ABSTRACT
Avoidance of disadvantageous genetic correlations among growth duration and yield traits is critical in developing crop varieties that efficiently use light and energy resources and produce high yields. To understand the genetic basis underlying the correlations among heading date and three major yield traits in rice, we investigated the four traits in a diverse and representative core collection of 266 cultivated rice accessions in both long-day and short-day environments, and conducted the genome-wide association study using 4.6 million single nucleotide polymorphisms (SNPs). There were clear positive correlation between heading date and grain number per panicle, and negative correlation between grain number per panicle and panicle number, as well as different degrees of correlations among other traits in different subspecies and environments. We detected 47 pleiotropic genes in 15 pleiotropic quantitative trait loci (pQTLs), 18 pleiotropic genes containing 37 pleiotropic SNPs in 8 pQTLs, 27 pQTLs with r2 of linkage disequilibrium higher than 0.2, and 39 pairs of interactive genes from 8 metabolic pathways that may contribute to the above phenotypic correlations, but these genetic bases were different for correlations among different traits. Distributions of haplotypes revealed that selection for pleiotropic genes or interactive genes controlling different traits focused on genotypes with weak effect or on those balancing two traits that maximized production but sometimes their utilization strategies depend on the traits and environment. Detection of pQTLs and interactive genes and associated molecular markers will provide an ability to overcome disadvantageous correlations and to utilize the advantageous correlations among traits through marker-assisted selection in breeding.
ABSTRACT
Dry direct-seeding of rice is rapidly increasing in China, but variable planting depth associated with machine sowing can lead to low seedling emergence rates. Phenotype analysis of 621 rice accessions showed that mesocotyl length (ML) was induced by deep soil covering and was important in deep-sowing tolerance in the field. Here, we performed and compared GWAS using three types of SNPs (non-synonymous SNP, non-synonymous SNPs and SNPs within promoters and 3 million randomly selected SNPs from the entire set of SNPs) and found that Non-Syn GWAS (GWAS using non-synonyomous SNP) decreased computation time and eliminated confounding by other loci relative to GWAS using randomly selected SNPs. Thirteen QTLs were finally detected, and two new major-effect genes, named OsML1 and OsML2, were identified by an integrated analysis. There were 2 and 7 non-synonymous SNPs in OsML1 and OsML2, respectively, from which 3 and 4 haplotypes were detected in cultivated rice. Combinations of superior haplotypes of OsML1 and OsML2 increased ML by up to 4 cm, representing high emergence rate (85%) in the field with 10 cm of soil cover. The studies provide key loci and naturally occurring alleles of ML that can be used in improving tolerance to dry direct-seeding.
