Learn best practices for determining gene function with RNAi
A Resource for RNAi Screeners
Topics covered in Frontiers in RNAi
The volume contains eleven chapters and covers a range of topics relevant to researchers just getting started with RNAi screening, as well as those who are interested to learn how the boundaries of RNAi screening applications are expanding.
The first few chapters tackle off-target effects, automation of a high throughput screening laboratory, data repositories, and pooled shRNA screening. Two chapters specifically discuss RNAi and infectious disease: one on how RNAi has been used to combat infectious disease and the other on mimic and inhibitor screens to identify host microRNAs important for viral infection and replication. Screening in 3-dimensional cell cultures and in difficult-to-transfect immune cells is also covered, as is screening siRNA libraries that have been spotted onto microarray slides. The final two chapters explore the use of RNAi screening to develop high performance bioproduction cell lines and to facilitate drug repurposing.
The scientists behind Frontiers in RNAi
The 46 contributing authors are members of the RNAi Global Initiative, an international group of biomedical researchers who collaborate to speed discovery through RNAi screening. Membership is open to not-for-profit biomedical research institutions that acquire one or more screening libraries from the Dharmacon suite of siRNA, microRNA and shRNA products. The Initiative was established in 2005 by Dharmacon and ten academic research institutions. Since then, membership has grown to over 60 institutions stretching across 5 continents. The group meets annually and remains in contact throughout the year on regular teleconferences. This is the second major collaboration resulting in a publication. The first was a review of statistical analysis methods for RNAi screens (Birmingham, et al. 2009; PMID 19644458).
Innovative tools for transient, long-term, inducible and in vivo RNAi applications.
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- RNAi Screening Libraries - Small gene families to genome-wide collections