Abstract
BackgroundSalinity-alkalinity stress is one of the major factors limiting rice production. The damage caused by alkaline salt stress to rice growth is more severe than that caused by neutral salt stress. At present, the genetic resources (quantitative trait loci (QTLs) and genes) that can be used by rice breeders to improve alkalinity tolerance are limited. Here, we assessed the alkalinity tolerance of rice at the seedling stage and performed a genome-wide association study (GWAS) based on genotypic data including 788,396 single-nucleotide polymorphisms (SNPs) developed by re-sequencing 295 japonica rice varieties.ResultsWe used the score of alkalinity tolerance (SAT), the concentrations of Na+ and K+ in the shoots (SNC and SKC, respectively) and the Na+/K+ ratio of shoots (SNK) as indices to assess alkalinity tolerance at the seedling stage in rice. Based on population structure analysis, the japonica rice panel was divided into three subgroups. Linkage disequilibrium (LD) analysis showed that LD decay occurred at 109.77 kb for the whole genome and varied between 13.79 kb and 415.77 kb across the 12 chromosomes, at which point the pairwise squared correlation coefficient (r2) decreased to half of its maximum value. A total of eight QTLs significantly associated with the SAT, SNC and SNK were identified by genome-wide association mapping. A common QTL associated with the SAT, SNC and SNK on chromosome 3 at the position of 15.0 Mb, which explaining 13.36~13.64% of phenotypic variation, was selected for further analysis. The candidate genes were filtered based on LD decay, Gene Ontology (GO) enrichment, RNA sequencing data, and quantitative real-time PCR (qRT-PCR) analysis. Moreover, sequence analysis revealed one 7-bp insertion/deletion (indel) difference in LOC_Os03g26210 (OsIRO3) between the alkalinity-tolerant and alkalinity-sensitive rice varieties. OsIRO3 encodes a bHLH-type transcription factor and has been shown to be a negative regulator of the Fe-deficiency response in rice.ConclusionBased on these results, OsIRO3 maybe a novel functional gene associated with alkalinity tolerance in japonica rice. This study provides resources for improving alkalinity tolerance in rice, and the functional molecular marker could be verified to breed new rice varieties with alkalinity tolerance via marker-assisted selection (MAS).
Highlights
Salinity-alkalinity stress is one of the major factors limiting rice production
A common Quantitative trait locus (QTL) on chromosome 3 associated with the score of alkalinity tolerance (SAT), SNC and SNK was selected for further analysis
Phenotypic variation of 295 japonica rice varieties in response to alkalinity treatment To assess the phenotypic variation in alkalinity tolerance in 295 japonica rice varieties at the seedling stage, four alkalinity tolerance indices were evaluated: the SAT, SNC, concentration of K+ in the shoots (SKC) and SNK
Summary
Salinity-alkalinity stress is one of the major factors limiting rice production. The damage caused by alkaline salt stress to rice growth is more severe than that caused by neutral salt stress. We assessed the alkalinity tolerance of rice at the seedling stage and performed a genome-wide association study (GWAS) based on genotypic data including 788,396 single-nucleotide polymorphisms (SNPs) developed by re-sequencing 295 japonica rice varieties. Results: We used the score of alkalinity tolerance (SAT), the concentrations of Na+ and K+ in the shoots (SNC and SKC, respectively) and the Na+/K+ ratio of shoots (SNK) as indices to assess alkalinity tolerance at the seedling stage in rice. Salinity-alkalinity stress is a major constraint to agricultural food production because it decreases crop yield and restricts the use of agricultural land. This problem is increasing annually due to climate change and poor irrigation management (Qadir et al 2014). Numerous studies have shown that in some respects, alkaline soils dominated by NaHCO3 and Na2CO3 may be more stressful than saline soils containing neutral salts such as NaCl and Na2SO4 (Tanji 2002; Wang et al 2008)
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