Fine mapping of RNA isoform diversity using an innovative targeted long-read RNA sequencing protocol with novel dedicated bioinformatics pipeline.


Journal

BMC genomics
ISSN: 1471-2164
Titre abrégé: BMC Genomics
Pays: England
ID NLM: 100965258

Informations de publication

Date de publication:
30 Sep 2024
Historique:
received: 30 04 2024
accepted: 28 08 2024
medline: 1 10 2024
pubmed: 1 10 2024
entrez: 30 9 2024
Statut: epublish

Résumé

Solving the structure of mRNA transcripts is a major challenge for both research and molecular diagnostic purposes. Current approaches based on short-read RNA sequencing and RT-PCR techniques cannot fully explore the complexity of transcript structure. The emergence of third-generation long-read sequencing addresses this problem by solving this sequence directly. However, genes with low expression levels are difficult to study with the whole transcriptome sequencing approach. To fix this technical limitation, we propose a novel method to capture transcripts of a gene panel using a targeted enrichment approach suitable for Pacific Biosciences and Oxford Nanopore Technologies platforms. We designed a set of probes to capture transcripts of a panel of genes involved in hereditary breast and ovarian cancer syndrome. We present SOSTAR (iSofOrmS annoTAtoR), a versatile pipeline to assemble, quantify and annotate isoforms from long read sequencing using a new tool specially designed for this application. The significant enrichment of transcripts by our capture protocol, together with the SOSTAR annotation, allowed the identification of 1,231 unique transcripts within the gene panel from the eight patients sequenced. The structure of these transcripts was annotated with a resolution of one base relative to a reference transcript. All major alternative splicing events of the BRCA1 and BRCA2 genes described in the literature were found. Complex splicing events such as pseudoexons were correctly annotated. SOSTAR enabled the identification of abnormal transcripts in the positive controls. In addition, a case of unexplained inheritance in a family with a history of breast and ovarian cancer was solved by identifying an SVA retrotransposon in intron 13 of the BRCA1 gene. We have validated a new protocol for the enrichment of transcripts of interest using probes adapted to the ONT and PacBio platforms. This protocol allows a complete description of the alternative structures of transcripts, the estimation of their expression and the identification of aberrant transcripts in a single experiment. This proof-of-concept opens new possibilities for RNA structure exploration in both research and molecular diagnostics.

Sections du résumé

BACKGROUND BACKGROUND
Solving the structure of mRNA transcripts is a major challenge for both research and molecular diagnostic purposes. Current approaches based on short-read RNA sequencing and RT-PCR techniques cannot fully explore the complexity of transcript structure. The emergence of third-generation long-read sequencing addresses this problem by solving this sequence directly. However, genes with low expression levels are difficult to study with the whole transcriptome sequencing approach. To fix this technical limitation, we propose a novel method to capture transcripts of a gene panel using a targeted enrichment approach suitable for Pacific Biosciences and Oxford Nanopore Technologies platforms.
RESULTS RESULTS
We designed a set of probes to capture transcripts of a panel of genes involved in hereditary breast and ovarian cancer syndrome. We present SOSTAR (iSofOrmS annoTAtoR), a versatile pipeline to assemble, quantify and annotate isoforms from long read sequencing using a new tool specially designed for this application. The significant enrichment of transcripts by our capture protocol, together with the SOSTAR annotation, allowed the identification of 1,231 unique transcripts within the gene panel from the eight patients sequenced. The structure of these transcripts was annotated with a resolution of one base relative to a reference transcript. All major alternative splicing events of the BRCA1 and BRCA2 genes described in the literature were found. Complex splicing events such as pseudoexons were correctly annotated. SOSTAR enabled the identification of abnormal transcripts in the positive controls. In addition, a case of unexplained inheritance in a family with a history of breast and ovarian cancer was solved by identifying an SVA retrotransposon in intron 13 of the BRCA1 gene.
CONCLUSIONS CONCLUSIONS
We have validated a new protocol for the enrichment of transcripts of interest using probes adapted to the ONT and PacBio platforms. This protocol allows a complete description of the alternative structures of transcripts, the estimation of their expression and the identification of aberrant transcripts in a single experiment. This proof-of-concept opens new possibilities for RNA structure exploration in both research and molecular diagnostics.

