Identification of quantitative trait loci for drought tolerance in Bukoba/Kijivu Andean mapping population of common bean.
Theor Appl Genet
; 136(11): 222, 2023 Oct 12.
Article
em En
| MEDLINE
| ID: mdl-37823979
KEY MESSAGE: Quantitative Trait Loci "hotspots" for drought tolerance were identified on chromosomes Pv06, Pv07 and Pv10 of common bean. Drought is a major production constraint of common bean (Phaseolus vulgaris L.) worldwide. The objective of this study was to identify the Quantitative Trait Loci (QTL) for drought tolerance in an Andean population of Recombinant Inbred Lines (RILs). A total of 155 F5:7 RILs derived from a cross between Kijivu (drought tolerant) and Bukoba (drought susceptible) were evaluated for drought tolerance in field and pot experiments. Four field experiments were conducted at three locations in Zambia in 2020 and 2021. All field trials were conducted in the dry season under irrigation. The 155 RILs were genotyped with 11,292 SNPs, and composite interval mapping was conducted to identify QTL for drought tolerance. Seed yield for Kijivu under drought stress was consistently higher than for Bukoba across all four field trials. A total of 60 QTL were identified for morphological, agronomic, and physiological traits under drought stress and non-stress conditions. However, the majority of these QTL were specific to drought stress. QTL "hotspots" for drought tolerance were identified on chromosomes Pv06, Pv07, and Pv10. Extensive co-localizations for agronomic and morpho-physiological traits under drought stress were observed at the three drought-tolerance QTL hotspots. Additionally, these three QTL hotspots overlapped with previously identified QTL for drought tolerance, while several others identified QTL are novel. The three identified QTL hotspots could be used in future marker-assisted selection for drought tolerance in common bean.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Phaseolus
/
Locos de Características Quantitativas
Tipo de estudo:
Diagnostic_studies
Idioma:
En
Ano de publicação:
2023
Tipo de documento:
Article