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Comparison of EM-seq and PBAT methylome library methods for low-input DNA

DNA methylation is the most studied epigenetic mark involved in regulation of gene expression. For low input samples, a limited number of methods for quantifying DNA methylation genome-wide has been evaluated. Here, we compared a series of input DNA amounts (1–10ng) from two methylome library prepar...

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Autores principales: Han, Yanan, Zheleznyakova, Galina Yurevna, Marincevic-Zuniga, Yanara, Kakhki, Majid Pahlevan, Raine, Amanda, Needhamsen, Maria, Jagodic, Maja
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9542412/
https://www.ncbi.nlm.nih.gov/pubmed/34709110
http://dx.doi.org/10.1080/15592294.2021.1997406
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author Han, Yanan
Zheleznyakova, Galina Yurevna
Marincevic-Zuniga, Yanara
Kakhki, Majid Pahlevan
Raine, Amanda
Needhamsen, Maria
Jagodic, Maja
author_facet Han, Yanan
Zheleznyakova, Galina Yurevna
Marincevic-Zuniga, Yanara
Kakhki, Majid Pahlevan
Raine, Amanda
Needhamsen, Maria
Jagodic, Maja
author_sort Han, Yanan
collection PubMed
description DNA methylation is the most studied epigenetic mark involved in regulation of gene expression. For low input samples, a limited number of methods for quantifying DNA methylation genome-wide has been evaluated. Here, we compared a series of input DNA amounts (1–10ng) from two methylome library preparation protocols, enzymatic methyl-seq (EM-seq) and post-bisulfite adaptor tagging (PBAT) adapted from single-cell PBAT. EM-seq takes advantage of enzymatic activity while PBAT relies on conventional bisulfite conversion for detection of DNA methylation. We found that both methods accurately quantified DNA methylation genome-wide. They produced expected distribution patterns around genomic features, high C-T transition efficiency at non-CpG sites and high correlation between input amounts. However, EM-seq performed better in regard to library and sequencing quality, i.e. EM-seq produced larger insert sizes, higher alignment rates and higher library complexity with lower duplication rate compared to PBAT. Moreover, EM-seq demonstrated higher CpG coverage, better CpG site overlap and higher consistency between input series. In summary, our data suggests that EM-seq overall performed better than PBAT in whole-genome methylation quantification of low input samples.
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spelling pubmed-95424122022-10-08 Comparison of EM-seq and PBAT methylome library methods for low-input DNA Han, Yanan Zheleznyakova, Galina Yurevna Marincevic-Zuniga, Yanara Kakhki, Majid Pahlevan Raine, Amanda Needhamsen, Maria Jagodic, Maja Epigenetics Research Paper DNA methylation is the most studied epigenetic mark involved in regulation of gene expression. For low input samples, a limited number of methods for quantifying DNA methylation genome-wide has been evaluated. Here, we compared a series of input DNA amounts (1–10ng) from two methylome library preparation protocols, enzymatic methyl-seq (EM-seq) and post-bisulfite adaptor tagging (PBAT) adapted from single-cell PBAT. EM-seq takes advantage of enzymatic activity while PBAT relies on conventional bisulfite conversion for detection of DNA methylation. We found that both methods accurately quantified DNA methylation genome-wide. They produced expected distribution patterns around genomic features, high C-T transition efficiency at non-CpG sites and high correlation between input amounts. However, EM-seq performed better in regard to library and sequencing quality, i.e. EM-seq produced larger insert sizes, higher alignment rates and higher library complexity with lower duplication rate compared to PBAT. Moreover, EM-seq demonstrated higher CpG coverage, better CpG site overlap and higher consistency between input series. In summary, our data suggests that EM-seq overall performed better than PBAT in whole-genome methylation quantification of low input samples. Taylor & Francis 2021-11-17 /pmc/articles/PMC9542412/ /pubmed/34709110 http://dx.doi.org/10.1080/15592294.2021.1997406 Text en © 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Paper
Han, Yanan
Zheleznyakova, Galina Yurevna
Marincevic-Zuniga, Yanara
Kakhki, Majid Pahlevan
Raine, Amanda
Needhamsen, Maria
Jagodic, Maja
Comparison of EM-seq and PBAT methylome library methods for low-input DNA
title Comparison of EM-seq and PBAT methylome library methods for low-input DNA
title_full Comparison of EM-seq and PBAT methylome library methods for low-input DNA
title_fullStr Comparison of EM-seq and PBAT methylome library methods for low-input DNA
title_full_unstemmed Comparison of EM-seq and PBAT methylome library methods for low-input DNA
title_short Comparison of EM-seq and PBAT methylome library methods for low-input DNA
title_sort comparison of em-seq and pbat methylome library methods for low-input dna
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9542412/
https://www.ncbi.nlm.nih.gov/pubmed/34709110
http://dx.doi.org/10.1080/15592294.2021.1997406
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