Our last pre-print of 2024! We created a simple-to-use, temporally-controlled CRISPR/Cas9 toolset that doesn’t compromise between background and induced editing.
https://t.co/nrdcIjzmMc
@AdrianoAguzzi Unfortunately not right now. You can request them through the Genentech MTA portal (please reference Andrew Ng, co-last author, in the request): https://t.co/XPmQb7mmPW
Our last pre-print of 2024! We created a simple-to-use, temporally-controlled CRISPR/Cas9 toolset that doesn’t compromise between background and induced editing.
https://t.co/nrdcIjzmMc
@Ella_Maru Notes: Some cell lines (SW480) have super high basal activity from the TRE3G promoter. A different promoter/inducer combo might reduce background. Other lines (HCT116) were poorly inducible. Extra control measures reduced background, but with a slight hit to induced editing.
@Ella_Maru Excellent question! General application of inducible Cas9 was a key emphasis of our work. In short, yes, we find the Ultra-tight system will work "best" for balancing induced vs. un-induced editing across cell lines.
We’ve been excited about sharing these fantastic new systems with the community (some of you had a preview at the last CSHL Genome Eng. conf.), and we would love to hear any feedback or answer any questions you might have for us.
The product of a wonderful collaboration across @genentech led by the brilliant duo of Rajini Srinivasan and Tao Sun, with essential guidance from @andrewng_synbio and contributions from many others.
Have you been interested combining Perturb-Seq screening with Cas12a’s unique capabilities for multiplexed guide RNA expression? Us too! So, we figured out some useful tricks to make it possible, which you can find in our new pre-print. Short thread below: https://t.co/wWmfD2ecq2
And, that worked out every bit as hoped! Shown here is one example of a known phenotype (KDM1a/LSD1 depletion = Vim and/or HLA-I upregulation). More examples in the main text and supplement.
@AlfredoAndere First-hand experience working with Benching in both Industry and Academia: Barriers for getting their software into Industry were high (feature set, cloud security, etc.). Building a brand in Academia was simpler. Trainees would bring their support for it to Industry later.