ArticleGenome biology2005
Promoter features related to tissue specificity as measured by Shannon entropy.
Article in Genome biology, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 268 papers.
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268 citing papers in PubMed.
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- Mapping putative enhancers in mouse oocytes and early embryos reveals TCF3/12 as key folliculogenesis regulators.Nature cell biology · 2024Article
- Long-read sequencing for 29 immune cell subsets reveals disease-linked isoforms.Nature communications · 2024Article
- A time-resolved multi-omics atlas of transcriptional regulation in response to high-altitude hypoxia across whole-body tissues.Nature communications · 2024Article
- Enhancer-promoter specificity in gene transcription: molecular mechanisms and disease associations.Experimental & molecular medicine · 2024Review
- Quantifying transcriptome diversity: a review.Briefings in functional genomics · 2024Review
- Single-cell transcriptome analysis dissects lncRNA-associated gene networks in Arabidopsis.Plant communications · 2024Article
- Correlating gene expression levels with transcription factor binding sites facilitates identification of key transcription factors from transcriptome data.Frontiers in genetics · 2024Article
- Homozygosity in any HLA locus is a risk factor for specific antibody production: the taboo concept 2.0.Frontiers in immunology · 2024Article
208 more citing papers are in PubMed but not listed here.
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6 authors.
Funding
Abstract
backgroundThe regulatory mechanisms underlying tissue specificity are a crucial part of the development and maintenance of multicellular organisms. A genome-wide analysis of promoters in the context of gene-expression patterns in tissue surveys provides a means of identifying the general principles for these mechanisms.
resultsWe introduce a definition of tissue specificity based on Shannon entropy to rank human genes according to their overall tissue specificity and by their specificity to particular tissues. We apply our definition to microarray-based and expressed sequence tag (EST)-based expression data for human genes and use similar data for mouse genes to validate our results. We show that most genes show statistically significant tissue-dependent variations in expression level. We find that the most tissue-specific genes typically have a TATA box, no CpG island, and often code for extracellular proteins. As expected, CpG islands are found in most of the least tissue-specific genes, which often code for proteins located in the nucleus or mitochondrion. The class of genes with no CpG island or TATA box are the most common mid-specificity genes and commonly code for proteins located in a membrane. Sp1 was found to be a weak indicator of less-specific expression. YY1 binding sites, either as initiators or as downstream sites, were strongly associated with the least-specific genes.
conclusionsWe have begun to understand the components of promoters that distinguish tissue-specific from ubiquitous genes, to identify associations that can predict the broad class of gene expression from sequence data alone.
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