Population-scale analysis of human microsatellites reveals novel sources of exonic variation.
Population-scale analysis of human microsatellites reveals novel sources of exonic variation.
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DOI：
10.1016/j.gene.2012.12.068
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发表时间：
2013-03-10
期刊：
影响因子：
3.5
通讯作者：
Garner HR
中科院分区：
文献类型：
--
作者：
McIver LJ;McCormick JF;Martin A;Fondon JW 3rd;Garner HR
使用我们的微卫星特异性基因分型方法，我们分析了串联重复序列，这是已知的高度可变的一些公认的生物标志物致病，在超过500人的外显子测序在1000个基因组项目试点研究。我们能够在目标区域对超过97%的微卫星位点进行基因分型。总共观察到25，115个变异，包括重复长度和单核苷酸多态性，对应于平均每个个体45.6个变异和每个酶1.1个变异的密度。标准变异检测没有报告94.2%的外显子重复长度变异，部分原因是比对技术对于重复区域并不理想。此外，一些标准的变异检测工具依赖于已知变异的数据库，使得它们不太可能调用重复长度变异，因为这些基因座中只有一小部分（约6，000个）已被准确表征。我们发现的数百种非同义变异的一个子集经过了实验验证，表明我们基于微卫星的基因分型方法的准确率为96.5%，在与癌症相关的基因中发现了一些新的变异。我们建议将基于微卫星的基因分型作为大规模测序研究的一部分，以确定新的变体。
Using our microsatellite specific genotyping method, we analyzed tandem repeats, which are known to be highly variable with some recognized as biomarkers causative of disease, in over 500 individuals who were exon sequenced in a 1000 Genomes Project pilot study. We were able to genotype over 97% of the microsatellite loci in the targeted regions. A total of 25,115 variations were observed, including repeat length and single nucleotide polymorphisms, corresponding to an average of 45.6 variations per individual and a density of 1.1 variations per kilobase. Standard variant detection did not report 94.2% of the exonic repeat length variations in part because the alignment techniques are not ideal for repetitive regions. Additionally some standard variation detection tools rely on a database of known variations, making them less likely to call repeat length variations as only a small percent of these loci (~6,000) have been accurately characterized. A subset of the hundreds of non-synonymous variations we identified was experimentally validated, indicating an accuracy of 96.5% for our microsatellite-based genotyping method, with some novel variants identified in genes associated with cancer. We propose that microsatellite-based genotyping be used as a part of large scale sequencing studies to identify novel variants.
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