Genetic Diversity, Population Structure, and Association Mapping of 10 Agronomic Traits in Sesame. Issue 1 (1st January 2016)

• Record Type: Journal Article
• Authors: Wei, Wenliang; Zhang, Yanxin; Wang, Linhai; Li, Donghua; Gao, Yuan; Zhang, Xiurong
• Is Part Of: Crop science. Volume 56:Issue 1(2016)
• Page Start: 331
• Page End: 343
• Publication Date: 2016-01-01
• Subjects: Crop science -- Periodicals; Cultures -- Périodiques; Cultures de plein champ -- Périodiques; Crop science; Nutzpflanzen; Zeitschrift; Pflanzenbau; Periodicals; 633
• DOI: 10.2135/cropsci2015.03.0153
• Languages: English
• ISSNs: 0011-183X

Abstract

ABSTRACT: To improve efficiency in sesame ( Sesamum indicum L.) breeding, it is important to understand the genetic basis and relatedness of advanced varieties developed during the past decades and to identify molecular markers associated with quantitative traits of agronomic importance. Seed yield and traits that contribute to yield are strongly influenced by traits related to plant height, but little is known about the genetic basis of height‐related traits in sesame. A sesame association panel was phenotyped in multienvironment trials and fingerprinted with 44 markers to conduct genetic diversity analysis and association mapping of four height‐related traits and six yield‐related traits. Population structure analyses revealed two subgroups within the panel. The Q model performed better in terms of controlling false associations than the mixed models and identified a total of 92 marker associations with these 10 traits in three environments at P < 0.01. Eleven markers were identified as linked to three height‐related traits and three yield‐related traits in more than one environment. Further, three markers (ID24, SSI259, and ZZM452) were simultaneously associated with multiple traits in different environments with stable and pleiotropic effects. In each of the three environments, ID71 was stably associated with the number of seeds per capsule and ZZM452 was associated with thousand‐seed weight. These results suggest that the relatively abundant diversity in this sesame association panel together with the power of the Q model are useful for association analysis of agronomic traits in sesame. The associations of markers with these traits will benefit marker‐assisted selection in sesame after further validation.