Cell type-selective disease-association of genes under high regulatory load

Nucleic Acids Research
Mafalda GalhardoLasse Sinkkonen

Abstract

We previously showed that disease-linked metabolic genes are often under combinatorial regulation. Using the genome-wide ChIP-Seq binding profiles for 93 transcription factors in nine different cell lines, we show that genes under high regulatory load are significantly enriched for disease-association across cell types. We find that transcription factor load correlates with the enhancer load of the genes and thereby allows the identification of genes under high regulatory load by epigenomic mapping of active enhancers. Identification of the high enhancer load genes across 139 samples from 96 different cell and tissue types reveals a consistent enrichment for disease-associated genes in a cell type-selective manner. The underlying genes are not limited to super-enhancer genes and show several types of disease-association evidence beyond genetic variation (such as biomarkers). Interestingly, the high regulatory load genes are involved in more KEGG pathways than expected by chance, exhibit increased betweenness centrality in the interaction network of liver disease genes, and carry longer 3' UTRs with more microRNA (miRNA) binding sites than genes on average, suggesting a role as hubs integrating signals within regulatory networks...Continue Reading

References

Dec 11, 1999·Nucleic Acids Research·M Kanehisa, S Goto
Dec 19, 2003·Nucleic Acids Research·Donna KarolchikW James Kent
Dec 21, 2004·Nucleic Acids Research·Ada HamoshVictor A McKusick
Jul 28, 2005·Journal of Biomedicine & Biotechnology·Maliackal Poulo JoySui Huang
Oct 4, 2005·Proceedings of the National Academy of Sciences of the United States of America·Aravind SubramanianJill P Mesirov
Dec 5, 2006·Biochemical and Biophysical Research Communications·Qinghua CuiEdwin Wang
Sep 11, 2008·Nucleic Acids Research·Allan Peter DavisCarolyn J Mattingly
Nov 8, 2008·Nucleic Acids Research·T S Keshava PrasadAkhilesh Pandey
Jan 30, 2010·Bioinformatics·Aaron R Quinlan, Ira M Hall
May 4, 2010·Nature Biotechnology·Cory Y McLeanGill Bejerano
Jul 20, 2010·Bioinformatics·W J KentD Karolchik
Oct 15, 2010·Nature Biotechnology·Anna Portela, Manel Esteller
Nov 26, 2010·Proceedings of the National Academy of Sciences of the United States of America·Menno P CreyghtonRudolf Jaenisch
Dec 17, 2010·Nature·Alvaro Rada-IglesiasJoanna Wysocka
Aug 23, 2011·Nature Genetics·Shankar MukherjiAlexander van Oudenaarden
Sep 8, 2012·Nature·UNKNOWN ENCODE Project Consortium
Sep 8, 2012·Science·Matthew T MauranoJohn A Stamatoyannopoulos
Sep 8, 2012·Genome Research·Benjamin VernotJoshua M Akey
Dec 12, 2012·Trends in Genetics : TIG·Laura I Furlong
Apr 23, 2013·Nature Methods·Merja HeinäniemiIlya Shmulevich
Jun 28, 2013·Human Mutation·Marialuisa QuadriVincenzo Bonifati
Oct 5, 2013·Haematologica·Joost H A Martens, Hendrik G Stunnenberg
Oct 15, 2013·Cell·Denes HniszRichard A Young
Oct 16, 2013·Proceedings of the National Academy of Sciences of the United States of America·Stephen C J ParkerUNKNOWN NISC Comparative Sequencing Program Authors
Jan 15, 2014·Nature Genetics·Lorenzo PasqualiJorge Ferrer
Feb 14, 2014·PloS One·Ashutosh K PandeyRobert W Williams
Mar 7, 2014·Journal of Clinical and Diagnostic Research : JCDR·M S Bhatia, Nirmaljit Kaur
May 27, 2014·Cell Reports·Rasmus SiersbækSusanne Mandrup
Oct 11, 2014·BioMed Research International·Valérie Drouet, Suzanne Lesage
Oct 19, 2014·Nucleic Acids Research·Allan Peter DavisCarolyn J Mattingly
Nov 5, 2014·Nature·Kyle Kai-How FarhBradley E Bernstein
Dec 6, 2014·Alzheimer's Research & Therapy·Jun-Ichi SatohKunimasa Arima
Feb 20, 2015·Nature·UNKNOWN Roadmap Epigenomics ConsortiumManolis Kellis

❮ Previous
Next ❯

Datasets Mentioned

BETA
GM12878
cells

Methods Mentioned

BETA
immunoprecipitation
ChIP-Seq
RNA-seq

Software Mentioned

TargetScan
ENSEMBL
fetchChromSizes
HOMER
BigBed
Bioconductor package ‘
DisGeNET
R
Matlab®
blockcluster

Related Concepts

Related Feeds

CREs: Gene & Cell Therapy

Gene and cell therapy advances have shown promising outcomes for several diseases. The role of cis-regulatory elements (CREs) is crucial in the design of gene therapy vectors. Here is the latest research on CREs in gene and cell therapy.

Cancer Epigenetics & Metabolism (Keystone)

Epigenetic changes are present and dysregulated in many cancers, including DNA methylation, non-coding RNA segments and post-translational protein modifications. The epigenetic changes may or may not provide advantages for the cancer cells. This feed focuses on the relationship between cell metabolism, epigenetics and tumor differentiation.