Project description:Contemporary high throughput technologies permit the rapid identification of transcription factor (TF) target genes on a genome-wide scale, yet the functional significance of TFs requires knowledge of target gene expression patterns, cooperating TFs and cis-regulatory element (CRE) structures. Here we investigated the myogenic regulatory network downstream of the Drosophila zinc finger TF Lame duck (Lmd) by combining both previously published and newly performed genomic data sets, including chromatin immunoprecipitation sequencing (ChIP-seq), genome-wide mRNA profiling, cell-specific expression patterns of putative transcriptional targets, analysis of histone mark signatures, studies of TF co-occupancy by additional mesodermal regulators, TF binding site determination using protein binding microarrays (PBMs), and machine learning of candidate CRE motif compositions. Our findings suggest that Lmd orchestrates an extensive myogenic regulatory network, a conclusion supported by the identification of Lmd-dependent genes, histone signatures of Lmd-bound genomic regions, and the relationship of these features to cell-specific gene expression patterns. The heterogeneous co-occupancy of Lmd-bound regions with additional mesodermal regulators revealed that different transcriptional inputs are used to mediate similar myogenic gene expression patterns. Machine learning further demonstrated diverse combinatorial motif patterns within tissue-specific Lmd-bound regions. PBM analysis established the complete spectrum of Lmd DNA binding specificities, and site-directed mutagenesis of Lmd and additional, newly discovered motifs in known enhancers demonstrated the critical role of these TF binding sites in supporting full enhancer activity. Collectively, these findings provide new insights into the transcriptional codes regulating muscle gene expression, and offer a generalizable approach for similar studies in other systems. Examination of Lmd occupancy to genomic DNA from sorted mesodermal cells

Project description:To elucidate how genomic sequences build transcriptional control networks we need to understand the connection between DNA sequence and transcription factor binding and function. Binding predictions based solely on consensus predictions are limited because a single factor can use degenerate sequence motifs and related transcription factors often prefer identical sequences. The ETS family transcription factor, ETS1, exemplifies these challenges. Unexpected, redundant occupancy of ETS1 and other ETS proteins is observed at promoters of housekeeping genes in T cells due to common sequence preferences and the presence of strong consensus motifs. However, ETS1 exhibits a specific function in T cell activation, thus unique transcriptional targets are predicted. To uncover the sequence motifs that mediate specific functions of ETS1, chromatin immunoprecipitation coupled with high-throughput sequencing (ChIP-seq) identified both promoter and enhancer binding events in Jurkat T cells. A comparison with DNase I sensitivity both validated the dataset and improved accuracy. Redundant occupancy of ETS1 with the ETS protein GABPA occurred primarily in promoters of housekeeping genes, whereas ETS1 specific occupancy occurred in the enhancers of T-cell specific genes. Two routes to ETS1 specificity were identified: an intrinsic preference of ETS1 for a variant of the ETS family consensus sequence and the presence of a composite sequence that can support cooperative binding with a RUNX transcription factor. Genome-wide occupancy of RUNX factors corroborated the importance of this partnership. Furthermore, genome-wide occupancy of co-activator CBP indicated tight co-localization with ETS1 at specific enhancers, but not redundant promoters. The distinct sequences associated with redundant versus specific ETS1 occupancy were predictive of promoter or enhancer location and the ontology of nearby genes. These findings demonstrate that diversity of binding motifs may enable variable transcription factor function at different genomic sites. Each ChIP sample was pooled from three independent immunoprecipitation experiments

Project description:To elucidate how genomic sequences build transcriptional control networks we need to understand the connection between DNA sequence and transcription factor binding and function. Binding predictions based solely on consensus predictions are limited because a single factor can use degenerate sequence motifs and related transcription factors often prefer identical sequences. The ETS family transcription factor, ETS1, exemplifies these challenges. Unexpected, redundant occupancy of ETS1 and other ETS proteins is observed at promoters of housekeeping genes in T cells due to common sequence preferences and the presence of strong consensus motifs. However, ETS1 exhibits a specific function in T cell activation, thus unique transcriptional targets are predicted. To uncover the sequence motifs that mediate specific functions of ETS1, chromatin immunoprecipitation coupled with high-throughput sequencing (ChIP-seq) identified both promoter and enhancer binding events in Jurkat T cells. A comparison with DNase I sensitivity both validated the dataset and improved accuracy. Redundant occupancy of ETS1 with the ETS protein GABPA occurred primarily in promoters of housekeeping genes, whereas ETS1 specific occupancy occurred in the enhancers of T-cell specific genes. Two routes to ETS1 specificity were identified: an intrinsic preference of ETS1 for a variant of the ETS family consensus sequence and the presence of a composite sequence that can support cooperative binding with a RUNX transcription factor. Genome-wide occupancy of RUNX factors corroborated the importance of this partnership. Furthermore, genome-wide occupancy of co-activator CBP indicated tight co-localization with ETS1 at specific enhancers, but not redundant promoters. The distinct sequences associated with redundant versus specific ETS1 occupancy were predictive of promoter or enhancer location and the ontology of nearby genes. These findings demonstrate that diversity of binding motifs may enable variable transcription factor function at different genomic sites.

Dataset Information

Learning the cis sequence elements that determine AP-1 monomer specificity (ChIP-seq data sets)

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