dHyperCas12a enables multiplexed CRISPRi screens

Domain: neuroscience
Published: 2026-02-12
Editorial outcome: major_revision

Abstract
Interactions between genes or cis-regulatory elements (CREs) underlie many biological processes. High-throughput CRISPR screens have allowed researchers to assess the impact of activation or repression of gene and regulatory elements on many phenotypes. However, assessment of interactions between those genes or elements remains limited. To enable efficient highly-multiplexed control of regulatory element activity, we combine a hyper-efficient version of Lachnospiraceae bacterium dCas12a (dHyperLbCas12a) with RNA Polymerase II expression of long CRISPR RNA (crRNA) arrays. We demonstrate this system with several activation and repression domains, in cultured primary immune cells, and to differentiate induced pluripotent stem cells. We also develop approaches to use dCas12a for simultaneous activation and repression. Lastly, we demonstrate that dHyperLbCas12a effectors can be used to dissect the independent and combinatorial contributions of CREs to gene expression. These tools create possibilities for highly multiplexed control of gene expression in many biological systems.

Introduction
Many biological systems depend on coordinated activity between genetic elements. In mammalian systems, it is common that several cis-regulatory elements (CREs) control the expression of the same gene both at steady state and in response to environmental conditions1–10. Recent work to experimentally test and validate thousands of CRE-gene pairs found between two and three CREs per gene, while predictive modeling of million of CRE-promoter interactions estimates about four CREs per gene11,12. It is also common that coordinated expression of several genes controls aspects of cell differentiation and disease13–28.

One way to evaluate the function of combinations of gene regulatory elements is to perturb their function in vitro or in vivo. Several technologies for genetic or epigenetic perturbation of regulatory elements have been developed based on bacterial clustered regularly interspaced short palindromic repeats (CRISPR) systems. Briefly, bacterial CRISPR systems typically use short CRISPR RNAs (crRNAs) to target a Cas nuclease to specific complementary ~20bp DNA sequences29–33. Those systems have been adapted for gene activation and repression by fusing an epigenome-modifying domain to nuclease-inactivated dead dCas proteins34,35. Moreover, by delivering multiple crRNAs at once, it is possible to study interactions between CREs. For example, dCas9-based studies of pairwise epigenetic perturbations have revealed combinations of transcription factors that enhance neuronal differentiation13; long-distance synergistic interactions between enhancers controlling MYC expression2; synthetic lethality in the human genome27; and hierarchies in CRE interactions19.

Scaling beyond pairwise or three-way combinations of sgRNAs is challenging, however, for several reasons. Cas9 requires an RNA molecule known as a trans-activating crRNA (tracrRNA) to bind the crRNA. To simplify studies using Cas9, the tracrRNA and crRNA are commonly expressed as a single ~100bp molecule known as a single guide RNA or sgRNA30,31. However, repetitive sequences in multiple sgRNA plasmids, including the tracrRNA, can also lead to extensive plasmid recombination36–39. Creating further design constraints, each sgRNA must either be expressed from its own promoter, or expressed as part of a longer sgRNA array that is cleaved via separately expressed enzymes40. Together, those complexities severely limit highly multiplexed Cas9 genome- or epigenome-editing screens.

In contrast, several features of the Cas12a nuclease make it ideally suited for highly multiplexed manipulation of gene regulatory elements. Like Cas9, deoxyribonuclease-inactivated dCas12a can be fused with epigenetic effectors to activate or repress gene expression25,41–44. Unlike Cas9, however, a ~40bp crRNA is sufficient to target Cas12a or dCas12a to sites in the human genome32,33. Cas12a also has an endoribonuclease activity that allows it to cleave individual crRNAs from a single pre-crRNA molecule containing a tandem array of many crRNAs32. Using those features, previous studies have targeted 25 genomic sites at once via a single pre-crRNA44. Several studies have also used that multiplexing capability in high-throughput genome-editing screens to identify synthetic lethal combinations of human genes; and in an epigenome-editing screen to identify combinations of gene regulatory elements contributing to cell fitness10,21,23–25,45.

Here, we introduce a suite of dCas12a epigenome editors for effective, highly multiplexed gene activation and repression; and demonstrate that those effectors, together with additional advances, enable multiplexed high-throughput screens of combinatorial regulatory element activity and cell fitness. To do so, we systematically compare epigenome editing activity across a wide range of dCas12a epigenome effectors. We identify dCas12a effectors sensitive enough to alter regulatory element activity when integrated into the genome by lentiviral transduction and show that these effectors can be used to modulate gene expression in cultured primary cells. We also demonstrate expression of complex pre-crRNA arrays that include selectable markers and up to 14 crRNAs from an RNA polymerase II promoter. Further, by combining crRNAs for different dCas12a proteins in a single pre-crRNA array, we can simultaneously activate and repress gene expression. We further show that dCas12a repressors can be successfully used in low MOI fitness screens. Together, those advances enable highly multiplexed high-throughput epigenome editing screens, which we demonstrate by dissecting the cis-regulatory architecture for a dose-dependent gene expression response to glucocorticoids.

Results
dHyperLbCas12a and dEnAsCas12a outperform other dCas12a variants for epigenome editing
To optimize the dCas12a epigenome editing system for high-throughput screening, we first evaluated which Cas12a variants are most effective for epigenome editing. In addition to the wild-type Cas12a from Acidaminococcus sp. BV3L6 (As) and Lachnospiraceae bacterium (Lb), several engineered Cas12a versions with improved activity have been recently published46–48. However, not all these variants have been used for epigenome editing, nor has their activation and repression strength been compared head-to-head in a single study. We systematically compared the strength of gene activation and gene repression across five dCas12a variants: the wild type, enhanced, and ultra versions of dAsCas12a; and the wild type and hyper versions of dLbCas12a. For activation, we fused each dCas12a variant to the tripartite synthetic activator VPR (VP64-p65-Rta), while for repression, we fused each dCas12a variant to a Krüppel-associated box (KRAB) domain from Kox1. We cloned each of the resulting dCas12a effector proteins into the same plasmid backbone, where they are expressed co-transcriptionally with a green fluorescent protein (EGFP). We then evaluated the effects on gene expression by co-transfecting each dCas12a effector into HEK293T cells along with a pre-crRNA array encoding three crRNAs targeting a gene of interest, or three non-targeting control crRNAs. Because Lb and AsCas12a have the same PAM sequence (TTTV), we used the same crRNA target sequences throughout, enabling well-controlled comparisons between As and Lb-derived Cas12a proteins. We then assessed the impact of each Cas12a variant on target gene expression 48 hours later using RT-qPCR (Fig. 1a, b).

