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Physiology, pathology and relatedness of human tissues from gene expression meta-analysis. | LitMetric

AI Article Synopsis

Article Abstract

Background: Development and maintenance of the identity of tissues is of central importance for multicellular organisms. Based on gene expression profiles, it is possible to divide genes in housekeeping genes and those whose expression is preferential in one or a few tissues and which provide specialized functions that have a strong effect on the physiology of the whole organism.

Results: We have surveyed the gene expression in 78 normal human tissues integrating publicly available microarray gene expression data. A total amount of 1601 genes were identified as selectively expressed in one or more tissues. The tissue-selective genes covered a wide range of cellular and molecular functions, and could be linked to 361 human diseases with Mendelian inheritance. Based on the gene expression profiles, we were able to form a network of tissues reflecting their functional relatedness and, to certain extent, their development. Using co-citation driven gene network technique and promoter analysis, we predicted a transcriptional module where the co-operation of the transcription factors E2F and NF-kappaB can possibly regulate a number of genes involved in the neurogenesis that takes place in the adult hippocampus.

Conclusions: Here we propose that integration of gene expression data from Affymetrix GeneChip experiments is possible through re-annotation and commonly used pre-processing methods. We suggest that some functional aspects of the tissues can be explained by the co-operation of multiple transcription factors that regulate the expression of selected groups of genes.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2268968PMC
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0001880PLOS

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