Literature DB >> 24308330

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

Claudia Calabrese, Marina Mangiulli, Caterina Manzari, Anna Maria Paluscio, Mariano Francesco Caratozzolo, Flaviana Marzano, Ivana Kurelac, Anna Maria D'Erchia, Domenica D'Elia, Flavio Licciulli, Sabino Liuni, Ernesto Picardi, Marcella Attimonelli, Giuseppe Gasparre, Anna Maria Porcelli, Graziano Pesole, Elisabetta Sbisà, Apollonia Tullo1.   

Abstract

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.

Entities:  

Mesh:

Year:  2013        PMID: 24308330      PMCID: PMC4046740          DOI: 10.1186/1471-2164-14-855

Source DB:  PubMed          Journal:  BMC Genomics        ISSN: 1471-2164            Impact factor:   3.969


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