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How Do You Identify m(6) A Methylation in Transcriptomes at High Resolution? A Comparison of Recent Datasets
A flurry of methods has been developed in recent years to identify N6-methyladenosine (m(6)A) sites across transcriptomes at high resolution. This raises the need to understand both the common features and those that are unique to each method. Here, we complement the analyses presented in the origin...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7251061/ https://www.ncbi.nlm.nih.gov/pubmed/32508872 http://dx.doi.org/10.3389/fgene.2020.00398 |
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author | Capitanchik, Charlotte Toolan-Kerr, Patrick Luscombe, Nicholas M. Ule, Jernej |
author_facet | Capitanchik, Charlotte Toolan-Kerr, Patrick Luscombe, Nicholas M. Ule, Jernej |
author_sort | Capitanchik, Charlotte |
collection | PubMed |
description | A flurry of methods has been developed in recent years to identify N6-methyladenosine (m(6)A) sites across transcriptomes at high resolution. This raises the need to understand both the common features and those that are unique to each method. Here, we complement the analyses presented in the original papers by reviewing their various technical aspects and comparing the overlap between m(6)A-methylated messenger RNAs (mRNAs) identified by each. Specifically, we examine eight different methods that identify m(6)A sites in human cells with high resolution: two antibody-based crosslinking and immunoprecipitation (CLIP) approaches, two using endoribonuclease MazF, one based on deamination, two using Nanopore direct RNA sequencing, and finally, one based on computational predictions. We contrast the respective datasets and discuss the challenges in interpreting the overlap between them, including a prominent expression bias in detected genes. This overview will help guide researchers in making informed choices about using the available data and assist with the design of future experiments to expand our understanding of m(6)A and its regulation. |
format | Online Article Text |
id | pubmed-7251061 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-72510612020-06-05 How Do You Identify m(6) A Methylation in Transcriptomes at High Resolution? A Comparison of Recent Datasets Capitanchik, Charlotte Toolan-Kerr, Patrick Luscombe, Nicholas M. Ule, Jernej Front Genet Genetics A flurry of methods has been developed in recent years to identify N6-methyladenosine (m(6)A) sites across transcriptomes at high resolution. This raises the need to understand both the common features and those that are unique to each method. Here, we complement the analyses presented in the original papers by reviewing their various technical aspects and comparing the overlap between m(6)A-methylated messenger RNAs (mRNAs) identified by each. Specifically, we examine eight different methods that identify m(6)A sites in human cells with high resolution: two antibody-based crosslinking and immunoprecipitation (CLIP) approaches, two using endoribonuclease MazF, one based on deamination, two using Nanopore direct RNA sequencing, and finally, one based on computational predictions. We contrast the respective datasets and discuss the challenges in interpreting the overlap between them, including a prominent expression bias in detected genes. This overview will help guide researchers in making informed choices about using the available data and assist with the design of future experiments to expand our understanding of m(6)A and its regulation. Frontiers Media S.A. 2020-05-20 /pmc/articles/PMC7251061/ /pubmed/32508872 http://dx.doi.org/10.3389/fgene.2020.00398 Text en Copyright © 2020 Capitanchik, Toolan-Kerr, Luscombe and Ule. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Capitanchik, Charlotte Toolan-Kerr, Patrick Luscombe, Nicholas M. Ule, Jernej How Do You Identify m(6) A Methylation in Transcriptomes at High Resolution? A Comparison of Recent Datasets |
title | How Do You Identify m(6) A Methylation in Transcriptomes at High Resolution? A Comparison of Recent Datasets |
title_full | How Do You Identify m(6) A Methylation in Transcriptomes at High Resolution? A Comparison of Recent Datasets |
title_fullStr | How Do You Identify m(6) A Methylation in Transcriptomes at High Resolution? A Comparison of Recent Datasets |
title_full_unstemmed | How Do You Identify m(6) A Methylation in Transcriptomes at High Resolution? A Comparison of Recent Datasets |
title_short | How Do You Identify m(6) A Methylation in Transcriptomes at High Resolution? A Comparison of Recent Datasets |
title_sort | how do you identify m(6) a methylation in transcriptomes at high resolution? a comparison of recent datasets |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7251061/ https://www.ncbi.nlm.nih.gov/pubmed/32508872 http://dx.doi.org/10.3389/fgene.2020.00398 |
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