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Series GSE97691 Query DataSets for GSE97691
Status Public on Apr 03, 2018
Title Divergence in DNA specificity among paralogous transcription factors contributes to their differential in vivo binding [RG_Runx1Runx2_v1]
Organism Homo sapiens
Experiment type Genome binding/occupancy profiling by array
Summary Members of transcription factor (TF) families, i.e. paralogous TFs, are oftentimes reported to have identical DNA-binding motifs, despite the fact that they perform distinct regulatory functions in the cell. Differential genomic targeting by paralogous TFs is generally assumed to be due to interactions with protein cofactors or the chromatin environment. Contrary to previous assumptions, we find that paralogous TFs have different intrinsic preferences for DNA, not captured by current motif models, and these differences partly explain differential genomic binding and functional specificity. Our finding was possible due to a unique combination of carefully designed high-throughput assays and rigorous computation modeling, integrated into a unified framework called iMADS. We used iMADS to quantity, model, and analyze specificity differences between 11 paralogous TFs from 4 distinct human TF families. Our finding of differential specificity between closely related TFs has important implications for the interpretation of the regulatory effects of non-coding genetic variants.
Overall design Four genomic-context protein binding microarray (gcPBM) experiments were performed for recombinant, full-length, human transcription factors Runx1 and Runx2. Briefly, the PBMs involved binding of GST-tagged transcription factors Runx1 and Runx2 to double-stranded 180K Agilent microarrays in order to determine their binding specificity for putative DNA binding sites in native genomic context. Each genomic DNA sequence represented on the array is present in 6 replicate spots. We report the gcPBM signal intensity for each spot.
Contributor(s) Gordan R
Citation(s) 29605182
NIH grant(s)
Grant ID Grant title Affiliation Name
R01 GM117106 New methods for quantitative modeling of protein-DNA interactions DUKE UNIVERSITY Raluca Gordan
Submission date Apr 12, 2017
Last update date Jul 18, 2018
Contact name Raluca Gordan
Organization name Duke University
Department Center for Genomic and Computational Biology
Street address 101 Science Dr, CIEMAS 2179
City Durham
State/province NC
ZIP/Postal code 27708
Country USA
Platforms (1)
GPL23293 Duke/RG_Runx1Runx2_v1 (Agilent 4x180k)
Samples (4)
GSM2575567 Runx1 at 10 nM concentration
GSM2575568 Runx1 at 50 nM concentration
GSM2575569 Runx2 at 10 nM concentration
This SubSeries is part of SuperSeries:
GSE97794 Divergence in DNA specificity among paralogous transcription factors contributes to their differential in vivo binding
BioProject PRJNA382675

Download family Format
SOFT formatted family file(s) SOFTHelp
MINiML formatted family file(s) MINiMLHelp
Series Matrix File(s) TXTHelp

Supplementary file Size Download File type/resource
GSE97691_Combined_Runx1_10nM_50nM_Runx2_10nM_50nM_log.xlsx 1.7 Mb (ftp)(http) XLSX
GSE97691_Combined_Runx1_10nM_50nM_Runx2_10nM_50nM_log_normalized.xlsx 2.2 Mb (ftp)(http) XLSX
GSE97691_RAW.tar 31.8 Mb (http)(custom) TAR (of TXT)
Processed data are available on Series record

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