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Preferential associations between co-regulated genes reveal a transcriptional interactome in erythroid cells.

ABSTRACT: The discovery of interchromosomal interactions in higher eukaryotes points to a functional interplay between genome architecture and gene expression, challenging the view of transcription as a one-dimensional process. However, the extent of interchromosomal interactions and the underlying mechanisms are unknown. Here we present the first genome-wide analysis of transcriptional interactions using the mouse globin genes in erythroid tissues. Our results show that the active globin genes associate with hundreds of other transcribed genes, revealing extensive and preferential intra- and interchromosomal transcription interactomes. We show that the transcription factor Klf1 mediates preferential co-associations of Klf1-regulated genes at a limited number of specialized transcription factories. Our results establish a new gene expression paradigm, implying that active co-regulated genes and their regulatory factors cooperate to create specialized nuclear hot spots optimized for efficient and coordinated transcriptional control.

SUBMITTER: Schoenfelder S

PROVIDER: S-EPMC3237402 | biostudies-literature | 2010 Jan

REPOSITORIES: biostudies-literature

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Preferential associations between co-regulated genes reveal a transcriptional interactome in erythroid cells.

Schoenfelder Stefan S Sexton Tom T Chakalova Lyubomira L Cope Nathan F NF Horton Alice A Andrews Simon S Kurukuti Sreenivasulu S Mitchell Jennifer A JA Umlauf David D Dimitrova Daniela S DS Eskiw Christopher H CH Luo Yanquan Y Wei Chia-Lin CL Ruan Yijun Y Bieker James J JJ Fraser Peter P

Nature genetics 20091213 1

The discovery of interchromosomal interactions in higher eukaryotes points to a functional interplay between genome architecture and gene expression, challenging the view of transcription as a one-dimensional process. However, the extent of interchromosomal interactions and the underlying mechanisms are unknown. Here we present the first genome-wide analysis of transcriptional interactions using the mouse globin genes in erythroid tissues. Our results show that the active globin genes associate ...[more]

PMID: 20010836

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Project description:BackgroundMicroRNAs (miRNAs) are important post-transcriptional regulators that have been demonstrated to play an important role in human diseases. Elucidating the associations between miRNAs and diseases at the systematic level will deepen our understanding of the molecular mechanisms of diseases. However, miRNA-disease associations identified by previous computational methods are far from completeness and more effort is needed.ResultsWe developed a computational framework to identify miRNA-disease associations by performing random walk analysis, and focused on the functional link between miRNA targets and disease genes in protein-protein interaction (PPI) networks. Furthermore, a bipartite miRNA-disease network was constructed, from which several miRNA-disease co-regulated modules were identified by hierarchical clustering analysis. Our approach achieved satisfactory performance in identifying known cancer-related miRNAs for nine human cancers with an area under the ROC curve (AUC) ranging from 71.3% to 91.3%. By systematically analyzing the global properties of the miRNA-disease network, we found that only a small number of miRNAs regulated genes involved in various diseases, genes associated with neurological diseases were preferentially regulated by miRNAs and some immunological diseases were associated with several specific miRNAs. We also observed that most diseases in the same co-regulated module tended to belong to the same disease category, indicating that these diseases might share similar miRNA regulatory mechanisms.ConclusionsIn this study, we present a computational framework to identify miRNA-disease associations, and further construct a bipartite miRNA-disease network for systematically analyzing the global properties of miRNA regulation of disease genes. Our findings provide a broad perspective on the relationships between miRNAs and diseases and could potentially aid future research efforts concerning miRNA involvement in disease pathogenesis.

Dataset Information

Preferential associations between co-regulated genes reveal a transcriptional interactome in erythroid cells.

Publications

Preferential associations between co-regulated genes reveal a transcriptional interactome in erythroid cells.

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