Literature DB >> 15388519

Genome-wide midrange transcription profiles reveal expression level relationships in human tissue specification.

Itai Yanai1, Hila Benjamin, Michael Shmoish, Vered Chalifa-Caspi, Maxim Shklar, Ron Ophir, Arren Bar-Even, Shirley Horn-Saban, Marilyn Safran, Eytan Domany, Doron Lancet, Orit Shmueli.   

Abstract

MOTIVATION: Genes are often characterized dichotomously as either housekeeping or single-tissue specific. We conjectured that crucial functional information resides in genes with midrange profiles of expression.
RESULTS: To obtain such novel information genome-wide, we have determined the mRNA expression levels for one of the largest hitherto analyzed set of 62 839 probesets in 12 representative normal human tissues. Indeed, when using a newly defined graded tissue specificity index tau, valued between 0 for housekeeping genes and 1 for tissue-specific genes, genes with midrange profiles having 0.15< tau<0.85 were found to constitute >50% of all expression patterns. We developed a binary classification, indicating for every gene the I(B) tissues in which it is overly expressed, and the 12-I(B) tissues in which it shows low expression. The 85 dominant midrange patterns with I(B)=2-11 were found to be bimodally distributed, and to contribute most significantly to the definition of tissue specification dendrograms. Our analyses provide a novel route to infer expression profiles for presumed ancestral nodes in the tissue dendrogram. Such definition has uncovered an unsuspected correlation, whereby de novo enhancement and diminution of gene expression go hand in hand. These findings highlight the importance of gene suppression events, with implications to the course of tissue specification in ontogeny and phylogeny. AVAILABILITY: All data and analyses are publically available at the GeneNote website, http://genecards.weizmann.ac.il/genenote/ and, GEO accession GSE803. CONTACT: doron.lancet@weizmann.ac.il SUPPLEMENTARY INFORMATION: Four tables available at the above site.

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Year:  2004        PMID: 15388519     DOI: 10.1093/bioinformatics/bti042

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  445 in total

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