Identification of Candidate Genes for Rice Nitrogen Use Efficiency by Genome-wide Association Analysis
[Objective]The exploration of germplasm and gene resources in rice for high nitrogen efficiency,along with the elucidation of their molecular mechanisms and genetic effects,represents a significant focus and goal within current research efforts on rice nitrogen use efficiency(NUE).[Method]To identify the variant loci and candidate genes associated with rice NUE,we collected 190 Asian rice accessions as an association population.After thorough filtering and screening,we obtained 3,934,195 high-quality single nucleotide polymorphisms(SNPs).Under field conditions,two nitrogen treatment levels were established:low nitrogen(Ni,90 kg/hm2)and normal nitrogen(N2,180 kg/hm2).We investigated the phenotypic data of rice leaf width in response to both low and normal nitrogen treatments at the maturity stage.Genome-wide association analysis(GWAS)was conducted by integrating the FarmCPU and MLM models.[Result]By calculating the phenotypic ratio Q(N1/N2)of leaf width under low and normal nitrogen levels,we found that the Q value exhibited a normal distribution.A total of 100 significant loci were identified on 12 chromosomes through GWAS for the Q value,leading to the determination of 39 candidate QTLs.This included the cloned NUE-related genes OsNR1.2 and OsNAC42.Additionally,we identified superior haplotypes and potential advantageous haplotype combinations of the candidate genes OsNR1.2 and OsNAC42,which provide valuable resources and information for enhancing rice NUE.[Conclusion]This study elucidated the genetic basis of rice leaf width under varying nitrogen treatments using GWAS and haplotype analysis.We identified candidate QTLs and genes associated with NUE,including OsNR1.2 and OsNAC42.Through haplotype analysis,we recognized advantageous haplotype combinations of these two genes,offering valuable resources and insights for the improvement of rice NUE.
ricenitrogen use efficiencyleaf widthgenome-wide association analysis
万方数据
维普
