Posters
« Back
Innovative technology that enables RNAi in difficult to transfect cells
EP22930
Poster Title: Innovative technology that enables RNAi in difficult to transfect cells
Submitted on 27 Apr 2015
Author(s): Christina Yamada, Kathryn Robinson, Allison St. Amand, Zaklina Strezoska, Greg Wardle, Anastasia Khvorova, Devin Leake
Affiliations: GE Healthcare Dharmacon, Inc.
Poster Views: 1,716
View poster »


Poster Information
Abstract: Delivery remains one of the last barriers for applying RNA interference (RNAi) in clinically relevant cell lines. Investigations at Dharmacon have led to the development of an innovative molecule for delivery in a wide variety of cell types. These modified siRNAs have been found to effectively silence target genes in cell types that are typically difficult to transfect using standard delivery methods. We present data for multiple cell types including SH-SY5Y (neuroblastoma), Jurkat (T-cells), and primary neurons. This technology, Dharmacon™ Accell™ siRNA reagents, allows for functional genomic studies in pertinent cell types. Moreover, in some instances, cells can be continuously dosed with these siRNAs, thus enabling knockdown of any target gene of interest for extended durations.Summary: Investigations at Dharmacon have led to the development of innovative siRNA molecules that can be delivered into difficult-to-transfect cells without additional lipid reagents, virus, or instruments. This technology, Accell siRNA reagents, enables gene knockdown for functional genomic studies in a wide variety of cell types. In some instances, cells can be continuously dosed with Accell siRNAs to enable target gene knockdown for extended durations.References: Report abuse »
Questions
Ask the author a question about this poster.
Ask a Question »

Creative Commons

Related Posters


Genetic Engineering in Male Sterility for Hybrid Variety Development
Abir Hasan Joy

VITVO: Mimicking In Vivo Complexity By The Innovative 3D Model
Olivia Candini1, Giulia Grisendi1, Elisabetta Manuela Foppiani1, Matteo Brogli1, Beatrice Aramini2, Valentina Masciale3, Carlotta Spano1, Tiziana Petrachi4, Elena Veronesi4, Pierfranco Conte5,6, Giorgio Mari1 & Massimo Dominici1,3

Digiceuticals
Helana Lutfi and Shaban Nuredini

Characterization of patient-derived organoids cultured on a gas-rich, liquid-liquid interface
James T. Shoemaker, Katherine R. Richardson, Jamie Arnst, Adam Marcus, Jelena Vukasinovic

Machine Learning: A New Breakthrough in Medical Diagnosis
Punitha Mahendran, Anis Joelaira, Chai Yong Chia, Fazidatul Aziz, Hasyimah Emran, Siew Fun Lee, Wai Kit Wong, Yee Yan Tang, Li Yang Wong