Hunan Engineering & Technology Research Center for Agricultural Big Data Analysis & Decision-making, College of Plant Protection, Hunan Agricultural University, 410128, Changsha, Hunan, China.
Hubei Key Laboratory of Food Crop Germplasm and Genetic Improvement, Food Crop Institute, Hubei Academy of Agricultural Sciences, 430064, Wuhan, Hubei, China.
Nat Commun. 2023 Jul 4;14(1):3930. doi: 10.1038/s41467-023-39534-x.
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 (113×5) 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.
由于杂种优势等非加性效应的存在,与常规稻相比,杂交稻的品质改良更具挑战性。在这里,我们描述了一个用于表型、效应和世代联合分析(JPEG)的流程。作为一个演示,我们分析了 113 个自交系(父本)、5 个测验系(母本)和它们的 565 个杂种(113×5)的 12 个粒质性状。我们对亲本进行单核苷酸多态性测序,并推断杂种的基因型。使用 JPEG 进行全基因组关联研究,鉴定出与至少 12 个性状之一相关的 128 个位点,包括分别具有加性效应、显性效应和加性和显性效应的 44、97 和 13 个位点。这些位点共同解释了每个性状杂种表现遗传变异的 30%以上。JPEG 统计分析流程可以帮助鉴定出具有改良粒质的优良杂交组合,用于培育水稻杂种。