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

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.

SUBMITTER: Greco D

PROVIDER: S-EPMC2268968 | biostudies-literature | 2008

REPOSITORIES: biostudies-literature

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

Greco Dario D Somervuo Panu P Di Lieto Antonio A Raitila Tuomas T Nitsch Lucio L Castrén Eero E Auvinen Petri P

PloS one 20080402 4

<h4>Background</h4>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.<h4>Results</h4>We have surveyed the gene expression in 78 normal human tissues integrating publicly available ...[more]

PMID: 18382664

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Project description:BACKGROUND:Infections with the West Nile virus (WNV) can attack neurological tissues in the host and alter gene expression levels therein. Several individual studies have analyzed these changes in the transcriptome based on measurements with DNA microarrays. Individual microarray studies produce a high-dimensional data structure with the number of studied genes exceeding the available sample size by far. Therefore, the level of scientific evidence of these studies is rather low and results can remain uncertain. Furthermore, the individual studies concentrate on different types of tissues or different time points after infection. A general statement regarding the transcriptional changes through WNV infection in neurological tissues is therefore hard to make. We screened public databases for transcriptome expression studies related to WNV infections and used different analysis pipelines to perform meta-analyses of these data with the goal of obtaining more stable results and increasing the level of evidence. RESULTS:We generated new lists of genes differentially expressed between WNV infected neurological tissues and control samples. A comparison with these genes to findings of a meta-analysis of immunological tissues is performed to figure out tissue-specific differences. While 5.879 genes were identified exclusively in the neurological tissues, 15 genes were found exclusively in the immunological tissues, and 44 genes were commonly detected in both tissues. Most findings of the original studies could be confirmed by the meta-analysis with a higher statistical power, but some genes and GO terms related to WNV were newly detected, too. In addition, we identified gene ontology terms related to certain infection processes, which are significantly enriched among the differentially expressed genes. In the neurological tissues, 17 gene ontology terms were found significantly different, and 2 terms in the immunological tissues. CONCLUSIONS:A critical discussion of our findings shows benefits but also limitations of the meta-analytic approach. In summary, the produced gene lists, identified gene ontology terms and network reconstructions appear to be more reliable than the results from the individual studies. Our meta-analysis provides a basis for further research on the transcriptional mechanisms by WNV infections in neurological tissues.

Dataset Information

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

Publications

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

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