Genetic Engineering & Biotechnology News (GEN) is the world's most widely read biotech publication. It provides the R&D; community with critical information on the tools, technologies, and trends that drive the biotech industry.
Issue link: http://gen.epubxp.com/i/729777
Genetic Engineering & Biotechnology News | GENengnews.com | OCTOBER 1, 2016 | 25 ing of samples during sequencing. The complete ThruPLEX Tag-seq library structure consists of P5/P7 sequences for flow cell attachment, sample indexes, sequencing primer binding sites, and UMT sequences. Each UMT consists of six degenerate bases, providing 4,096 unique sequence permuta- tions. Together, the UMTs on either side of a fragment produce more than 16 million tag combinations, ensuring that all fragments are labeled uniquely for identification during data analysis. This process allows reads with the same UMT to be grouped computation- ally into amplification families to determine real mutations, correcting errors generated through library preparation and sequencing. To build the consensus sequence, mu- tations present in all reads are called true, while those present in only some reads are false. Consensus sequence reads are then constructed to yield one read per original molecule that is free of library preparation and sequencing errors, correctly reflecting the sequence of the initial molecule. In ad- dition, during data analysis, UMTs allow the original DNA molecules to be counted. DNA fragments sharing the same UMT be- long to the same family and can be traced to the original molecule. Therefore, the number of unique DNA molecules can be determined by counting the number of UMTs in the li- brary. After error correction, the resulting consensus sequence is then used to detect low-frequency mutations with high sensitiv- ity and specificity (Figure 1). Sensitive Variant Detection To establish the level of variant detection using the ThruPLEX Tag-seq Kit, we mea- sured the limits of variant detection using reference standards engineered with vari- ants present at various allele frequencies. Using 10 ng and 30 ng of cfDNA Horizon reference standards, Baylor Miraca Genetics Laboratories and University College London generated libraries using ThruPLEX Tag-seq, followed by target enrichment to 5,000X coverage and sequencing on a HiSeq ® 2500 or NextSeq ® 500 system. Data processing and analysis were con- ducted using the ultra-fast Curio bioinformat- ics platform. Background errors (false-posi- tive calls) due to PCR artifacts and sequencing errors were dramatically reduced with Thru- PLEX Tag-seq library preparation (Figures 2A, 2B). Consequently, signal-to-noise ratio was also significantly improved (Figure 2C), providing more confident variant detection. To determine the level of variant detec- tion, six variants at different allele frequen- cies were examined to compare the expected mean allele frequency (MAF) to the detect- ed allele frequency. Variants were called at their expected frequencies down to 0.5% with 100% sensitivity and >99% specific- ity (Table 1). Lower detection limits can be achieved, depending on sample quality, in- put amount, capture efficiency, sequencing depth, and data-processing algorithms. Conclusion This data demonstrates that ThruPLEX Tag-seq, equipped with more than 16 million UMT combinations, is a powerful tool for confident detection of low-frequency variants. Variants at 0.5% allele frequency or lower can be detected with high sensitivity and specific- ity using just 10 ng of input DNA. The combi- nation of ThruPLEX Tag-seq's highly efficient chemistry and single-tube workflow preserves molecular complexity, allowing researchers to discover more information from precious samples. Researchers have the freedom to use any commercially available capture panels, or to design custom capture panels to inter- rogate genomic regions of interest that span hundreds of genes and study variants present at low allele frequencies. View it Now! On Demand DURATION 60 minutes COST Complimentary Speakers Continuous BioProcessing: Not a Revolution but an Evolution The next evolutionary frontier for the biopharmaceutical industry is the widespread adoption of integrated continuous bioprocessing for biologics manufacturing. The key to its success, however, is the availability of novel upstream and downstream technologies that will not only reduce facility footprint, capital expenses, and product cost of goods, but will also increase process productivity, flexibility, and further facilitate the utilization of single-use and/or disposable technologies. This presentation will provide a risk-based and data-driven overview of an integrated bioprocessing platform, highlighting challenges and opportunities for product development. A live Q&A; session will follow the presentations, offering you a chance to pose questions to our expert panelists. Who Should Attend • Process development scientists • B iomanufacturing and scale-up technologists • Chief scientific officers and chief technical officers • Tech transfer specialists and pilot-scale scientists • CMO scientists Free Registration! www.GENengnews.com/continuous Webinars You Will Learn • The evolving nature of continuous bioprocessing technologies . • Scalability solutions. • Practical applications and methodologies of continuous bioprocessing systems. • That decreased costs, smaller operational footprint, and improved asset utilization are invaluable benefits. Produced with support from Engin Ayturk, Ph.D. Senior R&D; Manager BioPharm Applications R&D;, Integrated Continuous BioProcessing Pall Life Sciences Peter Levison, Ph.D. Senior Marketing Director Downstream Processing Pall Life Sciences Kristine Angevine (kangevine@rubicongen omics.com) is product manager I, Edward Jan is senior product manager, Matt Carroll is senior director of internal operations and bioinformatics at Rubicon Genomics. Web- site: www.rubicongenomics.com. Jinglan Zhang is clinical molecular and biochemical geneticist and Hongzheng Dai is ABMGG clinical molecular genetics & genomics fel- low at Baylor Miraca Genetics Laborato- ries. Richard Yim is a doctoral researcher at University College London. Shawn Quinn is partner at Curio Genomics. OMICS Tutorial