Identifying candidate alleles and landraces for adaptation of domesticated common bean (Phaseolus vulgaris L.) to heat and drought using an envGWAS approach - Correa, Miguel; Ospina, Jessica; Franco, Jorge; Sonder, Kai; Wenzl, Peter; Carvajal Yepes, Monica (2025)
The Alliance Bioversity International-CIAT is the keeper of a worldwide collection of bean germplasm from around the world which contains ca. 38,000 accessions from the genus Phaseolus. The germplasm bank represents a vast source of novel and underutilized genetic variation that is key for present and future breeding efforts, particularly under the current scenarios of climate change, in which changes in average temperature and precipitation are expected. One way to characterize and facilitate access to crop diversity is by genotyping the collection, which would allow us to assess the diversity, perform association studies, and identify possible redundancies in the collection. The present work presents the progress of a large-scale allele mining effort in which 10,000 common bean landraces (P. vulgaris L.) are being genotyped to identify genome regions and alleles associated with adaptation to high temperatures and low precipitation by using climate data from their sites of origin through an environmental Genome-Wide Association Study (envGWAS). Currently, we have extracted the DNA of over 8,100 accessions using a modified CTAB extraction protocol and genotyped 5,084 accessions on the DArT-seq platform. DArT-seq enables calling both co-dominant Single Nucleotide Polymorphisms (SNPs) and presence/absence markers (SilicoDArTs). By estimating genetic distances and admixture coefficients, we assigned landraces to either the Andean or Mesoamerican common-bean genepools, while identifying accessions derived from crosses between the pools. Climate and soil variables from the collection sites of a subset of 8,185 accessions with quality georeferencing data were extracted from publicly available databases. We estimated the growing season based on average monthly precipitation data and performed a clustering analysis to group accessions into environments. Using the preliminary genetic and environmental datasets, we tested two envGWAS models: BLINK and lfmm2. Preliminary results point to significant marker-environment associations, in addition to associations specific to the Andean and Mesoamerican genepools.