Linkage analysis, GWAS, transcriptome analysis to identify candidate genes for rice seedlings in response to high temperature stress

Abstract

Background Rice plants suffer from the rising temperature which is becoming more and more prominent. Mining heat-resistant genes and applying them to rice breeding is a feasible and effective way to solve the problem. Result Three main biomass traits, including shoot length, dry weight, and fresh weight, changed after abnormally high-temperature treatment in the rice seedling stage of a recombinant inbred lines and the natural indica germplasm population. Based on a comparison of the results of linkage analysis and genome-wide association analysis, two loci with lengths of 57 kb and 69 kb in qDW7 and qFW6, respectively, were associated with the rice response to abnormally high temperatures at the seedling stage. Meanwhile, based on integrated transcriptome analysis, some genes are considered as important candidate genes. Combining with known genes and analysis of homologous genes, it was found that there are eight genes in candidate intervals that need to be focused on in subsequent research. Conclusions The results indicated several relevant loci, which would help researchers to further discover beneficial heat-resistant genes that can be applied to rice heat-resistant breeding.

Loci and Natural Alleles for Low-Nitrogen-Induced Growth Response Revealed by the Genome-Wide Association Study Analysis in Rice (Oryza sativa L.)

“…Increasing evidence has revealed that N supply has a significant impact on plant growth and development (McAllister et al, 2012;Chen et al, 2016). However, the conventional approach of linkage mapping has been used to identify potential genes with phenotypic variation, and even when this approach was limited to a biparental experimental population, it was timeconsuming Wei et al, 2021).…”

Unravelling Rubber Tree Growth by Integrating GWAS and Biological Network-Based Approaches

“…This step was performed mainly because of the absence of available data for several neglected species in public databases (Schaefer et al, 2018), such as H. brasiliensis. Moreover, transcriptome assemblies are a way of categorizing a broader range of important genes found under stress conditions (Valdés et al, 2013;Wei et al, 2021), as already reported by other Hevea studies (Ahn et al, 2017;Mantello et al, 2019). Additionally, because of the recent availability of the Hevea genome (Liu et al, 2020a), more studies are required for complete and accurate gene categorization.…”

Integrating GWAS and transcriptomics to identify candidate genes conferring heat tolerance in rice

“…Over the past decade, the loci underlying tens of rice traits were identified by GWAS, and several important genes were successfully verified by further transgenic experiments (Wang et al, 2020;Chen et al, 2022a). For heat tolerance, Wei et al identified 77 loci associated with survival rate after heat treatment at the seedling stage by GWAS based on a panel of 255 rice accessions and identified LOC_Os02g12890 as an important candidate gene that may respond to high-temperature stress based on integrated transcriptome analysis (Wei et al, 2021). In addition, Yang et al detected ten heat-associated QTL by GWAS with 221 rice accessions and selected 11 promising candidate genes by combining GWAS and transcriptome data (Yang et al, 2022).…”

“…For heat tolerance, Wei et al. identified 77 loci associated with survival rate after heat treatment at the seedling stage by GWAS based on a panel of 255 rice accessions and identified LOC_Os02g12890 as an important candidate gene that may respond to high-temperature stress based on integrated transcriptome analysis ( Wei et al., 2021 ). In addition, Yang et al.…”