Genome-wide association mapping and agronomic impact of cowpea root architecture

• Published in: Theoretical and applied genetics Vol. 130; no. 2; pp. 419 - 431
• Main Authors: Burridge, James D., Schneider, Hannah M., Huynh, Bao-Lam, Roberts, Philip A., Bucksch, Alexander, Lynch, Jonathan P.
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.02.2017; Springer; Springer Nature B.V
• Subjects: Agriculture; Architecture; Biochemistry; Biomedical and Life Sciences; Biotechnology; breeding; breeding programs; Chromosome Mapping; Corn; cowpeas; crop production; Drought; genetic analysis; Genetic Association Studies; Genetic Markers; genome; genome-wide association study; Genomes; Genomics; Genotype & phenotype; heritability; image analysis; Life Sciences; Models, Genetic; nodulation; Original Article; Phenotype; Plant Biochemistry; Plant Breeding; Plant Breeding/Biotechnology; Plant Genetics and Genomics; Plant Roots - growth & development; Polymorphism, Single Nucleotide; Quantitative genetics; Quantitative Trait Loci; root tips; soil resources; Striga; Striga gesnerioides; Vigna - genetics; Vigna - growth & development; United States > US; Root Crown; Root Architecture; Phene; Quantitative Trait Locus; Root Trait
• DOI: 10.1007/s00122-016-2823-y
• ISSN: 0040-5752

Key message Genetic analysis of data produced by novel root phenotyping tools was used to establish relationships between cowpea root traits and performance indicators as well between root traits and Striga tolerance. Selection and breeding for better root phenotypes can improve acquisition of soil resources and hence crop production in marginal environments. We hypothesized that biologically relevant variation is measurable in cowpea root architecture. This study implemented manual phenotyping (shovelomics) and automated image phenotyping (DIRT) on a 189-entry diversity panel of cowpea to reveal biologically important variation and genome regions affecting root architecture phenes. Significant variation in root phenes was found and relatively high heritabilities were detected for root traits assessed manually (0.4 for nodulation and 0.8 for number of larger laterals) as well as repeatability traits phenotyped via DIRT (0.5 for a measure of root width and 0.3 for a measure of root tips). Genome-wide association study identified 11 significant quantitative trait loci (QTL) from manually scored root architecture traits and 21 QTL from root architecture traits phenotyped by DIRT image analysis. Subsequent comparisons of results from this root study with other field studies revealed QTL co-localizations between root traits and performance indicators including seed weight per plant, pod number, and Striga ( Striga gesnerioides ) tolerance. The data suggest selection for root phenotypes could be employed by breeding programs to improve production in multiple constraint environments.