Dataset Information

Transcription Factor GFI1B in Health and Disease.

ABSTRACT: Many human diseases arise through dysregulation of genes that control key cell fate pathways. Transcription factors (TFs) are major cell fate regulators frequently involved in cancer, particularly in leukemia. The GFI1B gene, coding a TF, was identified by sequence homology with the oncogene growth factor independence 1 (GFI1). Both GFI1 and GFI1B have six C-terminal C2H2 zinc fingers and an N-terminal SNAG (SNAIL/GFI1) transcriptional repression domain. Gfi1 is essential for neutrophil differentiation in mice. In humans, GFI1 mutations are associated with severe congenital neutropenia. Gfi1 is also required for B and T lymphopoiesis. However, knockout mice have demonstrated that Gfi1b is required for development of both erythroid and megakaryocytic lineages. Consistent with this, human mutations of GFI1B produce bleeding disorders with low platelet count and abnormal function. Loss of Gfi1b in adult mice increases the absolute numbers of hematopoietic stem cells (HSCs) that are less quiescent than wild-type HSCs. In keeping with this key role in cell fate, GFI1B is emerging as a gene involved in cancer, which also includes solid tumors. In fact, abnormal activation of GFI1B and GFI1 has been related to human medulloblastoma and is also likely to be relevant in blood malignancies. Several pieces of evidence supporting this statement will be detailed in this mini review.

SUBMITTER: Anguita E

PROVIDER: S-EPMC5368270 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Publications

Transcription Factor GFI1B in Health and Disease.

Anguita Eduardo E Candel Francisco J FJ Chaparro Alberto A Roldán-Etcheverry Juan J JJ

Frontiers in oncology 20170328

Many human diseases arise through dysregulation of genes that control key cell fate pathways. Transcription factors (TFs) are major cell fate regulators frequently involved in cancer, particularly in leukemia. The <i>GFI1B</i> gene, coding a TF, was identified by sequence homology with the oncogene growth factor independence 1 (<i>GFI1</i>). Both GFI1 and GFI1B have six C-terminal C2H2 zinc fingers and an N-terminal SNAG (SNAIL/GFI1) transcriptional repression domain. Gfi1 is essential for neutr ...[more]

PMID: 28401061

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Project description:Identifying transcription factors (TF) involved in producing a genome-wide transcriptional profile is an essential step in building mechanistic model that can explain observed gene expression data. We developed a statistical framework for constructing genome-wide signatures of TF activity, and for using such signatures in the analysis of gene expression data produced by complex transcriptional regulatory programs. Our framework integrates ChIP-seq data and appropriately matched gene expression profiles to identify True REGulatory (TREG) TF-gene interactions. It provides genome-wide quantification of the likelihood of regulatory TF-gene interaction that can be used to either identify regulated genes, or as genome-wide signature of TF activity. To effectively use ChIP-seq data, we introduce a novel statistical model that integrates information from all binding "peaks" within 2 Mb window around a gene's transcription start site (TSS), and provides gene-level binding scores and probabilities of regulatory interaction. In the second step we integrate these binding scores and regulatory probabilities with gene expression data to assess the likelihood of True REGulatory (TREG) TF-gene interactions. We demonstrate the advantages of TREG framework in identifying genes regulated by two TFs with widely different distribution of functional binding events (ER? and E2f1). We also show that TREG signatures of TF activity vastly improve our ability to detect involvement of ER? in producing complex diseases-related transcriptional profiles. Through a large study of disease-related transcriptional signatures and transcriptional signatures of drug activity, we demonstrate that increase in statistical power associated with the use of TREG signatures makes the crucial difference in identifying key targets for treatment, and drugs to use for treatment. All methods are implemented in an open-source R package treg. The package also contains all data used in the analysis including 494 TREG binding profiles based on ENCODE ChIP-seq data. The treg package can be downloaded at http://GenomicsPortals.org.

Dataset Information

Transcription Factor GFI1B in Health and Disease.

Publications

Transcription Factor GFI1B in Health and Disease.

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