The dHyperLbCas12a had the strongest effects for both activation and repression, though dEnAsCas12a showed consistently strong activity as well. dEnAsCas12a has the additional benefit of recognizing several non-canonical PAM sequences, with an estimated sevenfold increase in target sites in the human genome over wild-type Lb and AsCas12a46. Our results also replicated previous studies showing that wild-type AsCas12a has lower epigenome-editing activity than wild-type LbCas12a, but that the engineered dAsCas12a variants have comparable activity41,46. Due to claims that dHyperLbCas12a most strongly outperforms other dCas12a variants under low crRNA conditions48, we also tested the activators in a low crRNA condition where we transfected 1/10th the amount of pre-crRNA array as in Fig. 1b. Under those conditions, dHyperLbCas12a had the strongest gene activation as well (Supplementary Fig. 1a). The dCas12a constructs we evaluated all have a C-terminal nuclear localization signal (NLS). We also evaluated adding an additional NLS to the N-terminus of the dCas12a protein, but found no increase in gene expression (Supplementary Fig. 1b). Taken together, we focused on developing multiplexed high-throughput screening using dHyperLbCas12a due to its high overall activity, and dEnAsCas12a due to its expanded targeting range.

Improved dCas12a pre-crRNA expression for long arrays via an RNA Pol II promoter
Next, we focused on optimizing the Cas12a array expression system. In bacteria, RNA polymerase expresses Cas12a pre-crRNA arrays without a 5’ cap or poly-A tail, and synthetic mammalian systems recreate that structure using RNA Pol III. Expression with RNA Pol III limits the length of the pre-crRNA array, however. For example, a recent study showed that U6-driven pre-crRNA array expression drops off after ~4 crRNAs23. Because our goal is to enable highly multiplexed screening involving arrays of >4 crRNAs, we expected that driving array expression with RNA Pol III would be insufficient, and we would need to use a different expression system.

We hypothesized that an RNA pol II promoter would effectively drive longer arrays due to the higher processivity of RNA pol II compared to RNA pol III. To test this, we created pre-crRNA arrays containing ten crRNAs wherein we placed three crRNAs targeting the HBE1 promoter either at the front or back of the array. We then expressed the pre-crRNA arrays via the RNA pol III promoter U6 or the RNA pol II promoter CAG, which was chosen due to its consistently high transcription across many cell types and DNA delivery mechanisms49 (Fig. 1c). We then co-transfected the pre-crRNA arrays along with plasmids expressing variants of dCas12a-VPR or dCas12a-P300 (described below) into HEK293T cells. As negative controls, we used pre-crRNA arrays containing ten non-targeting crRNAs (Fig. 1d, e). When we used the U6 promoter to express the pre-crRNA arrays, all dCas12a variants robustly activated HBE1 expression when HBE1-targeting crRNAs were at the front of the array, but there was little or no HBE1 activation for three of the four dCas12a epigenome activators when we moved the HBE1-targeting crRNAs to the back of the array. Expressing the same pre-crRNA arrays using the CAG promoter rescued HBE1 activation from the back of the pre-crRNA array for all dCas12a variants tested. There was also no substantial difference in HBE1 activation from the front or back of the pre-crRNA array. Together, those results indicate that RNA Pol II improves the expression of long pre-crRNA arrays.

dCas12a-SID fusions enable multiplexed gene repression
To date, dCas12a-based repression studies have largely used the KRAB repressor domain10,42,44,48. Though KRAB is a potent repressor of transcription, there are potential advantages for repressing via other effector domains. First, KRAB is a potent repressor that recruits KAP1 and induces heterochromatin50. In some cases, more subtle repression may be more relevant to model disease. Second, there are also reports that heterochromatin formation can spread over long distances in some cases, causing potential off-target effects. For example, targeting KRAB to an enhancer element can repress multiple enhancers or gene promoters nearby in some cases51, but not always52,53. Third, there are cases when dCas12a-KRAB fusions have little to no effect on gene expression, and alternative effectors may be able to repress those genes10,44,54.

To develop additional dCas12a-based repressors, we created and tested dCas12a fusions to four copies of the Sin3A interacting domain (SID) derived from Mad1. The SID domain mediates gene repression through recruitment of Sin3A and the histone deacetylases HDAC1 and HDAC255. Previous studies have also shown that SID fusion proteins can repress enhancers and promoters4,56, and we sought here to extend those findings to dCas12a fusions.

We first compared fusions of KRAB, 3xKRAB, 4xSID, and both 3xKRAB and 4xSID to dLbCas12a or dEnAsCas12a. We co-transfected plasmids encoding those fusion proteins and a pre-crRNA array containing three crRNAs targeting the VEGFA or RAB5A (one spacer sequence originally reported in ref. 44) promoter into HEK293T cells. We then evaluated changes in VEGFA and RAB5A expression relative to cells expressing the same fusion protein but a control pre-crRNA array targeting an unrelated gene (Supplementary Fig. 2a, b). The C-terminal fusions of KRAB and 4xSID had the strongest overall repressive effect for both dLbCas12a and dEnAsCas12a, demonstrating that the dCas12a-4xSID fusions can repress gene expression.

We further evaluated dCas12a-4xSID repression using multiple crRNAs targeted to the promoter of individual genes. We cloned dEnAsCas12a and dHyperLbCas12a repressor fusions into a plasmid backbone with a stronger promoter and a strong NLS48 (Fig. 2a). We then tested the efficacy of these repressors in HEK293T cells using a pre-crRNA array containing three crRNAs targeting VEGFA or RAB11A (Fig. 2b). All repressors tested were able to induce significant and robust gene repression, with dHyperLbCas12a repressor fusions achieving >50% repression for both gene targets (p<0.005, FDR-adjusted Student’s T-test) (Figs. 2c, d and 1).

Next, we tested multiplexed repression by targeting several genes simultaneously. To do so, we co-transfected the dCas12a-based repressors with a pre-crRNA array targeting four different genes into HEK293T cells (Fig. 2e). All repressors significantly repressed all four target genes (p<0.05 for EnAs repressors, p<0.005 for HyperLb repressors, FDR-adjusted Student’s T-test), including PIK3C3 which is only targeted by a single crRNA. The dCas12a-4xSID fusions were as effective as dCas12a-KRAB fusions at repressing gene expression (Fig. 2f, g). Taken together, these data demonstrate that dCas12a-SID repressors are highly effective and can serve as an alternative to dCas12a-KRAB.

