Prediction and assessment of splicing alterations: implications for clinical testing
Sequence variants that may result in splicing alterations are a particular class of inherited variants for which consequences can be more readily assessed, using a combination of bioinformatic prediction methods and in vitro assays. There is also a general agreement that a variant would invariably b...
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Veröffentlicht in: | Human mutation 2008-11, Vol.29 (11), p.1304-1313 |
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creator | Spurdle, Amanda B Couch, Fergus J Hogervorst, Frans B.L Radice, Paolo Sinilnikova, Olga M |
description | Sequence variants that may result in splicing alterations are a particular class of inherited variants for which consequences can be more readily assessed, using a combination of bioinformatic prediction methods and in vitro assays. There is also a general agreement that a variant would invariably be considered pathogenic on the basis of convincing evidence that it results in transcript(s) carrying a premature stop codon or an in-frame deletion disrupting known functional domain(s). This commentary discusses current practices used to assess the clinical significance of this class of variants, provides suggestions to improve assessment, and highlights the issues involved in routine assessment of potential splicing aberrations. We conclude that classification of sequence variants that may alter splicing is greatly enhanced by supporting in vitro analysis. Additional studies that assess large numbers of variants for induction of splicing aberrations and exon skipping are needed to define the contribution of splicing/exon skipping to cancer and disease. These studies will also provide the impetus for development of algorithms that better predict splicing patterns. To facilitate variant classification and development of more specific bioinformatic tools, we call for the deposition of all laboratory data from splicing analyses into national and international databases. Hum Mutat 29(11), 1304-1313, 2008. |
doi_str_mv | 10.1002/humu.20901 |
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There is also a general agreement that a variant would invariably be considered pathogenic on the basis of convincing evidence that it results in transcript(s) carrying a premature stop codon or an in-frame deletion disrupting known functional domain(s). This commentary discusses current practices used to assess the clinical significance of this class of variants, provides suggestions to improve assessment, and highlights the issues involved in routine assessment of potential splicing aberrations. We conclude that classification of sequence variants that may alter splicing is greatly enhanced by supporting in vitro analysis. Additional studies that assess large numbers of variants for induction of splicing aberrations and exon skipping are needed to define the contribution of splicing/exon skipping to cancer and disease. These studies will also provide the impetus for development of algorithms that better predict splicing patterns. To facilitate variant classification and development of more specific bioinformatic tools, we call for the deposition of all laboratory data from splicing analyses into national and international databases. 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Mutat</addtitle><description>Sequence variants that may result in splicing alterations are a particular class of inherited variants for which consequences can be more readily assessed, using a combination of bioinformatic prediction methods and in vitro assays. There is also a general agreement that a variant would invariably be considered pathogenic on the basis of convincing evidence that it results in transcript(s) carrying a premature stop codon or an in-frame deletion disrupting known functional domain(s). This commentary discusses current practices used to assess the clinical significance of this class of variants, provides suggestions to improve assessment, and highlights the issues involved in routine assessment of potential splicing aberrations. We conclude that classification of sequence variants that may alter splicing is greatly enhanced by supporting in vitro analysis. Additional studies that assess large numbers of variants for induction of splicing aberrations and exon skipping are needed to define the contribution of splicing/exon skipping to cancer and disease. These studies will also provide the impetus for development of algorithms that better predict splicing patterns. To facilitate variant classification and development of more specific bioinformatic tools, we call for the deposition of all laboratory data from splicing analyses into national and international databases. Hum Mutat 29(11), 1304-1313, 2008.