Assessment of branch point prediction tools to predict physiological branch points and their alteration by variants
Branch points (BPs) map within short motifs upstream of acceptor splice sites (3'ss) and are essential for splicing of pre-mature mRNA. Several BP-dedicated bioinformatics tools, including HSF, SVM-BPfinder, BPP, Branchpointer, LaBranchoR and RNABPS were developed during the last decade. Here,...
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| Veröffentlicht in: | BMC genomics 2020-01, Vol.21 (1), p.86-86, Article 86 |
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| creator | Leman, Raphaël Tubeuf, Hélène Raad, Sabine Tournier, Isabelle Derambure, Céline Lanos, Raphaël Gaildrat, Pascaline Castelain, Gaia Hauchard, Julie Killian, Audrey Baert-Desurmont, Stéphanie Legros, Angelina Goardon, Nicolas Quesnelle, Céline Ricou, Agathe Castera, Laurent Vaur, Dominique Le Gac, Gérald Ka, Chandran Fichou, Yann Bonnet-Dorion, Françoise Sevenet, Nicolas Guillaud-Bataille, Marine Boutry-Kryza, Nadia Schultz, Inès Caux-Moncoutier, Virginie Rossing, Maria Walker, Logan C Spurdle, Amanda B Houdayer, Claude Martins, Alexandra Krieger, Sophie |
| description | Branch points (BPs) map within short motifs upstream of acceptor splice sites (3'ss) and are essential for splicing of pre-mature mRNA. Several BP-dedicated bioinformatics tools, including HSF, SVM-BPfinder, BPP, Branchpointer, LaBranchoR and RNABPS were developed during the last decade. Here, we evaluated their capability to detect the position of BPs, and also to predict the impact on splicing of variants occurring upstream of 3'ss.
We used a large set of constitutive and alternative human 3'ss collected from Ensembl (n = 264,787 3'ss) and from in-house RNAseq experiments (n = 51,986 3'ss). We also gathered an unprecedented collection of functional splicing data for 120 variants (62 unpublished) occurring in BP areas of disease-causing genes. Branchpointer showed the best performance to detect the relevant BPs upstream of constitutive and alternative 3'ss (99.48 and 65.84% accuracies, respectively). For variants occurring in a BP area, BPP emerged as having the best performance to predict effects on mRNA splicing, with an accuracy of 89.17%.
Our investigations revealed that Branchpointer was optimal to detect BPs upstream of 3'ss, and that BPP was most relevant to predict splicing alteration due to variants in the BP area. |
| doi_str_mv | 10.1186/s12864-020-6484-5 |
| format | Article |
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We used a large set of constitutive and alternative human 3'ss collected from Ensembl (n = 264,787 3'ss) and from in-house RNAseq experiments (n = 51,986 3'ss). We also gathered an unprecedented collection of functional splicing data for 120 variants (62 unpublished) occurring in BP areas of disease-causing genes. Branchpointer showed the best performance to detect the relevant BPs upstream of constitutive and alternative 3'ss (99.48 and 65.84% accuracies, respectively). For variants occurring in a BP area, BPP emerged as having the best performance to predict effects on mRNA splicing, with an accuracy of 89.17%.
Our investigations revealed that Branchpointer was optimal to detect BPs upstream of 3'ss, and that BPP was most relevant to predict splicing alteration due to variants in the BP area.</description><identifier>ISSN: 1471-2164</identifier><identifier>EISSN: 1471-2164</identifier><identifier>DOI: 10.1186/s12864-020-6484-5</identifier><identifier>PMID: 31992191</identifier><language>eng</language><publisher>England: BioMed Central Ltd</publisher><subject>Accuracy ; Adenosine ; Algorithms ; Benchmark ; Benchmarking ; Bioinformatics ; Branch point ; Computational biology ; Datasets ; Diseases ; Evaluation ; Genes ; Genomics ; HSF ; Life Sciences ; Messenger RNA ; Methods ; mRNA ; Open source software ; Physiology ; Prediction ; RNA ; RNA sequencing ; RNA splicing ; Scientific software ; Splicing ; SVM-BPfinder</subject><ispartof>BMC genomics, 2020-01, Vol.21 (1), p.86-86, Article 86</ispartof><rights>COPYRIGHT 2020 BioMed Central Ltd.</rights><rights>2020. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><rights>The Author(s). 