Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/36432
Title: Multiple platform assessmant of the EGF dependent transcritpome by microarrays and deep TAG sequencing analysis
Author: Llorens, Franc
Hummel, Manuela
Pastor Durán, Xavier
Ferrer, Anna
Pluvinet, Raquel
Vivancos, Ana
Castillo, Ester
Iraola Guzmán, Susana
Mosquera, A. M.
González Barca, Eva
Lozano, J.
Ingham, M.
Dohm, J. C.
Noguera, Marc
Kofler, R.
Río Fernández, José Antonio del
Bayés Colomer, Mònica
Himmelbauer, H.
Sumoy, Lauro
Keywords: Factor de creixement epidèrmic
Genètica humana
Microxips d'ADN
Epidermal growth factor
Human genetics
DNA microarrays
Issue Date: 2011
Publisher: BioMed Central
Abstract: Abstract Background: Epidermal Growth Factor (EGF) is a key regulatory growth factor activating many processes relevant to normal development and disease, affecting cell proliferation and survival. Here we use a combined approach to study the EGF dependent transcriptome of HeLa cells by using multiple long oligonucleotide based microarray platforms (from Agilent, Operon, and Illumina) in combination with digital gene expression profiling (DGE) with the Illumina Genome Analyzer. Results: By applying a procedure for cross-platform data meta-analysis based on RankProd and GlobalAncova tests, we establish a well validated gene set with transcript levels altered after EGF treatment. We use this robust gene list to build higher order networks of gene interaction by interconnecting associated networks, supporting and extending the important role of the EGF signaling pathway in cancer. In addition, we find an entirely new set of genes previously unrelated to the currently accepted EGF associated cellular functions. Conclusions: We propose that the use of global genomic cross-validation derived from high content technologies (microarrays or deep sequencing) can be used to generate more reliable datasets. This approach should help to improve the confidence of downstream in silico functional inference analyses based on high content data.
Note: Reproducció del document publicat a: http://www.biomedcentral.com/1471-2164/12/326
It is part of: Bmc Genomics, 2011, vol. 12, p. 326-330
URI: http://hdl.handle.net/2445/36432
ISSN: 1471-2164
Appears in Collections:Articles publicats en revistes (Biologia Cel·lular, Fisiologia i Immunologia)

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