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

Yang Lv; Jie Ma; Yueying Wang; Quan Wang; Xueli Lu; Haitao Hu; Qian Qian; Longbiao Guo; Lianguang Shang

doi:10.3389/fpls.2021.770736

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

Front Plant Sci. 2021 Nov 5:12:770736. doi: 10.3389/fpls.2021.770736. eCollection 2021.

Authors

Yang Lv^{1

2}, Jie Ma², Yueying Wang², Quan Wang³, Xueli Lu², Haitao Hu², Qian Qian², Longbiao Guo², Lianguang Shang³

Affiliations

¹ Rice Research Institute, Shenyang Agricultural University, Shenyang, China.
² State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China.
³ Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China.

Abstract

Nitrogen is essential for plant growth and yield, and it is, therefore, crucial to increase the nitrogen-use efficiency (NUE) of crop plants in fields. In this study, we measured four major low-nitrogen-induced growth response (LNGR) agronomic traits (i.e., plant height, tiller number, chlorophyll content, and leaf length) of the 225-rice-variety natural population from the Rice 3K Sequencing Project across normal nitrogen (NN) and low nitrogen (LN) environments. The LNGR phenotypic difference between NN and LN levels was used for gene analysis using a genome-wide association study (GWAS) combined with 111,205 single-nucleotide polymorphisms (SNPs) from the available sequenced data from the 3K project. We obtained a total of 56 significantly associated SNPs and 4 candidate genes for 4 LNGR traits. Some loci were located in the candidate regions, such as MYB61, OsOAT, and MOC2. To further study the role of candidate genes, we conducted haplotype analyses to identify the elite germplasms. Moreover, several other plausible candidate genes encoding LN-related or NUE proteins were worthy of mining. Our study provides novel insight into the genetic control of LNGR and further reveals some related novel haplotypes and potential genes with phenotypic variation in rice.

Keywords: GWAS; gene mining; haplotype analysis; low-nitrogen-induced growth response; rice.