Reference : Integrated analysis of transcript-level regulation of metabolism reveals disease-rele...
Scientific journals : Article
Life sciences : Biochemistry, biophysics & molecular biology
http://hdl.handle.net/10993/11297
Integrated analysis of transcript-level regulation of metabolism reveals disease-relevant nodes of the human metabolic network
English
Galhardo, Mafalda Sofia* mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Life Science Research Unit >]
Sinkkonen, Lasse* mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Life Science Research Unit >]
Berninger, Philippe mailto [University of Basel > Biozentrum]
Lin, Jake mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
Sauter, Thomas mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Life Science Research Unit >]
Heinäniemi, Merja mailto [University of Eastern Finland > A. I. Virtanen Institute for Molecular Sciences]
* These authors have contributed equally to this work.
5-Nov-2013
Nucleic Acids Research
Oxford University Press
Yes (verified by ORBilu)
International
0305-1048
1362-4962
Oxford
United Kingdom
[en] Metabolic diseases and comorbidities represent an ever-growing epidemic where multiple cell types impact tissue homeostasis. Here, the link between the metabolic and gene regulatory networks was studied through experimental and computational analysis. Integrating gene regulation data with a human metabolic network prompted the establishment of an open-sourced web portal, IDARE (Integrated Data Nodes of Regulation), for visualizing various gene-related data in context of metabolic pathways. Motivated by increasing availability of deep sequencing studies, we obtained ChIP-seq data from widely studied human umbilical vein endothelial cells. Interestingly, we found that association of metabolic genes with multiple transcription factors (TFs) enriched disease-associated genes. To demonstrate further extensions enabled by examining these networks together, constraintbased modeling was applied to data from human preadipocyte differentiation. In parallel, data on gene expression, genome-wide ChIP-seq profiles for peroxisome proliferator-activated receptor (PPAR) c, CCAAT/enhancer binding protein (CEBP) a, liver X receptor (LXR) and H3K4me3 and microRNA target identification for miR-27a, miR-29a and miR-222 were collected. Disease-relevant key nodes, including mitochondrial glycerol-phosphateacyltransferase (GPAM), were exposed from metabolic pathways predicted to change activity by focusing on association with multiple regulators. In both cell types, our analysis reveals the convergence of microRNAs and TFs within the branched chain amino acid (BCAA) metabolic pathway, possibly providing an explanation for its downregulation in obese and diabetic conditions.
Luxembourg Centre for Systems Biomedicine (LCSB): Bioinformatics Core (R. Schneider Group)
University of Luxembourg - UL
http://hdl.handle.net/10993/11297
10.1093/nar/gkt989
http://nar.oxfordjournals.org/content/early/2013/11/05/nar.gkt989.full
The original publication is available at http://nar.oxfordjournals.org

File(s) associated to this reference

Fulltext file(s):

FileCommentaryVersionSizeAccess
Open access
Galhardo,Sinkkonen,Sauter,Heinäniemi-NAR2013.pdfPublisher postprint10.97 MBView/Open

Additional material(s):

File Commentary Size Access
Open access
Galhardo,Sinkkonen,Sauter,Heinäniemi-NAR2013(SUPPLEMENT).pdf6.4 MBView/Open

Bookmark and Share SFX Query

All documents in ORBilu are protected by a user license.