The Hidden World of Microbiomes and Their Impact on Our Lives
Microbiomes are the diverse communities of microorganisms that inhabit different parts of our bodies, as well as the environment around us.
Similar seed effects in independent siRNA screens
A 2013 study on Parkin translocation used genome-wide siRNA libraries from Ambion (single Silencer Select siRNAs) and Dharmacon (pools of 4 siGENOME siRNAs).
The Iron Law of RNAi Screening
This is the lead singer of a band called Iron Law. He looks like a researcher experiencing massive frustration after discovering what we call the Iron Law of RNAi Screening.
Low hit validation rate for Dharmacon siGENOME screens
Good experimental design is important when validating hits from RNAi screens.
Clearly compensating
Genetic compensation by transcriptional adaptation is a process whereby knocking out a gene (e.g by CRISPR or TALEN) results in the deregulation of genes that make up for the loss of gene function.
Pooling only 4 siRNAs increases off-target effects
Low-complexity pools (with 4 siRNAs per gene) should thus lead to overall stronger off-target effects than single siRNAs.
Citations of our Nucleic Acids Research Paper
Our 2014 Nucleic Acids Research paper provides an excellent overview of the siPOOL technology. Google Scholar shows that our paper has been cited 64 times.
Performing target validation well
This blogpost describes issues encountered in target validation and how to safeguard against poor reproducibility in RNAi experiments.
Low complexity pooling does not prevent siRNA off-targets
Low-complexity siRNA pooling (e.g. Dharmacon siGENOME SMARTpools) does not prevent siRNA off-targets. It may in fact exacerbate off-target effects. Only high-complexity pooling (siPOOLs) can reliably ensure on-target phenotypes.
What is the probability of an siRNA off-target phenotype?
Conventional siRNAs have a high probability of giving off-target phenotypes. siRNA off-target effects can be reduced by using more specific reagents or narrowing the assay focus (to reduce the number of relevant genes).
