SplicerEX: a tool for the automated detection and classification of mRNA changes from conventional and splice-sensitive microarray expression data.


The key postulate that one gene encodes one protein has been overhauled with the discovery that one gene can generate multiple RNA transcripts through alternative mRNA processing. In this study, we describe SplicerEX, a novel and uniquely motivated algorithm designed for experimental biologists that (1) detects widespread changes in mRNA isoforms from both conventional and splice sensitive microarray data, (2) automatically categorizes mechanistic changes in mRNA processing, and (3) mitigates known technological artifacts of exon array-based detection of alternative splicing resulting from 5' and 3' signal attenuation, background detection limits, and saturation of probe set signal intensity. In this study, we used SplicerEX to compare conventional and exon-based Affymetrix microarray data in a model of EBV transformation of primary human B cells. We demonstrated superior detection of 3'-located changes in mRNA processing by the Affymetrix U133 GeneChip relative to the Human Exon Array. SplicerEX-identified exon-level changes in the EBV infection model were confirmed by RT-PCR and revealed a novel set of EBV-regulated mRNA isoform changes in caspases 6, 7, and 8. Finally, SplicerEX as compared with MiDAS analysis of publicly available microarray data provided more efficiently categorized mRNA isoform changes with a significantly higher proportion of hits supported by previously annotated alternative processing events. Therefore, SplicerEX provides an important tool for the biologist interested in studying changes in mRNA isoform usage from conventional or splice-sensitive microarray platforms, especially considering the expansive amount of archival microarray data generated over the past decade. SplicerEX is freely available upon request.





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Publication Info

Robinson, Timothy J, Eleonora Forte, Raul E Salinas, Shaan Puri, Matthew Marengo, Mariano A Garcia-Blanco and Micah A Luftig (2012). SplicerEX: a tool for the automated detection and classification of mRNA changes from conventional and splice-sensitive microarray expression data. RNA (New York, N.Y.), 18(8). pp. 1435–1445. 10.1261/rna.033621.112 Retrieved from https://hdl.handle.net/10161/24737.

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Raul Salinas

Research Associate, Senior

Micah Alan Luftig

Professor of Molecular Genetics and Microbiology

The Luftig laboratory studies viruses that cause cancer with an overarching goal of defining the basic molecular mechanisms underlying pathogenesis and leveraging these findings for diagnostic value and therapeutic intervention. Our work primarily focuses on the common herpesvirus, Epstein-Barr virus (EBV). This virus latently infects virtually all adults worldwide being acquired early in life. In the immune suppressed, EBV promotes lymphomas in the B cells that it naturally infects. However, EBV can also infect epithelial cells and other lymphocytes contributing to human cancers as wide-ranging as nasopharyngeal and gastric carcinoma to aggressive NK/T-cell, Burkitt, and Hodgkin lymphomas. Overall, EBV contributes to approximately 2% of all human cancers worldwide leading to nearly 200,000 deaths annually.

We use cutting-edge, cross-disciplinary and highly collaborative approaches to characterize the temporal dynamics and single cell heterogeneity of EBV infection. With these strategies, we aim to discover fundamental molecular circuits underlying transcriptional control, viral manipulation of host signaling pathways, and metabolic regulation that collectively influence infected cell fate decisions. By understanding the nature of viral control of infected host cells, we are also well positioned to discover vulnerabilities in EBV-associated diseases and characterize new therapeutic interventions in cell-based and pre-clinical animal models.

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