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首页> 外文期刊>Journal of Molecular Biology >Identifying Transcription Error-Enriched Genomic Loci Using Nuclear Run-on Circular-Sequencing Coupled with Background Error Modeling
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Identifying Transcription Error-Enriched Genomic Loci Using Nuclear Run-on Circular-Sequencing Coupled with Background Error Modeling

机译：使用核循环循环测序识别转录误差的基因组基因座，耦合与背景误差建模

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摘要

RNA polymerase transcribes certain genomic loci with higher errors rates. These transcription error-enriched genomic loci (TEELs) have implications in disease. Current deep-sequencing methods cannot distinguish TEELs from post-transcriptional modifications, stochastic transcription errors, and technical noise, impeding efforts to elucidate the mechanisms linking TEELs to disease. Here, we describe background error model-coupled precision nuclear run-on circular-sequencing (EmPC-seq) to discern genomic regions enriched for transcription misincorporations. EmPC-seq innovatively combines a nuclear run-on assay for capturing nascent RNA before post-transcriptional modifications, a circular-sequencing step that sequences the same nascent RNA molecules multiple times to improve accuracy, and a statistical model for distinguishing error-enriched regions among stochastic polymerase errors. Applying EmPC-seq to the ribosomal RNA transcriptome, we show that TEELs of RNA polymerase I are not randomly distributed but clustered together, with higher error frequencies at nascent transcript 3' ends. Our study establishes a reliable method of identifying TEELs with nucleotide precision, which can help elucidate their molecular origins. (C) 2020 Elsevier Ltd. All rights reserved.
机译：RNA聚合酶通过更高的误差率转录某些基因组基因座。这些转录误诊的基因组基因座（TEELS）对疾病有影响。目前的深序方法无法区分特点从转录后修改，随机转录错误和技术噪音，阻碍努力阐明将Tebels与疾病联系起来的机制。在这里，我们描述了背景误差模型耦合精密核循环循环测序（EMPC-SEQ），以辨别富含转录MISCLINGS的基因组区域。 EMPC-SEQ在转录后修饰之前，创新核延线测定用于捕获新生RNA，循环测序步骤序列多次序列以提高精度，以及用于区分误富集的区域的统计模型随机聚合酶误差。将EMPC-SEQ施加到核糖体RNA转录组，我们表明RNA聚合酶I的特点不是随机分布但聚集在一起，在新生转录物3'末端具有更高的误差频率。我们的研究建立了一种可靠的方法，鉴定具有核苷酸精度的特点，可以帮助阐明其分子起源。 （c）2020 elestvier有限公司保留所有权利。

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