A novel use of random priming-based single-strand library preparation for whole genome sequencing of formalin-fixed paraffin-embedded tissue samples

Saunderson, Emily A., Baker, Ann Marie, Williams, Marc, Curtius, Kit, Jones, J. Louise, Graham, Trevor A. and Ficz, Gabriella (2020) A novel use of random priming-based single-strand library preparation for whole genome sequencing of formalin-fixed paraffin-embedded tissue samples. NAR Genomics and Bioinformatics, 2 (1). ISSN 2631-9268

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Abstract

The desire to analyse limited amounts of biological material, historic samples and rare cell populations has collectively driven the need for efficient methods for whole genome sequencing (WGS) of limited amounts of poor quality DNA. Most protocols are designed to recover double-stranded DNA (dsDNA) by ligating sequencing adaptors to dsDNA with or without subsequent polymerase chain reaction amplification of the library. While this is sufficient for many applications, limited DNA requires a method that can recover both single-stranded DNA (ssDNA) and dsDNA. Here, we present a WGS library preparation method, called ‘degraded DNA adaptor tagging’ (DDAT), adapted from a protocol designed for whole genome bisulfite sequencing. This method uses two rounds of random primer extension to recover both ssDNA and dsDNA. We show that by using DDAT we can generate WGS data from formalin-fixed paraffin-embedded (FFPE) samples using as little as 2 ng of highly degraded DNA input. Furthermore, DDAT WGS data quality was higher for all FFPE samples tested compared to data produced using a standard WGS library preparation method. Therefore, the DDAT method has potential to unlock WGS data from DNA previously considered impossible to sequence, broadening opportunities to understand the role of genetics in health and disease.

Item Type: Article
Additional Information: Publisher Copyright: © The Author(s) 2019. Published by Oxford University Press on behalf of NAR Genomics and Bioinformatics.
Uncontrolled Keywords: genetics,structural biology,molecular biology,computer science applications,applied mathematics ,/dk/atira/pure/subjectarea/asjc/1300/1311
Faculty \ School:
UEA Research Groups: Faculty of Medicine and Health Sciences > Research Centres > Metabolic Health
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Depositing User: LivePure Connector
Date Deposited: 01 Nov 2022 14:31
Last Modified: 06 Jun 2024 15:20
URI: https://ueaeprints.uea.ac.uk/id/eprint/89459
DOI: 10.1093/nargab/lqz017

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