Refining the major-effect QTL and candidate genes associated with grain number per panicle by QTL-seq in rice (Oryza sativa L.)

Abstract

Rice grain yield is a major focus of rice breeding, and with grain number per panicle being a major trait that largely determines overall grain yield. Despite its importance, the genetic architecture and underlying mechanisms governing grain number per panicle are not well understood. In this study, we adopted a whole-genome resequencing-based QTL-seq analysis to trace genomic regions related with grain number per panicle using a mapping population derived from a cross between CB12132 (High grain number) and IET28835 (Low grain number). This approach revealed five candidate genomic regions: qGNPP1.1 (10.40 Mb to 12.76 Mb), qGNPP1.2 (24.61 Mb to 25.33 Mb), qGNPP1.3 (26.57 Mb to 27.26 Mb), qGNPP4.1 (27.70 Mb to 31.34 Mb), and qGNPP5.1 (2.12 Mb to 5.50 Mb) on chromosomes 1, 4, and 5, respectively. Further, we searched for possible candidate genes using a comprehensive approach that included the analysis of gene sequences, functional annotation, and expression patterns. A total of 23 candidate genes, including most possible genes Os01g0292900 (SPL1), Os01g0622000 (OsCUGT1), Os01g0655300 (SDG705), Os04g0615000 (NAL1), Os04g0559800 (SMG2) and Os05g0155200 (ERS2), were identified across the five candidate genomic regions. Collectively, our study results shed light on the genetic mechanisms underlying grain number per panicle in rice and will be helpful for improving grain yield in future rice breeding programs.