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Multi-trait genome-wide association studies reveal novel pleiotropic loci associated with yield and yield-related traits in rice
Chunhai Liu, Chao Wu, Zheming Yuan, Bingchuan Tian, Peiyi Yu, Deze Xu, Xingfei Zheng, Lanzhi Li
2026, 25 (4): 1359-1372.   DOI: 10.1016/j.jia.2024.07.026
Abstract167)      PDF in ScienceDirect      

Rice yield is a complex trait affected by many related traits.  Traditional single-trait genome-wide association studies (GWAS) have limitations when studying complex traits, as they cannot account for the genetic relationships among multiple traits.  Multi-trait GWAS can consider the relationships among multiple traits and identify pleiotropic loci, so it is more suitable for complex traits such as rice yield than single-trait GWAS.  In this study, we conducted a multi-trait GWAS on 11 two-trait combinations of yield and yield-related traits with 575 hybrid rice varieties across two environments.  All these yield-related traits showed significant genetic correlations with yield (YD), including filled grains per panicle (FGPP), 1,000-grain weight (KGW), tillers per plant (TP), primary branch number (PB), secondary branch number (SB), and main panicle length (MPL).  In total, we identified 44 pleiotropic quantitative trait loci (pQTLs), including 29 new pQTLs not found in a single-trait GWAS.  We then screened 23 pQTLs showing common effects in two traits as key pQTLs.  These key pQTLs were subsequently analyzed by haplotype analysis, which identified 13 pleiotropic candidate genes.  Finally, we identified two optimal yield-enhancing allele combinations by pyramiding the superior haplotypes: GS3-GL3.1-OsCIPK17 for the YD-KGW combination and GNP12 for the YD-FGPP and YD-SB combinations.  This study provides pleiotropic candidate genes and allele combinations that exhibit superior differences in both yield and yield-related traits, offering valuable information for future high-yielding rice breeding.

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