Conversion of MyoD to a neurogenic factor: binding site specificity determines lineage.

MyoD and NeuroD2, master regulators of myogenesis and neurogenesis, bind to a "shared" E-box sequence (CAGCTG) and a "private" sequence (CAGGTG or CAGATG, respectively). To determine whether private-site recognition is sufficient to confer lineage specification, we generated a MyoD mutant with the DNA-binding specificity of NeuroD2. This chimeric mutant gained binding to NeuroD2 private sites but maintained binding to a subset of MyoD-specific sites, activating part of both the muscle and neuronal programs.

Genome-wide binding of the basic helix-loop-helix myogenic inhibitor musculin has substantial overlap with MyoD: implications for buffering activity.

Background: Musculin (MSC) is a basic helix-loop-helix transcription factor that inhibits myogenesis during normal development and contributes to the differentiation defect in rhabdomyosarcoma. As one of many transcription factors that impede myogenesis, its binding on a genome-wide scale relative to the widespread binding of the myogenic factor MyoD is unknown.

Methods: Chromatin immunoprecipitation coupled to high-throughput sequencing was performed for endogenous MSC in rhabdomyosarcoma cells and its binding was compared to that of MyoD in the same type of cells.

Discriminative motif analysis of high-throughput dataset.

Motivation: High-throughput ChIP-seq studies typically identify thousands of peaks for a single transcription factor (TF). It is common for traditional motif discovery tools to predict motifs that are statistically significant against a naïve background distribution but are of questionable biological relevance.

Results: We describe a simple yet effective algorithm for discovering differential motifs between two sequence datasets that is effective in eliminating systematic biases and scalable to large datasets.

Skeletal muscle programming and re-programming.

The discovery of the transcription factor MyoD and its ability to induce muscle differentiation was the first demonstration of genetically programmed cell transdifferentiation. MyoD functions by activating a feed-forward circuit to regulate muscle gene expression. This requires binding to specific E-boxes throughout the genome, followed by recruitment of chromatin modifying complexes and transcription machinery.

Comparison of endogenous and overexpressed MyoD shows enhanced binding of physiologically bound sites.

Background: Transcription factor overexpression is common in biological experiments and transcription factor amplification is associated with many cancers, yet few studies have directly compared the DNA-binding profiles of endogenous versus overexpressed transcription factors.

Methods: We analyzed MyoD ChIP-seq data from C2C12 mouse myotubes, primary mouse myotubes, and mouse fibroblasts differentiated into muscle cells by overexpression of MyoD and compared the genome-wide binding profiles and binding site characteristics of endogenous and overexpressed MyoD.

Results: Overexpressed MyoD bound to the same sites occupied by endogenous MyoD and possessed the same E-box sequence preference and co-factor site enrichments, and did not bind to new sites with distinct characteristics.

Comparison of genome-wide binding of MyoD in normal human myogenic cells and rhabdomyosarcomas identifies regional and local suppression of promyogenic transcription factors.

Rhabdomyosarcoma is a pediatric tumor of skeletal muscle that expresses the myogenic basic helix-loop-helix protein MyoD but fails to undergo terminal differentiation. Prior work has determined that DNA binding by MyoD occurs in the tumor cells, but myogenic targets fail to activate. Using MyoD chromatin immunoprecipitation coupled to high-throughput sequencing and gene expression analysis in both primary human muscle cells and RD rhabdomyosarcoma cells, we demonstrate that MyoD binds in a similar genome-wide pattern in both tumor and normal cells but binds poorly at a subset of myogenic genes that fail to activate in the tumor cells.

Genetic and epigenetic determinants of neurogenesis and myogenesis.

The regulatory networks of differentiation programs have been partly characterized; however, the molecular mechanisms of lineage-specific gene regulation by highly similar transcription factors remain largely unknown. Here we compare the genome-wide binding and transcription profiles of NEUROD2-mediated neurogenesis with MYOD-mediated myogenesis. We demonstrate that NEUROD2 and MYOD bind a shared CAGCTG E box motif and E box motifs specific for each factor: CAGGTG for MYOD and CAGATG for NEUROD2.

DUX4 activates germline genes, retroelements, and immune mediators: implications for facioscapulohumeral dystrophy.

Facioscapulohumeral dystrophy (FSHD) is one of the most common inherited muscular dystrophies. The causative gene remains controversial and the mechanism of pathophysiology unknown. Here we identify genes associated with germline and early stem cell development as targets of the DUX4 transcription factor, a leading candidate gene for FSHD.

Polycomb-mediated repression during terminal differentiation: what don't you want to be when you grow up?

Chromatin-modifying enzymes are known to be critical components for the correct differentiation of embryonic stem cells into specific lineages, such as neurons. Recently, the role of Polycomb group proteins has been studied in the specification and differentiation of muscle stem cells. In this perspective, we review a recent study by Juan and colleagues (pp.

Genome-wide transcription factor binding: beyond direct target regulation.

The binding of transcription factors to specific DNA target sequences is the fundamental basis of gene regulatory networks. Chromatin immunoprecipitation combined with DNA tiling arrays or high-throughput sequencing (ChIP-chip and ChIP-seq, respectively) has been used in many recent studies that detail the binding sites of various transcription factors. Surprisingly, data from a variety of model organisms and tissues have demonstrated that transcription factors vary greatly in their number of genomic binding sites, and that binding events can significantly exceed the number of known or possible direct gene targets.