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  Meta-analysis of heterogeneous Down Syndrome data reveals consistent genome-wide dosage effects related to neurological processes

Vilardell, M., Rasche, A., Thormann, A., Maschke-Dutz, E., Perez-Jurado, L. A., Lehrach, H., et al. (2011). Meta-analysis of heterogeneous Down Syndrome data reveals consistent genome-wide dosage effects related to neurological processes. BMC Genomics, 12, 229. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/21569303 http://www.biomedcentral.com/1471-2164/12/229 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3110572/pdf/1471-2164-12-229.pdf?tool=pmcentrez.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0010-78C6-1 Version Permalink: http://hdl.handle.net/11858/00-001M-0000-0010-78C7-0
Genre: Journal Article

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Vilardell, M.1, Author              
Rasche, A.2, Author              
Thormann, A.2, Author              
Maschke-Dutz, E.1, Author              
Perez-Jurado, L. A., Author
Lehrach, H.1, Author              
Herwig, R., Author
Affiliations:
1Dept. of Vertebrate Genomics (Head: Hans Lehrach), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1433550              
2Bioinformatics (Ralf Herwig), Dept. of Vertebrate Genomics (Head: Hans Lehrach), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1479648              

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Free keywords: Animals; Brain/*metabolism; Chromosomes, Human, Pair 21/genetics; Down Syndrome/*genetics/metabolism; Gene Dosage/*genetics; Gene Expression Profiling; Genome, Human/genetics; Genomics/*methods; Humans; Mice; Molecular Sequence Annotation; Oligonucleotide Array Sequence Analysis; Phenotype; Proteomics; Reverse Transcriptase Polymerase Chain Reaction; Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization; Transcription Factors/metabolism; Transcription, Genetic
 Abstract: BACKGROUND: Down syndrome (DS; trisomy 21) is the most common genetic cause of mental retardation in the human population and key molecular networks dysregulated in DS are still unknown. Many different experimental techniques have been applied to analyse the effects of dosage imbalance at the molecular and phenotypical level, however, currently no integrative approach exists that attempts to extract the common information. RESULTS: We have performed a statistical meta-analysis from 45 heterogeneous publicly available DS data sets in order to identify consistent dosage effects from these studies. We identified 324 genes with significant genome-wide dosage effects, including well investigated genes like SOD1, APP, RUNX1 and DYRK1A as well as a large proportion of novel genes (N = 62). Furthermore, we characterized these genes using gene ontology, molecular interactions and promoter sequence analysis. In order to judge relevance of the 324 genes for more general cerebral pathologies we used independent publicly available microarry data from brain studies not related with DS and identified a subset of 79 genes with potential impact for neurocognitive processes. All results have been made available through a web server under http://ds-geneminer.molgen.mpg.de/. CONCLUSIONS: Our study represents a comprehensive integrative analysis of heterogeneous data including genome-wide transcript levels in the domain of trisomy 21. The detected dosage effects build a resource for further studies of DS pathology and the development of new therapies.

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 Dates: 2011
 Publication Status: Published in print
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Title: BMC Genomics
Source Genre: Journal
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Pages: - Volume / Issue: 12 Sequence Number: - Start / End Page: 229 Identifier: ISSN: 1471-2164 (Electronic) 1471-2164 (Linking)