Lentiviral delivery of dHyperCas12a-KRAB enables strong gene repression
High-throughput, multiplexed screens require stably expressed dCas12a fusions, typically achieved via lentiviral delivery. A challenge is that previous studies have found that expression of dCas12a-KRAB fusions from low copy number integrated lentiviral vectors can result in low activity10. We hypothesized that dHyperLbCas12a effectors, which have the strongest activity under low crRNA expression (Supplementary Fig. 1a), can overcome that limitation.

To test that hypothesis, we created a HepG2 hepatocellular carcinoma cell line that stably expressed dHyperLbCas12a-KRAB. We then lentivirally transduced a construct expressing a pre-crRNA array containing four crRNAs targeting the promoter of hexokinase domain containing 1 (HKDC1), a gene involved in maternal glucose homeostasis57–59. In doing so, we repressed HKDC1 expression by 85%. That amount of repression was comparable to the ~75% reduction in HKDC1 transcript we observed in HKDC1 knockout cell lines (Supplementary Fig. 2c). From those results, we conclude that lentiviral delivery of dHyperLbCas12a-KRAB is highly effective at repressing the expression of individual genes.

We further generalized that outcome to multiplexed repression in two additional cell types. First, we created A549 lung adenocarcinoma cell lines that stably expressed dHyperLbCas12a-KRAB or dHyperLbCas12a-4xSID. We then transduced the cell lines with a construct expressing a pre-crRNA array with crRNAs targeting the promoters of MYC, PIK3C3 (crRNA spacer sequence originally reported in ref. 44), RAB11A, and VEGFA. In that system, dHyperLbCas12a-KRAB significantly repressed all four target genes, while dHyperLbCas12a-4xSID repressed two (p≤0.05, FDR-adjusted Student’s T-test). For dHyperLbCas12a-KRAB, repression ranged from only ~10% repression for MYC to 55–60% repression for VEGFA and RAB11A. Meanwhile, dHyperLbCas12a-4xSID was unable to repress MYC or VEGFA but achieved ~15% repression of PIK3C3 and 35% repression of RAB11A (Supplementary Fig. 2d). Because MYC and PIK3C3 are both essential genes in A549 cells, it is possible that the weaker repression of those target genes resulted from effects on cell fitness60. In support of that possibility, we used flow cytometry to sort A549 repressor cell lines transfected with the multiplexed pre-crRNA array plasmid and found that dCas12a repressor expression was several-fold lower in array-expressing cells than in a bulk transfected population (Supplementary Fig. 2e).

Next, we co-transduced human T cells from three independent donors with dHyperLbCas12a-KRAB or dEnAsCas12a-KRAB and either a pre-crRNA array targeting the promoters of SLA2, GATA3, MAP4K1, GRAP, and LAT2 or a control pre-crRNA array containing ten non-targeting crRNAs (Fig. 2h). We observe similar trends for both Cas12a orthologues. For example, both dEnAsCas12a- and dHyperLbCas12a-KRAB showed the strongest repression of GRAP and LAT2, though dHyperLbCas12a showed stronger repression (mean log2 fold change across donors of −0.89 and −0.87 vs. −0.47 and −0.42) consistent with our previous findings (Fig. 2i, j). While we do not observe effects for all target genes in this cell type, these results indicate the potential of using dCas12a for multiplexed repression in primary cells.

Taken together, these results demonstrate that dHyperLbCas12a repressors are suitable for use in multiplexed, high-throughput studies. Also, as a step towards low multiplicity of infection screens, we demonstrate repression when pre-crRNA array constructs are transduced and expressed from the genome at a copy number that is much lower than with transient transfection.

dCas12a-P300 fusions activate gene expression from promoters and enhancers
Gene activation using dCas12a has most frequently been shown using fusions to the VPR activation domain41,42,46,48. While VPR is a potent activator of transcription, it has mostly been used to target gene promoters, not enhancer elements, and has been shown to be toxic in certain contexts25,61–63. Fusions of dCas9 to the histone acetyltransferase domain from P300 have been shown to be highly effective for targeting the non-coding genome61,64. This presents a hypothesis that distal regulatory elements may be more effectively controlled via P300 than VPR fusions. dLbCas12a, but not dAsCas12a, has been shown to activate gene expression from both enhancers and promoters using single crRNAs when fused to P30043. We also tested activation using dAsCas12a-P300 and dLbCas12a-P300 fusions at two genomic loci using single crRNAs (Supplementary Fig. 3a, b). We found that dLbCas12a-P300 activated both target genes, while dAsCas12a-P300 activated one of the genes, consistent with previous reports that LbCas12a is a stronger epigenome editor than AsCas12a, and our dCas12-VPR and KRAB comparisons (Fig. 1a, b)41. From this, we conclude that the dLbCas12a-P300 fusions more strongly and more robustly activate gene expression than dAsCas12a-P300 fusions.

Above, we show that fusing KRAB and VPR to other variants of dCas12a can enhance repression or activation. Based on that result, we hypothesize that dEnAsCas12a-P300 and dHyperLbCas12a-P300 will also be able to activate gene expression when targeted to gene promoters and regulatory elements. Specifically, we created dEnAsCas12a-P300 and dHyperLbCas12a-P300 fusions in a plasmid containing a strong promoter and an NLS48 (Fig. 3a). We then created pre-crRNA arrays of three crRNAs targeting each of the HBE1 promoter, the MYOD1 promoter, or a MYOD1 enhancer ~5 kb upstream of the MYOD1 promoter64,65. We co-transfected plasmids expressing the dCas12a activators with plasmids expressing the pre-crRNA arrays into HEK293T cells. (Fig. 3b). All four fusion proteins modestly but significantly increased target gene expression (p<0.005, FDR-adjusted Student’s T-test). dEnAsCas12a-P300 activation strength ranged from 1.2- to 18.2-fold, while dHyperLbCas12a activation strength ranged from 2.6- to 16.7-fold over non-targeting control. Contrary to our expectations, dCas12a-VPR led to stronger MYOD1 activation from the distal enhancer than dCas12a-P300 for both orthologues (Fig. 3c, d).

