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Multienvironment trials (METs) are widely used to assess the performance of promising crop germplasm. Though seldom designed to elucidate genetic mechanisms, MET data sets are often much larger than could be duplicated for genetic research and, given proper interpretation, may offer valuable insights into the genetics of adaptation across time and space. The Cooperative Dry Bean Nursery (CDBN) is a MET for common bean ( Phaseolus vulgaris ) grown for > 70 years in the United States and Canada, consisting of 20-50 entries each year at 10-20 locations. The CDBN provides a rich source of phenotypic data across entries, years, and locations that is amenable to genetic analysis. To study stable genetic effects segregating in this MET, we conducted genome-wide association studies (GWAS) using best linear unbiased predictions derived across years and locations for 21 CDBN phenotypes and genotypic data (1.2 million SNPs) for 327 CDBN genotypes. The value of this approach was confirmed by the discovery of three candidate genes and genomic regions previously identified in balanced GWAS. Multivariate adaptive shrinkage (mash) analysis, which increased our power to detect significant correlated effects, found significant effects for all phenotypes. Mash found two large genomic regions with effects on multiple phenotypes, supporting a hypothesis of pleiotropic or linked effects that were likely selected on in pursuit of a crop ideotype. Overall, our results demonstrate that statistical genomics approaches can be used on MET phenotypic data to discover significant genetic effects and to define genomic regions associated with crop improvement., (Copyright © 2020 MacQueen et al.)

The genetic improvement of economically important production traits of dry bean ( Phaseolus vulgaris L.), for geographic regions where production is threatened by drought and high temperature stress, is challenging because of the complex genetic nature of these traits. Large scale SNP data sets for the two major gene pools of bean, Andean and Middle American, were developed by mapping multiple pools of genotype-by-sequencing reads and identifying over 200k SNPs for each gene pool against the most recent assembly of the P. vulgaris genome sequence. Moderately sized B ean A biotic S tress E valuation (BASE) panels, consisting of genotypes appropriate for production in Central America and Africa, were assembled. Phylogenetic analyses demonstrated the BASE populations represented broad genetic diversity for the appropriate races within the two gene pools. Joint mixed linear model genome-wide association studies with data from multiple locations discovered genetic factors associated with four production traits in both heat and drought stress environments using the BASE panels. Pleiotropic genetic factors were discovered using a multi-trait mixed model analysis. SNPs within or near candidate genes associated with hormone signaling, epigenetic regulation, and ROS detoxification under stress conditions were identified and can be used as genetic markers in dry bean breeding programs., (Copyright © 2019 Oladzad et al.)