Genetic Basis Underlying Correlations Among Growth Duration and Yield Traits Revealed by GWAS in Rice (Oryza sativa L.)

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.

Identification of QTLs associated with curd architecture in cauliflower

“…It is also interesting to note that several QTLs controlling stalk length (qSL.C6-1, qSL.C6-2) and curd solidity (qCS.C6-1, qCS.C6-4) are probably involved in pleiotropic effects. Similar pleiotropic QTLs were widely found in different species [15][16][17][18]. In cauliflower, co-localizations of QTLs controlling earliness and curd size were also reported, and were considered to be the result of artificial selection for pyramiding these two agronomic traits from different origins [19].…”

Genetic Analysis of Agronomic Traits and Grain Iron and Zinc Concentrations in a Doubled Haploid Population of Rice (Oryza sativa L.)

“…Co-localized QTLs are important for simultaneous improvement of traits of interest such as grain Fe and Zn concentrations in rice from plant breeder point of view 48 . QTLs controlling correlated traits were usually mapped in the same or close chromosome regions 49 . Some previous studies have reported the phenomenon of QTL co-locations for rice micronutrient concentrations 15,19,23 .…”

Genetic interactions among Ghd7, Ghd7.1, Ghd8 and Hd1 contribute to large variation in heading date in rice

“…Grain yield is positively correlated with heading date, especially in low latitude areas where the temperature is warm year-round (Gao et al , 2014; Li et al , 2018). In this study, due to continuously high temperature stress during the rice flowering stage in Wuhan, the seed setting rates were significantly decreased; therefore, we analyzed the relationship between heading date and SPP instead of that between heading date and grain yield.…”