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ARS Home » Pacific West Area » Pullman, Washington » Plant Germplasm Introduction and Testing Research » Research » Publications at this Location » Publication #404766
Research Project: Genetic Resource and Information Management for Pulse, Temperate Forage Legume, Oilseed, Vegetable, Grasses, Sugar, Ornamental, and Other Crops

Location: Plant Germplasm Introduction and Testing Research

Title: Identification of QTL for protein and dietary fiber in a Middle American dry bean diversity panel

Author
item Wallace, Lyle
item Coyne, Clarice

Submitted to: ASA-CSSA-SSSA Annual Meeting Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: 10/29/2023
Publication Date: N/A
Citation: N/A

Interpretive Summary: Protein and dietary fiber have significant importance to the health and well-being of people around the world. The protein from common bean is a key source of protein for tens of millions of people around the world, and dietary fiber plays a key role in the health of Americans by providing protection from heart disease and cancer. This study will look at the genetic constituents of protein and dietary fiber production in common bean through a GWAS study, which will help with the breeding of improved varieties of common bean.

Technical Abstract: Plant based protein is critical to food security for tens of millions of people worldwide who rely on legumes as a primary and needed source of protein in the diet due to the expense and unavailability of animal protein. Common bean is also an outstanding source of dietary fiber, which is greatly needed in developed, Western societies where overnutrition, diabetes, heart disease, and colon cancer are common, in part, from a lack of fiber in the diet. In this study, 235 lines from a Middle American dry bean diversity panel were characterized for protein and dietary fiber in replicated plots over two years. Near infrared measurements were taken of harvested seed to determine protein and dietary fiber content. This data, along with genotyping-by-sequencing data, was utilized in a GWAS analysis to identify QTL for these traits. Several GWAS models were tested, including MLM, MLMM, SUPER, and FarmCPU. The best model fit and sensitivity with the least type I and type II statistical errors was found to be the FarmCPU model. The QTL identified with FarmCPU can be readily converted into markers, such as KASP markers, for marker assisted selection in breeding. This research may lead to improved pinto and black bean market classes, which are two of the most eaten market classes of common bean across the world.