Genome-Wide Association Mapping Reveals Novel Putative Gene Candidates Governing Reproductive Stage Heat Stress Tolerance in Rice

Abstract

Temperature rise predicted for the future will severely affect rice productivity because the crop is highly sensitive to heat stress at the reproductive stage. Breeding tolerant varieties is an economically viable option to combat heat stress, for which the knowledge of target genomic regions associated with the reproductive stage heat stress tolerance (RSHT) is essential. A set of 192 rice genotypes of diverse origins were evaluated under natural field conditions through staggered sowings for RSHT using two surrogate traits, spikelet fertility and grain yield, which showed significant reduction under heat stress. These genotypes were genotyped using a 50 k SNP array, and the association analysis identified 10 quantitative trait nucleotides (QTNs) for grain yield, of which one QTN (qHTGY8.1) was consistent across the different models used. Only two out of 10 MTAs coincided with the previously reported QTLs, making them novel. A total of 22 QTNs were observed for spikelet fertility, among which qHTSF5.1 was consistently found across three models. Of the QTNs identified, seven coincided with previous reports, while the remaining QTNs were new. The genes near the QTNs were found associated with the protein–protein interaction, protein ubiquitination, stress signal transduction, and so forth, qualifying them to be putative for RSHT. An in silico expression analysis revealed the predominant expression of genes identified for spikelet fertility in reproductive organs. Further validation of the biological relevance of QTNs in conferring heat stress tolerance will enable their utilization in improving the reproductive stage heat stress tolerance in rice.

RicePilaf: a post-GWAS/QTL dashboard to integrate pangenomic, coexpression, regulatory, epigenomic, ontology, pathway, and text-mining information to provide functional insights into rice QTLs and GWAS loci

“…Genome-wide association studies (GWASs) and quantitative trait locus (QTL) analysis in rice have identified a multitude of genetic loci influencing a wide range of important traits. Recent examples include GWAS/QTL analysis on variations in environmental stress responses (e.g., cold tolerance [ 2 ], heat tolerance [ 3 , 4 ], and anaerobic germination [ 5 , 6 ]), disease tolerance (e.g., blast [ 7 ]), mineral contents (e.g., cadmium accumulation [ 8 ]), morphological traits (e.g., plant height [ 9 ], grain weight [ 10 ], and grain size and panicle length [ 11 ]), and other yield-related traits (e.g., preharvest sprouting [ 12 ] and seed longevity [ 13 ]). This list is only expected to grow given the immense interest in the genetics of rice traits and the easy availability of genotyping resources covering millions of single-nucleotide polymorphisms (SNPs) across thousands of rice varieties [ 14 ].…”

Genome-wide association study reveals novel genomic regions governing agronomic and grain quality traits and superior allelic combinations for Basmati rice improvement

“…Genome-wide association study (GWAS) is a very popular quantitative genomics tool, which has gained prominence in mapping quantitative traits with the advent of high-density genotyping platforms, like SNP arrays. GWAS has played a pivotal role in identifying many important genes which govern various complex agronomic traits such as flowering time, plant height and panicle length in rice ( Begum et al., 2015 ; Yano et al., 2016 ; Reig-Valiente et al., 2018 ; Zhang et al., 2019 ; Zhou and Huang, 2019 ; Verma et al., 2021 ), particularly using collections of unrelated diverse germplasm ( Huang et al., 2012 ; Qiu et al., 2021 ; Ravikiran et al., 2022 ). Although GWAS is helpful in mining novel alleles for complex traits, it requires further validation in breeding populations for its usefulness in marker-assisted breeding ( Begum et al., 2015 ).…”