水产群体基因组重测序数据分析软件包的开发

为了帮助水生动物学研究者解决群体遗传学基础分析的困难，本实验在调研现有的水生动物重测序数据分析研究和成果的基础上，基于水生动物群体遗传学的常用方法和通用分析软件，构建可于本地运行的、能够完成大部分基因组重测序数据基础计算的软件包。软件包首先将质控过滤后的重测序数据与参考基因组序列进行比对，利用比对结果检测基因组的遗传变异，对群体进行系统发育分析、群体结构分析、主成分分析、遗传多样性重要量化指标的计算和选择性消除分析等，并通过R或Python语言工具包对分析结果进行可视化。根据该软件包对来自3个群体、共约30尾大黄鱼个体的简化基因组测序数据进行分析测试的结果，完成了软件包携带的测序数据比对、单核苷酸多态性(SNP)鉴定、系统进化树构建、群体结构预测、连锁不平衡检测和多样性指标等计算功能，并且较好地图形可视化了分析结果。该群体基因组重测序分析的简易软件包可用于野生和自然群体的群体遗传学分析的大部分基础统计、计算和绘图，适合包括水生生物学在内的相关领域的生物学研究者进行群体基因组学研究。本研究为水生动物重测序数据分析提供便利，节约科研时间，减少人力物力成本。相关源码和使用说明文档已公开上传至...

Development of a software package for the analysis of genome resequencing data in aquatic populations

In recent decades, genome resequencing has been widely applied to study the genetic diversity in wild populations or cultured populations, such as estimation of divergence of populations and detection of artificial or environmental selection on the chromosomes. However, owing to lack of bioinformatics skills, most of the researchers have to resort to commercial platforms to analyze resequencing data, which needs high costs and long analysis period. The commercial platforms usually use the universal pipelines without personalized analysis, which sometime causes the erroneous results due to unreasonable parameters or reference genome data. Owing to the increasing demands of genome resequence data analysis in aquatic animals, we developed a user-friendly software package to facilitate population genetics analysis of genome resequencing data for aquatic biologists who may lack bioinformatics skills. By surveying the current research and achievements in the analysis of resequencing data in aquatic animals, the constructed software package integrated different bioinformatic tools, encompassing mapping the quality-controlled reads to the reference genome, detecting genetic variations, performing phylogeny and principal component analysis, clarifying population structure, calculating quantitative indicators of genetic diversity, and completing selective sweep analysis. All of the resulting data were finally visualized with an R or a Python language package. The present package was tested by analyzing the resequencing data of 30 Larimichthys crocea individuals of 3 populations, which successfully completed all of the designed tasks, such as alignment of the reads, identification of single nucleotide polymorphism (SNP), construction of phylogenetic tree and population structure, illustration of linkage disequilibrium decay and calculation of main diversity indexes. The generated outputs were well-visualized. The software package functionally integrated most of the basic statistics, calculation, and plotting for the analysis of wild and natural populations, which enabled most of the researchers to locally perform the data mining of genome resequence data to save time and costs. The corresponding source codes and instruction manuals have been uploaded to GitHub: https://github.com/xqteng/Re-seq_analysis.