Joint analysis of phenotype-effect-generation identifies loci associated with grain quality traits in rice hybrids

Genetic improvement of grain quality is more challenging in hybrid rice than in inbred rice due to additional nonadditive effects such as dominance. Here, we describe a pipeline developed for joint analysis of phenotypes, effects, and generations (JPEG). As a demonstration, we analyze 12 grain quality traits of 113 inbred lines (male parents), five tester lines (female parents), and 565 (113x5) of their hybrids. We sequence the parents for single nucleotide polymorphisms calling and infer the genotypes of the hybrids. Genome-wide association studies with JPEG identify 128 loci associated with at least one of the 12 traits, including 44, 97, and 13 loci with additive effects, dominant effects, and both additive and dominant effects, respectively. These loci together explain more than 30% of the genetic variation in hybrid performance for each of the traits. The JEPG statistical pipeline can help to identify superior crosses for breeding rice hybrids with improved grain quality. Genetic dissection of hybrids is more difficult than inbreds as nonadditive effects are involved. Here, the authors report a pipeline for joint analysis of phenotypes, effects, and generations and demonstrate its usefulness in identification of loci associated with quality traits and improving predict accuracy in genomic selection of hybrid rice.

Automated summary

Genetic improvement of grain quality in hybrid rice is challenging due to nonadditive effects. A pipeline called JPEG was developed for joint analysis of phenotypes, effects, and generations. 128 loci associated with grain quality traits were identified using JPEG, which can help to improve grain quality in breeding rice hybrids.