Program in Molecular Medicine, University of Maryland School of Medicine, Baltimore, Maryland 21201, USA.
Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, Maryland 21201, USA.
Genome Res. 2017 Nov;27(11):1916-1929. doi: 10.1101/gr.218032.116. Epub 2017 Aug 30.
Mobile element insertions (MEIs) represent ∼25% of all structural variants in human genomes. Moreover, when they disrupt genes, MEIs can influence human traits and diseases. Therefore, MEIs should be fully discovered along with other forms of genetic variation in whole genome sequencing (WGS) projects involving population genetics, human diseases, and clinical genomics. Here, we describe the Mobile Element Locator Tool (MELT), which was developed as part of the 1000 Genomes Project to perform MEI discovery on a population scale. Using both Illumina WGS data and simulations, we demonstrate that MELT outperforms existing MEI discovery tools in terms of speed, scalability, specificity, and sensitivity, while also detecting a broader spectrum of MEI-associated features. Several run modes were developed to perform MEI discovery on local and cloud systems. In addition to using MELT to discover MEIs in modern humans as part of the 1000 Genomes Project, we also used it to discover MEIs in chimpanzees and ancient (Neanderthal and Denisovan) hominids. We detected diverse patterns of MEI stratification across these populations that likely were caused by (1) diverse rates of MEI production from source elements, (2) diverse patterns of MEI inheritance, and (3) the introgression of ancient MEIs into modern human genomes. Overall, our study provides the most comprehensive map of MEIs to date spanning chimpanzees, ancient hominids, and modern humans and reveals new aspects of MEI biology in these lineages. We also demonstrate that MELT is a robust platform for MEI discovery and analysis in a variety of experimental settings.
移动元件插入(MEI)代表人类基因组中所有结构变异的约 25%。此外,当它们扰乱基因时,MEI 会影响人类特征和疾病。因此,在涉及人群遗传学、人类疾病和临床基因组学的全基因组测序(WGS)项目中,应该与其他形式的遗传变异一起充分发现 MEI。在这里,我们描述了移动元件定位工具(MELT),它是作为 1000 基因组计划的一部分开发的,用于在人群规模上进行 MEI 发现。使用 Illumina WGS 数据和模拟,我们证明 MELT 在速度、可扩展性、特异性和敏感性方面优于现有的 MEI 发现工具,同时还检测到更广泛的 MEI 相关特征。开发了几种运行模式来在本地和云系统上执行 MEI 发现。除了在 1000 基因组计划中使用 MELT 发现现代人中的 MEI 之外,我们还使用它发现了黑猩猩和古(尼安德特人和丹尼索万人)人类中的 MEI。我们在这些人群中检测到了 MEI 分层的各种模式,这些模式可能是由(1)来源元素产生 MEI 的不同速率,(2)MEI 遗传的不同模式,以及(3)古 MEI 向现代人类基因组的渗透引起的。总体而言,我们的研究提供了迄今为止最全面的 MEI 图谱,涵盖了黑猩猩、古人类和现代人,并揭示了这些谱系中 MEI 生物学的新方面。我们还证明,MELT 是在各种实验环境中进行 MEI 发现和分析的强大平台。