Gillian May, Shamit Soneji, Alex J. Tipping, Jose Teles, Simon J. McGowan, Mengchu Wu, Yanping Guo, Cristina Fugazza, John Brown, Goran Karlsson, Cristina Pina, Victor Olariu, Stephen Taylor, Daniel G. Tenen, Carsten Peterson and Tariq Enver
Dynamic analysis of gene expression and genome-wide description factor binding during lineage specification of multipotent progenitors
Cell Stem Cell 13, 754-768 (2013)
Abstract:
We used the paradigmatic GATA-PU.1 axis to explore, at the systems level, dynamic relationships between transcription factor (TF) binding and global gene expression programs as multipotent cells differentiate. We combined global ChIP-seq of GATA1, GATA2, and PU.1 with expression profiling during differentiation to erythroid and neutrophil line- ages. Our analysis reveals (1) differential complexity of sequence motifs bound by GATA1, GATA2, and PU.1; (2) the scope and interplay of GATA1 and GATA2 programs within, and during transitions between, different cell compartments, and the extent of their hard-wiring by DNA motifs; (3) the potential to predict gene expression trajectories based on global associations between TF-binding data and target gene expression; and (4) how dynamic modeling of DNA-binding and gene expression data can be used to infer regulatory logic of TF circuitry. This rubric exemplifies the utility of this cross-platform resource for deconvoluting the complexity of tran- scriptional programs controlling stem/progenitor cell fate in hematopoiesis.
LU TP 12-18
We used the paradigmatic GATA-PU.1 axis to explore, at the systems level, dynamic relationships between transcription factor (TF) binding and global gene expression programs as multipotent cells differentiate. We combined global ChIP-seq of GATA1, GATA2, and PU.1 with expression profiling during differentiation to erythroid and neutrophil line- ages. Our analysis reveals (1) differential complexity of sequence motifs bound by GATA1, GATA2, and PU.1; (2) the scope and interplay of GATA1 and GATA2 programs within, and during transitions between, different cell compartments, and the extent of their hard-wiring by DNA motifs; (3) the potential to predict gene expression trajectories based on global associations between TF-binding data and target gene expression; and (4) how dynamic modeling of DNA-binding and gene expression data can be used to infer regulatory logic of TF circuitry. This rubric exemplifies the utility of this cross-platform resource for deconvoluting the complexity of tran- scriptional programs controlling stem/progenitor cell fate in hematopoiesis.
LU TP 12-18