We also evaluated whether all three crRNAs were needed, and whether there were additive or epistatic interactions between the crRNAs as reported previously41,42,66,67. We created pre-crRNA arrays that used three crRNAs to target either the HBE1 or MYOD1 promoter in all one-, two-, and three-way combinations of those crRNAs. We then co-transfected the pre-crRNA array plasmids into HEK293T cells along with a dCas12a activator and assessed gene activation (Supplementary Fig. 3c–f). Generally, for dCas12a-VPR fusion proteins, multiple crRNAs increased activation strength. At both loci tested, the strongest pre-crRNA array contained more than one crRNA, and combinations of three crRNAs were at least as strong as the best single crRNA. In contrast, for P300, we frequently observed reduced activation when we delivered multiple crRNAs, including examples where the combinations of crRNAs had weaker effects than the best single crRNA. Previous studies have also shown mixed effects from using multiple Cas9 gRNAs or Cas12a crRNAs, suggesting potential steric hindrance between the P300 fusions43,66.

Both dCas12a-VPR and dCas12a-P300 fusions can drive multiplexed gene activation in human cell lines
We next evaluated whether dCas12a activators are also capable of highly multiplexed gene activation. We first evaluated activity using transient delivery that typically achieves a high copy number of plasmids in each cell. To do so, we co-transfected dCas12a activators with a plasmid expressing a pre-crRNA array of ten crRNAs from an RNA Pol II promoter into HEK293T cells. The crRNAs consisted of one crRNA targeting the AR promoter (originally reported in ref. 46), three crRNAs targeting the HBE1 promoter, and six crRNAs targeting either the promoter or a distal regulatory region of MYOD1 (Fig. 4a). In all but one case, the dCas12a fusions significantly increased expression of all three target genes (p<0.01, FDR-adjusted Student’s T-test, dHyperLbCas12a-VPR activation of AR was not significant) (Fig. 4b, c). The range of activation varied among genes and between activators. For example, activation of HBE1 was stronger with VPR fusions (up to ~3200-fold) than with P300 fusions (up to five fold); whereas activation of MYOD1 was consistently ~16-fold for both P300 and VPR. Meanwhile, activation of AR was weaker overall (1.2–2.0-fold). That range of AR activation was the same order of magnitude as observed in previous studies41.

Many study designs require lentiviral delivery or integration of DNA expression cassettes. Those delivery approaches result in fewer effective molecules per cell and thus require more potent effector proteins. We therefore evaluated whether the dCas12a system could drive robust, multiplexed gene activation when delivered via lentivirus. We generated A549 lung adenocarcinoma cell lines that stably expressed dHyperLbCas12a-P300 or dHyperLbCas12a-VPR. We then transfected those cell lines with the same pre-crRNA array targeting AR, MYOD1, and HBE1 and found comparable effects on gene expression (Fig. 4d). Both MYOD1 and HBE1 were significantly upregulated (p<0.005, FDR-adjusted Student’s T-test), with effects ranging from 6-fold to ~2500-fold; whereas there was no significant effect on AR expression.

To evaluate generality to other cell models, we also evaluated multiplexed activation in a HepG2 liver cancer cell line stably expressing dHyperLbCas12a-P300. In that model, MYOD1 and HBE1 were also significantly upregulated (p<0.001, FDR-adjusted Student’s T-test) with effects ranging from ~100–600-fold. In that HepG2 model, the effect on MYOD1 was stronger than the effect on HBE1 (Supplementary Fig. 4a).

To generalize to additional gene loci, we also created two unique pre-crRNA arrays that each contain two crRNAs targeted to the promoter of HKDC1. We find that dHyperLbCas12a-P300 is able to significantly upregulate HKDC1 expression using either array (p<0.001, FDR-adjusted Student’s T-test) with similar effect size of ~3–4-fold upregulation (Supplementary Fig. 4b). This result underscores the robustness of stably expressed dHyperLbCas12a-P300 since, unlike HBE1 and MYOD1, HKDC1 has moderate basal expression in these cells (nTPM=17.1), making it harder to detect increases in expression.

dHyperLbCas12a-VPR fusions enable multiplexed gene activation in cultured primary human cells
Model systems for studying primary cell differentiation commonly involve controlling the expression of several genes at once16,68. As a key step towards such highly multiplexed control of gene regulation in primary cells, we focused on demonstrating dCas12a-based gene activation in T cells and in a human induced pluripotent stem cell (iPSC)-based model of neuronal differentiation.

To demonstrate multiplexed control of gene expression in T cells, we co-transduced dHyperLbCas12a-VPR along with the pre-crRNA array targeting AR, HBE1, and MYOD1 into primary human CD3+ T cells from three different donors. The results were similar to those observed in cell lines, namely that there was significant activation (p<0.05, One-Sided Student’s Paired T-Test) of HBE1 and MYOD1, with effects ranging from ~45-350-fold upregulation (Fig. 4e). Also as in the cell lines, there was little or no activation of AR gene expression.

To demonstrate multiplexed control of gene expression in iPSC cell differentiation, we used an iPSC cell line that had previously been modified to express mCherry co-translationally with β3-tubulin, a marker of neuronal differentiation13. We further modified the line to stably express dHyperLbCas12a-VPR. We designed a pre-crRNA array of three crRNAs to target the promoter of NGN3, a strong driver of neuronal differentiation, to act as a positive control. We also designed a pre-crRNA array containing seven crRNAs that target three core neurogenic transcription factors (deemed Core): NGN1, NGN2, and NGN3. We designed a pre-crRNA array containing seven crRNAs that target four accessory genes that have been shown to enhance neuronal differentiation when co-activated in tandem with a core factor (deemed Accessory): LHX6, LHX8, SOX2, and E2F713. Lastly, we designed a pre-crRNA array containing all 14 crRNAs and targeting both core and accessory factors together (deemed Core+Accessory) (Fig. 4f).

We transduced the dHyperLbCas12a-VPR cell line with these pre-crRNA arrays and then measured the percentage of cells that were mCherry positive when gating such that ~1% of cells transduced with a pre-crRNA array containing non-targeting control crRNAs are mCherry positive (Fig. 4g and Supplementary Fig. 5). We find that ~4% of cells that received the NGN3 targeting array are mCherry positive, while ~1.25% of cells that received the core pre-crRNA array and ~3.5% of cells that received the Core+Accessory pre-crRNA array are mCherry positive. As expected, activation of the accessory factors alone did not lead to an increase in mCherry positive cells over control (Fig. 4h). While we did not observe higher rates of mCherry positive cells in the Core or Core+Accessory conditions vs. the NGN3-targeting array, we do observe an (~3x) increase in mCherry positive cells between Core and Core+Accessory conditions, suggesting increased differentiation efficiency due to multiplexed activation. Furthermore, we observe increased (~2x) MFI of the mCherry positive population in the Core+Accessory condition vs. both the NGN3 and Core conditions, suggesting higher TUBB3 expression in these cells (Fig. 4i). The ability of dHyperLbCas12a-VPR to activate TUBB3, a marker for early stages of neuronal differentiation, indicates that the system may be deployed in future neuronal cell differentiation studies where manipulating the expression of many genes at once is needed.