Identifiants

pubmed: 39350015
doi: 10.1186/s12864-024-10741-0
pii: 10.1186/s12864-024-10741-0
doi:

Substances chimiques

RNA Isoforms 0
BRCA2 Protein 0
BRCA1 Protein 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

909

Subventions

Organisme : French Cancéropôle Nord-Ouest (CNO)
ID : 2018/06

Informations de copyright

© 2024. The Author(s).

Références

Pan Q, Shai O, Lee LJ, Frey BJ, Blencowe BJ. ‘Deep surveying of alternative splicing complexity in the human transcriptome by high-throughput sequencing’, Nat. Genet., vol. 40, no. 12, pp. 1413–1415, Dec. 2008, https://doi.org/10.1038/ng.259
Navaratnam DS, Bell TJ, Tu TD, Cohen EL, Oberholtzer JC. ‘Differential Distribution of Ca2+-Activated K + Channel Splice Variants among Hair Cells along the Tonotopic Axis of the Chick Cochlea’, Neuron, vol. 19, no. 5, pp. 1077–1085, Nov. 1997, https://doi.org/10.1016/S0896-6273(00)80398-0
Rosenblatt KP, Sun Z-P, Heller S, Hudspeth AJ. ‘Distribution of Ca2+-Activated K + Channel Isoforms along the Tonotopic Gradient of the Chicken’s Cochlea’, Neuron, vol. 19, no. 5, pp. 1061–1075, Nov. 1997, https://doi.org/10.1016/S0896-6273(00)80397-9
Bonnal SC, López-Oreja I, Valcárcel J. Roles and mechanisms of alternative splicing in cancer — implications for care. Nat Rev Clin Oncol. 2020;17. https://doi.org/10.1038/s41571-020-0350-x . 8, Art. 8, Aug.
Park E, Pan Z, Zhang Z, Lin L, Xing Y. The Expanding Landscape of Alternative Splicing Variation in Human populations. Am J Hum Genet. Jan. 2018;102(1):11–26. https://doi.org/10.1016/j.ajhg.2017.11.002 .
Rogalska ME, Vivori C, Valcárcel J. Regulation of pre-mRNA splicing: roles in physiology and disease, and therapeutic prospects. Nat Rev Genet. Dec. 2022;1–19. https://doi.org/10.1038/s41576-022-00556-8 .
Cheung R, et al. A multiplexed assay for exon Recognition reveals that an unappreciated fraction of Rare genetic variants cause large-effect splicing disruptions. Mol Cell. Jan. 2019;73(1):183–94. https://doi.org/10.1016/j.molcel.2018.10.037.e8 .
Wai HA et al. Jun., ‘Blood RNA analysis can increase clinical diagnostic rate and resolve variants of uncertain significance’, Genet. Med., vol. 22, no. 6, Art. no. 6, 2020, https://doi.org/10.1038/s41436-020-0766-9
Truty R, et al. Spectrum of splicing variants in disease genes and the ability of RNA analysis to reduce uncertainty in clinical interpretation. Am J Hum Genet. Apr. 2021;108(4):696–708. https://doi.org/10.1016/j.ajhg.2021.03.006 .
Bournazos AM, et al. Standardized practices for RNA diagnostics using clinically accessible specimens reclassifies 75% of putative splicing variants. Genet Med. Jan. 2022;24(1):130–45. https://doi.org/10.1016/j.gim.2021.09.001 .
Goyenvalle A et al. Dec., ‘Rescue of Dystrophic Muscle Through U7 snRNA-Mediated Exon Skipping’, Science, vol. 306, no. 5702, pp. 1796–1799, 2004, https://doi.org/10.1126/science.1104297
Meulemans L, et al. Skipping nonsense to maintain function: the paradigm of BRCA2 exon 12. Cancer Res. Jan. 2020. https://doi.org/10.1158/0008-5472.CAN-19-2491 .
