Cargando…

Systematic and benchmarking studies of pipelines for mammal WGBS data in the novel NGS platform

BACKGROUND: Whole genome bisulfite sequencing (WGBS), possesses the aptitude to dissect methylation status at the nucleotide-level resolution of 5-methylcytosine (5-mC) on a genome-wide scale. It is a powerful technique for epigenome in various cell types, and tissues. As a recently established next...

Descripción completa

Detalles Bibliográficos
Autores principales: Lin, Qun-ting, Yang, Wei, Zhang, Xin, Li, Qi-gang, Liu, Yong-feng, Yan, Qin, Sun, Lei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9890740/
https://www.ncbi.nlm.nih.gov/pubmed/36721080
http://dx.doi.org/10.1186/s12859-023-05163-w
_version_ 1784881000444067840
author Lin, Qun-ting
Yang, Wei
Zhang, Xin
Li, Qi-gang
Liu, Yong-feng
Yan, Qin
Sun, Lei
author_facet Lin, Qun-ting
Yang, Wei
Zhang, Xin
Li, Qi-gang
Liu, Yong-feng
Yan, Qin
Sun, Lei
author_sort Lin, Qun-ting
collection PubMed
description BACKGROUND: Whole genome bisulfite sequencing (WGBS), possesses the aptitude to dissect methylation status at the nucleotide-level resolution of 5-methylcytosine (5-mC) on a genome-wide scale. It is a powerful technique for epigenome in various cell types, and tissues. As a recently established next-generation sequencing (NGS) platform, GenoLab M is a promising alternative platform. However, its comprehensive evaluation for WGBS has not been reported. We sequenced two bisulfite-converted mammal DNA in this research using our GenoLab M and NovaSeq 6000, respectively. Then, we systematically compared those data via four widely used WGBS tools (BSMAP, Bismark, BatMeth2, BS-Seeker2) and a new bisulfite-seq tool (BSBolt). We interrogated their computational time, genome depth and coverage, and evaluated their percentage of methylated Cs. RESULT: Here, benchmarking a combination of pre- and post-processing methods, we found that trimming improved the performance of mapping efficiency in eight datasets. The data from two platforms uncovered ~ 80% of CpG sites genome-wide in the human cell line. Those data sequenced by GenoLab M achieved a far lower proportion of duplicates (~ 5.5%). Among pipelines, BSMAP provided an intriguing representation of 5-mC distribution at CpG sites with 5-mC levels > ~ 78% in datasets from human cell lines, especially in the GenoLab M. BSMAP performed more advantages in running time, uniquely mapped reads percentages, genomic coverage, and quantitative accuracy. Finally, compared with the previous methylation pattern of human cell line and mouse tissue, we confirmed that the data from GenoLab M performed similar consistency and accuracy in methylation levels of CpG sites with that from NovaSeq 6000. CONCLUSION: Together we confirmed that GenoLab M was a qualified NGS platform for WGBS with high performance. Our results showed that BSMAP was the suitable pipeline that allowed for WGBS studies on the GenoLab M platform. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-023-05163-w.
format Online
Article
Text
id pubmed-9890740
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-98907402023-02-02 Systematic and benchmarking studies of pipelines for mammal WGBS data in the novel NGS platform Lin, Qun-ting Yang, Wei Zhang, Xin Li, Qi-gang Liu, Yong-feng Yan, Qin Sun, Lei BMC Bioinformatics Research BACKGROUND: Whole genome bisulfite sequencing (WGBS), possesses the aptitude to dissect methylation status at the nucleotide-level resolution of 5-methylcytosine (5-mC) on a genome-wide scale. It is a powerful technique for epigenome in various cell types, and tissues. As a recently established next-generation sequencing (NGS) platform, GenoLab M is a promising alternative platform. However, its comprehensive evaluation for WGBS has not been reported. We sequenced two bisulfite-converted mammal DNA in this research using our GenoLab M and NovaSeq 6000, respectively. Then, we systematically compared those data via four widely used WGBS tools (BSMAP, Bismark, BatMeth2, BS-Seeker2) and a new bisulfite-seq tool (BSBolt). We interrogated their computational time, genome depth and coverage, and evaluated their percentage of methylated Cs. RESULT: Here, benchmarking a combination of pre- and post-processing methods, we found that trimming improved the performance of mapping efficiency in eight datasets. The data from two platforms uncovered ~ 80% of CpG sites genome-wide in the human cell line. Those data sequenced by GenoLab M achieved a far lower proportion of duplicates (~ 5.5%). Among pipelines, BSMAP provided an intriguing representation of 5-mC distribution at CpG sites with 5-mC levels > ~ 78% in datasets from human cell lines, especially in the GenoLab M. BSMAP performed more advantages in running time, uniquely mapped reads percentages, genomic coverage, and quantitative accuracy. Finally, compared with the previous methylation pattern of human cell line and mouse tissue, we confirmed that the data from GenoLab M performed similar consistency and accuracy in methylation levels of CpG sites with that from NovaSeq 6000. CONCLUSION: Together we confirmed that GenoLab M was a qualified NGS platform for WGBS with high performance. Our results showed that BSMAP was the suitable pipeline that allowed for WGBS studies on the GenoLab M platform. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-023-05163-w. BioMed Central 2023-01-31 /pmc/articles/PMC9890740/ /pubmed/36721080 http://dx.doi.org/10.1186/s12859-023-05163-w Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Lin, Qun-ting
Yang, Wei
Zhang, Xin
Li, Qi-gang
Liu, Yong-feng
Yan, Qin
Sun, Lei
Systematic and benchmarking studies of pipelines for mammal WGBS data in the novel NGS platform
title Systematic and benchmarking studies of pipelines for mammal WGBS data in the novel NGS platform
title_full Systematic and benchmarking studies of pipelines for mammal WGBS data in the novel NGS platform
title_fullStr Systematic and benchmarking studies of pipelines for mammal WGBS data in the novel NGS platform
title_full_unstemmed Systematic and benchmarking studies of pipelines for mammal WGBS data in the novel NGS platform
title_short Systematic and benchmarking studies of pipelines for mammal WGBS data in the novel NGS platform
title_sort systematic and benchmarking studies of pipelines for mammal wgbs data in the novel ngs platform
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9890740/
https://www.ncbi.nlm.nih.gov/pubmed/36721080
http://dx.doi.org/10.1186/s12859-023-05163-w
work_keys_str_mv AT linqunting systematicandbenchmarkingstudiesofpipelinesformammalwgbsdatainthenovelngsplatform
AT yangwei systematicandbenchmarkingstudiesofpipelinesformammalwgbsdatainthenovelngsplatform
AT zhangxin systematicandbenchmarkingstudiesofpipelinesformammalwgbsdatainthenovelngsplatform
AT liqigang systematicandbenchmarkingstudiesofpipelinesformammalwgbsdatainthenovelngsplatform
AT liuyongfeng systematicandbenchmarkingstudiesofpipelinesformammalwgbsdatainthenovelngsplatform
AT yanqin systematicandbenchmarkingstudiesofpipelinesformammalwgbsdatainthenovelngsplatform
AT sunlei systematicandbenchmarkingstudiesofpipelinesformammalwgbsdatainthenovelngsplatform