Together, these results demonstrate that dCas12a activators are capable of multiplexed activation of gene expression in multiple primary cell systems in which dCas12a effectors have been integrated and remain stably expressed.

Multiplexed activation and repression within a single cell using dCas12a effectors
The use of epigenome editors from two different Cas12a orthologues created an opportunity for simultaneous gene activation and repression within a single cell. Since Cas12a will process crRNAs from a transcript containing other elements, and each Cas12a orthologue specifically recognizes its own direct repeat sequence, we hypothesized that a hybrid array containing both As and LbCas12a crRNAs could enable programmed activation and repression from a single array. To test that possibility, we created a hybrid pre-crRNA array containing four AsCas12a crRNAs targeting the HBE1 or MYOD1 promoters and four LbCas12a crRNAs targeting the RAB11A or MYC promoters, separated by a non-targeting crRNA (Fig. 5a). We validated the hybrid pre-crRNA array with single dCas12a effectors by co-transfecting with either dHyperLbCas12a-KRAB or dEnAsCas12-VPR into HEK293T cells. Doing so increased expression of HBE1 and MYOD1 with dEnAsCas12-VPR, and decreased expression of MYC and RAB11A with dHyperLbCas12a-KRAB (Supplementary Fig. 6a, b).

We then evaluated simultaneous activation and repression by co-transfecting a dEnAsCas12 activator, a dHyperLbCas12a repressor, and hybrid pre-crRNA arrays into HEK293T cells. We evaluated two combinations of activators and repressors: dEnAsCas12a-VPR for activation with dHyperLbCas12a-KRAB for repression; and dEnAsCas12a-P300 for activation with dHyperLbCas12a-4xSID for repression. For both pairs of effectors, we observed significant and simultaneous activation and repression of all the target genes (Fig. 5b, c, p<0.05, FDR-adjusted two-sided Student’s T-test). From this, we demonstrate that hybrid pre-crRNA arrays can simultaneously activate and repress gene expression within the same cell.

To generalize this result, we also designed and tested a similar pre-crRNA array containing the same crRNA sequences, but with dHyperLbCas12a activators and dEnAsCas12a repressors. As before, we first tested the ability of single dCas12a effectors to use the pre-crRNA array and found that dHyperLbCas12a-VPR and dEnAsCas12a-KRAB could significantly activate or repress the target genes when co-transfected with the hybrid crRNA (Supplementary Fig. 6c, d). We next co-transfected a dHyperLbCas12a activator and a dEnAsCas12a repressor along with the hybrid pre-crRNA array into HEK293T cells. We found that dHyperLbCas12-VPR was able to significantly activate both target genes (p<0.05, FDR-adjusted Student’s T-test), but dEnAsCas12a-KRAB was unable to repress either target gene (Supplementary Fig. 6e). Meanwhile, the combination of dHyperLbCas12a-P300 and dEnAsCas12a-SID was able to significantly activate HBE1 and MYOD1 expression while significantly repressing RAB11A expression (p<0.01, FDR-adjusted Student’s T-test), but not MYC expression (p=0.172, FDR-adjusted Student’s T-test) (Supplementary Fig. 6f).

Cas12a nucleases can exhibit low activity, as measured by indel formation, using the crRNAs of other Cas12a orthologues69. If this low-level orthologous crosstalk activity is also observed with CRISPRi and CRISPRa, then it could interfere with the hybrid pre-crRNA array system. However, since both Cas12a orthologues are co-transfected in our system, we wanted to test not just whether each dCas12a can use the orthologous crRNA, but also whether it can use the orthologous crRNA when competing with its homologous dCas12a.

To evaluate crosstalk in such a setting, we co-transfected dHyperLbCas12a-VPR with the hybrid pre-crRNA array containing AsCas12a crRNAs for activation, as well as either dEnAsCas12a or Cas9 as a transfection control for the number and size of plasmids. We found that, by itself, dHyperLbCas12a-VPR can use AsCas12a crRNAs but with less efficacy than homologous LbCas12a crRNAs. Specifically, when dHyperLbCas12a-VPR was co-transfected with Cas9, there was 150-fold activation of HBE1 and no significant activation of MYOD1 (Supplementary Fig. 6g). The observed activation of HBE1 was ~30-fold less than when dHyperLbCas12a-VPR was co-transfected with its homologous hybrid pre-crRNA array (Supplementary Fig. 6a).

However, that crosstalk is alleviated when dHyperLbCas12a and dEnAsCas12a are both present and competing for crRNAs. Specifically, when dHyperLbCas12a-VPR was co-transfected with dEnAsCas12a, we observed no significant activation of either gene, and relative HBE1 expression dropped to a 1.25-fold change over non-targeting control (Supplementary Fig. 6g).

That result was essentially similar when we tested dEnAsCas12a-VPR in the same way. Specifically, dEnAsCas12a-VPR was able to significantly activate HBE1 by ~6.5 fold using LbCas12a crRNAs when co-transfected with Cas9. However, there was no effect when dEnAsCas12a-VPR was co-transfected with dHyperLbCas12a (Supplementary Fig. 6h). Together, these results confirm that while dEnAsCas12a and dHyperLbCas12a can use orthologous crRNAs for activation, they are not able to do so when the homologous dCas12a is also present and competing for crRNAs, such as in the hybrid pre-crRNA array system developed here.

Large-scale comparison of dCas12a repressors in a low MOI fitness screen
To enable large-scale comparison of the dCas12a repressors described above and to assess their suitability for use in screening applications, we performed a screen of genes that are predicted to impact cell proliferation. We created a library containing 171 arrays targeting the promoters of 145 core essential genes70, 48 pre-crRNA arrays targeting the promoters of 20 cell surface control genes45, 50 non-targeting pre-crRNA arrays, and 25 intergenic control pre-crRNA arrays. Each pre-crRNA array contained four crRNAs, and we required that all gene targets have at least four crRNAs with a CRISPick on-target efficiency score of ≥ 30%. We created an As and LbCas12a version of this library using the same spacer sequences but As- or Lb-specific direct repeats.

