Frontiers in plant science · 2026
Decoding the genetic architecture of seed quality traits in mungbean through quantitative trait loci mapping.
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Ren Chunxiu, Qiao Lipan, Qiao Jiaqi, Sun Huimei, Li Hongjie, Li Bin, Hao Xiaopeng, Yang Fan, Huo Dongao
Аннотация
INTRODUCTION: Mungbean [Vigna radiata (L.) R. Wilczek] has emerged as a highly valued crop owing to its unique functional properties. Improving seed quality represents a major goal in mungbean breeding; however, the systematic identification of quantitative trait loci (QTLs) governing key seed quality traits remains limited.
METHODS: In this study, a recombinant inbred line (RIL) population derived from a cross between Zhonglv1 and HB211 was developed, and phenotypic data were collected across three distinct environments. Three complementary QTL mapping methods-composite interval mapping (CIM), inclusive composite interval mapping (ICIM), and multiple QTL mapping (MQM)-were utilized to detect genomic regions associated with protein, starch, oil, and moisture content.
RESULTS AND DISCUSSION: In total, 162 QTLs were identified, including 44, 30, 43, and 45 QTLs were identified for protein, starch, oil, and moisture content, respectively. Among these, stable QTLs were consistently detected across multiple environments and methods, highlighting their potential utility in breeding applications. The putative candidate genes underlying these robust QTLs were further annotated, providing preliminary insights into the genetic control of seed quality traits. This study establishes a comprehensive genetic framework for future functional studies and the development of improved mungbean varieties with enhanced seed quality.
METHODS: In this study, a recombinant inbred line (RIL) population derived from a cross between Zhonglv1 and HB211 was developed, and phenotypic data were collected across three distinct environments. Three complementary QTL mapping methods-composite interval mapping (CIM), inclusive composite interval mapping (ICIM), and multiple QTL mapping (MQM)-were utilized to detect genomic regions associated with protein, starch, oil, and moisture content.
RESULTS AND DISCUSSION: In total, 162 QTLs were identified, including 44, 30, 43, and 45 QTLs were identified for protein, starch, oil, and moisture content, respectively. Among these, stable QTLs were consistently detected across multiple environments and methods, highlighting their potential utility in breeding applications. The putative candidate genes underlying these robust QTLs were further annotated, providing preliminary insights into the genetic control of seed quality traits. This study establishes a comprehensive genetic framework for future functional studies and the development of improved mungbean varieties with enhanced seed quality.