S_9502 Houston Lab

Low-input RNA-seq library preparation presents several challenges. If you’re working with fragmented or limited RNA amounts, mRNA enrichment and ribosomal RNA (rRNA) removal steps can cause further loss of RNA before the cDNA synthesis steps. Multiple enzymatic and bead cleanup steps after cDNA synthesis can result in a loss of diversity during each step. For some applications where high numbers of samples need to be processed, workflow inefficiencies mean that it is often not possible to simultaneously run over 384 samples or achieve the volume of NGS library prep required to do a small molecule or CRISPR screen.

If you’re looking to overcome these bottlenecks and optimize your workflow based on sample number, read budgets and sequencing platform, then join our webinar. We’ll reveal a new, low-input RNA library preparation kit that integrates rRNA removal and includes sample-specific barcodes to facilitate cDNA pooling. Discover how you can effortlessly increase throughput and ultraplex >18,000 samples into each flow cell lane of an Illumina sequencer. Whether you’re interested in 3’ RNA-seq or complete transcriptome RNA-seq, find out how this versatile kit allows you to do both with just 500 pg to 100 ng of total RNA or enriched mRNA, providing you with ultimate flexibility. We’ll also discuss how you can achieve differential gene expression insights with the help of the intuitive GeneGlobe RNA-seq Analysis Portal, access to which is included with the kit.

About the speaker
Samuel Rulli, Ph.D., Director, Global Product Management, RNA-seq profiling, NGS assay technologies
Dr. Samuel Rulli received his Ph.D. in Molecular and Cellular Biology from Tulane University in 2002,studying the gastric proton pump. After his postdoctoral training at Johns Hopkins University and the National Cancer Institute, he joined QIAGEN in 2009. As the Associate Director of Global Product Management for NGS technologies, Samuel has been instrumental in developing gene expression analysis solutions for qPCR and NGS.
Next Generation Sequencing