ArticlePLoS computational biology2011
Validation of skeletal muscle cis-regulatory module predictions reveals nucleotide composition bias in functional enhancers.
Article in PLoS computational biology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Single-nucleus RNA-seq of differentiating human myoblasts reveals the extent of fate heterogeneity.Nucleic acids research · 2016Article
- A KAP1 phosphorylation switch controls MyoD function during skeletal muscle differentiation.Genes & development · 2015Article
- GAMI-CRM: Using de novo motif inference to detect cis-regulatory modules.Proceedings of the ... Congress on Evolutionary Computation. Congress on Evolutionary Computation · 2014Article
- Unveiling combinatorial regulation through the combination of ChIP information and in silico cis-regulatory module detection.Nucleic acids research · 2012Article
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Authors and funding
4 authors.
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Abstract
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.
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