ArticleGenome biology2013
Sequence signatures extracted from proximal promoters can be used to predict distal enhancers.
Article in Genome biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
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- Macrophage-enriched novel functional long noncoding RNAs LRRC75A-AS1 and GAPLINC regulate polarization and innate immune responses.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2024Article
- Altering transcription factor binding reveals comprehensive transcriptional kinetics of a basic gene.Nucleic acids research · 2021Article
- Live Imaging of embryogenic structures in Brassica napus microspore embryo cultures highlights the developmental plasticity of induced totipotent cells.Plant reproduction · 2020Article
- Pervasive and CpG-dependent promoter-like characteristics of transcribed enhancers.Nucleic acids research · 2020Article
- Identifying functions and prognostic biomarkers of network motifs marked by diverse chromatin states in human cell lines.Oncogene · 2020Article
- Sequence Characteristics Distinguish Transcribed Enhancers from Promoters and Predict Their Breadth of Activity.Genetics · 2019Article
- Variation of gene expression in plants is influenced by gene architecture and structural properties of promoters.PloS one · 2019Article
- Mutational analysis of a Drosophila neuroblast enhancer governing nubbin expression during CNS development.Genesis (New York, N.Y. : 2000) · 2018Article
- cuRRBS: simple and robust evaluation of enzyme combinations for reduced representation approaches.Nucleic acids research · 2017Article
- Genome-Wide Prediction of DNA Methylation Using DNA Composition and Sequence Complexity in Human.International journal of molecular sciences · 2017Article
- In silico identification of enhancers on the basis of a combination of transcription factor binding motif occurrences.Scientific reports · 2016Article
- Human endogenous retroviruses sustain complex and cooperative regulation of gene-containing loci and unannotated megabase-sized regions.Retrovirology · 2015Article
- Computational schemes for the prediction and annotation of enhancers from epigenomic assays.Methods (San Diego, Calif.) · 2015Review
- The RUNX2 cistrome in osteoblasts: characterization, down-regulation following differentiation, and relationship to gene expression.The Journal of biological chemistry · 2014Article
- Novel principles of gamma-retroviral insertional transcription activation in murine leukemia virus-induced end-stage tumors.Retrovirology · 2014Article
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5 authors.
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Abstract
backgroundGene expression is controlled by proximal promoters and distal regulatory elements such as enhancers. While the activity of some promoters can be invariant across tissues, enhancers tend to be highly tissue-specific.
resultsWe compiled sets of tissue-specific promoters based on gene expression profiles of 79 human tissues and cell types. Putative transcription factor binding sites within each set of sequences were used to train a support vector machine classifier capable of distinguishing tissue-specific promoters from control sequences. We obtained reliable classifiers for 92% of the tissues, with an area under the receiver operating characteristic curve between 60% (for subthalamic nucleus promoters) and 98% (for heart promoters). We next used these classifiers to identify tissue-specific enhancers, scanning distal non-coding sequences in the loci of the 200 most highly and lowly expressed genes. Thirty percent of reliable classifiers produced consistent enhancer predictions, with significantly higher densities in the loci of the most highly expressed compared to lowly expressed genes. Liver enhancer predictions were assessed in vivo using the hydrodynamic tail vein injection assay. Fifty-eight percent of the predictions yielded significant enhancer activity in the mouse liver, whereas a control set of five sequences was completely negative.
conclusionsWe conclude that promoters of tissue-specific genes often contain unambiguous tissue-specific signatures that can be learned and used for the de novo prediction of enhancers.
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