DeepG4: A deep learning approach to predict cell-type specific active G-quadruplex regions.

DNA is a complex molecule carrying the instructions an organism needs to develop, live and reproduce. In 1953, Watson and Crick discovered that DNA is composed of two chains forming a double-helix. Later on, other structures of DNA were discovered and shown to play important roles in the cell, in pa...

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Autores principales:	Vincent Rocher, Matthieu Genais, Elissar Nassereddine, Raphael Mourad
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/fa6917e498234847a88643103b214c39
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spelling	oai:doaj.org-article:fa6917e498234847a88643103b214c392021-12-02T19:58:05ZDeepG4: A deep learning approach to predict cell-type specific active G-quadruplex regions.1553-734X1553-735810.1371/journal.pcbi.1009308https://doaj.org/article/fa6917e498234847a88643103b214c392021-08-01T00:00:00Zhttps://doi.org/10.1371/journal.pcbi.1009308https://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358DNA is a complex molecule carrying the instructions an organism needs to develop, live and reproduce. In 1953, Watson and Crick discovered that DNA is composed of two chains forming a double-helix. Later on, other structures of DNA were discovered and shown to play important roles in the cell, in particular G-quadruplex (G4). Following genome sequencing, several bioinformatic algorithms were developed to map G4s in vitro based on a canonical sequence motif, G-richness and G-skewness or alternatively sequence features including k-mers, and more recently machine/deep learning. Recently, new sequencing techniques were developed to map G4s in vitro (G4-seq) and G4s in vivo (G4 ChIP-seq) at few hundred base resolution. Here, we propose a novel convolutional neural network (DeepG4) to map cell-type specific active G4 regions (e.g. regions within which G4s form both in vitro and in vivo). DeepG4 is very accurate to predict active G4 regions in different cell types. Moreover, DeepG4 identifies key DNA motifs that are predictive of G4 region activity. We found that such motifs do not follow a very flexible sequence pattern as current algorithms seek for. Instead, active G4 regions are determined by numerous specific motifs. Moreover, among those motifs, we identified known transcription factors (TFs) which could play important roles in G4 activity by contributing either directly to G4 structures themselves or indirectly by participating in G4 formation in the vicinity. In addition, we used DeepG4 to predict active G4 regions in a large number of tissues and cancers, thereby providing a comprehensive resource for researchers. Availability: https://github.com/morphos30/DeepG4.Vincent RocherMatthieu GenaisElissar NassereddineRaphael MouradPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 17, Iss 8, p e1009308 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Vincent Rocher Matthieu Genais Elissar Nassereddine Raphael Mourad DeepG4: A deep learning approach to predict cell-type specific active G-quadruplex regions.
description	DNA is a complex molecule carrying the instructions an organism needs to develop, live and reproduce. In 1953, Watson and Crick discovered that DNA is composed of two chains forming a double-helix. Later on, other structures of DNA were discovered and shown to play important roles in the cell, in particular G-quadruplex (G4). Following genome sequencing, several bioinformatic algorithms were developed to map G4s in vitro based on a canonical sequence motif, G-richness and G-skewness or alternatively sequence features including k-mers, and more recently machine/deep learning. Recently, new sequencing techniques were developed to map G4s in vitro (G4-seq) and G4s in vivo (G4 ChIP-seq) at few hundred base resolution. Here, we propose a novel convolutional neural network (DeepG4) to map cell-type specific active G4 regions (e.g. regions within which G4s form both in vitro and in vivo). DeepG4 is very accurate to predict active G4 regions in different cell types. Moreover, DeepG4 identifies key DNA motifs that are predictive of G4 region activity. We found that such motifs do not follow a very flexible sequence pattern as current algorithms seek for. Instead, active G4 regions are determined by numerous specific motifs. Moreover, among those motifs, we identified known transcription factors (TFs) which could play important roles in G4 activity by contributing either directly to G4 structures themselves or indirectly by participating in G4 formation in the vicinity. In addition, we used DeepG4 to predict active G4 regions in a large number of tissues and cancers, thereby providing a comprehensive resource for researchers. Availability: https://github.com/morphos30/DeepG4.
format	article
author	Vincent Rocher Matthieu Genais Elissar Nassereddine Raphael Mourad
author_facet	Vincent Rocher Matthieu Genais Elissar Nassereddine Raphael Mourad
author_sort	Vincent Rocher
title	DeepG4: A deep learning approach to predict cell-type specific active G-quadruplex regions.
title_short	DeepG4: A deep learning approach to predict cell-type specific active G-quadruplex regions.
title_full	DeepG4: A deep learning approach to predict cell-type specific active G-quadruplex regions.
title_fullStr	DeepG4: A deep learning approach to predict cell-type specific active G-quadruplex regions.
title_full_unstemmed	DeepG4: A deep learning approach to predict cell-type specific active G-quadruplex regions.
title_sort	deepg4: a deep learning approach to predict cell-type specific active g-quadruplex regions.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/fa6917e498234847a88643103b214c39
work_keys_str_mv	AT vincentrocher deepg4adeeplearningapproachtopredictcelltypespecificactivegquadruplexregions AT matthieugenais deepg4adeeplearningapproachtopredictcelltypespecificactivegquadruplexregions AT elissarnassereddine deepg4adeeplearningapproachtopredictcelltypespecificactivegquadruplexregions AT raphaelmourad deepg4adeeplearningapproachtopredictcelltypespecificactivegquadruplexregions
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DeepG4: A deep learning approach to predict cell-type specific active G-quadruplex regions.

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