Validation of Skeletal Muscle cis-Regulatory Module Predictions Reveals Nucleotide Composition Bias in Functional Enhancers

We performed a genome-wide scan for muscle-specific cis-regulatory modules (CRMs) using three computational prediction programs. Based on the predictions, 339 candidate CRMs were tested in cell culture with NIH3T3 fibroblasts and C2C12 myoblasts for capacity to direct selective reporter gene expression to differentiated C2C12 myotubes. A subset of 19 CRMs validated as functional in the assay. The rate of predictive success reveals striking limitations of computational regulatory sequence analysis methods for CRM discovery. Motif-based methods performed no better than predictions based only on sequence conservation. Analysis of the properties of the functional sequences relative to inactive sequences identifies nucleotide sequence composition can be an important characteristic to incorporate in future methods for improved predictive specificity. Muscle-related TFBSs predicted within the functional sequences display greater sequence conservation than non-TFBS flanking regions. Comparison with recent MyoD and histone modification ChIP-Seq data supports the validity of the functional regions. Author Summary: For efficient identification of genomic sequences responsible for regulating gene expression, a number of computer programs have been developed for automatic annotation of these regulatory regions. We searched for potential regulatory regions responsible for controlling the expression of skeletal muscle-specific genes using these programs, and validated the predictions in a popular cell culture model for muscle. We were able to identify 19 previously uncharacterized regulatory regions for muscle genes. The accuracy of the predictions made by these programs leaves much to be desired, leading us to conclude that other signals in addition to the sequence information will be required to achieve sufficient predictive power for genome annotation. Genomic regions with confirmed regulatory function were compared against non-functional sequences, revealing sequence conservation, composition and chromatin modification properties as important signals in determining regulatory region functionality.