Open Access Highly Accessed Research article

Multiple platform assessment of the EGF dependent transcriptome by microarray and deep tag sequencing analysis

Franc Llorens1234, Manuela Hummel56, Xavier Pastor567, Anna Ferrer56, Raquel Pluvinet7, Ana Vivancos689, Ester Castillo68, Susana Iraola110, Ana M Mosquera11125, Eva González1356, Juanjo Lozano1141556, Matthew Ingham1668, Juliane C Dohm178, Marc Noguera187, Robert Kofler171968, Jose Antonio del Río234, Mònica Bayés166, Heinz Himmelbauer1768 and Lauro Sumoy1567*

Author Affiliations

1 Bioinformatics and Genomics Program, Center for Genomic Regulation (CRG) - Universitat Pompeu Fabra (UPF), Barcelona, Spain

2 Molecular and Cellular Neurobiotechnology Group, Institut de Bioenginyeria de Catalunya (IBEC)-Parc Científic de Barcelona, Barcelona, Spain

3 Department of Cell Biology, University of Barcelona (UB), Barcelona, Spain

4 Networked Biomedical Research Center for Neurodegenerative Diseases (CIBERNED), Madrid, Spain

5 Microarray Unit, Genomics Core Facility, Center for Genomic Regulation (CRG) - Universitat Pompeu Fabra (UPF), Barcelona, Spain

6 Genomics Core Facility, Center for Genomic Regulation (CRG) - Universitat Pompeu Fabra (UPF), Barcelona, Spain

7 Genomics Unit, Institute of Predictive and Personalized Medicine of Cancer (IMPPC), Badalona, Spain

8 Ultrasequencing Unit, Genomics Core Facility, Center for Genomic Regulation (CRG) - Universitat Pompeu Fabra (UPF), Barcelona, Spain

9 Cancer Genomics Group, Vall d'Hebron Institute of Oncology, Barcelona, Spain

10 Genes and Disease Program, Center for Genomic Regulation (CRG) - Universitat Pompeu Fabra (UPF), Barcelona, Spain

11 Endocrinology Section, Hospital de Sant Joan de Deu, Esplugues de Llobregat, Spain

12 Networked Biomedical Research Center for Diabetes and Associated Metabolic Diseases (CIBERDEM), Barcelona, Spain

13 Servei de Inmunologia, Hospital Clínic i Provincial de Barcelona, Barcelona, Spain

14 Institut d'Investigacions Biomèdiques August Pi i Sunyer, Barcelona, Spain

15 Networked Biomedical Research Center for Hepatic and Digestive Diseases (CIBERHED), Barcelona, Spain

16 Spanish National center for Genomic Analysis (CNAG), Barcelona, Spain

17 Max Planck Institute for Molecular Genetics, Berlin, Germany

18 IRSI-Caixa, Badalona, Spain

19 Institute for Population Genetics, University of Veterinary Medicine, Vienna, Austria

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BMC Genomics 2011, 12:326  doi:10.1186/1471-2164-12-326

Published: 23 June 2011

Additional files

Additional file 1:

Figure S1. Activation of signaling pathways in HeLa cells after EGF stimulation. Serum-starved HeLa cells were stimulated with EGF at the indicated times in the presence or absence of kinase inhibitors. Total cell extracts were prepared as indicated in Materials and Methods and samples were subjected to SDS-PAGE and immunoblotting using the indicated antibodies (A, C, D). (B) Total RNA was prepared as indicated in Material and Methods and samples were subjected to reverse transcription and RT-qPCR using specific primers for the indicated genes. Experiments were carried out in triplicate and in all cases deviation was lower than 10%. (D) Immunoblots showing ERK and p90rsk phosphorylation on the three sets used for this study. Total ERK was used as a loading control.

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Additional file 2:

Table S1. Gene lists of SAM test overlap by Venn Diagram of 3 microarray platforms and DGE (provided as word file).

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Additional file 3:

Table S2. Table of cross platform GSEA enrichment scores and significance values (provided as word file).

