Complex patterns of local adaptation in teosinte

TL;DR

This study investigates the genetic basis of local adaptation in teosinte, revealing complex hierarchical structure, the role of inversions and noncoding regions, and highlighting the importance of considering population structure in adaptive locus identification.

Contribution

It provides a comprehensive genome-wide analysis of local adaptation in teosinte, emphasizing the significance of inversions and noncoding regions, and discusses implications for plant genome adaptation studies.

Findings

Identification of four mega-base scale inversions with altitudinal clines

Inversions and non-genic regions are key to local adaptation

Population structure biases adaptive locus detection

Abstract

Populations of widely distributed species often encounter and adapt to specific environmental conditions. However, comprehensive characterization of the genetic basis of adaptation is demanding, requiring genome-wide genotype data, multiple sampled populations, and a good understanding of population structure. We have used environmental and high-density genotype data to describe the genetic basis of local adaptation in 21 populations of teosinte, the wild ancestor of maize. We found that altitude, dispersal events and admixture among subspecies formed a complex hierarchical genetic structure within teosinte. Patterns of linkage disequilibrium revealed four mega-base scale inversions that segregated among populations and had altitudinal clines. Based on patterns of differentiation and correlation with environmental variation, inversions and nongenic regions play an important role in local adaptation of teosinte. Further, we note that strongly differentiated individual populations can bias the identification of adaptive loci. The role of inversions in local adaptation has been predicted by theory and requires attention as genome-wide data become available for additional plant species. These results also suggest a potentially important role for noncoding variation, especially in large plant genomes in which the gene space represents a fraction of the entire genome.