Lopez-Perolio I et al. Mar., ‘Alternative splicing and ACMG-AMP-2015-based classification of PALB2 genetic variants: an ENIGMA report’, J. Med. Genet., p. jmedgenet-2018-105834, 2019, https://doi.org/10.1136/jmedgenet-2018-105834
Gonorazky HD, et al. Expanding the boundaries of RNA sequencing as a Diagnostic Tool for Rare mendelian disease. Am J Hum Genet. Mar. 2019;104(3):466–83. https://doi.org/10.1016/j.ajhg.2019.01.012 .
Mercer TR et al. Nov., ‘Targeted RNA sequencing reveals the deep complexity of the human transcriptome’, Nat. Biotechnol., vol. 30, no. 1, pp. 99–104, 2011, https://doi.org/10.1038/nbt.2024
Davy G et al. Oct., ‘Detecting splicing patterns in genes involved in hereditary breast and ovarian cancer’, Eur. J. Hum. Genet. EJHG, vol. 25, no. 10, pp. 1147–1154, 2017, https://doi.org/10.1038/ejhg.2017.116
Adamson SI, Zhan L, Graveley BR. Vex-seq: high-throughput identification of the impact of genetic variation on pre-mRNA splicing efficiency. Genome Biol. Jun. 2018;19(1):71. https://doi.org/10.1186/s13059-018-1437-x .
Steijger T et al. Dec., ‘Assessment of transcript reconstruction methods for RNA-seq’, Nat. Methods, vol. 10, no. 12, Art. no. 12, 2013, https://doi.org/10.1038/nmeth.2714
Workman RE et al. Dec., ‘Nanopore native RNA sequencing of a human poly(A) transcriptome’, Nat. Methods, vol. 16, no. 12, Art. no. 12, 2019, https://doi.org/10.1038/s41592-019-0617-2
Glinos DA et al. Aug., ‘Transcriptome variation in human tissues revealed by long-read sequencing’, Nature, vol. 608, no. 7922, Art. no. 7922, 2022, https://doi.org/10.1038/s41586-022-05035-y
Treutlein B, Gokce O, Quake SR, Südhof TC. ‘Cartography of neurexin alternative splicing mapped by single-molecule long-read mRNA sequencing’, Proc. Natl. Acad. Sci. U. S. A., vol. 111, no. 13, pp. E1291-1299, Apr. 2014, https://doi.org/10.1073/pnas.1403244111
de Jong LC, et al. Nanopore sequencing of full-length BRCA1 mRNA transcripts reveals co-occurrence of known exon skipping events. Breast Cancer Res. Nov. 2017;19(1):127. https://doi.org/10.1186/s13058-017-0919-1 .
Deveson IW, et al. Universal Alternative Splicing of Noncoding Exons. Cell Syst. Feb. 2018;6(2):245–55. https://doi.org/10.1016/j.cels.2017.12.005 . .e5.
Hardwick SA et al. ‘Targeted, High-Resolution RNA Sequencing of Non-coding Genomic Regions Associated With Neuropsychiatric Functions’, Front. Genet., vol. 10, 2019, Accessed: Jun. 28, 2023. [Online]. Available: https://www.frontiersin.org/articles/ https://doi.org/10.3389/fgene.2019.00309
Lagarde J et al. Dec., ‘High-throughput annotation of full-length long noncoding RNAs with capture long-read sequencing’, Nat. Genet., vol. 49, no. 12, Art. no. 12, 2017, https://doi.org/10.1038/ng.3988
Singh M, et al. High-throughput targeted long-read single cell sequencing reveals the clonal and transcriptional landscape of lymphocytes. Nat Commun. Jul. 2019;10(1):3120. https://doi.org/10.1038/s41467-019-11049-4 .
Hardwick SA, et al. Single-nuclei isoform RNA sequencing unlocks barcoded exon connectivity in frozen brain tissue. Nat Biotechnol. Jul. 2022;40(7):1082–92. https://doi.org/10.1038/s41587-022-01231-3 .
