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

Abstract

High-throughput sequencing of full-length transcripts using long reads has paved the way for the discovery of thousands of novel transcripts, even in well-annotated mammalian species. The advances in sequencing technology have created a need for studies and tools that can characterize these novel variants. Here, we present SQANTI, an automated pipeline for the classification of long-read transcripts that can assess the quality of data and the preprocessing pipeline using 47 unique descriptors. We apply SQANTI to a neuronal mouse transcriptome using Pacific Biosciences (PacBio) long reads and illustrate how the tool is effective in characterizing and describing the composition of 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, resulting 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. 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.

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• Single-cell isoform analysis in human immune cells · 2022
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• Reference genome assemblies reveal the origin and evolution of allohexaploid oat · 2022
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• Error correction enables use of Oxford Nanopore technology for reference-free transcriptome analysis · 2021
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• Detection of aberrant splicing events in RNA-seq data using FRASER · 2021
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• isoCirc catalogs full-length circular RNA isoforms in human transcriptomes · 2021
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• Comprehensive characterization of single-cell full-length isoforms in human and mouse with long-read sequencing · 2021
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• Single-cell RNA-seq analysis of mouse preimplantation embryos by third-generation sequencing. · 2020
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• Comprehensive identification of mRNA isoforms reveals the diversity of neural cell-surface molecules with roles in retinal development and disease · 2020
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• Opportunities and challenges in long-read sequencing data analysis · 2020
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• High throughput error corrected Nanopore single cell transcriptome sequencing · 2020
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• Getting the Entire Message: Progress in Isoform Sequencing · 2019
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• Realizing the potential of full-length transcriptome sequencing · 2019
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• Transcriptome assembly from long-read RNA-seq alignments with StringTie2 · 2019
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• A comprehensive examination of Nanopore native RNA sequencing for characterization of complex transcriptomes · 2019
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• The PRIDE database and related tools and resources in 2019: improving support for quantification data · 2018
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• Single-cell RNAseq for the study of isoforms—how is that possible? · 2018
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