2020</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c628t-1f2b4360879664e4de6e94c01a0a87fcb8d41815ae28479d2f607085cec87d393</citedby><cites>FETCH-LOGICAL-c628t-1f2b4360879664e4de6e94c01a0a87fcb8d41815ae28479d2f607085cec87d393</cites><orcidid>0000-0003-1978-7133 ; 0000-0002-5104-9125 ; 0000-0001-6671-1567 ; 0000-0001-7610-7355 ; 0000-0003-3236-7280</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6988378/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6988378/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2096,27901,27902,53766,53768</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/31992191$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttps://hal.science/hal-03616666$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Leman, Raphaël</creatorcontrib><creatorcontrib>Tubeuf, Hélène</creatorcontrib><creatorcontrib>Raad, Sabine</creatorcontrib><creatorcontrib>Tournier, Isabelle</creatorcontrib><creatorcontrib>Derambure, Céline</creatorcontrib><creatorcontrib>Lanos, Raphaël</creatorcontrib><creatorcontrib>Gaildrat, Pascaline</creatorcontrib><creatorcontrib>Castelain, Gaia</creatorcontrib><creatorcontrib>Hauchard, Julie</creatorcontrib><creatorcontrib>Killian, Audrey</creatorcontrib><creatorcontrib>Baert-Desurmont, Stéphanie</creatorcontrib><creatorcontrib>Legros, Angelina</creatorcontrib><creatorcontrib>Goardon, Nicolas</creatorcontrib><creatorcontrib>Quesnelle, Céline</creatorcontrib><creatorcontrib>Ricou, Agathe</creatorcontrib><creatorcontrib>Castera, Laurent</creatorcontrib><creatorcontrib>Vaur, Dominique</creatorcontrib><creatorcontrib>Le Gac, Gérald</creatorcontrib><creatorcontrib>Ka, Chandran</creatorcontrib><creatorcontrib>Fichou, Yann</creatorcontrib><creatorcontrib>Bonnet-Dorion, Françoise</creatorcontrib><creatorcontrib>Sevenet, Nicolas</creatorcontrib><creatorcontrib>Guillaud-Bataille, Marine</creatorcontrib><creatorcontrib>Boutry-Kryza, Nadia</creatorcontrib><creatorcontrib>Schultz, Inès</creatorcontrib><creatorcontrib>Caux-Moncoutier, Virginie</creatorcontrib><creatorcontrib>Rossing, Maria</creatorcontrib><creatorcontrib>Walker, Logan C</creatorcontrib><creatorcontrib>Spurdle, Amanda B</creatorcontrib><creatorcontrib>Houdayer, Claude</creatorcontrib><creatorcontrib>Martins, Alexandra</creatorcontrib><creatorcontrib>Krieger, Sophie</creatorcontrib><title>Assessment of branch point prediction tools to predict physiological branch points and their alteration by variants</title><title>BMC genomics</title><addtitle>BMC Genomics</addtitle><description>Branch points (BPs) map within short motifs upstream of acceptor splice sites (3'ss) and are essential for splicing of pre-mature mRNA. Several BP-dedicated bioinformatics tools, including HSF, SVM-BPfinder, BPP, Branchpointer, LaBranchoR and RNABPS were developed during the last decade. Here, we evaluated their capability to detect the position of BPs, and also to predict the impact on splicing of variants occurring upstream of 3'ss.
We used a large set of constitutive and alternative human 3'ss collected from Ensembl (n = 264,787 3'ss) and from in-house RNAseq experiments (n = 51,986 3'ss). We also gathered an unprecedented collection of functional splicing data for 120 variants (62 unpublished) occurring in BP areas of disease-causing genes. Branchpointer showed the best performance to detect the relevant BPs upstream of constitutive and alternative 3'ss (99.48 and 65.84% accuracies, respectively). For variants occurring in a BP area, BPP emerged as having the best performance to predict effects on mRNA splicing, with an accuracy of 89.17%.
Our investigations revealed that Branchpointer was optimal to detect BPs upstream of 3'ss, and that BPP was most relevant to predict splicing alteration due to variants in the BP area.</description><subject>Accuracy</subject><subject>Adenosine</subject><subject>Algorithms</subject><subject>Benchmark</subject><subject>Benchmarking</subject><subject>Bioinformatics</subject><subject>Branch point</subject><subject>Computational biology</subject><subject>Datasets</subject><subject>Diseases</subject><subject>Evaluation</subject><subject>Genes</subject><subject>Genomics</subject><subject>HSF</subject><subject>Life Sciences</subject><subject>Messenger RNA</subject><subject>Methods</subject><subject>mRNA</subject><subject>Open source software</subject><subject>Physiology</subject><subject>Prediction</subject><subject>RNA</subject><subject>RNA sequencing</subject><subject>RNA splicing</subject><subject>Scientific 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of branch point prediction tools to predict physiological branch points and their alteration by variants</title><author>Leman, Raphaël ; Tubeuf, Hélène ; Raad, Sabine ; Tournier, Isabelle ; Derambure, Céline ; Lanos, Raphaël ; Gaildrat, Pascaline ; Castelain, Gaia ; Hauchard, Julie ; Killian, Audrey ; Baert-Desurmont, Stéphanie ; Legros, Angelina ; Goardon, Nicolas ; Quesnelle, Céline ; Ricou, Agathe ; Castera, Laurent ; Vaur, Dominique ; Le Gac, Gérald ; Ka, Chandran ; Fichou, Yann ; Bonnet-Dorion, Françoise ; Sevenet, Nicolas ; Guillaud-Bataille, Marine ; Boutry-Kryza, Nadia ; Schultz, Inès ; Caux-Moncoutier, Virginie ; Rossing, Maria ; Walker, Logan C ; Spurdle, Amanda B ; Houdayer, Claude ; Martins, Alexandra ; Krieger, 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Stéphanie</au><au>Legros, Angelina</au><au>Goardon, Nicolas</au><au>Quesnelle, Céline</au><au>Ricou, Agathe</au><au>Castera, Laurent</au><au>Vaur, Dominique</au><au>Le Gac, Gérald</au><au>Ka, Chandran</au><au>Fichou, Yann</au><au>Bonnet-Dorion, Françoise</au><au>Sevenet, Nicolas</au><au>Guillaud-Bataille, Marine</au><au>Boutry-Kryza, Nadia</au><au>Schultz, Inès</au><au>Caux-Moncoutier, Virginie</au><au>Rossing, Maria</au><au>Walker, Logan C</au><au>Spurdle, Amanda B</au><au>Houdayer, Claude</au><au>Martins, Alexandra</au><au>Krieger, Sophie</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Assessment of branch point prediction tools to predict physiological branch points and their alteration by variants</atitle><jtitle>BMC genomics</jtitle><addtitle>BMC Genomics</addtitle><date>2020-01-28</date><risdate>2020</risdate><volume>21</volume><issue>1</issue><spage>86</spage><epage>86</epage><pages>86-86</pages><artnum>86</artnum><issn>1471-2164</issn><eissn>1471-2164</eissn><abstract>Branch points (BPs) map within short motifs upstream of acceptor splice sites (3'ss) and are essential for splicing of pre-mature mRNA. Several BP-dedicated bioinformatics tools, including HSF, SVM-BPfinder, BPP, Branchpointer, LaBranchoR and RNABPS were developed during the last decade. Here, we evaluated their capability to detect the position of BPs, and also to predict the impact on splicing of variants occurring upstream of 3'ss.
We used a large set of constitutive and alternative human 3'ss collected from Ensembl (n = 264,787 3'ss) and from in-house RNAseq experiments (n = 51,986 3'ss). We also gathered an unprecedented collection of functional splicing data for 120 variants (62 unpublished) occurring in BP areas of disease-causing genes. Branchpointer showed the best performance to detect the relevant BPs upstream of constitutive and alternative 3'ss (99.48 and 65.84% accuracies, respectively). For variants occurring in a BP area, BPP emerged as having the best performance to predict effects on mRNA splicing, with an accuracy of 89.17%.
Our investigations revealed that Branchpointer was optimal to detect BPs upstream of 3'ss, and that BPP was most relevant to predict splicing alteration due to variants in the BP area.</abstract><cop>England</cop><pub>BioMed Central Ltd</pub><pmid>31992191</pmid><doi>10.1186/s12864-020-6484-5</doi><tpages>1</tpages><orcidid>https://orcid.org/0000-0003-1978-7133</orcidid><orcidid>https://orcid.org/0000-0002-5104-9125</orcidid><orcidid>https://orcid.org/0000-0001-6671-1567</orcidid><orcidid>https://orcid.org/0000-0001-7610-7355</orcidid><orcidid>https://orcid.org/0000-0003-3236-7280</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1471-2164 |
| ispartof | BMC genomics, 2020-01, Vol.21 (1), p.86-86, Article 86 |
| issn | 1471-2164 1471-2164 |
| language | eng |
| recordid | cdi_gale_infotracmisc_A616352643 |
| source | DOAJ Directory of Open Access Journals; EZB-FREE-00999 freely available EZB journals; PubMed Central; SpringerLink Journals - AutoHoldings; PubMed Central Open Access; Springer Nature OA Free Journals |
| subjects | Accuracy Adenosine Algorithms Benchmark Benchmarking Bioinformatics Branch point Computational biology Datasets Diseases Evaluation Genes Genomics HSF Life Sciences Messenger RNA Methods mRNA Open source software Physiology Prediction RNA RNA sequencing RNA splicing Scientific software Splicing SVM-BPfinder |
| title | Assessment of branch point prediction tools to predict physiological branch points and their alteration by variants |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-31T19%3A42%3A09IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_doaj_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Assessment%20of%20branch%20point%20prediction%20tools%20to%20predict%20physiological%20branch%20points%20and%20their%20alteration%20by%20variants&rft.jtitle=BMC%20genomics&rft.au=Leman,%20Rapha%C3%ABl&rft.date=2020-01-28&rft.volume=21&rft.issue=1&rft.spage=86&rft.epage=86&rft.pages=86-86&rft.artnum=86&rft.issn=1471-2164&rft.eissn=1471-2164&rft_id=info:doi/10.1186/s12864-020-6484-5&rft_dat=%3Cgale_doaj_%3EA616352643%3C/gale_doaj_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2357424478&rft_id=info:pmid/31992191&rft_galeid=A616352643&rft_doaj_id=oai_doaj_org_article_da6b4502084e4b2a87009788da78c331&rfr_iscdi=true |