基于SLAF-seq简化基因组技术的沙冬青SNP位点开发及遗传分析

SNP Sites Developed by Specific Length Amplification Fragment Sequencing(SLAF-seq) and Genetic Analysis in Ammopitanthus mongolicus

选取分布在内蒙古、宁夏、甘肃10个地点的沙冬青个体,用SLAF-seq简化基因组技术进行测序。以大豆基因组为参照,通过生物信息学分析进行实验方案的系统设计,筛选特异长度的DNA片断,构建SLAF-seq文库,并通过高通量测序的方式获得海量序列,再通过软件分析比对,获得多态性SLAF标签,最后在多态性SLAF标签上开发大量特异性SNP位点。结果共获得374 265个SLAF标签,其中多态性SLAF标签56 295个。通过序列分析,共开发得到127 278个SNP。对所有的SNP根据完整度>0.5,MAF>0.05过滤,共得到102 025个高一致性的群体SNP。基于过滤后的SNP,运用数学统计学方法,对10份沙冬青个体完成系统进化树、群体结构、PCA分析,从基因组水平揭示不同个体之间的遗传分化关系。结果表明,通过群体结构分析发现这10个地点的沙冬青都来源于同一祖先,但由于地理位置的影响使得这10个地点的沙冬青在生长发育过程中发生了遗传分化。通过系统进化树发现分布在内蒙古的沙冬青具有较近的亲缘关系,甘肃和宁夏的沙冬青有较近的亲缘关系。

Ten site of Ammopiptanthus mongolicus distributed in Inner Mongolia, Ningxia and Gansu Province were used as experiment materials for sequencing by specific-locus amplified fragment sequencing（SLAF-seq）. The scheme of the experiment was designed based on bio-informatics technology. Taking Glycine max as the reference genome, specific size of DNA were chosen to construct the SLAF-seq library. After high-throughput sequencing, a great amount of sequences were obtained and used to obtain the polymorphism SLAF tags by software alignment, then found the distribution of specific SNP sites. In total, we obtained 374 265 SLAF tags, including 56 295 polymorphic SLAF tags. According to these conditions that integrity 〉0.5 and MAF〉0.05 screening from all SNP, obtained 102 025 group SNP which have high consistency. Phylogenetic relationship population structure and PCA analysis of ten individuals of A.mongolicus were analyzed using mathematical statistic method based on screening SNP, from the level of the genome to reveal the genetic differentiation between different groups. The results show that these A.mongolicus in ten different sites all originate from the same ancestor, but due to these factor that geographical location make the A.mongolicus produced genetic differentiation. Therefore, A.mongolicus growing in Inner Mongolia have close relationship, and that distributed in Ningxia and Gansu Province have close relationship.