High-fidelity, large-scale targeted profiling of microsatellites

生物 微卫星 仿形(计算机编程) 计算生物学 遗传学 忠诚 进化生物学 基因 计算机科学 等位基因 电信 操作系统
作者
Caitlin A. Loh,Danielle A. Shields,Adam Schwing,Gilad D. Evrony
出处
期刊:Genome Research [Cold Spring Harbor Laboratory Press]
卷期号:: gr.278785.123-gr.278785.123
标识
DOI:10.1101/gr.278785.123
摘要

Microsatellites are highly mutable sequences that can serve as markers for relationships among individuals or cells within a population. The accuracy and resolution of reconstructing these relationships depends on the fidelity of microsatellite profiling and the number of microsatellites profiled. However, current methods for targeted profiling of microsatellites incur significant "stutter" artifacts that interfere with accurate genotyping, and sequencing costs preclude whole-genome microsatellite profiling of a large number of samples. We developed a novel method for accurate and cost-effective targeted profiling of a panel of > 150,000 microsatellites per sample, along with a computational tool for designing large-scale microsatellite panels. Our method addresses the greatest challenge for microsatellite profiling - "stutter" artifacts - with a low-temperature hybridization capture that significantly reduces these artifacts. We also developed a computational tool for accurate genotyping of the resulting microsatellite sequencing data that uses an ensemble approach integrating three microsatellite genotyping tools, which we optimize by analysis of de novo microsatellite mutations in human trios. Altogether, our suite of experimental and computational tools enables high-fidelity, large-scale profiling of microsatellites, which may find utility in diverse applications such as lineage tracing, population genetics, ecology, and forensics.

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