Abel Fothi, Hongbo Liu, Katalin Susztak, Tamás Arányi
{"title":"Improve-RRBS:校正缩减代表测序读数 3' 修剪的新型工具","authors":"Abel Fothi, Hongbo Liu, Katalin Susztak, Tamás Arányi","doi":"10.1093/bioadv/vbae076","DOIUrl":null,"url":null,"abstract":"\n \n \n 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.\n \n \n \n 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.\n \n \n \n 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.\n \n \n \n Supplementary data are available at Bioinformatics Advances online.\n","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":"15 3","pages":""},"PeriodicalIF":4.6000,"publicationDate":"2024-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Improve-RRBS: a novel tool to correct the 3’ trimming of reduced representation sequencing reads\",\"authors\":\"Abel Fothi, Hongbo Liu, Katalin Susztak, Tamás Arányi\",\"doi\":\"10.1093/bioadv/vbae076\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n \\n \\n 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.\\n \\n \\n \\n 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.\\n \\n \\n \\n 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.\\n \\n \\n \\n Supplementary data are available at Bioinformatics Advances online.\\n\",\"PeriodicalId\":2,\"journal\":{\"name\":\"ACS Applied Bio Materials\",\"volume\":\"15 3\",\"pages\":\"\"},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2024-05-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Applied Bio Materials\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1093/bioadv/vbae076\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MATERIALS SCIENCE, BIOMATERIALS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/bioadv/vbae076","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
Improve-RRBS: a novel tool to correct the 3’ trimming of reduced representation sequencing reads
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.
期刊介绍:
ACS Applied Bio Materials is an interdisciplinary journal publishing original research covering all aspects of biomaterials and biointerfaces including and beyond the traditional biosensing, biomedical and therapeutic applications.
The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrates knowledge in the areas of materials, engineering, physics, bioscience, and chemistry into important bio applications. The journal is specifically interested in work that addresses the relationship between structure and function and assesses the stability and degradation of materials under relevant environmental and biological conditions.