Document detail
ID

oai:pubmedcentral.nih.gov:6245...

Topic
Research
Author
Legeay, Marc Aubourg, Sébastien Renou, Jean-Pierre Duval, Béatrice
Langue
en
Editor

BioMed Central

Category

BMC Systems Biology

Year

2018

listing date

12/12/2023

Keywords
ripening reveals sense mechanisms method specific study genes regulation as-impacted data interactions
Metrics

Abstract

BACKGROUND: Systems biology aims to analyse regulation mechanisms into the cell.

By mapping interactions observed in different situations, differential network analysis has shown its power to reveal specific cellular responses or specific dysfunctional regulations.

In this work, we propose to explore on a large scale the role of natural anti-sense transcription on gene regulation mechanisms, and we focus our study on apple (Malus domestica) in the context of fruit ripening in cold storage.

RESULTS: We present a differential functional analysis of the sense and anti-sense transcriptomic data that reveals functional terms linked to the ripening process.

To develop our differential network analysis, we introduce our inference method of an Extended Core Network; this method is inspired by C3NET, but extends the notion of significant interactions.

By comparing two extended core networks, one inferred with sense data and the other one inferred with sense and anti-sense data, our differential analysis is first performed on a local view and reveals AS-impacted genes, genes that have important interactions impacted by anti-sense transcription.

The motifs surrounding AS-impacted genes gather transcripts with functions mostly consistent with the biological context of the data used and the method allows us to identify new actors involved in ripening and cold acclimation pathways and to decipher their interactions.

Then from a more global view, we compute minimal sub-networks that connect the AS-impacted genes using Steiner trees.

Those Steiner trees allow us to study the rewiring of the AS-impacted genes in the network with anti-sense actors.

CONCLUSION: Anti-sense transcription is usually ignored in transcriptomic studies.

The large-scale differential analysis of apple data that we propose reveals that anti-sense regulation may have an important impact in several cellular stress response mechanisms.

Our data mining process enables to highlight specific interactions that deserve further experimental investigations.

ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12918-018-0613-7) contains supplementary material, which is available to authorized users.

Legeay, Marc,Aubourg, Sébastien,Renou, Jean-Pierre,Duval, Béatrice, 2018, Large scale study of anti-sense regulation by differential network analysis, BioMed Central

Document

Open Open

Share

Source

Articles recommended by ES/IODE AI

Investigation of Heavy Metal Analysis on Medicinal Plants Used for the Treatment of Skin Cancer by Traditional Practitioners in Pretoria
heavy metals medicinal plants skin cancer icp-ms health risk assessment treatment cancer plants 0 metal health medicinal