O’Leary NA, et al. Reference sequence (RefSeq) database at NCBI: current status, taxonomic expansion, and functional annotation. Nucleic Acids Res. Jan. 2016;44:D733–45. https://doi.org/10.1093/nar/gkv1189 . no. D1.
Leman R et al. Mar., ‘SpliceLauncher: a tool for detection, annotation and relative quantification of alternative junctions from RNAseq data’, Bioinformatics, vol. 36, no. 5, pp. 1634–1636, 2020, https://doi.org/10.1093/bioinformatics/btz784
Love MI, Huber W, Anders S. Moderated estimation of Fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15(12):550. https://doi.org/10.1186/s13059-014-0550-8 .
doi: 10.1186/s13059-014-0550-8 pubmed: 25516281 pmcid: 4302049
Dong X et al. Nov., ‘Benchmarking long-read RNA-sequencing analysis tools using in silico mixtures’, Nat. Methods, vol. 20, no. 11, pp. 1810–1821, 2023, https://doi.org/10.1038/s41592-023-02026-3
Li H. Minimap2: pairwise alignment for nucleotide sequences. Bioinforma Oxf Engl. Sep. 2018;34(18):3094–100. https://doi.org/10.1093/bioinformatics/bty191 .
Kovaka S, Zimin AV, Pertea GM, Razaghi R, Salzberg SL, Pertea M. Transcriptome assembly from long-read RNA-seq alignments with StringTie2. Genome Biol. Dec. 2019;20(1):278. https://doi.org/10.1186/s13059-019-1910-1 .
Quinlan AR, Hall IM. ‘BEDTools: a flexible suite of utilities for comparing genomic features’, Bioinforma. Oxf. Engl., vol. 26, no. 6, pp. 841–842, Mar. 2010, https://doi.org/10.1093/bioinformatics/btq033
Robinson JT et al. Jan., ‘Integrative genomics viewer’, Nat. Biotechnol., vol. 29, no. 1, Art. no. 1, 2011, https://doi.org/10.1038/nbt.1754
Colombo M et al. Jul., ‘Comprehensive annotation of splice junctions supports pervasive alternative splicing at the BRCA1 locus: a report from the ENIGMA consortium’, Hum. Mol. Genet., vol. 23, no. 14, pp. 3666–3680, 2014, https://doi.org/10.1093/hmg/ddu075
Fackenthal JD et al. Aug., ‘Naturally occurring BRCA2 alternative mRNA splicing events in clinically relevant samples’, J. Med. Genet., vol. 53, no. 8, pp. 548–558, 2016, https://doi.org/10.1136/jmedgenet-2015-103570
Leman R et al. Dec., ‘SPiP: Splicing Prediction Pipeline, a machine learning tool for massive detection of exonic and intronic variant effects on mRNA splicing’, Hum. Mutat., vol. 43, no. 12, pp. 2308–2323, 2022, https://doi.org/10.1002/humu.24491
Castéra L et al. Nov., ‘Next-generation sequencing for the diagnosis of hereditary breast and ovarian cancer using genomic capture targeting multiple candidate genes’, Eur. J. Hum. Genet. EJHG, vol. 22, no. 11, pp. 1305–1313, 2014, https://doi.org/10.1038/ejhg.2014.16
Leman R, et al. 2022-RA-935-ESGO Development of an academic genomic instability score for ovarian cancers. Int J Gynecol Cancer. Oct. 2022;32. https://doi.org/10.1136/ijgc-2022-ESGO.596 . no. Suppl 2.
Richards S, et al. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med off J Am Coll Med Genet. May 2015;17(5):405–24. https://doi.org/10.1038/gim.2015.30 .
Walsh T et al. Dec., ‘CRISPR-Cas9/long-read sequencing approach to identify cryptic mutations in BRCA1 and other tumour suppressor genes’, J. Med. Genet., vol. 58, no. 12, pp. 850–852, 2021, https://doi.org/10.1136/jmedgenet-2020-107320

