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SCL and associated proteins distinguish active from repressive GATA transcription factor complexes.

ABSTRACT: GATA-1 controls hematopoietic development by activating and repressing gene transcription, yet the in vivo mechanisms that specify these opposite activities are unknown. By examining the composition of GATA-1-associated protein complexes in a conditional erythroid rescue system as well as through the use of tiling arrays we detected the SCL/TAL1, LMO2, Ldb1, E2A complex at all positively acting GATA-1-bound elements examined. Similarly, the SCL complex is present at all activating GATA elements in megakaryocytes and mast cells. In striking contrast, at sites where GATA-1 functions as a repressor, the SCL complex is depleted. A DNA-binding defective form of SCL maintains association with a subset of active GATA elements indicating that GATA-1 is a key determinant for SCL recruitment. Knockdown of LMO2 selectively impairs activation but not repression by GATA-1. ETO-2, an SCL-associated protein with the potential for transcription repression, is also absent from GATA-1-repressed genes but, unlike SCL, fails to accumulate at GATA-1-activated genes. Together, these studies identify the SCL complex as a critical and consistent determinant of positive GATA-1 activity in multiple GATA-1-regulated hematopoietic cell lineages.

SUBMITTER: Tripic T

PROVIDER: S-EPMC2652367 | biostudies-literature | 2009 Mar

REPOSITORIES: biostudies-literature

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SCL and associated proteins distinguish active from repressive GATA transcription factor complexes.

Tripic Tamara T Deng Wulan W Cheng Yong Y Zhang Ying Y Vakoc Christopher R CR Gregory Gregory D GD Hardison Ross C RC Blobel Gerd A GA

Blood 20081114 10

GATA-1 controls hematopoietic development by activating and repressing gene transcription, yet the in vivo mechanisms that specify these opposite activities are unknown. By examining the composition of GATA-1-associated protein complexes in a conditional erythroid rescue system as well as through the use of tiling arrays we detected the SCL/TAL1, LMO2, Ldb1, E2A complex at all positively acting GATA-1-bound elements examined. Similarly, the SCL complex is present at all activating GATA elements ...[more]

PMID: 19011221

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Project description:BackgroundInitiation of transcription is essential for most of the cellular responses to environmental conditions and for cell and tissue specificity. This process is regulated through numerous proteins, their ligands and mutual interactions, as well as interactions with DNA. The key such regulatory proteins are transcription factors (TFs) and transcription co-factors (TcoFs). TcoFs are important since they modulate the transcription initiation process through interaction with TFs. In eukaryotes, transcription requires that TFs form different protein complexes with various nuclear proteins. To better understand transcription regulation, it is important to know the functional class of proteins interacting with TFs during transcription initiation. Such information is not fully available, since not all proteins that act as TFs or TcoFs are yet annotated as such, due to generally partial functional annotation of proteins. In this study we have developed a method to predict, using only sequence composition of the interacting proteins, the functional class of human TF binding partners to be (i) TF, (ii) TcoF, or (iii) other nuclear protein. This allows for complementing the annotation of the currently known pool of nuclear proteins. Since only the knowledge of protein sequences is required in addition to protein interaction, the method should be easily applicable to many species.ResultsBased on experimentally validated interactions between human TFs with different TFs, TcoFs and other nuclear proteins, our two classification systems (implemented as a web-based application) achieve high accuracies in distinguishing TFs and TcoFs from other nuclear proteins, and TFs from TcoFs respectively.ConclusionAs demonstrated, given the fact that two proteins are capable of forming direct physical interactions and using only information about their sequence composition, we have developed a completely new method for predicting a functional class of TF interacting protein partners with high precision and accuracy.

Dataset Information

SCL and associated proteins distinguish active from repressive GATA transcription factor complexes.

Publications

SCL and associated proteins distinguish active from repressive GATA transcription factor complexes.

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