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

Vincent Rocher¹, Matthieu Genais², Elissar Nassereddine¹

¹Molecular, Cellular and Developmental biology department (MCD), Centre de Biologie Intégrative (CBI), University of Toulouse, CNRS, UPS, Toulouse, France.

Plos Computational Biology

|August 12, 2021

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A new deep learning model, DeepG4, accurately maps active G-quadruplex (G4) regions in DNA, identifying specific motifs and transcription factors involved in G4 formation and activity across various cell types and cancers.

Area of Science:

Genomics
Bioinformatics
Molecular Biology

Background:

DNA's double-helix structure is well-known, but other DNA structures like G-quadruplexes (G4s) also play crucial cellular roles.
Existing methods for mapping G4s rely on sequence motifs or machine learning, with recent advancements in sequencing technologies (G4-seq, G4 ChIP-seq) offering higher resolution.

Purpose of the Study:

To develop a novel convolutional neural network, DeepG4, for precise mapping of cell-type-specific active G4 regions.
To identify key DNA motifs and transcription factors (TFs) associated with G4 activity.

Main Methods:

A convolutional neural network (DeepG4) was designed to predict active G4 regions using in vitro and in vivo data.
Bioinformatic analysis was employed to identify sequence motifs predictive of G4 activity.

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The model was applied to predict active G4 regions across numerous tissues and cancers.

Main Results:

DeepG4 accurately predicts active G4 regions across different cell types.
The study identified numerous specific DNA motifs, rather than flexible patterns, that determine active G4 regions.
Known transcription factors were identified as potentially influencing G4 activity directly or indirectly.

Conclusions:

DeepG4 provides a powerful tool for mapping active G4 regions with high accuracy.
The findings reveal specific sequence motifs and TFs crucial for G4 activity, advancing our understanding of G4s' roles in cellular processes.
The comprehensive prediction of active G4 regions in various tissues and cancers offers a valuable resource for further research.