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.

Marker-assisted selection (MAS) and genomic selection (GS) breeding have greatly improved the efficiency of rice breeding.  Due to the influences of epistasis and gene pleiotropy, ensuring the actual breeding effect of MAS and GS is still a difficult challenge to overcome.  In this study, 113 indica rice varieties (V) and their 565 testcross hybrids (TC) were used as the materials to investigate the genetic basis of 12 quality traits and nine agronomic traits.  The original traits and general combining ability of the parents, as well as the original traits and mid-parent heterosis of TC, were subjected to genome-wide association analysis.  In total, 381 primary significantly associated loci (SAL) and 1,759 secondary SALs that had epistatic interactions with these primary SALs were detected.  Among these loci, 322 candidate genes located within or nearby the SALs were screened, 204 of which were cloned genes.  A total of 39 MAS molecular modules that are beneficial for trait improvement were identified by pyramiding the superior haplotypes of candidate genes and desirable epistatic alleles of the secondary SALs.  All the SALs were used to construct genetic networks, in which 91 pleiotropic loci were investigated.  Additionally, we estimated the accuracy of genomic prediction in the parent V and TC by incorporating either no SALs, primary SALs, secondary SALs or epistatic effect SALs as covariates.  Although the prediction accuracies of the four models were generally not significantly different in the TC dataset, the incorporation of primary SALs, secondary SALs, and epistatic effect SALs significantly improved the prediction accuracies of 5 (26%), 3 (16%), and 11 (58%) traits in the V dataset, respectively.  These results suggested that SALs and epistatic effect SALs identified based on an additive genotype can provide considerable predictive power for the parental lines.  They also provide insights into the genetic basis of complex traits and valuable information for molecular breeding in rice.