Shaanxi University of Technology, Hanzhong, 72300, Shaanxi, China.
Shaanxi Province Key Laboratory of Bio-resources, Hanzhong, 72300, Shaanxi, China.
BMC Genomics. 2022 Aug 2;23(1):550. doi: 10.1186/s12864-022-08707-1.
The Qinba region is the transition region between Indica and Japonica varieties in China. It has a long history of Indica rice planting of more than 7000 years and is also a planting area for fine-quality Indica rice. The aims of this study are to explore different genetic markers applied to the analysis population structure, genetic diversity, selection and optimization of molecular markers of Indica rice, thus providing more information for the protection and utilization on germplasm resources of Indica rice.
Fifteen phenotypic traits, a core set of 48 SSR markers which originated protocol for identification of rice varieties-SSR marker method in agricultural industry standard of the People's Republic of China (Ministry of Agriculture of the PRC, NY/T1433-2014, Protocol for identification of rice varieties-SSR marker method, 2014), and SNPs data obtained by genotyping-by-sequencing (GBS, NlaIII and MseI digestion, referred to as SNPs-NlaIII and SNPs-MseI, respectively) for this panel of 93 samples using the Illumina HiSeq2000 sequencing platform, were employed to explore the genetic diversity and population structure of 93 samples.
The average of coefficient of variation (CV) and diversity index (H) were 29.72% and 1.83 ranging from 3.07% to 137.43%, and from 1.45 to 2.03, respectively. The correlation coefficient between 15 phenotypic traits ranged from 0.984 to -0.604. The first four PCs accounted for 70.693% phenotypic variation based on phenotypic analysis. A total of 379 alleles were obtained using SSR markers, encompassing an average of 8.0 alleles per primer. Polymorphic bands (PPB) and polymorphism information content (PIC) was 88.65% and 0.77, respectively. The Mantel test showed that the correlation between the genetic distance matrix based on SNPs-NlaIII and SNPs-MseI was the largest (R=0.88), and that based on 15 phenotypic traits and SSR was the smallest (R=0.09). The 93 samples could be clustered into two subgroups by 3 types of genetic markers. Molecular variance analysis revealed that the genetic variation was 2% among populations and 98% within populations (the Nm was 0.16), Tajima's D value was 1.66, the FST between the two populations was 0.61 based on 72,824 SNPs.
The population genetic variation explained by SNPs was larger than that explained by SSRs. The gene flow of 93 samples used in this study was larger than that of naturally self-pollinated crops, which may be caused by long-term breeding selection of Indica rice in the Qinba region. The genetic structure of the 93 samples was simple and lacked rare alleles.
秦巴地区是中国籼稻和粳稻品种的过渡地带。它有着 7000 多年的籼稻种植历史，也是优质籼稻种植区。本研究旨在探索不同的遗传标记应用于籼稻分析群体结构、遗传多样性、选择和优化分子标记，从而为籼稻种质资源的保护和利用提供更多信息。
本研究使用了 93 个样本的 15 个表型性状、48 个核心 SSR 标记（来源于中华人民共和国农业行业标准《农作物品种鉴定 SSR 标记法》（农业部，NY/T1433-2014）和通过测序的基因型（GBS，NlaIII 和 MseI 消化，分别称为 SNPs-NlaIII 和 SNPs-MseI）获得的 SNP 数据，在 Illumina HiSeq2000 测序平台上对这 93 个样本进行了遗传多样性和群体结构分析。
15 个表型性状的平均变异系数（CV）和多样性指数（H）分别为 29.72%和 1.83，范围分别为 3.07%至 137.43%和 1.45 至 2.03。15 个表型性状之间的相关系数范围为 0.984 至-0.604。基于表型分析，前四个主成分（PCs）占表型变异的 70.693%。SSR 标记共获得 379 个等位基因，每个引物平均 8.0 个等位基因。多态性带（PPB）和多态信息含量（PIC）分别为 88.65%和 0.77。Mantel 检验显示，基于 SNPs-NlaIII 和 SNPs-MseI 的遗传距离矩阵之间的相关性最大（R=0.88），而基于 15 个表型性状和 SSR 的相关性最小（R=0.09）。这 93 个样本可以根据 3 种遗传标记分为两个亚群。分子方差分析表明，群体间遗传变异为 2%，群体内遗传变异为 98%（Nm 为 0.16），Tajima's D 值为 1.66，基于 72824 个 SNPs 的两个群体之间的 FST 值为 0.61。
SNP 解释的群体遗传变异大于 SSR 解释的群体遗传变异。本研究中使用的 93 个样本的基因流大于自然自花授粉作物，这可能是由于秦巴地区长期对籼稻进行选育。93 个样本的遗传结构简单，缺乏稀有等位基因。
