The genetic diversity and structure of indica rice in China as detected by single nucleotide polymorphism analysis

• Published in: BMC genetics Vol. 17; no. 53; p. 53
• Main Authors: Xu, Qun, Yuan, Xiaoping, Wang, Shan, Feng, Yue, Yu, Hanyong, Wang, Yiping, Yang, Yaolong, Wei, Xinghua, Li, Ximing
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 15.03.2016; BioMed Central
• Subjects: Analysis; Arrays; Biological diversity; China; Chromosomes, Plant - genetics; Gene Frequency; Genetic aspects; Genetic diversity; Genome, Plant; Genomes; Genotype; Oryza - genetics; Phylogeography; Physiological aspects; Polymorphism; Polymorphism, Single Nucleotide; Rice; Single nucleotide polymorphisms; China; Array; Rice (Oryza sativa L.); Genetic diversity; Structure; Single nucleotide polymorphism (SNP)
• ISSN: 1471-2156; 1471-2156
• DOI: 10.1186/s12863-016-0361-x

Rice (Oryza sativa L.) is the staple food of more than half of the world's population. The identification of genetic diversity in local varieties of rice compared with that of improved or introduced varieties is important in breeding elite varieties for sustainable agriculture. Array-based single nucleotide polymorphism (SNP) detection is a useful technique for such studies and breeding applications. We developed a 5291-SNP genome-wide array and used it to genotype 471 indica rice accessions in China using Illumina's Infinium technology. Local, introduced, and improved rice varieties were clustered into three sub-groups, with some overlapping shown in principal component analysis and neighbor-joining tree, also confirmed by model-based structure. A minor allele frequency ≥ 0.2 was observed in 72% of polymorphic SNPs in local rice varieties, which was higher than that in other sub-groups. Local rice varieties also had the highest mean polymorphism information content (PIC) and genetic diversity. Analysis of molecular variance showed that 90.61% of genetic variation was a result of differences within sub-groups. Our results revealed that SNP analysis clustered local varieties, introduced varieties, and improved varieties into three clear sub-groups. The distribution of parameter PIC values on sub-group genomes revealed that genetic differentiation among them might not be on a genome-wide scale, but rather on selected loci or chromosomal intervals. The result of Gene Ontology enrichment analysis showed that genes nearby those selected SNPs associated different molecular functions or various traits among sub-groups.