Next, we transduced the appropriate library at an MOI of 0.2 into A549 cells stably expressing either dHyperLbCas12a-KRAB, dHyperLbCas12a-4xSID, dEnAsCas12a-KRAB, or dEnAsCas12a-4xSID, with three replicates per cell line. Cells were selected for crRNA array expression using puromycin, and cell pellets were collected to assess relative pre-crRNA array abundance at 5-, 7-, 14-, and 21-days post-transduction (Fig. 6a).

There was strong concordance in read counts between replicates for all dCas12a repressor screens. Specifically, correlation between replicates at day 21 was R>0.91 for the KRAB repressor screens and R>0.79 for the SID repressor screens (Supplementary Figs. 7 and 8).

The strongest and most consistent repressive effects occurred in the dHyperLbCas12a-KRAB screen. That screen had a much higher correlation between replicates for log2 fold changes of pre-crRNA arrays targeting essential genes (R>0.8) compared to all the other repressors (−0.081<R<0.276). That screen also had greater effects compared to the other repressors (Fig. 6b–e and Supplementary Fig. 9). Representative examples for each system show genes that were significantly repressed by both dHyperLbCas12a repressors and dEnAsCas12-KRAB; by both dHyperLbCas12a repressors but not the dEnAsCas12a repressors; and by dHyperLbCas12a-KRAB alone (Fig. 6h–j).

Overall, we conclude that KRAB is a stronger repressor than 4xSID for targeting gene promoters, and that dHyperLbCas12a-KRAB is suitable for use in low MOI screens, while dEnAsCas12a is not. We based that conclusion on comparing effects across the four screens. Using a linear model of change in log2 fold change over time and a threshold of FDR<0.001, we detected 28 significantly depleted pre-crRNAs targeting essential genes in the dHyperLbCas12a-KRAB condition, five in the dHyperLbCas12a-4xSID condition, two in the dEnAsCas12a-KRAB condition, and zero in the dEnAsCas12a-4xSID condition using DESeq2. We obtained similar results at the gene level when performing a time course analysis with the MAGeCK MLE module and Wald FDR<0.05; 31 genes were significantly depleted in the dHyperLbCas12a-KRAB condition, five in the dHyperLbCas12a-4xSID condition, one in the dEnAsCas12a-KRAB condition, and zero in the dEnAsCas12a-4xSID condition (Supplementary Data 1). Comparing these hits to DepMap gene essentiality data for A549 cells, we find that the dHyperLbCas12a-KRAB hits are strongly enriched in highly essential genes (gene effect≤-1)71 (Supplementary Fig. 10). Furthermore, we note that the effects of dHyperLbCas12a-4xSID were stronger than those of either dEnAsCas12a repressor and were most closely correlated with dHyperLbCas12a-KRAB (R=0.68 vs. R=0.38 for dEnAsCas12a-KRAB and R=0.13 for dEnAsCas12a-4xSID), even if they did not achieve significance.

High-throughput multiplexed epigenome editing screens via dHyperLbCas12a-KRAB
The above findings create the foundation for high-throughput combinatorial epigenome editing screens with the dCas12a platform. To demonstrate that possibility, we performed a combinatorial screen of two enhancers that previously were hypothesized to control activation of the Period 1 (PER1) gene expression in response to glucocorticoids. Glucocorticoids are steroid hormones that have a major role in peripheral circadian rhythms throughout the body72. PER1 is a key gene in that regulation, where it plays an especially important role in peripheral circadian rhythms73. PER1 expression oscillates throughout the day in conjunction with oscillating cortisol levels, raising questions about the role of cortisol in controlling its expression throughout the body74. Importantly, cortisol levels in peripheral tissues are much lower than in circulating blood, and sensitivity to very low cortisol concentrations may be especially important for PER1 expression75. For example, in A549 cells, PER1 stands out because its expression is uniquely sensitive to very low concentrations of glucocorticoids8. The mechanism by which such low concentrations of glucocorticoids activate PER1 expression remains unresolved. Based on ChIP-seq and reporter assays studies, there are two promoter-proximal glucocorticoid-responsive regulatory elements, denoted here as Enhancer A and Enhancer B, that may cause glucocorticoid-dependent PER1 activation. Furthermore, Enhancer A can control reporter gene expression at very low glucocorticoid concentrations, suggesting it may be responsible for the PER1 gene expression response at those low concentrations8 (Fig. 7a).

We first definitively established that Enhancer A and Enhancer B together control the PER1 glucocorticoid response. To do so, we transduced A549 cells stably expressing dHyperLbCas12a-KRAB with either a pre-crRNA array targeting both Enhancer A and Enhancer B, or a non-targeting pre-crRNA array. We then selected cells for pre-crRNA expression, and treated them for three hours with either 100nM dexamethasone (Dex) or ethanol as a vehicle control. With non-targeting crRNAs, PER1 expression increased nearly 11-fold with dex treatment; while with crRNAs targeting Enhancer A and Enhancer B, PER1 expression increased by only ~1.3-fold in the dex condition (p=8.8×10−6, Student’s T-Test) (Fig. 7b). Together, these results indicate that Enhancer A and Enhancer B together account for all or nearly all of the PER1 glucocorticoid response.

Enhancer A and Enhancer B were also sensitive to specific chromatin modifications. The PER1 response was not significantly altered when we repeated the experiments in A549 cells expressing dHyperLbCas12a-4xSID instead of dHyperLbCas12a-KRAB (p=0.45, Student’s T-Test). That finding suggests the PER1 glucocorticoid response is differentially sensitive to KAP1-mediated vs Sin3a-mediated repression; and that the dCas12a repressors described here can identify such differential sensitivities. Additionally, activating the enhancers with VPR or P300 in the absence of glucocorticoids did not significantly increase PER1 expression (p=0.48, p=0.20, Student’s T-test) (Supplementary Fig. 11), indicating that glucocorticoid receptor binding and co-factor recruitment may be necessary for PER1 activation via those enhancers.

Next, to dissect the independent and combinatorial contributions of Enhancer A and Enhancer B, we designed a library of pre-crRNA arrays to target dCas12a-KRAB to the enhancers alone or in combination (Fig. 7c). Overall, our design was to deliver pre-crRNA arrays containing six crRNAs, where the first three crRNAs target Enhancer B, and the second three target Enhancer A. To target the enhancers together, we used on-target crRNAs in all six positions. To target Enhancer A or Enhancer B individually, we used non-targeting crRNAs in the first three or the second three positions, respectively. In total, we designed nine on-target crRNAs per enhancer, and assembled DNA sequences for all 84 unique triples thereof (Fig. 7c and Supplementary Fig. 12a). We also designed ten sets of three non-targeting crRNAs to target enhancers individually.

