PJB-2020-177
Association mapping of economic traits based on QTL clusters/hotspots linked SSR markers in Upland cotton.
Muhammad Atif Wahid
Abstract
Cotton productivity has decreased over last decade owing to various agronomic factors including narrow genetic base of cultivated Upland cotton. Natural diversity conserved in the germplasm could be dissected by linkage disequilibrium (LD)-based association mapping. To date, numerous QTL clusters/hotspots have been detected based on meta-analyses. In this study, QTL clusters/hotspots-linked simple sequence repeat (SSR) markers were employed to validate QTL effects in 503 Upland cotton accessions using association mapping, so that these markers could be efficiently employed in marker-assisted breeding programs. Among 298 clusters/hotspots-linked SSRs, 72 polymorphic ones were utilized to explore genetic variation and linkage disequilibrium (LD) decay in the diverse set of 503 cultivars. Association mapping using generalized linear model (GLM) approach detected 23 significant loci associated with 14 economic traits. These markers were relegated to forty-eight QTL clusters which were widely distributed on 17 chromosomes. Amongst them, 6 QTL hotspots and 22 meta-QTL were associated to different traits. The significantly associated markers identified through association mapping will facilitate substantial gains in marker-assisted breeding and further research on QTL fine mapping and candidate gene prediction.
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