scholarly journals Large-scale identification of sequence variants influencing human transcription factor occupancy in vivo

2015 ◽  
Vol 47 (12) ◽  
pp. 1393-1401 ◽  
Author(s):  
Matthew T Maurano ◽  
Eric Haugen ◽  
Richard Sandstrom ◽  
Jeff Vierstra ◽  
Anthony Shafer ◽  
...  
2016 ◽  
Vol 48 (1) ◽  
pp. 101-101
Author(s):  
Matthew T Maurano ◽  
Eric Haugen ◽  
Richard Sandstrom ◽  
Jeff Vierstra ◽  
Anthony Shafer ◽  
...  

2007 ◽  
Author(s):  
Adam Margolin ◽  
Teresa Palomero ◽  
Pavel Sumazin ◽  
Andrea Califano ◽  
Adolfo Ferrando ◽  
...  

Blood ◽  
2004 ◽  
Vol 104 (11) ◽  
pp. 1610-1610
Author(s):  
Paresh Vyas ◽  
Boris Guyot ◽  
Veronica Valverde-Garduno ◽  
Eduardo Anguita ◽  
Isla Hamlett ◽  
...  

Abstract Normal differentiation of red cells, platelets and eosinophils from a myeloid progenitor requires expression of the transcription factor GATA1. Moreover, GATA1 expression level influences lineage output; higher levels promote erythromegakaryocytic differentiation and lower levels eosinophil maturation. Conversely, repression of GATA1 expression is required for monocyte/neutrophil development. GATA1 expression is principally controlled transcriptionally. Thus, dissecting the molecular basis of transcriptional control of GATA1 expression will be one important facet in understanding how myeloid lineages are specified. To address this question we sought to identify all DNA sequences important for GATA1 expression. Previous analysis identified 3 murine (m)Gata1 cis-elements (an upstream enhancer, mHS-3.5, a haematopoietic IE promoter and elements in a GATA1 intron, mHS+3.5) conserved in sequence between human(h) and mouse. These studies also suggested additional unidentified elements were required for erythroid and eosinophil GATA1 expression. We compared sequence, mapped DNase I hypersensitive sites (HS) and determined histone H3/H4 acetylation over ~120 kb flanking the hGATA1 locus and corresponding region in mouse to pinpoint cis-elements. Remarkably, despite lying in a ~10 MB conserved syntenic segment, the chromatin structures of both GATA1 loci are strikingly different. Two previously unidentified haematopoietic cis-elements, one in each species (mHS-25 and hHS+14), are not conserved in position and sequence and have enhancer activity in erythroid cells. Chromatin immunoprecipitation studies show both mHS-25 and hHS+14 are bound in vivo in red cells by the transcription factors GATA1, SCL, LMO2, Ldb1. These findings suggest that some cis-elements regulating human and mouse GATA1 genes differ. Further analysis of in vivo transcription factor occupancy at GATA1 cis-elements in primary mouse eosinophils and red cells, megakaryocytic cells (L8057) and control fibroblasts show lineage- and cis-element-specific patterns of regulator binding (see table below). In red cells and megakaryocytes, GATA1, SCL, LMO2 and Ldb1 bind at two regulatory elements (mhHS-25 and mHS-3.5). Interestingly, the megakaryocyte transcriptional regulator Fli1 factor binds to mHS+3.5 specifically in megakaryocytes. In eosinophils, a different pattern of DNase I HS and transcription factor binding is seen. GATA1, PU.1 and C/EBPe (all regulate eosinophil gene expression) bind IE promoter and/or mHS+3.5. Collectively, these results suggest lineage-specific GATA1 expession is dependent on combinations of cis-elements and haematopoietic trans-acting factors that are unique for each lineage. DNase I Hypersensitive sites and transcription factor occupancy at mGATA1 cis-elements. mHS-26/-25* mHS-3.5 mIE mHS+3.5 m: mouse, h: human, *: HS identified in this study, TF: transcription factor Primary erythroid cells HS present, GATA1, SCL, LMO2, Ldb1 HS present, GATA1, SCL, LMO2, Ldb1 HS present, GATA1 HS present, GATA1 Megakaryocytic cells HS present, GATA1, SCL, LMO2, Ldb1 HS present, GATA1, SCL, LMO2, Ldb1 HS present, GATA1 HS present, GATA1 and Fli1 Primary eosinophils HS absent HS present, No TF detected HS present, GATA1 and C/EBPε HS present, GATA1, C/EBP ε and PU.1 Fibroblasts HS absent HS absent HS absent HS absent


