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深度测序文库的全基因组规模验证。

Genome-scale validation of deep-sequencing libraries.

作者信息

Schmidt Dominic, Stark Rory, Wilson Michael D, Brown Gordon D, Odom Duncan T

机构信息

Cancer Research UK, Cambridge Research Institute, Li Ka Shing Centre, Cambridge, UK.

出版信息

PLoS One. 2008;3(11):e3713. doi: 10.1371/journal.pone.0003713. Epub 2008 Nov 12.

Abstract

Chromatin immunoprecipitation followed by high-throughput (HTP) sequencing (ChIP-seq) is a powerful tool to establish protein-DNA interactions genome-wide. The primary limitation of its broad application at present is the often-limited access to sequencers. Here we report a protocol, Mab-seq, that generates genome-scale quality evaluations for nucleic acid libraries intended for deep-sequencing. We show how commercially available genomic microarrays can be used to maximize the efficiency of library creation and quickly generate reliable preliminary data on a chromosomal scale in advance of deep sequencing. We also exploit this technique to compare enriched regions identified using microarrays with those identified by sequencing, demonstrating that they agree on a core set of clearly identified enriched regions, while characterizing the additional enriched regions identifiable using HTP sequencing.

摘要

染色质免疫沉淀结合高通量(HTP)测序(ChIP-seq)是在全基因组范围内建立蛋白质-DNA相互作用的强大工具。目前其广泛应用的主要限制是测序仪的使用机会往往有限。在此,我们报告一种方法,即单克隆抗体测序(Mab-seq),它能对用于深度测序的核酸文库进行基因组规模的质量评估。我们展示了如何使用市售的基因组微阵列来最大化文库构建效率,并在深度测序之前快速在染色体规模上生成可靠的初步数据。我们还利用该技术比较了通过微阵列鉴定的富集区域与通过测序鉴定的富集区域,结果表明它们在一组明确鉴定的核心富集区域上是一致的,同时还对使用HTP测序可鉴定的其他富集区域进行了表征。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d688/2577887/a21f495996ca/pone.0003713.g001.jpg

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