapping, trait decomposition into endophenotypes, and incorporation of structural variation enable the identification of adaptive loci. Using Arabidopsis thaliana as a model system, we demonstrate how these approaches reveal functionally validated variants missed by traditional studies. Finally, we discuss integration strategies and emerging technologies that will advance our understanding of the genetics of adaptation. • Wild populations of models bridge molecular, developmental, and ecological knowledge. • Mapping using natural populations can identify adaptively evolving loci. • Mapping at the local geographic scale can reduce confounding and improve power. • Trait decomposition to endophenotypes improves genetic mapping resolution. • Structural variation is emerging as an important source of adaptive variation.

Source: Current Opinion in Genetics & Development

DOI: 10.1016/j.gde.2025.102432

Authors: Yulia Yarkhunova-Kreye, Angela M Hancock

Institutions: Max Planck Institute for Plant Breeding Research, University of Cologne

Language: English

Topic: Genetic Mapping and Diversity in Plants and Animals

Subfield: Genetics

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: hybrid

Estimated APC paid: $4,200

Funder: Deutsche Forschungsgemeinschaft