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Happy to answer questions if you're interested. More about the lab and our research here: thenormanlab.com

thenormanlab.com

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msk.wd108.myworkdayjobs.com

We're also hiring a research technician. This is an opportunity to learn CRISPR screening and single-cell genomics directly from the people who developed these approaches. Previous techs have gone on to great biotech roles and graduate programs. msk.wd108.myworkdayjobs.com/MSKCC_Career...

Research Technician, Norman Lab

About Us: The people of Memorial Sloan Kettering Cancer Center (MSK) are united by a singular mission: ending cancer for life. Our specialized care teams provide personalized, compassionate, expert ca...

msk.wd1.myworkdayjobs.com

We're looking for a postdoc with expertise in ECM biology, fibrosis, or mechanobiology who wants to apply functional genomics tools to their questions OR someone with a technology development background who wants to help build new methods. msk.wd1.myworkdayjobs.com/MSKCC_Career...

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My lab at MSKCC in New York is hiring for two positions. Join us at the frontier of functional genomics, studying fibroblast state transitions, combinatorial genetics, and ECM in disease. Please share with anyone who might be a good fit! (Mustache not required.)

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In my excitement I forgot to actually link the preprint! www.biorxiv.org/content/10.6...

biorxiv.org

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These technologies open several future directions in large-scale genetics. The lab is actively recruiting postdoctoral fellows and technicians. If you’re interested in working at the frontiers of experimental genomics, please get in touch!

This project has been ongoing nearly since the start of my lab. Huge thanks to lead authors Anran (Angel) Tang and Rico Ardy for years of persistence, and to Rafaela Mendes for foundational early work during the height of COVID.

One key implication: we think comprehensive genetic interaction mapping among all human genes may be within reach. Scaling to ~10,000 expressed genes would require ~2.5 billion lineages—about 100× beyond what we show here.

Why AP-1? Our results show that it responds to diverse biological processes. So AP-1 activity provides a readout with fitness-like breadth without requiring large changes in cell growth or death, enabling interaction mapping at much larger scale.

Using PORTAL with an AP-1 reporter, we measured 665,856 pairwise perturbations across 612 genes and 46 million clonal lineages. To our knowledge, this is the largest exhaustively measured GI map in human cells, and the first at this scale with a non-fitness phenotype.

Finally, we developed a dual-sgRNA PORTAL vector using compact “mini” Pol III promoters. These pieces together enable systematic genetic interaction mapping, our main application. (P.S. The same cassette can also be used for dual-sgRNA CROP-seq experiments.)

Each clonal lineage thus becomes an independent replicate. (We show that single-cell resolution is also possible via combinatorial indexing.) For example, here we see knockdown of KDM5C increasing AP-1 reporter activity across hundreds of lineages.

The PORTAL vector actually produces two transcripts: • a pathway-responsive reporter • a constitutive identity transcript for normalization Both carry the sgRNA and a clonal barcode in their 3′ ends, linking phenotype to lineage.

To address the second bottleneck, we developed PORTAL (Perturbation Output via Reporter Transcriptional Activity in Lineages). Instead of reading perturbation identity from genomic DNA, PORTAL encodes perturbation effects in expressed transcripts.

CAP cloning should be broadly useful wherever transformation is limiting, including lineage tracing, MPRAs, combinatorial protein or antibody engineering, toxic ORF libraries, synthetic biology circuits, and, as we show, new scales of functional genomic screens…

The result is extremely even, high-complexity libraries. For example, we cloned a library of 812 × 812 guide pairs × 120,000 clonal barcodes (~80 billion elements), recovering 99.99% of guide pairs with near-Gaussian representation.

CAP cloning instead assembles and amplifies linear DNA in vitro, then uses TelN protelomerase to generate exonuclease-resistant, covalently closed molecules that package directly into lentivirus. (Shoutout to Touchlight who pioneered this chemistry.)

In traditional cloning, you construct plasmids in vitro and then transform them into bacteria to amplify. That transformation step is where complexity dies, as anyone who has failed to clone a library has experienced firsthand.

