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.

中文翻译：

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移动元素定位器工具（MELT）：人口规模的移动元素发现和生物学。

流动元件插入（MEI）占人类基因组所有结构变异的约25％。而且，当MEI破坏基因时，它们会影响人类的特征和疾病。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，应该充分发现MEI以及其他形式的遗传变异。在这里，我们描述了移动元素定位工具（MELT），该工具是1000基因组计划的一部分，旨在在人口规模上进行MEI发现。通过使用Illumina WGS数据和模拟，我们证明了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，同时还检测了与MEI相关的更广泛的功能。开发了几种运行模式以在本地和云系统上执行MEI发现。除了作为1000个基因组计划的一部分，使用MELT在现代人类中发现MEI外，我们还使用它在黑猩猩和古代（尼安德特人和Denisovan）人类中发现MEI。我们在这些人群中发现了多种MEI分层模式，这可能是由于以下因素造成的：（1）源元素产生的MEI速率不同;（2）MEI遗传的模式多样;（3）古代MEI渗入现代人类基因组中。总的来说，我们的研究提供了迄今为止涵盖黑猩猩，古人类和现代人类的最全面的MEI图谱，并揭示了这些谱系中MEI生物学的新方面。我们还证明，MELT是在各种实验设置中进行MEI发现和分析的强大平台。