{"title":"A reliable method for quantification of splice variants using RT-qPCR","authors":"Julia Camacho Londoño, Stephan E. Philipp","doi":"10.1186/s12867-016-0060-1","DOIUrl":null,"url":null,"abstract":"<p>The majority of protein isoforms arise from alternative splicing of the encoding primary RNA transcripts. To understand the significance of single splicing events, reliable techniques are needed to determine their incidence. However, existing methods are labour-intensive, error-prone or of limited use.</p><p>Here, we present an improved method to determine the relative incidence of transcripts that arise from alternative splicing at a single site. Splice variants were quantified within a single sample using one-step reverse transcription quantitative PCR. Amplification products obtained with variant specific primer pairs were compared to those obtained with primer pairs common to both variants. The identities of variant specific amplicons were simultaneously verified by melt curve analysis. Independent calculations of the relative incidence of each variant were performed. Since the relative incidences of variants have to add upto 100?%, the method provides an internal control to monitor experimental errors and uniform reverse transcription. The reliability of the method was tested using mixtures of cDNA templates as well as RNA samples from different sources.</p><p>The method described here, is easy to set up and does not need unrelated reference genes and time consuming, error-prone standard curves. It provides a reliable and precise technique to distinguish small differences of the relative incidence of two splice variants.</p>","PeriodicalId":497,"journal":{"name":"BMC Molecular Biology","volume":"17 1","pages":""},"PeriodicalIF":2.9460,"publicationDate":"2016-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s12867-016-0060-1","citationCount":"28","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMC Molecular Biology","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1186/s12867-016-0060-1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Biochemistry, Genetics and Molecular Biology","Score":null,"Total":0}
引用次数: 28
Abstract
The majority of protein isoforms arise from alternative splicing of the encoding primary RNA transcripts. To understand the significance of single splicing events, reliable techniques are needed to determine their incidence. However, existing methods are labour-intensive, error-prone or of limited use.
Here, we present an improved method to determine the relative incidence of transcripts that arise from alternative splicing at a single site. Splice variants were quantified within a single sample using one-step reverse transcription quantitative PCR. Amplification products obtained with variant specific primer pairs were compared to those obtained with primer pairs common to both variants. The identities of variant specific amplicons were simultaneously verified by melt curve analysis. Independent calculations of the relative incidence of each variant were performed. Since the relative incidences of variants have to add upto 100?%, the method provides an internal control to monitor experimental errors and uniform reverse transcription. The reliability of the method was tested using mixtures of cDNA templates as well as RNA samples from different sources.
The method described here, is easy to set up and does not need unrelated reference genes and time consuming, error-prone standard curves. It provides a reliable and precise technique to distinguish small differences of the relative incidence of two splice variants.
期刊介绍:
BMC Molecular Biology is an open access journal publishing original peer-reviewed research articles in all aspects of DNA and RNA in a cellular context, encompassing investigations of chromatin, replication, recombination, mutation, repair, transcription, translation and RNA processing and function.