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The first and likely most broadly useful advance is CAP cloning (Covalently closed Assembly Products), a new approach for cloning ultracomplex lentiviral libraries by avoiding bacterial transformation.

Two bottlenecks limit scaling. First, even constructing very large perturbation libraries is hard. Second, most screens read out only a single molecule per cell—the sgRNA—which is an inefficient use of cells. We address both with new technologies.

Genome-wide pooled CRISPR screens have been transformative tools. But many important problems lie beyond genome scale: mapping genetic interactions, interpreting variants, and perturbing regulatory elements all require far more perturbations than current methods support.

Tommy Vierbuchen @tvierbuchen.bsky.social · 27/08/2025

New preprint on technologies to scale up CRISPR screens. We use them to map 665,856 pairwise genetic perturbations and outline a path to comprehensive interaction mapping in human cells. We also introduce an approach for cloning lentiviral libraries with billions of elements.

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Reposted by Thomas Norman

A mouse organoid platform for modeling cerebral cortex development and cis-regulatory evolution in vitro: Developmental Cell www.cell.com/developmenta...

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There’s more to come in this space, but I am thrilled to see this work finally published. Huge thanks to first authors Kaden Southard and Rico Ardy, and co-authors Anran Tang, Deirdre O'Sullivan, Eli Metzner, and Karthik Guruvayurappan.

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We posit that this state antagonism can potentially be exploited therapeutically to ablate the disease-associated inflammatory state. More broadly, as perturbation atlases grow there may be an opportunity to map a regulatory graph of states defined by antagonistic interactions.

Inflammatory fibroblasts secrete collagen. This enabled a striking experiment visualizing “state antagonism.” The pro-inflammatory TF EGR3 increases collagen expression, while the pro-universal TF KLF4 decreases it. When both are activated together, the effects cancel out.

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Takehome 4: There is a regulatory logic underlying transcriptional states. We noticed that TFs that promoted the universal fibroblast state often appeared to be repressors of the inflammatory state. What then happens if we try to drive cells into both states at the same time?

These comparisons let us identify TFs driving four fibroblast states described in the literature: universal, inflammatory, myofibroblast, and antigen presentation. Our in vitro signatures flag these subpopulations across four independent fibroblast atlases in a new main figure.

During revision, several new fibroblast cell atlases were released, allowing us to compare our perturbation results to fibroblasts observed in diverse tissues and disease contexts.

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Takehome 3: Cell atlases make single-cell functional genomics data interpretable. Our goal in doing all these perturbations was to see if we could push primary fibroblasts into the transcriptional states they exhibit in vivo, some of which are linked to function or disease.

A second challenge we encountered was surprisingly strong off-target effects from dCas9 binding at 3-5 nt sequences matching the protospacer seed region, which we could observe directly via CUT&RUN. This is a critical consideration for studies of enhancers and high MOI designs.

I do think there is an excellent opportunity here for a community or consortium effort to scale this approach genome-wide and systematically define active guides. These inactive reagents are a pernicious and widespread challenge in functional genomics.

We overcame this issue through the elegant strategy of applying brute force. Since Perturb-seq can now be scaled to measure >10,000 perturbations, we simply tested six guides each for 1,836 human TFs. We report active guides for 1319 of them.

Takehome 2: CRISPRa has some practical challenges. Here I must include what may be the most popular part of the preprint, now known as Extended Data Fig. 1C. It shows the high failure rate of CRISPRa guides targeting a model target locus, CD45.

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A second advantage, which partly motivated this work, is that CRISPRa makes it easy to multiplex perturbations by expressing multiple guides simultaneously. This is important for TFs as combinatorial regulation is a major area of interest for us and others.

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Takehome 1: CRISPRa is a great tool for perturbing transcription factors (TFs). We observe that it usually leads to physiological expression levels, which is a key advantage over ORF overexpression for some use cases.

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A tweetorial describing our preprint is linked at thenormanlab.com, so I’ll focus here on key improvements (as the paper got quite a lot better in review) and some lingering thoughts.

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