Webinar highlights – Maximizing miRNA-seq success from liquid biopsy samples

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Development of markers that facilitate earlier and non-invasive diagnosis is a primary goal of disease research. This is where microRNAs come in. Studies have indicated that the expression levels of these non-coding RNA molecules are altered in disease states, including cancer and neurodegeneration. Evidence of their presence in biofluids means that their potential as important biomarkers that can be detected by noninvasive procedures is now widely acknowledged. miRNA sequencing (miRNA-seq) is an emerging technology for microRNA expression studies, but it’s been plagued by various challenges, limiting its utilization.

Recently, our miRNA-seq expert, Dr. Jonathan Shaffer, presented a webinar discussing the current miRNA sequencing landscape, with its numerous pitfalls. For example, most sequencing experiments generate just 25–30% on-target data. Furthermore, miRNAs are expressed at low levels in biofluids and sample input requirements are simply too high – additionally, these samples may be contaminated with other RNA types. Current gel-reliant workflows are time consuming and tedious, and increasingly difficult with large sample numbers, and also run the risk of contaminating non-miRNA RNA species – gel excision is, after all, not an exact science.

Dr. Shaffer also presented an overview of our innovative new QIAseq miRNA Library Kit, highlighting its innovative features that enable miRNA-focused sequencing for reliable miRNA quantification and discovery. The kit is a Sample to Insight solution designed to specifically address each one of the bottlenecks that plague current miRNA-seq methods, maximizing on-target reads, dynamic range and discovery potential. Enabling gel-free miRNA sequencing library prep from as little as 1 ng of total RNA, the kit also includes integrated bioinformatics, optimizing miRNA-seq for biofluid microRNA research. For increased stringency and to eliminate bias, the kit employs Unique Molecular Indices (UMIs), allowing reliable quantification of individual miRNA molecules.

Data normalization can be tricky when it comes to small RNA sequencing – Dr. Shaffer noted that no consensus exists for the best way to do it. However, he presented 4 different options and discussed the strategy behind them as well as the best uses for each, such as which is best for followup qPCR studies (geNorm) and which are most appropriate for sequencing from biofluids (DESeq2 and Trimmed Mean of M).

Dr. Shaffer also presented complete workflows for both serum and exosomes, application data, and more information about data analysis, and held a Q&A with the audience afterward. Want to check out the rest of the webinar? You can join Dr. Jonathan Shaffer again on March 20 at 1 p.m. EST, 10 a.m. PST, 7 p.m. CET, for the webinar, as well as a live Q&A session shortly afterwards. Register now!

Devika Mathur

Devika Mathur is a Senior Technical & Marketing Writer at QIAGEN. Devika joined QIAGEN in 2008 and has been responsible for creating literature for numerous QIAGEN products, including the REPLI-g and QIAseq product lines, and has written extensively on various scientific topics ranging from next-generation sequencing and single cell analysis to PCR and sample preparation. Devika is a graduate from University College Cork, Ireland, and has a microbiology research background, focusing primarily on the molecular characterization of the replication module of the lactococcal bacteriophage Tuc2009.

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