</description><subject>Algorithms</subject><subject>Alternative Splicing</subject><subject>bioinformatic prediction</subject><subject>cancer</subject><subject>Codon, Nonsense</subject><subject>Computational Biology - methods</subject><subject>Genes, Neoplasm</subject><subject>Genetic Predisposition to Disease</subject><subject>Genetic Testing - methods</subject><subject>Genetic Variation</subject><subject>Humans</subject><subject>oncology</subject><subject>Sequence Deletion</subject><subject>splicing</subject><subject>unclassified variant</subject><issn>1059-7794</issn><issn>1098-1004</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2008</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kctu1DAYhSMEohfY8ACQZYWU4vuFBRKqoEVMAYkZVWJjeXyZGpJ4aielffs6ZCiwYWX7-PuPj3yq6hkExxAA9Opy7MZjBCSAD6p9CKRoikweTnsqG84l2asOcv4OABCU4sfVHhSSQkLEfrX8kpwNZgixr3Vva52zy7lz_VBHX-dtG0zoN7VuB5f0ROXXdegmeT7VPqbatKEvQlsPLg8Ff1I98rrN7uluPayW798tT86axefTDydvF42hEMPGMuKI0ZhzixD3nljKJEfSa4PAmjPOASMC-bUVzhKLJKLYGy40khBLig-rN7Ptdlx3zpoSOulWbVPodLpVUQf1700fLtUmXiskMCIcFIOjnUGKV2PJrrqQjWtb3bs4ZgU5Z4xxJklBX86oSTHn5Pz9MxCoqQU1taB-tVDg538H-4Puvr0AcAZ-htbd_sdKna3OV79Nm3km5MHd3M_o9EMxjjlVF59O1flHhBlYfFMXhX8x815HpTcpZLX6iooRgJQyKiC-AxmDrMU</recordid><startdate>200811</startdate><enddate>200811</enddate><creator>Spurdle, Amanda B</creator><creator>Couch, Fergus J</creator><creator>Hogervorst, Frans B.L</creator><creator>Radice, Paolo</creator><creator>Sinilnikova, Olga M</creator><general>Wiley Subscription Services, Inc., A Wiley Company</general><scope>FBQ</scope><scope>BSCLL</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8FD</scope><scope>FR3</scope><scope>P64</scope><scope>RC3</scope><scope>5PM</scope></search><sort><creationdate>200811</creationdate><title>Prediction and assessment of splicing alterations: implications for clinical testing</title><author>Spurdle, Amanda B ; Couch, Fergus J ; Hogervorst, Frans B.L ; Radice, Paolo ; Sinilnikova, Olga M</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c5131-d64e4ca377d227ff4d569729fac20b767706482fbd8ed4d29253fc78a2913953</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2008</creationdate><topic>Algorithms</topic><topic>Alternative Splicing</topic><topic>bioinformatic prediction</topic><topic>cancer</topic><topic>Codon, Nonsense</topic><topic>Computational Biology - methods</topic><topic>Genes, Neoplasm</topic><topic>Genetic Predisposition to Disease</topic><topic>Genetic Testing - methods</topic><topic>Genetic Variation</topic><topic>Humans</topic><topic>oncology</topic><topic>Sequence Deletion</topic><topic>splicing</topic><topic>unclassified variant</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Spurdle, Amanda B</creatorcontrib><creatorcontrib>Couch, Fergus J</creatorcontrib><creatorcontrib>Hogervorst, Frans B.L</creatorcontrib><creatorcontrib>Radice, Paolo</creatorcontrib><creatorcontrib>Sinilnikova, Olga M</creatorcontrib><creatorcontrib>IARC Unclassified Genetic Variants Working Group</creatorcontrib><creatorcontrib>for the IARC Unclassified Genetic Variants Working Group</creatorcontrib><collection>AGRIS</collection><collection>Istex</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Human mutation</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Spurdle, Amanda B</au><au>Couch, Fergus J</au><au>Hogervorst, Frans B.L</au><au>Radice, Paolo</au><au>Sinilnikova, Olga M</au><aucorp>IARC Unclassified Genetic Variants Working Group</aucorp><aucorp>for the IARC Unclassified Genetic Variants Working Group</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Prediction and assessment of splicing alterations: implications for clinical testing</atitle><jtitle>Human mutation</jtitle><addtitle>Hum. Mutat</addtitle><date>2008-11</date><risdate>2008</risdate><volume>29</volume><issue>11</issue><spage>1304</spage><epage>1313</epage><pages>1304-1313</pages><issn>1059-7794</issn><eissn>1098-1004</eissn><abstract>Sequence variants that may result in splicing alterations are a particular class of inherited variants for which consequences can be more readily assessed, using a combination of bioinformatic prediction methods and in vitro assays. There is also a general agreement that a variant would invariably be considered pathogenic on the basis of convincing evidence that it results in transcript(s) carrying a premature stop codon or an in-frame deletion disrupting known functional domain(s). This commentary discusses current practices used to assess the clinical significance of this class of variants, provides suggestions to improve assessment, and highlights the issues involved in routine assessment of potential splicing aberrations. We conclude that classification of sequence variants that may alter splicing is greatly enhanced by supporting in vitro analysis. Additional studies that assess large numbers of variants for induction of splicing aberrations and exon skipping are needed to define the contribution of splicing/exon skipping to cancer and disease. These studies will also provide the impetus for development of algorithms that better predict splicing patterns. To facilitate variant classification and development of more specific bioinformatic tools, we call for the deposition of all laboratory data from splicing analyses into national and international databases. Hum Mutat 29(11), 1304-1313, 2008.</abstract><cop>Hoboken</cop><pub>Wiley Subscription Services, Inc., A Wiley Company</pub><pmid>18951448</pmid><doi>10.1002/humu.20901</doi><tpages>10</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Alternative Splicing bioinformatic prediction cancer Codon, Nonsense Computational Biology - methods Genes, Neoplasm Genetic Predisposition to Disease Genetic Testing - methods Genetic Variation Humans oncology Sequence Deletion splicing unclassified variant |
title | Prediction and assessment of splicing alterations: implications for clinical testing |
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