Xu Qun, Yuan Xiaoping, Wang Shan, Feng Yue, Yu Hanyong, Wang Yiping, Yang Yaolong, Wei Xinghua, Li Ximing
State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006, China.
BMC Genet. 2016 Mar 15;17:53. 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.
水稻（Oryza sativa L.）是世界上一半以上人口的主食。与改良品种或引进品种相比，鉴定当地水稻品种的遗传多样性对于培育可持续农业的优良品种至关重要。基于芯片的单核苷酸多态性（SNP）检测是此类研究和育种应用的一种有用技术。
我们开发了一个包含5291个SNP的全基因组芯片，并使用Illumina公司的Infinium技术对中国的471份籼稻种质进行基因分型。当地品种、引进品种和改良品种被聚类为三个亚组，主成分分析和邻接树显示有一些重叠，基于模型的结构分析也证实了这一点。在当地水稻品种中，72%的多态性SNP的次要等位基因频率≥0.2，高于其他亚组。当地水稻品种还具有最高的平均多态性信息含量（PIC）和遗传多样性。分子方差分析表明，90.61%的遗传变异是亚组内差异的结果。
我们的结果表明，SNP分析将当地品种、引进品种和改良品种聚类为三个清晰的亚组。亚组基因组上参数PIC值的分布表明，它们之间的遗传分化可能不是全基因组范围的，而是在选定的位点或染色体区间。基因本体富集分析结果表明，那些选定SNP附近的基因与亚组间不同的分子功能或各种性状相关。
