Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/85180
Title: Systematic evaluation of library preparation methods and sequencing platforms for high-throughput whole genome bisulfite sequencing
Authors: Schuster, Stephan C.
Beck, Stephan
Kim, Changhoon
Chambers, John Campbell
Loh, Marie
Zhou, Li
Ng, Hong Kiat
Drautz-Moses, Daniela I.
Keywords: Science::Biological sciences
Genomics
Biotechnology
Issue Date: 2019
Source: Zhou, L., Ng, H. K., Drautz-Moses, D. I., Schuster, S. C., Beck, S., Kim, C., . . . Loh, M. (2019). Systematic evaluation of library preparation methods and sequencing platforms for high-throughput whole genome bisulfite sequencing. Scientific Reports, 9(1), 10383-. doi:10.1038/s41598-019-46875-5
Series/Report no.: Scientific Reports
Abstract: Whole genome bisulfite sequencing (WGBS), with its ability to interrogate methylation status at single CpG site resolution epigenome-wide, is a powerful technique for use in molecular experiments. Here, we aim to advance strategies for accurate and efficient WGBS for application in future large-scale epidemiological studies. We systematically compared the performance of three WGBS library preparation methods with low DNA input requirement (Swift Biosciences Accel-NGS, Illumina TruSeq and QIAGEN QIAseq) on two state-of-the-art sequencing platforms (Illumina NovaSeq and HiSeq X), and also assessed concordance between data generated by WGBS and methylation arrays. Swift achieved the highest proportion of CpG sites assayed and effective coverage at 26x (P < 0.001). TruSeq suffered from the highest proportion of PCR duplicates, while QIAseq failed to deliver across all quality metrics. There was little difference in performance between NovaSeq and HiSeq X, with the exception of higher read duplication rate on the NovaSeq (P < 0.05), likely attributable to the higher cluster densities on its flow cells. Systematic biases exist between WGBS and methylation arrays, with lower precision observed for WGBS across the range of depths investigated. To achieve a level of precision broadly comparable to the methylation array, a minimum coverage of 100x is recommended.
URI: https://hdl.handle.net/10356/85180
http://hdl.handle.net/10220/49792
DOI: 10.1038/s41598-019-46875-5
Schools: Lee Kong Chian School of Medicine (LKCMedicine) 
Research Centres: Singapore Centre for Environmental Life Sciences and Engineering 
Rights: © 2019 The Author(s). This 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 license, and indicate if changes were made. Te images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:LKCMedicine Journal Articles

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