2026-06-14T03:32:30Zhttps://repisalud.isciii.es/rest/oai/request
oai:repisalud.isciii.es:20.500.12105/66862024-10-31T11:45:43Zcom_20.500.12105_19604com_20.500.12105_2051col_20.500.12105_19605col_20.500.12105_19607
Repisalud author Tardaguila, Manuel author de la Fuente, Lorena author Marti, Cristina author Pereira, Cecile author Pardo-Palacios, Francisco Jose author del Risco, Hector author Ferrell, Marc author Mellado, Maravillas author Macchietto, Marissa author Verheggen, Kenneth author Edelmann, Mariola author Ezkurdia, Iakes author Vazquez, Jesus author Tress, Michael author Mortazavi, Ali author Martens, Lennart author Rodriguez-Navarro, Susana author Moreno-Manzano, Victoria author Conesa, Ana funder National Institutes of Health (Estados Unidos) funder University of Florida (Estados Unidos) funder Ministerio de Economía y Competitividad (España) funder Ministerio de Educación (España) 2018-11-22T08:10:53Z 2018-11-22T08:10:53Z 2018 Genome Res. 2018; 28(3):396-441 10.1101/gr.222976.117 1549-5469 1088-9051 Genome Research 29440222 http://hdl.handle.net/20.500.12105/6686 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. eng SQANTI: extensive characterization of long-read transcript sequences for quality control in full-length transcriptome identification and quantification journal article URL https://repisalud.isciii.es/bitstreams/ab1724db-8b93-409a-b0c5-50a668a87ce1/download File MD5 27bdbdeeee0048781f02d2e7eec06ebe 4032089 application/pdf SQANTExtensiveCharacterization_2018.pdf URL https://repisalud.isciii.es/bitstreams/7fac1098-5746-489a-b49a-27c7fe361c89/download File MD5 7d3413a3c09ce7aceccb36c749b02a93 902483 application/vnd.openxmlformats-officedocument.wordprocessingml.document SQANTExtensiveCharacterization_2018_Supplemental_Figures.docx URL https://repisalud.isciii.es/bitstreams/e9495c87-cca4-45a5-a460-6f93ad635105/download File MD5 56a18a8c84c38f3be283c5995554ee3a 27098 application/vnd.openxmlformats-officedocument.wordprocessingml.document SQANTExtensiveCharacterization_2018_Supplemental_Methods.docx URL https://repisalud.isciii.es/bitstreams/04a41ffb-bd6a-4709-bd68-17c7d87db63f/download File MD5 6b01966d22578e0dcb60f8893b65d42d 158311 application/vnd.openxmlformats-officedocument.spreadsheetml.sheet SQANTExtensiveCharacterization_2018_Supplemental_Tables.xlsx URL https://repisalud.isciii.es/bitstreams/c22c8eeb-7693-4dd4-a1fe-2756eb48fcd7/download File MD5 d01481acc39da9ee3c4eee9feeaf1be2 104314 text/plain SQANTExtensiveCharacterization_2018.pdf.txt URL https://repisalud.isciii.es/bitstreams/54144691-dbcb-4d93-ab06-5598d4ceca8c/download File MD5 30d457b68278c8ad447cdb77cdfb3f3f 33224 text/plain SQANTExtensiveCharacterization_2018_Supplemental_Figures.docx.txt URL https://repisalud.isciii.es/bitstreams/ef63fb3e-4b3d-4ffa-a257-a0de3a28b7d8/download File MD5 3853004797bbdbd5ae31cc0f84c1de8d 14294 text/plain SQANTExtensiveCharacterization_2018_Supplemental_Methods.docx.txt URL https://repisalud.isciii.es/bitstreams/88eb710c-6854-42db-af3a-08cc7a4fbd35/download File MD5 72f7baa08a8524625df3a995e77a29ca 18882 text/plain SQANTExtensiveCharacterization_2018_Supplemental_Tables.xlsx.txt