SQANTI: extensive characterization of long-read transcript sequences for quality control in full-length transcriptome identification and quantification

By M. Tardaguila, Lorena de la Fuente, C. Martí, Cecile Pereira, Francisco J. Pardo-Palacios, Héctor del Risco, Marc Ferrell, Maravillas Mellado, Marissa G. Macchietto, K. Verheggen and 9 more. bioRxiv, 2017

376 citations recorded by the source corpus.

High-throughput sequencing of full-length transcripts using long reads has paved the way for the discovery of thousands of novel transcripts, even in very well annotated organisms as mice and humans. Nonetheless, there is a need for studies and tools that characterize these novel isoforms. Here we present SQANTI, an automated pipeline for the classification of long-read transcripts that computes 47 descriptors that can be used to assess the quality of the data and of the preprocessing pipelines. We applied SQANTI to a neuronal mouse transcriptome using PacBio long reads and illustrate how the tool is effective in readily describing the composition of and characterizing the full-length transcriptome. We perform extensive evaluation of ToFU PacBio transcripts by PCR to reveal that an important number of the novel transcripts are technical artifacts of the sequencing approach, and that SQANTI quality descriptors can be used to engineer a filtering strategy to remove them. Most novel transcripts in this curated transcriptome are novel combinations of existing splice sites, result more frequently in novel ORFs than novel UTRs and are enriched in both general metabolic and neural specific functions. We show that these new transcripts have a major impact in the correct quantification of transcript levels by state-of-the-art short-read based quantification algorithms. By comparing our iso-transcriptome with public proteomics databases we find that alternative isoforms are elusive to proteogenomics detection and are variable in protein changes with respect to the principal isoform of their genes. SQANTI allows the user to maximize the analytical outcome of long read technologies by providing the tools to deliver quality-evaluated and curated full-length transcriptomes. SQANTI is available at https://bitbucket.org/ConesaLab/sqanti.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/6a9163ab09a4f2c20cffad5bc8870dc4bf2ac191

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In Molecular Biology

Citations in the corpus

Piercing the dark matter: bioinformatics of long-range sequencing and mapping (2018, background): “Nevertheless, there have been large discrepancies observed in the number of potential isoforms between different pipelines 106 .”
The PRIDE database and related tools and resources in 2019: improving support for quantification data (2018, background): “Two popular applications are proteogenomics approaches (for human and the main model organisms, e.g. (33,34)), and the discov-Nucleic ery of novel PTMs (Post-Translational Modifications).”