To construct the screening library, we used a nested cloning strategy to simultaneously assemble the pre-crRNA array and a series of 8bp barcodes that encode the contents of the array (Supplementary Fig. 12)76,77. In the first round of cloning, we inserted the crRNAs targeting Enhancer B or non-targeting crRNAs (Supplementary Fig. 12b). In the second round of cloning, we inserted the crRNAs targeting Enhancer A or non-targeting crRNAs (Supplementary Fig. 12c). That resulted in a library of 8836 unique pre-crRNA arrays composed of 7056 pre-crRNA arrays targeting both enhancers, 1680 pre-crRNA arrays targeting the enhancers individually, and 100 pre-crRNA arrays targeting neither enhancer (Fig. 7c, d and Supplementary Fig. 12d). In parallel, we separately constructed a control library of 10,000 non-targeting six-crRNA arrays and three pre-crRNAs targeting the PER1 promoter (Supplementary Fig. 13). Since most (80%) of the PER1-targeting library consists of pre-crRNAs targeting both enhancers, this large control library will enable better separation between cells with high and low PER1 expression. When constructing the targeting and control libraries, we also enabled sorting crRNA-expressing cells by co-transcribing a selectable marker with the pre-crRNA44 (Fig. 7d and Supplementary Fig. 12) and high-throughput sequencing of the barcode by including TruSeq adapter sequences flanking the embedded barcode (Supplementary Fig. 12). We confirmed the library construction via sequencing on an Illumina NextSeq instrument. We recovered all on-target pre-crRNA arrays, and 9890 of the 10,000 negative control pre-crRNA arrays. The missing negative control pre-crRNA arrays were explained by missing or low-abundant crRNAs during DNA synthesis. Aside from those dropouts, the pre-crRNA arrays were evenly represented in the assay library (Fig. 7e, f).

To assay the pre-crRNA libraries, we lentivirally transduced them into A549 cells stably expressing dHyperLbCas12a-KRAB (Fig. 8a). Ten days post-transduction, we treated crRNA-expressing cells with either low (200pM) or high (100nM) concentrations of the synthetic glucocorticoid dexamethasone, or with ethanol to control for solvent effects. After three hours, we collected cells with the highest and lowest 12% PER1 expression78 (Supplementary Fig. 14a and 15). Finally, we estimated the abundance of each array in the sorted cell populations via high-throughput sequencing of the barcodes. We also confirmed that pre-crRNA arrays remained intact and correctly associated with the corresponding barcode throughout the screen, consistent with findings from other Cas12a studies79 (Supplementary Fig. 16 and Supplementary text).

Overall, we found that Enhancer A controls the PER1 response to low glucocorticoid concentrations, and that both Enhancers A and B together control the PER1 response at high glucocorticoid concentrations. Specifically, at 200pM dexamethasone, pre-crRNA arrays targeting Enhancer A were ~2.6-fold enriched in low-PER1-expressing cells, and depleted by 2.9-fold in high-PER1-expressing cells. In contrast, pre-crRNA arrays targeting only Enhancer B were 1.7-fold enriched in low-PER1-expressing cells and depleted by 1.4-fold in high-PER1-expressing cells (Fig. 8c, f). At 100nM dexamethasone, pre-crRNA arrays that target both Enhancer A and Enhancer B were ~5.4-fold enriched in low-PER1-expressing cells and 3.7-fold depleted in high-PER1-expressing cells; and pre-crRNA arrays targeting only Enhancer A or only Enhancer B had intermediate effects (3.9-fold and 3.0-fold enriched, and 2.7- and 2.4-fold depleted, respectively) (Fig. 8d, g). Finally, in the ethanol treatment condition, the on-target pre-crRNA arrays were only weakly depleted from high-PER1-expressing cells (up to 1.4-fold) (Fig. 8b, e). Together, these results reveal glucocorticoid-dose-dependent enhancer activity controlling PER1 expression.

We did not find strong evidence for substantial heterogeneity in the effects of the individual crRNAs. Specifically, we tested if, when targeting enhancer A or B individually, any of the crRNAs consistently increased or decreased the effect of the pre-crRNA array (Supplementary Data 2). In the 100nM Dex high bin, two of the nine crRNAs targeting enhancer A had significant effects, and six of the nine crRNAs targeting enhancer B had a significant effect (FDR <0.05). Of those eight crRNAs with significant effects, four increased crRNA array activity, and four decreased that activity. However, the magnitude of those effects were small, with changes in mean pre-crRNA enrichment of between 10% and 36% when those crRNAs were present (Supplementary Fig. 17a–c). The individual crRNA effects also did not correlate with GC content or the on-target activity score predicted by CRISPick (Supplementary Data 2).

Methods
Plasmid generation
Unless otherwise noted, cloning was performed using PCR of desired insert fragments with Q5 (New England Biolabs (NEB)), followed by Gibson Assembly using NEBuilder HiFi 2x Master Mix (NEB) to add inserts into the desired digested plasmid backbone. Cloning reactions were transformed into chemically competent NEB Stable E. Coli (NEB), purified using the Zyppy Plasmid Miniprep Kit (Zymo), and validated using Sanger sequencing (Azenta). All primers and oligos for creating crRNAs were obtained from IDT. All Cas12a ORFs and epigenome editing domain sequences can be found in Supplementary Data 3. All key plasmids from this study are available on Addgene (catalog numbers 244204–244223).

First-generation dCas12a effector fusions were cloned into the FUGW plasmid backbone. FUGW-dLbCas12a was a gift from Dr. Charles Gersbach, and the dLbCas12a sequence was originally derived from pY109 (Addgene 847740). dAsCas12a and dEnAsCas12a were derived from Addgene plasmids (114078 and 107943, respectively)46. Mutations to make dAsCas12a-Ultra were introduced into the dAsCas12a plasmid. A gene fragment (Twist) with the dHyperLbCas12a ORF was synthesized and cloned into the same FUGW backbone. Effector fusions were generated using Gibson assembly or by standard subcloning methods. The 4xSID sequence was derived from Addgene 1063994, and the 3xKRAB sequence was taken from Addgene 12813244. Versions of each dCas12a effector were made with either a T2A-EGFP or T2A-puroR using subcloning. These constructs were used in Fig. 1a, b, Supplementary Figs. 1, 2a, b, and 3a–f.

