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  • lexogen
    Registered Vendor
    • Aug 2012
    • 49

    Release of SLAMseq kits for metabolic RNA sequencing

    Today Lexogen, the transcriptomics and next-generation sequencing company, launched the SLAMseq product family for high throughput metabolic sequencing of RNA. The kits are based on a new technology developed at the Institute of Molecular Biotechnology (IMBA) at the Vienna BioCenter in Austria, which was published in Nature Methods.

    Current RNA-Seq methods can measure steady-state RNA levels. However, they cannot resolve the underlying kinetics of RNA turnover that contribute to total RNA levels. This has been a limitation for the application of RNA-Seq in basic research for understanding RNA metabolic pathways and gene regulation.

    Lexogen has realized a family of kits based on the new genome-wide, non-invasive, quantitative, fast, and reliable SLAMseq (thiol (SH)-Linked Alkylation for the Metabolic Sequencing of RNA) method, developed by Stefan Ameres’ research group at IMBA. Compared to standard RNA-Seq the SLAMseq protocol adds only two extra steps: labeling of the RNA by adding one compound to the culture medium and pre-processing the total RNA before continuing with a standard RNA-Seq protocol. SLAMseq can differentiate between nascent RNA and existing RNA, while standard RNA-Seq measures total steady-state RNA levels only. Hence, SLAMseq allows for parallel quantification of total and newly synthesized RNA levels, without the need for biochemical isolation. Sampling at different time points reveals the complete in vivo and transcriptome-wide kinetics of RNA synthesis and degradation.

    Think of what you can do when you know RNA transcription and degradation rates transcriptome-wide...!

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  • GATTACAT
    Reply to Nine Things a Sample Prep Scientist Thinks About Before Sequencing
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    Love this - good data definitely starts from good input, and poor input can only give relatively poor data. I particularly like the mention of Nanodrop/absorbance based methods for quantification. It's such a toss up if you'll get an accurate reading or what amounts to a randomly generated number, and a lot of library/sequencing related issues can be traced back to poor quant.
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