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Large-scale analysis by SAGE reveals new mechanisms of v-erbA oncogene action.

ABSTRACT: BACKGROUND: The v-erbA oncogene, carried by the Avian Erythroblastosis Virus, derives from the c-erbAalpha proto-oncogene that encodes the nuclear receptor for triiodothyronine (T3R). v-ErbA transforms erythroid progenitors in vitro by blocking their differentiation, supposedly by interference with T3R and RAR (Retinoic Acid Receptor). However, v-ErbA target genes involved in its transforming activity still remain to be identified. RESULTS: By using Serial Analysis of Gene Expression (SAGE), we identified 110 genes deregulated by v-ErbA and potentially implicated in the transformation process. Bioinformatic analysis of promoter sequence and transcriptional assays point out a potential role of c-Myb in the v-ErbA effect. Furthermore, grouping of newly identified target genes by function revealed both expected (chromatin/transcription) and unexpected (protein metabolism) functions potentially deregulated by v-ErbA. We then focused our study on 15 of the new v-ErbA target genes and demonstrated by real time PCR that in majority their expression was activated neither by T3, nor RA, nor during differentiation. This was unexpected based upon the previously known role of v-ErbA. CONCLUSION: This paper suggests the involvement of a wealth of new unanticipated mechanisms of v-ErbA action.

SUBMITTER: Bresson C

PROVIDER: S-EPMC2194726 | biostudies-literature | 2007

REPOSITORIES: biostudies-literature

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Large-scale analysis by SAGE reveals new mechanisms of v-erbA oncogene action.

Bresson Corinne C Keime Celine C Faure Claudine C Letrillard Yann Y Barbado Maud M Sanfilippo Sandra S Benhra Najate N Gandrillon Olivier O Gonin-Giraud Sandrine S

BMC genomics 20071026

<h4>Background</h4>The v-erbA oncogene, carried by the Avian Erythroblastosis Virus, derives from the c-erbAalpha proto-oncogene that encodes the nuclear receptor for triiodothyronine (T3R). v-ErbA transforms erythroid progenitors in vitro by blocking their differentiation, supposedly by interference with T3R and RAR (Retinoic Acid Receptor). However, v-ErbA target genes involved in its transforming activity still remain to be identified.<h4>Results</h4>By using Serial Analysis of Gene Expressio ...[more]

PMID: 17961265

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Project description:MotivationWith the advancement of high-throughput techniques, large-scale profiling of biological systems with multiple experimental perturbations is becoming more prevalent. Pathway analysis incorporates prior biological knowledge to analyze genes/proteins in groups in a biological context. However, the hypotheses under investigation are often confined to a 1D space (i.e. up, down, either or mixed regulation). Here, we develop direction pathway analysis (DPA), which can be applied to test hypothesis in a high-dimensional space for identifying pathways that display distinct responses across multiple perturbations.ResultsOur DPA approach allows for the identification of pathways that display distinct responses across multiple perturbations. To demonstrate the utility and effectiveness, we evaluated DPA under various simulated scenarios and applied it to study insulin action in adipocytes. A major action of insulin in adipocytes is to regulate the movement of proteins from the interior to the cell surface membrane. Quantitative mass spectrometry-based proteomics was used to study this process on a large-scale. The combined dataset comprises four separate treatments. By applying DPA, we identified that several insulin responsive pathways in the plasma membrane trafficking are only partially dependent on the insulin-regulated kinase Akt. We subsequently validated our findings through targeted analysis of key proteins from these pathways using immunoblotting and live cell microscopy. Our results demonstrate that DPA can be applied to dissect pathway networks testing diverse hypotheses and integrating multiple experimental perturbations.Availability and implementationThe R package 'directPA' is distributed from CRAN under GNU General Public License (GPL)-3 and can be downloaded from: http://cran.r-project.org/web/packages/directPA/index.htmlContactjean.yang@sydney.edu.auSupplementary informationSupplementary data are available at Bioinformatics online.

Project description:As a growing number of complementary transcripts, susceptible to exert various regulatory functions, are being found in eukaryotes, high throughput analytical methods are needed to investigate their expression in multiple biological samples. Serial Analysis of Gene Expression (SAGE), based on the enumeration of directionally reliable short cDNA sequences (tags), is capable of revealing antisense transcripts. We initially detected them by observing tags that mapped on to the reverse complement of known mRNAs. The presence of such tags in individual SAGE libraries suggested that SAGE datasets contain latent information on antisense transcripts. We raised a collection of virtual tags for mining these data. Tag pairs were assembled by searching for complementarities between 24-nt long sequences centered on the potential SAGE-anchoring sites of well-annotated human expressed sequences. An analysis of their presence in a large collection of published SAGE libraries revealed transcripts expressed at high levels from both strands of two adjacent, oppositely oriented, transcription units. In other cases, the respective transcripts of such cis-oriented genes displayed a mutually exclusive expression pattern or were co-expressed in a small number of libraries. Other tag pairs revealed overlapping transcripts of trans-encoded unique genes. Finally, we isolated a group of tags shared by multiple transcripts. Most of them mapped on to retroelements, essentially represented in humans by Alu sequences inserted in opposite orientations in the 3'UTR of otherwise different mRNAs. Registering these tags in separate files makes possible computational searches focused on unique sense-antisense pairs. The method developed in the present work shows that SAGE datasets constitute a major resource of rapidly investigating with high sensitivity the expression of antisense transcripts, so that a single tag may be detected in one library when screening a large number of biological samples.

Dataset Information

Large-scale analysis by SAGE reveals new mechanisms of v-erbA oncogene action.

Publications

Large-scale analysis by SAGE reveals new mechanisms of v-erbA oncogene action.

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