SIRVs – Spike-In RNA Variant Mixes Designed for Splice Variant Detection

RNA is complex, and its sequencing is even more complex. One of the biggest complications originates from the fact that RNA consists of numerous variations such as alternative splicing and isoforms which are introduced during the process of transcription and splicing. To overcome the difficulties in RNA-Seq data analysis, “spike-in controls” are essential in RNA-Seq experiments as they provide a firm basis on which the workflow and platform properties can be properly assessed.

To this date, ERCC (External RNA Controls Consortium) Spike-In Mix has been serving very well for part of this purpose. It has good dynamic range of transcript concentration and it provides decent reference for accurate measurement. However, it has the limitation of addressing only the concentration of transcripts, and it does not provide any reference for the diverse variations occurring at transcript level.

Researchers at Lexogen conceived the idea of having a new RNA standard which reflects these diverse variations occurring in transcripts. After several years of development, today we are very happy tthey have released the SIRVs, the Spike-In RNA Variant Mixes, the new RNA spike-in control which provides the reference for transcript variants.

SIRVs contain 69 artificial transcript variants which mimic 7 human model genes. They possess the typical characteristics of RNA, such as alternative splicing, alternative TSS and TES (transcription start site and end site), overlapping genes, and antisense transcripts. SIRVs behave identically to mRNA in most aspects, and have no significant similarities to any known sequences. Once spiked into your RNA samples and sequenced together, it provides a precise assessment of the data analysis pipeline such as accuracy of mapping, assembly of isoforms, and quantification of the transcripts.


It is the only RNA standard which provides reference for transcript variants, and the researchers feel it will become one of the most essential materials for the RNA-Seq analysis.

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