Dataset Information

Mining Salt Tolerance SNP Loci and Prediction of Candidate Genes in the Rice Bud Stage by Genome-Wide Association Analysis.

ABSTRACT: Mining salt tolerance genes is significant for breeding high-quality salt-tolerant rice varieties in order to improve the utilization of saline-alkaline land. In this study, 173 rice accessions were measured for their germination potential (GP), germination rate (GR), seedling length (SL), root length (RL), germination potential relative to salt damage rate (GPR), germination rate relative to salt damage rate (GRR), seedling length relative to salt damage rate (SLR), relative salt damage rate at the germination stage (RSD) and comprehensive relative salt damage rate in the early seedling stage (CRS) under normal and salt stress conditions. Genome-wide association analysis was performed with 1,322,884 high-quality SNPs obtained by resequencing. Eight quantitative trait loci (QTLs) related to salt tolerance traits at the germination stage were detected in 2020 and 2021. They were related to the GPR (qGPR2) and SLR (qSLR9), which were newly discovered in this study. Three genes were predicted as salt tolerance candidate genes: LOC_Os02g40664, LOC_Os02g40810, and LOC_Os09g28310. At present, marker-assisted selection (MAS) and gene-edited breeding are becoming more widespread. Our discovery of candidate genes provides a reference for research in this field. The elite alleles identified in this study may provide a molecular basis for cultivating salt-tolerant rice varieties.

SUBMITTER: Wang R

PROVIDER: S-EPMC10255615 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature

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Publications

Mining Salt Tolerance SNP Loci and Prediction of Candidate Genes in the Rice Bud Stage by Genome-Wide Association Analysis.

Wang Rui R Zhou Zhenzhen Z Xiong Mengyuan M Du Mingyu M Lin Xingxing X Liu Cuiping C Lu Mingwei M Liu Zhengbo Z Chang Yinping Y Liu Erbao E

Plants (Basel, Switzerland) 20230530 11

Mining salt tolerance genes is significant for breeding high-quality salt-tolerant rice varieties in order to improve the utilization of saline-alkaline land. In this study, 173 rice accessions were measured for their germination potential (GP), germination rate (GR), seedling length (SL), root length (RL), germination potential relative to salt damage rate (GPR), germination rate relative to salt damage rate (GRR), seedling length relative to salt damage rate (SLR), relative salt damage rate at ...[more]

PMID: 37299141

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Project description:BackgroundRice is considered as a salt-sensitive plant, particularly at early vegetative stage, and its production is suffered from salinity due to expansion of salt affected land in areas under cultivation. Hence, significant increase of rice productivity on salinized lands is really necessary. Today genome-wide association study (GWAS) is a method of choice for fine mapping of QTLs involved in plant responses to abiotic stresses including salinity stress at early vegetative stage. In this study using > 33,000 SNP markers we identified rice genomic regions associated to early stage salinity tolerance. Eight salinity-related traits including shoot length (SL), root length (RL), root dry weight (RDW), root fresh weight (RFW), shoot fresh weight (SFW), shoot dry weight (SDW), relative water content (RWC) and TW, and 4 derived traits including SL-R, RL-R, RDW-R and RFW-R in a diverse panel of rice were evaluated under salinity (100 mM NaCl) and normal conditions in growth chamber. Genome-wide association study (GWAS) was applied based on MLM(+Q + K) model.ResultsUnder stress conditions 151 trait-marker associations were identified that were scattered on 10 chromosomes of rice that arranged in 29 genomic regions. A genomic region on chromosome 1 (11.26 Mbp) was identified which co-located with a known QTL region SalTol1 for salinity tolerance at vegetative stage. A candidate gene (Os01g0304100) was identified in this region which encodes a cation chloride cotransporter. Furthermore, on this chromosome two other candidate genes, Os01g0624700 (24.95 Mbp) and Os01g0812000 (34.51 Mbp), were identified that encode a WRKY transcription factor (WRKY 12) and a transcriptional activator of gibberellin-dependent alpha-amylase expression (GAMyb), respectively. Also, a narrow interval on the same chromosome (40.79-42.98 Mbp) carries 12 candidate genes, some of them were not so far reported for salinity tolerance at seedling stage. Two of more interesting genes are Os01g0966000 and Os01g0963000, encoding a plasma membrane (PM) H+-ATPase and a peroxidase BP1 protein. A candidate gene was identified on chromosome 2 (Os02g0730300 at 30.4 Mbp) encoding a high affinity K+ transporter (HAK). On chromosome 6 a DnaJ-encoding gene and pseudouridine synthase gene were identified. Two novel genes on chromosome 8 including the ABI/VP1 transcription factor and retinoblastoma-related protein (RBR), and 3 novel genes on chromosome 11 including a Lox, F-box and Na+/H+ antiporter, were also identified.ConclusionKnown or novel candidate genes in this research were identified that can be used for improvement of salinity tolerance in molecular breeding programmes of rice. Further study and identification of effective genes on salinity tolerance by the use of candidate gene-association analysis can help to precisely uncover the mechanisms of salinity tolerance at molecular level. A time dependent relationship between salt tolerance and expression level of candidate genes could be recognized.

Project description:BackgroundImproving the salt tolerance of direct-seeding rice at the seed germination stage is a major breeding goal in many Asian rice-growing countries, where seedlings must often establish in soils with a high salt content. Thus, it is important to understand the genetic mechanisms of salt tolerance in rice and to screen for germplasm with salt tolerance at the seed germination stage. Here, we investigated seven seed germination-related traits under control and salt-stress conditions and conducted a genome-wide association study based on the re-sequencing of 478 diverse rice accessions.ResultsThe analysis used a mixed linear model and was based on 6,361,920 single nucleotide polymorphisms in 478 rice accessions grouped into whole, indica, and non-indica panels. Eleven loci containing 22 significant salt tolerance-associated single nucleotide polymorphisms were identified based on the stress-susceptibility indices (SSIs) of vigor index (VI) and mean germination time (MGT). From the SSI of VI, six major loci were identified, explaining 20.2% of the phenotypic variation. From the SSI of MGT, five major loci were detected, explaining 26.4% of the phenotypic variation. Of these, seven loci on chromosomes 1, 5, 6, 11, and 12 were close to six previously identified quantitative gene loci/genes related to tolerance to salinity or other abiotic stresses. The strongest association region for the SSI of MGT was identified in a ~ 13.3 kb interval (15450039-15,463,330) on chromosome 1, near salt-tolerance quantitative trait loci controlling the Na+: K+ ratio, total Na+ uptake, and total K+ concentration. The strongest association region for the SSI of VI was detected in a ~ 164.2 kb interval (526662-690,854) on chromosome 2 harboring two nitrate transporter family genes (OsNRT2.1 and OsNRT2.2), which affect gene expression under salt stress. The haplotype analysis indicated that OsNRT2.2 was associated with subpopulation differentiation and its minor/rare tolerant haplotype was detected.ConclusionsThese results provide valuable information for salt tolerance-related gene cloning and for understanding the genetic mechanisms of salt tolerance at the seed germination stage. This information will be useful to improve the salt tolerance of direct-seeding rice varieties by genomic selection or marker-assisted selection.

Dataset Information

Mining Salt Tolerance SNP Loci and Prediction of Candidate Genes in the Rice Bud Stage by Genome-Wide Association Analysis.

Publications

Mining Salt Tolerance SNP Loci and Prediction of Candidate Genes in the Rice Bud Stage by Genome-Wide Association Analysis.

Similar Datasets

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