2008 ◽  
Vol 106 (1) ◽  
pp. 244-249 ◽  
Author(s):  
A. A. Margolin ◽  
T. Palomero ◽  
P. Sumazin ◽  
A. Califano ◽  
A. A. Ferrando ◽  
...  

2013 ◽  
Vol 113 (suppl_1) ◽  
Author(s):  
Joachim Altschmied ◽  
Nicole Büchner ◽  
Sascha Jakob ◽  
Sabrina Farrokh ◽  
Christine Goy ◽  
...  

Grainyhead-like 3 (GRHL3) is a member of the evolutionary conserved Grainyhead family of transcription factors. In humans, three isoforms are derived from differential first exon usage and alternative splicing, which differ only in their N-terminus. Isoform 2, the only variant also present in mouse, is required for endothelial cell (EC) migration and protects against apoptosis. The functions of the human specific isoforms 1 and 3, which are derived from an alternatively spliced pre-mRNA, have not yet been investigated, although all three isoforms are expressed in EC. Therefore, we have assessed their effects on EC migration and apoptosis. Overexpression of the two proteins had opposite effects on EC migration, with isoform 1 acting pro-migratory. This protein also protected EC against apoptosis in an eNOS-dependent manner, whereas isoform 3 had no effect. These opposing outcomes with respect to apoptosis EC were corroborated by isoform-specific knockdowns. With reporter assays using a GRHL3-specific luciferase reporter we demonstrated that both are active transcription factors. Microarray analyses revealed that they induce divergent target gene sets in EC. Two validated targets, Akt2 and Mxi1, which are upregulated by isoform1, are regulators of Akt1-, and thus eNOS-phosphorylation and apoptosis, which could explain the effects of this protein on these processes. In vivo, overexpression of isoform 3 in zebrafish embryos resulted in increased lethality and severe deformations, while isoform 1 had no deleterious effect. In conclusion, our data demonstrate that the splice variant derived isoforms 1 and 3 of the human transcription factor GRHL3 induce opposing effects in primary human endothelial cells and in a whole animal model, most likely through the induction of different target genes.


2018 ◽  
Author(s):  
Han Yuan ◽  
Meghana Kshirsagar ◽  
Lee Zamparo ◽  
Yuheng Lu ◽  
Christina S. Leslie

AbstractDecoding transcription factor (TF) binding signals in genomic DNA is a fundamental problem. Here we present a prediction model called BindSpace that learns to embed DNA sequences and TF class/family labels into the same space. By training on binding data for hundreds of TFs and embedding over 1M DNA sequences, BindSpace achieves state-of-the-art multiclass binding prediction performance, in vitro and in vivo, and can distinguish signals of closely related TFs.


2015 ◽  
Author(s):  
Yaron Orenstein ◽  
Ron Shamir

Recent technological advancements enable measuring the binding of a transcription factor to thousands of DNA sequences, in order to infer its binding preferences. High-throughput-SELEX measures protein-DNA binding by deep sequencing over several cycles of enrichment. We devised a new algorithm called HTS-IBIS for the inference task. HTS-IBIS corrects for technological biases, selects the cycle and k, and builds a motif starting from a consensus k-mer in that cycle. In large scale tests, HTS-IBIS outperformed the extant automatic algorithm for the motif finding task on both in vitro and in vivo binding prediction.


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