Integrative analysis of the zinc finger transcription factor Lame duck in the Drosophila myogenic gene regulatory network
Name
Busser-2012-Integrative analysis.pdf
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Author(s)
Busser, Brian W.
Huang, Di
Rogacki, Kevin R.
Lane, Elizabeth A.
Shokri, Leila
Ni, Ting
Gamble, Caitlin E.
Gisselbrecht, Stephen S.
Zhu, Jun
Bulyk, Martha L.
Date Issued
November 2012
Journal
Proceedings of the National Academy of Sciences of the United States of America
Publisher
National Academy of Sciences (U.S.)
Citation
Busser, B. W. et al. “Integrative Analysis of the Zinc Finger Transcription Factor Lame Duck in the Drosophila Myogenic Gene Regulatory Network.” Proceedings of the National Academy of Sciences 109.50 (2012): 20768–20773. ©2013 National Academy of Sciences
Version
Final published version
Abstract
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 ChIP sequencing (ChIP-seq), genome-wide mRNA profiling, cell-specific expression patterns of putative transcriptional targets, analysis of histone mark signatures, studies of TF cooccupancy 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 cooccupancy 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 insights into the transcriptional codes regulating muscle gene expression and offer a generalizable approach for similar studies in other systems.
MIT Department
Harvard University--MIT Division of Health Sciences and Technology
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1073/pnas.1210415109
