10.3389/fpls.2018.00650.s001
Fengmei Li
Fengmei
Li
Jianyin Xie
Jianyin
Xie
Xiaoyang Zhu
Xiaoyang
Zhu
Xueqiang Wang
Xueqiang
Wang
Yan Zhao
Yan
Zhao
Xiaoqian Ma
Xiaoqian
Ma
Zhanying Zhang
Zhanying
Zhang
Muhammad A. R. Rashid
Muhammad A. R.
Rashid
Zhifang Zhang
Zhifang
Zhang
Linran Zhi
Linran
Zhi
Shuyang Zhang
Shuyang
Zhang
Jinjie Li
Jinjie
Li
Zichao Li
Zichao
Li
Hongliang Zhang
Hongliang
Zhang
Image_1_Genetic Basis Underlying Correlations Among Growth Duration and Yield Traits Revealed by GWAS in Rice (Oryza sativa L.).pdf
Frontiers
2018
genetic correlation
genome wide association study
pleiotropic gene
pleiotropic QTL
gene interaction
2018-05-22 07:41:42
Figure
https://frontiersin.figshare.com/articles/figure/Image_1_Genetic_Basis_Underlying_Correlations_Among_Growth_Duration_and_Yield_Traits_Revealed_by_GWAS_in_Rice_Oryza_sativa_L_pdf/6298904
<p>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 r<sup>2</sup> 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.</p>