Improve-RRBS: a novel tool to correct the 3’ trimming of reduced representation sequencing reads

IF 2.4 Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY Bioinformatics advances Pub Date : 2024-05-24 DOI:10.1093/bioadv/vbae076
Abel Fothi, Hongbo Liu, Katalin Susztak, Tamás Arányi
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Abstract

Reduced Representation Bisulfite Sequencing (RRBS) is a popular approach to determine DNA methylation of the CpG-rich regions of the genome. However, we observed that false positive differentially methylated sites (DMS) are also identified using the standard computational analysis. During RRBS library preparation the MspI digested DNA undergo end-repair by a cytosine at the 3’ end of the fragments. After sequencing, Trim Galore cuts these end-repaired nucleotides. However, Trim Galore fails to detect end-repair when it overlaps with the 3’ end of the sequencing reads. We found that these non-trimmed cytosines bias methylation calling, thus can identify DMS erroneously. To circumvent this problem, we developed improve-RRBS, which efficiently identifies and hides these cytosines from methylation calling with a false positive rate of maximum 0.5%. To test improve-RRBS, we investigated four datasets from four laboratories and two different species. We found non-trimmed 3’ cytosines in all datasets analyzed and as much as > 50% of false positive DMS under certain conditions. By applying improve-RRBS, these DMS completely disappeared from all comparisons. improve-RRBS is a freely available python package https://pypi.org/project/iRRBS/ or https://github.com/fothia/improve-RRBS to be implemented in RRBS pipelines. Supplementary data are available at Bioinformatics Advances online.
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Improve-RRBS:校正缩减代表测序读数 3' 修剪的新型工具
还原表征亚硫酸氢盐测序(RRBS)是确定基因组 CpG 富集区 DNA 甲基化的一种常用方法。然而,我们观察到,使用标准计算分析也能发现假阳性差异甲基化位点(DMS)。 在 RRBS 文库制备过程中,MspI 消化的 DNA 会在片段的 3' 端发生胞嘧啶末端修复。测序后,Trim Galore 会切割这些末端修复的核苷酸。然而,当末端修复与测序读数的 3' 端重叠时,Trim Galore 无法检测到。我们发现,这些未修剪的胞嘧啶会影响甲基化调用,从而错误地识别出 DMS。为了规避这个问题,我们开发了 improve-RRBS,它能有效地识别和隐藏甲基化调用中的这些胞嘧啶,假阳性率不超过 0.5%。为了测试 improve-RRBS,我们调查了来自四个实验室和两个不同物种的四个数据集。我们在分析的所有数据集中都发现了未修剪的 3' 胞嘧啶,而且在某些条件下,DMS 的假阳性率高达 50% 以上。通过应用 improve-RRBS,这些 DMS 从所有比较中完全消失了。improve-RRBS 是一个免费提供的 python 软件包 https://pypi.org/project/iRRBS/ 或 https://github.com/fothia/improve-RRBS,可在 RRBS 管道中实现。 补充数据可在 Bioinformatics Advances 在线查阅。
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