Escherichia coli Long-term Evolution Experiment 500 and 1000 Generation Population Sequencing. Escherichia coli REL606

New mutations leading to structural variation (SV) in genomes — in the form of mobile element insertions, large deletions, gene duplications, and other chromosomal rearrangements — can play a key role in microbial evolution. Yet, SV is considerably more difficult to predict from short-read genome resequencing data than single-nucleotide variation and small indels, so it is not yet routinely identified in DNA sequencing data that profiles population-level genetic diversity over time in evolution experiments. We implemented an algorithm for detecting polymorphic SV as part of the breseq computational pipeline for analyzing resequencing data from haploid microbial genomes. This procedure examines split-read alignments, in which the two ends of a single sequencing read match disjoint locations in the reference genome, in order to detect structural variants and estimate their frequencies within a sample. We tested our algorithm on 500- and 1000-generation population samples from the Lenski E. coli long-term evolution experiment (LTEE). Knowledge of genes that are targets of selection in the LTEE and mutations present in previously sequenced clonal isolates allowed us to evaluate the accuracy of our procedure and to analyze the contribution of SV to total genetic diversity in these 12 independently evolving population.

可引发基因组结构变异（Structural Variation, SV）的新型突变，以可移动元件插入、大片段缺失、基因重复及其他染色体重排等形式存在，在微生物进化进程中扮演关键角色。然而，相较于单核苷酸变异与小插入缺失（indels），从短读长基因组重测序数据中预测结构变异的难度显著更高，因此在进化实验中用于表征种群水平遗传多样性随时间变化的DNA测序数据中，结构变异尚未实现常规鉴定。我们将一款用于检测多态性结构变异的算法整合至breseq计算流程中，该流程用于分析单倍体微生物基因组的重测序数据。该分析流程通过分析拆分比对序列（split-read alignments）——即单条测序读段的两端与参考基因组上不连续位置匹配的现象——来检测结构变异，并估算其在样本中的出现频率。我们将该算法应用于兰斯基大肠杆菌长期进化实验（Long-Term Evolution Experiment, LTEE）的500代与1000代种群样本中开展测试。借助对该实验中受选择靶向基因以及此前已测序克隆分离株所携带突变的认知，我们得以评估该分析流程的准确性，并解析结构变异对这12个独立进化种群总遗传多样性的贡献。