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  1. Prikvačeni tweet
    29. pro 2019.

    Tweetorial from on our recent work to use RNA-targeting CRISPRs for high-throughput screens in human cells. We are very excited by the possibility of using these tools for new kinds of functional genomics & transcriptomics and welcome feedback on the study.

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  2. proslijedio/la je Tweet
    3. velj

    Congrats to Aaron and Yilan on our NCB review on RNA-targeting CRISPR systems!

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  3. proslijedio/la je Tweet

    To understand the brain, we must understand what it’s made of — its cells. Using the Patch-seq method, our researchers describe the electrical and morphological properties of transcriptomic cell types in mouse visual cortex. 📄

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  4. proslijedio/la je Tweet
    31. sij

    Single-cell nucleic acid sequencing has become an essential biomedical research tool. Now makes a strong case that single-cell proteomics will yield another dimension of vital insights w/

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  5. 30. sij

    "Middling correlation" between RNA and protein in CCLE proteomics dataset

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  6. proslijedio/la je Tweet
    29. sij

    Inside today's paper: A whole spread of coronavirus stories, including the hunt for a vaccine to prevent infection, courtesy of yours truly and via

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  7. 25. sij

    Finally, thinking to the future, one thing that is evident is that there is a lot of room for new strategies to design efficient, PAM-flexible — or perhaps even PAM-independent — Cas9 enzymes. (15/15)

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  8. 25. sij

    Second, none of the three PAM flexible Cas9 mutants were capable of matching the activity of wild-type Cas9 at NGG PAM sites, so these mutations likely incur a fitness cost. (14/15)

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  9. 25. sij

    What to make of all this? First, multi-CRISPR pooled screens provide a controlled way to benchmark different genome editing tools. (13/15)

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  10. 25. sij

    Although there was only a partial rescue for nuclease activity (yield an intermediate level of activity between xCas9 and Cas9-NG), we found that — much to our surprise — xCas9-NG yielded a better transcriptional activator than either existing PAM-flexible enzyme. (12/15)

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  11. 25. sij

    Given this data, we wondered whether the lower activity of xCas9 could be rescued using the Cas9-NG mutations. So, we made a frankenzyme: xCas9-NG. (11/15)

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  12. 25. sij

    At this point, you might have noticed that there is also a difference in the PAM-flexible Cas9 variants: Specifically, that Cas9-NG outperforms xCas9 at NGH PAMs. (H= not G) Indeed, this is the case across all of our screens: knock-out, CRISPRi, and CRISPRa. (10/15)

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  13. 25. sij

    We also detected Cas9-NG activity at unconventional NAD PAMs. Upon testing, we found that some (but not all) NAD target sites work with Cas9-NG. For example, only Cas9-NG can drive CD45 expression at the NAA target site shown in the last row below. (9/15)

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  14. 25. sij

    Since CRISPRi and CRISPRa require binding at the target site (but not cutting since they utilize nuclease-null dCas9), we wondered if results might be different for those applications. But they were broadly the same as what we’d seen with nuclease. (8/15)

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  15. 25. sij

    And, in case you’re curious, if you deep sequence the target sites, DNA editing/indels are very well correlated (as expected) with protein loss across all enzymes: (7/15)

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  16. 25. sij

    Overall, we found that PAM flexibility of Cas9 mutants comes at a cost of reduced editing efficacy. For example, here are several guides targeting the cell-surface marker CD46. Overall, wild-type Cas9 leads to highest knock-out. (6/15)

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  17. 25. sij

    Thus, in a single screen, we could capture both target site/PAM preferences and also relative efficiency of each Cas9 variant. (5/15)

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  18. 25. sij

    So, instead of a typical CRISPR pooled screen with a library of guide RNAs, we also had all 3 different Cas9 enzymes in the same pool (transduced separately). For the multi-CRISPR pooled screen, we added a 6nt barcode after the gRNA to encode enzyme & KO/i/a modality. (4/15)

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  19. 25. sij

    First a little background: For gain-of-function screens, we were interested to know whether we could target smaller regions (and hence those containing few NGG PAMs) using the recent variants, xCas9 and Cas9-NG, which only requiring a single G at the target site. (3/15)

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  20. 25. sij

    First, this work was co-led by postdocs Mat Legut and Zharko Daniloski and aided by several others in our group. (Special shout-out to Xinhe Xue, who spent her PhD rotation helping us launch this project and then joined our lab!) (2/15)

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  21. 25. sij

    TWEETORIAL on our new preprint: A genome engineering shootout (!) between wild-type Cas9 and 2 different PAM-flexible CRISPR enzymes — xCas9 and Cas9-NG — across 3 different tasks: knock-out, CRISPRi, and CRISPRa (1/15)

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