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Association Mapping and Genetic Dissection of Nitrogen Use Efficiency-related Traits in Rice (Oryza Sativa L.)

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Publisher Springer
Date 2016 Feb 29
PMID 26922174
Citations 17
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Abstract

The increases in the usage of nitrogen fertilizer result in deleterious impacts on the environment; thus, there is an urgent need to improve nitrogen use efficiency (NUE) in crops including rice (Oryza sativa L.). Attentions have focused on quantitative trait loci (QTL) mapping of NUE-related traits using single experimental population, but to date, very few studies have taken advantage of association mapping to examine hundreds of lines for identifying potentially novel QTLs in rice. Here, we conducted association analysis on NUE-related traits using a population containing 184 varieties, which were genotyped with 157 genome-wide simple sequence repeat (SSR) markers. We detected eight statistically significant marker loci associating with NUE-related traits, of which two QTLs at RM5639 and RM3628 harbored known NUE-related genes GS1;2 and AspAt3, respectively. At a novel NUE-related locus RM5748, we developed Kompetitive Allele Specific PCR (KASP) single nucleotide polymorphism (SNP) markers and searched for putative NUE-related genes which are close to the associated SNP marker. Based on a transcriptional map of N stress responses constructed by our lab, we evaluated expressions of the NUE-related genes in this region and validated their effect on NUE. Meanwhile, we analyzed NUE-related alleles of the eight loci that could be utilized in marker-assisted selection. Moreover, we estimated breeding values of all the varieties through genomic prediction approach that could be beneficial for rice NUE enhancement.

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References
1.
Suganuma N, Yamamoto A, Itou A, Hakoyama T, Banba M, Hata S . cDNA macroarray analysis of gene expression in ineffective nodules induced on the Lotus japonicus sen1 mutant. Mol Plant Microbe Interact. 2004; 17(11):1223-33. DOI: 10.1094/MPMI.2004.17.11.1223. View

2.
Devlin B, Roeder K . Genomic control for association studies. Biometrics. 2001; 55(4):997-1004. DOI: 10.1111/j.0006-341x.1999.00997.x. View

3.
Hu B, Wang W, Ou S, Tang J, Li H, Che R . Variation in NRT1.1B contributes to nitrate-use divergence between rice subspecies. Nat Genet. 2015; 47(7):834-8. DOI: 10.1038/ng.3337. View

4.
Yu J, Buckler E . Genetic association mapping and genome organization of maize. Curr Opin Biotechnol. 2006; 17(2):155-60. DOI: 10.1016/j.copbio.2006.02.003. View

5.
Pritchard J, Stephens M, Donnelly P . Inference of population structure using multilocus genotype data. Genetics. 2000; 155(2):945-59. PMC: 1461096. DOI: 10.1093/genetics/155.2.945. View