A platform independent RNA-Seq protocol for the detection of transcriptome complexity.

BACKGROUND: Recent studies have demonstrated an unexpected complexity of transcription in eukaryotes. The majority of the genome is transcribed and only a little fraction of these transcripts is annotated as protein coding genes and their splice variants. Indeed, most transcripts are the result of antisense, overlapping and non-coding RNA expression. In this frame, one of the key aims of high throughput transcriptome sequencing is the detection of all RNA species present in the cell and the first crucial step for RNA-seq users is represented by the choice of the strategy for cDNA library construction. The protocols developed so far provide the utilization of the entire library for a single sequencing run with a specific platform. RESULTS: We set up a unique protocol to generate and amplify a strand-specific cDNA library representative of all RNA species that may be implemented with all major platforms currently available on the market (Roche 454, Illumina, ABI/SOLiD). Our method is reproducible, fast, easy-to-perform and even allows to start from low input total RNA. Furthermore, we provide a suitable bioinformatics tool for the analysis of the sequences produced following this protocol. CONCLUSION: We tested the efficiency of our strategy, showing that our method is platform-independent, thus allowing the simultaneous analysis of the same sample with different NGS technologies, and providing an accurate quantitative and qualitative portrait of complex whole transcriptomes.

ASPicDB: a database of annotated transcript and protein variants generated by alternative splicing.

Alternative splicing is emerging as a major mechanism for the expansion of the transcriptome and proteome diversity, particularly in human and other vertebrates. However, the proportion of alternative transcripts and proteins actually endowed with functional activity is currently highly debated. We present here a new release of ASPicDB which now provides a unique annotation resource of human protein variants generated by alternative splicing. A total of 256,939 protein variants from 17,191 multi-exon genes have been extensively annotated through state of the art machine learning tools providing information of the protein type (globular and transmembrane), localization, presence of PFAM domains, signal peptides, GPI-anchor propeptides, transmembrane and coiled-coil segments. Furthermore, full-length variants can be now specifically selected based on the annotation of CAGE-tags and polyA signal and/or polyA sites, marking transcription initiation and termination sites, respectively. The retrieval can be carried out at gene, transcript, exon, protein or splice site level allowing the selection of data sets fulfilling one or more features settled by the user. The retrieval interface also enables the selection of protein variants showing specific differences in the annotated features. ASPicDB is available at http://www.caspur.it/ASPicDB/.

Identification of tumor-associated cassette exons in human cancer through EST-based computational prediction and experimental validation.

BACKGROUND: Many evidences report that alternative splicing, the mechanism which produces mRNAs and proteins with different structures and functions from the same gene, is altered in cancer cells. Thus, the identification and characterization of cancer-specific splice variants may give large impulse to the discovery of novel diagnostic and prognostic tumour biomarkers, as well as of new targets for more selective and effective therapies. RESULTS: We present here a genome-wide analysis of the alternative splicing pattern of human genes through a computational analysis of normal and cancer-specific ESTs from seventeen anatomical groups, using data available in AspicDB, a database resource for the analysis of alternative splicing in human. By using a statistical methodology, normal and cancer-specific genes, splice sites and cassette exons were predicted in silico. The condition association of some of the novel normal/tumoral cassette exons was experimentally verified by RT-qPCR assays in the same anatomical system where they were predicted. Remarkably, the presence in vivo of the predicted alternative transcripts, specific for the nervous system, was confirmed in patients affected by glioblastoma. CONCLUSION: This study presents a novel computational methodology for the identification of tumor-associated transcript variants to be used as cancer molecular biomarkers, provides its experimental validation, and reports specific biomarkers for glioblastoma.

Identification and functional characterization of two new transcriptional variants of the human p63 gene.

p63 belongs to a family of transcription factors, which, while demonstrating striking conservation of functional domains, regulate distinct biological functions. Its principal role is in the regulation of epithelial commitment, differentiation and maintenance programs, during embryogenesis and in adult tissues. The p63 gene has a complex transcriptional pattern, producing two subclasses of N-terminal isoforms (TA and DeltaN) which are alternatively spliced at the C-terminus. Here, we report the identification of two new C-terminus p63 variants, we named p63 delta and epsilon, that increase from 6 to 10 the number of the p63 isoforms. Expression analysis of all p63 variants demonstrates a tissue/cell-type-specific nature of p63 alternative transcript expression, probably related to their different cellular functions. We demonstrate that the new p63 variants as DeltaN isoforms are active as transcription factors as they have nuclear localization and can modulate the expression of p63 target genes. Moreover, we report that, like DeltaNp63alpha, DeltaNp63delta and epsilon sustain cellular proliferation and that their expression decreases during keratinocyte differentiation, suggesting their involvement in this process. Taken together, our results demonstrate the existence of novel p63 proteins whose expression should be considered in future studies on the roles of p63 in the regulation of cellular functions.