PreprintArticleVersion 1Preserved in Portico This version is not peer-reviewed
Rice (Oryza sativa L.) Grain Size, Shape, and Weight-Related QTLs Identified using GWAS with Multiple GAPIT Models and High-Density SNP Chip DNA Markers
Kabange, N.R.; Dzorkpe, G.D.; Park, D.-S.; Kwon, Y.; Lee, S.-B.; Lee, S.-M.; Kang, J.-W.; Jang, S.-G.; Oh, K.-W.; Lee, J.-H. Rice (Oryza sativa L.) Grain Size, Shape, and Weight-Related QTLs Identified Using GWAS with Multiple GAPIT Models and High-Density SNP Chip DNA Markers. Plants2023, 12, 4044.
Kabange, N.R.; Dzorkpe, G.D.; Park, D.-S.; Kwon, Y.; Lee, S.-B.; Lee, S.-M.; Kang, J.-W.; Jang, S.-G.; Oh, K.-W.; Lee, J.-H. Rice (Oryza sativa L.) Grain Size, Shape, and Weight-Related QTLs Identified Using GWAS with Multiple GAPIT Models and High-Density SNP Chip DNA Markers. Plants 2023, 12, 4044.
Kabange, N.R.; Dzorkpe, G.D.; Park, D.-S.; Kwon, Y.; Lee, S.-B.; Lee, S.-M.; Kang, J.-W.; Jang, S.-G.; Oh, K.-W.; Lee, J.-H. Rice (Oryza sativa L.) Grain Size, Shape, and Weight-Related QTLs Identified Using GWAS with Multiple GAPIT Models and High-Density SNP Chip DNA Markers. Plants2023, 12, 4044.
Kabange, N.R.; Dzorkpe, G.D.; Park, D.-S.; Kwon, Y.; Lee, S.-B.; Lee, S.-M.; Kang, J.-W.; Jang, S.-G.; Oh, K.-W.; Lee, J.-H. Rice (Oryza sativa L.) Grain Size, Shape, and Weight-Related QTLs Identified Using GWAS with Multiple GAPIT Models and High-Density SNP Chip DNA Markers. Plants 2023, 12, 4044.
Abstract
This study investigated novel quantitative traits loci (QTLs) associated with the control of grain shape and size as well as grain weight in rice. We employed a joint strategy multiple GAPIT (Genome Association and Prediction Integrated Tool) models [(Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK)), Fixed and random model Circulating Probability Uniform (FarmCPU), Settlement of MLM Under Progressive Exclusive Relationship (SUPER), and General Linear Model (GLM)]–High Density SNP Chip DNA Markers (60,461) to conduct a Genome-Wide Association Study (GWAS). GWAS was performed using genotype and grain-related phenotypes of 143 recombinant inbred lines (RILs). Data show that parental lines (Ilpum and Tung Tin Wan Hein 1, TTWH1, Oryza sativa L., ssp. japonica and indica, respectively) exhibited divergent phenotypes for all analyzed grain traits), which was reflected in their derived population. GWAS results revealed the association between seven SNP Chip makers and quantitative trait loci (QTLs) for grain length, co-detected by all GAPIT models on (Chr) 1–3, 5, 7, and 11), were qGL1-1BFSG (AX-95918134, Chr1: 3820526 bp) explains 65.2%–72.5% of the phenotypic variance explained (PVE). In addition, qGW1-1BFSG (AX-273945773, Chr1: 5623288 bp) for grain width explains 15.5%–18.9% of PVE. Furthermore, BLINK or FarmCPU identified three QTLs for grain thickness independently, and explain 74.9% (qGT1Blink, AX-279261704, Chr1: 18023142 bp) and 54.9% (qGT2-1Farm, AX-154787777, Chr2: AX-154787777 bp) of the observed PVE. For t length-to-width ratio, the qLWR2BFSG (AX-274833045, Chr2: 10000097 bp) explains nearly 15.2%–32% of PVE for LWR. Likewise, the major QTL for thousand-grain weight (TGW) was detected on Chr6 (qTGW6BFSG, AX-115737727, 28484619 bp) and explains 32.8%–54% of PVE. The qTGW6BFSG QTL coincides with qGW6-1Blink for grain width and explained 32.8%–54% of PVE. Putative Candidate genes pooled from major QTLs for each grain traits have interesting annotated functions that require functional studies to elucidate their function in the control of grain size, shape, or weight in rice. Genome selection analysis proposed makers useful for downstream marker-assisted selection based on genetic merit of RILs.
Keywords
SNP Chip DNA Marker; GAPIT; GWAS; Genomic Selection; Grain traits; Rice
Subject
Biology and Life Sciences, Plant Sciences
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
,
