Unique molecular indices (UMI) and their application in detecting novel gene fusions and gene expression and genetic variation

C.E. CREDITS: P.A.C.E. CE | Florida CE

Speakers

Samuel Rulli
Global Product Manager at QIAGEN
Biography
Dr Samuel Rulli received his PhD in 2002 from Tulane University and pursued post-doctoral research at Johns Hopkins University and the National Cancer Institute in Frederick, MD. Trained as a molecular biologist, Dr. Rulli started working in industry in 2007 and has worked on different assay detection technologies for gene expression and nucleic acid analysis. Currently he is a global product manager at QIAGEN specializing in qPCR & NGS based detection of both protein and non-coding RNAs by pathway and disease.

Abstract:

Tumor heterogeneity has been known for a while but quantifying heterogeneity is still a challenge. NGS is the method of choice in the analysis of tumor heterogeneity, however, there are some inherent challenges associated with it. These include false positives, gaps in the gene due to overrepresentation and incomplete representation of low-frequency transcripts – all contributing to an inaccurate picture. Conventional library prep strategies for NGS are based on PCR, which introduces sequence-based bias and amplification noise, leading to these inaccuracies.

In this webinar, we will cover

Principles of UMI and the new QIAseq product porfolio
How UMI along with SPE (single primer extension) allows for increased uniformity across difficult-to-sequence regions, removal of library construction bias, improved data analysis and sequencing optimization
How data generated from using UMI and SPE is directly comparable to analysis derived from whole transcriptome and exome sequencing
Application of UMI and SPE in the discovery of novel gene fusions and in the analysis of gene expression and genetic variation

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