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Additional file 4:

Table S3. Table of 20192 genes analyzed by RankProd analysis of microarray data (provided as excel file).

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Additional file 5:

Table S4. Table of reads generated by the DGE pipeline for each of the runs. Summary table of read mapping statistics generated by the DGE pipeline for each of the runs.

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Additional file 6:

Table S5. Table of 20322 RefSeq genes analyzed by RankProd analysis of microarrays and DGE (provided as excel file).

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Additional file 7:

Table S6. Table of 1164 genes found significant by RankProd analysis of microarrays and tag ultrasequencing (provided as excel file).

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Additional file 8:

Figure S2. Time course RT-qPCR analysis of potential EGF-regulated mRNAs. Total RNA samples from serum-starved HeLa cells stimulated with EGF at the indicated times (15 min to 24 h) were subjected to quantitative real-time PCR (see Methods for details). Data represent mean fold induction of at least two independent experiments. SFA3 was used as the reference. (A) The upper panel shows the graphical representation. (B) RT-qPCR Fold Changes and corresponding Fold Changes derived from the three microarray platforms and by ultrasequencing.

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Additional file 9:

Figure S3. Correlation plot between DGE and microarray log2ratio values. Comparison of estimated log2ratios from DGE (Y-axis) and the average of all three microarray platforms (X-axis). We consider only genes that were interrogated using all platforms and genes with a mean number of counts across lanes greater than 0. Genes with counts greater than 32 reads in all samples (colored red or green) or less than 32 reads (black) in at least one sample are shown. (Red dots) Genes called differentially expressed based on DGE data at a 10% FDR by RankProd. (Green dots) Genes not called differentially expressed but above 32 counts. (Inset box) Correlation between technologies is higher when considering only genes above the 32 count detection level than when all genes are included.

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Additional file 10:

Figure S4. Heat maps of genes found regulated at 6 h after EGF treatment of HeLa cells in our study and known to be related to EGF signaling. Some genes detected in a subset of all platforms are also included for the sake of completion. (A) Modulators of EGF signaling; (B) non-EGF agonists of EGFR and cytokines linked to the EGF family locus on chromosome 4q13.3; (C) EGF-interacting and related proteins; (D)genes described as early and delayed early response to EGF including DNA and RNA binding proteins; and (E) components of the ERBB receptor endocytosis and intracellular trafficking complexes.

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Additional file 11:

Figure S5. Metallothionein gene expression after EGF treatment. Log2ratio of EGF-treated versus untreated heat maps of metallothionein gene expression after EGF treatment in (A) HeLa cells at 6 h as determined in this study using Agilent, Operon, and Illumina microarrays, and DGE sequencing; (B) RT-qPCR for 6 metallothionein family members, (C) metallothioneins in HeLa cells in the time course study by Amit et al using the Affymetrix platform, without replication (relative log2ratios obtained by log2intensity subtraction of the 0 time point value from each time point).

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Additional file 12:

Figure S6. Pathway analysis based on the Ingenuity Pathway Knowledge base. The three best ranked networks derived from EGF-regulated genes as determined by the RankProd test were (A) Cell Death, Embryonic Development, Renal and Urological Disease (B) Amino Acid Metabolism, Post-Translational Modification, Small Molecule Biochemistry and (C) Cell Cycle, Cancer, Cardiovascular System Development and Function. Upregulated genes are indicated by red symbols and down-regulated genes by green symbols. The shape of the node denotes the main function of the protein encoded by the gene. Smooth lines indicate interaction between the products of the genes; dashed lines indicate an indirect interaction and lines with an arrow indicate an "acts on" relationship. Regulated genes are shown as grey boxes; non-regulated genes associated with the regulation of some of these genes are shown as white.

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Additional file 13:

Table S7. Significantly regulated genes associated to regulated KEGG cellular functions as determined by GlobalAncova (supplied as word).

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Additional file 14:

Table S8. List of primers used in this study.

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