March 24, 2021

NDSU dry bean researchers earn GENETICS journal award

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A paper co-authored by NDSU dry bean researchers Juan Osorno, Phillip McClean and Rian Lee has been selected as one of the 2020 GENETICS Editors’ Choice Awards.

Osorno leads the dry edible bean breeding project at NDSU. McClean leads the dry beans genetics and genomics program, where Lee is the research specialist. McClean also is the director of the genomics and bioinformatics program at NDSU.

The article is titled “Genetic Associations in Four Decades of Multienvironment Trials Reveal Agronomic Trait Evolution in Common Bean.” The journal’s editorial board chose the articles from a collection of the best GENETICS publications of 2020, called the Spotlight Collection. The award was announced on the “Genes to Genomes” blog for the Genetics Society of America on Feb. 26.

The lead authors of the article are Alice MacQueen and Thomas Juenger from the University of Texas at Austin. Other contributing authors are Jeffrey White from the USDA-ARS in Maricopa, Arizona; Jeremy Schmutz from Hudson-Alpha Institute for Biotechnology in Huntsville, Alabama; Phillip Miklas from the USDA-ARS in Prosser, Washington; and Jim Myers from Oregon State University.

This collaborative effort analyzed almost 40 years of Multi Environment Trials (MET) data from the Cooperative Dry Bean Nursery (CDBN). Historically, the CDBN is among the oldest crop MET studied in the United States. It has been grown for approximately 70 years in the U.S. and Canada, consisting of 20 to 50 entries at about 10 locations each year. Unfortunately, genotypic data for all genotypes tested across the years could not be recovered, so an approximately 40-year subset was evaluated. Although the CDBN was not initially designed to elucidate genetic mechanisms, MET data sets are often much larger than could be duplicated for genetic research and, given proper interpretation, offer valuable insights into the genetics of adaptation across time and space. The CDBN provides a source of phenotypic data across entries, years and locations that is amenable to genetic analysis.

To study stable genetic effects segregating in this MET, MacQueen and colleagues conducted genome-wide association studies across years and locations for 21 CDBN traits and 1.2 million SNP markers for 327 genotypes. The value of this approach was confirmed by the discovery of three candidate genes and genomic regions previously identified. In addition, two large genomic regions with effects on multiple phenotypes were found, supporting a hypothesis of pleiotropic or linked effects that were likely selected by plant breeders to develop a specific crop ideotype. Overall, the results demonstrate that statistical genomics approaches combined with MET phenotypic data can discover significant genetic effects and define genomic regions associated with crop improvement.

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