Auteurs

Camille Aucouturier (C)

Laboratoire de biologie et de génétique du cancer, Département de Biopathologie, Centre François Baclesse, Caen, 14000, France.
Cancer and Brain Genomics, FHU G4 Genomics, Inserm U1245, Normandie University, Rouen, 76183, France.
Normandie Univ, UNICAEN, Caen, 14000, France.

Nicolas Soirat (N)

Laboratoire de biologie et de génétique du cancer, Département de Biopathologie, Centre François Baclesse, Caen, 14000, France.
Cancer and Brain Genomics, FHU G4 Genomics, Inserm U1245, Normandie University, Rouen, 76183, France.
SeqOne Genomics, Montpellier, 34000, France.

Laurent Castéra (L)

Laboratoire de biologie et de génétique du cancer, Département de Biopathologie, Centre François Baclesse, Caen, 14000, France.
Cancer and Brain Genomics, FHU G4 Genomics, Inserm U1245, Normandie University, Rouen, 76183, France.

Denis Bertrand (D)

SeqOne Genomics, Montpellier, 34000, France.

Alexandre Atkinson (A)

Laboratoire de biologie et de génétique du cancer, Département de Biopathologie, Centre François Baclesse, Caen, 14000, France.

Thibaut Lavolé (T)

Laboratoire de biologie et de génétique du cancer, Département de Biopathologie, Centre François Baclesse, Caen, 14000, France.

Nicolas Goardon (N)

Laboratoire de biologie et de génétique du cancer, Département de Biopathologie, Centre François Baclesse, Caen, 14000, France.
Cancer and Brain Genomics, FHU G4 Genomics, Inserm U1245, Normandie University, Rouen, 76183, France.

Céline Quesnelle (C)

Laboratoire de biologie et de génétique du cancer, Département de Biopathologie, Centre François Baclesse, Caen, 14000, France.

Julien Levilly (J)

Laboratoire de biologie et de génétique du cancer, Département de Biopathologie, Centre François Baclesse, Caen, 14000, France.

Sosthène Barbachou (S)

Laboratoire de biologie et de génétique du cancer, Département de Biopathologie, Centre François Baclesse, Caen, 14000, France.

Angelina Legros (A)

Laboratoire de biologie et de génétique du cancer, Département de Biopathologie, Centre François Baclesse, Caen, 14000, France.

Olivier Caron (O)

Département Médecine Oncologique, Institut Gustave Roussy, Villejuif, France.

Louise Crivelli (L)

Service d'Oncogénétique, Centre Eugène Marquis, Rennes, France.

Philippe Denizeau (P)

Service de génétique clinique, Centre Hospitalier Universitaire Rennes, Rennes, France.

Pascaline Berthet (P)

Service d'Oncogénétique, Département de Biopathologie, Centre François Baclesse, Caen, 14000, France.

Agathe Ricou (A)

Laboratoire de biologie et de génétique du cancer, Département de Biopathologie, Centre François Baclesse, Caen, 14000, France.
Cancer and Brain Genomics, FHU G4 Genomics, Inserm U1245, Normandie University, Rouen, 76183, France.

Flavie Boulouard (F)

Laboratoire de biologie et de génétique du cancer, Département de Biopathologie, Centre François Baclesse, Caen, 14000, France.
Cancer and Brain Genomics, FHU G4 Genomics, Inserm U1245, Normandie University, Rouen, 76183, France.

Dominique Vaur (D)

Laboratoire de biologie et de génétique du cancer, Département de Biopathologie, Centre François Baclesse, Caen, 14000, France.
Cancer and Brain Genomics, FHU G4 Genomics, Inserm U1245, Normandie University, Rouen, 76183, France.

Sophie Krieger (S)

Laboratoire de biologie et de génétique du cancer, Département de Biopathologie, Centre François Baclesse, Caen, 14000, France.
Cancer and Brain Genomics, FHU G4 Genomics, Inserm U1245, Normandie University, Rouen, 76183, France.
Normandie Univ, UNICAEN, Caen, 14000, France.

Raphael Leman (R)

Laboratoire de biologie et de génétique du cancer, Département de Biopathologie, Centre François Baclesse, Caen, 14000, France. r.leman@baclesse.unicancer.fr.
Cancer and Brain Genomics, FHU G4 Genomics, Inserm U1245, Normandie University, Rouen, 76183, France. r.leman@baclesse.unicancer.fr.

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