The FUGW vector was then modified using Gibson assembly and subcloning to create a second generation of dCas12a effector fusions. The hUbc promoter was replaced with the EF1A promoter. The nucleoplasmin NLS on the C-terminus of dEnAsCas12a was exchanged for two copies of the c-Myc NLS. Lastly, the T2A-puroR was replaced by T2A-BlasticidinR. These dCas12a effectors were used in Figs. 1c, d, 2–8, and Supplementary Figs. 2c–e, 4, and 6–11.

For expression of Cas12a pre-crRNA arrays using U6, pRDA_052 (Addgene 136474)45 was used for AsCas12a and an FUGW plasmid was used for LbCas12a. These constructs were used in Figs. 1a, b, 2c, d, 3c, d and Supplementary Figs. 1, 2a, b, and 3a–f. The FUGW LbCas12a crRNA expression vector was modified for U6 expression of either As or LbCas12a crRNAs by inserting an Esp3I cloning site flanked by two direct repeat sequences just downstream of the U6 promoter. These plasmids also included an hUbc promoter to express mCherry-P2A-PuroR for selection. These plasmids were used in Fig. 1c, d. A pHAGE plasmid was modified using Gibson assembly for CAG expression of either As or LbCas12a crRNAs. First, the promoter was changed from EF1A to CAG. Next, an mCherry-P2A-puroR ORF, followed by the MALAT1 triplex sequence used in a previous study44, followed by two direct repeat sequences flanking an Esp3I cloning site, were inserted into the vector downstream of the CAG promoter. Finally, a kanamycin resistance cassette was inserted between the direct repeat sequences in order to limit recombination. This plasmid was used in Figs. 1c, d, 2f–j, and 4–7 and Supplementary Figs. 2c–e, 3g, and 4b. The sequence of this transcript can be found in Supplementary Information.

Cloning of crRNAs into expression vectors was performed using one-pot golden gate cloning (Figs. 1a, b, 2c, d, 3c, d, and 7 and Supplementary Figs. 1, 2a–c, 3a–f, 4b, and 11). All crRNA spacer sequences used in this study can be found in Supplementary Data 4. Briefly, pairs of oligos were annealed, then phosphorylated using T4 Polynucleotide Kinase (NEB) in a 50 μL reaction. Next, 40 fmol of plasmid backbone and 2 μL of each annealed oligo pair were added to a 20 μL one-pot Golden Gate reaction (2 μL Cutsmart Buffer (NEB), 2 μL 10mM ATP (NEB), 1 μL Esp3I (NEB), 1 μL T4 DNA Ligase (NEB), H2O to 20 μL). Reactions were incubated at 37°C for 2 h, then enzymes were heat-inactivated at 80°C for 10 min. Subsequently, 0.5 μL of Esp3I was added to each sample, and digestion was performed at 37°C for 1 h before proceeding to transformation81,86. Long pre-crRNA arrays in Figs. 1c, d, 2f–j, 4, 5 and Supplementary Figs. 2d, e, 4a, 6 were constructed using PCR followed by Golden Gate cloning. Briefly, the crRNA array was created by using multiple rounds of low-cycle-number PCR. Primers added one crRNA to each end of the growing array with each round of PCR. The last round of PCR also added Esp3I sites for Golden Gate cloning. This amplicon was then cloned into the plasmid backbone using one-pot Golden Gate cloning with 40 fmol of plasmid and 120 fmol of PCR product. Long pre-crRNA arrays in Figs. 2i, j and 4g, h were synthesized as Golden Gate-compatible gene fragments (Twist) with Esp3I sites and 5’ and 3’ primer sequences for PCR amplification. Gene fragments were first amplified using low-cycle-number PCR. PCR products were purified using DNA Clean and Concentrator (Zymo), and then the amplicon was then cloned into the plasmid backbone using one-pot Golden Gate cloning with 40 fmol of plasmid and 120 fmol of PCR product.

CRISPRi library generation
First, CRISPick was used to design a library targeting the promoters of 291 previously identified core essential gene, 25 cell surface controls, and a handful of A549-specific essential genes using the CRISPRi window (TSS-50 to TSS+300) and the TTTV PAM45,70. We also used CRISPick to generate 200 non-targeting crRNAs and 100 intergenic control crRNAs. We identified 145 core essential genes and 20 cell surface control genes that had at least four crRNAs with an on-target activity score ≥0.3. We also designed crRNAs to target thirteen synthetic lethal gene pairs that had at least two crRNAs with an on-target activity score ≥0.3 either individually or in combination. Using these spacers, we designed a library of pre-cRNA arrays containing four crRNAs each. The final library was composed of 171 pre-crRNA arrays targeting the promoters of 145 core essential genes, 48 pre-crRNA arrays targeting the promoters of 20 cell surface control genes, 50 non-targeting pre-crRNA arrays, 25 intergenic control crRNA arrays, and 600 pre-crRNA arrays targeting the synthetic lethal genes either individually or in combination for a total of 893 pre-crRNA arrays. Spacer sequences used in the screening libraries and oligos ordered for cloning these libraries can be found in Supplementary Data 1.

The pre-crRNA arrays were ordered as two separate oligo pools (Twist), one for dHyperLbCas12a and one for dEnAsCas12a. These contained the same spacer sequences, but different direct repeat sequences. Each oligo pool was amplified via 8 low-cycle-number PCR reactions (Q5, NEB). PCR products were purified using the DNA Clean and Concentrator Kit (Zymo). These DNA fragments were then input into eight ligation one-pot Goldengate reactions using 360 fmol of PCR product and 40 fmol of the CAG crRNA expression vector described above. These products were pooled and concentrated using the DNA Clean and Concentrator kit before being electroporated into Endura chemically competent cells (Lucigen). The 893-member library was purified using the MidiPlus kit (Qiagen).

PER1 and non-targeting crRNA library generation
First, the CAG crRNA expression vector described above was modified to have the 3’ TruSeq adapter sequence downstream of the Esp3I cloning site instead of a flanking direct repeat sequence. This was done with Gibson Assembly. This sequence can be found in the Supplementary Information. Spacer sequences used in the PER1 and non-targeting libraries and oligos ordered for cloning these libraries can be found in Supplementary Data 2.

Next, nine unique crRNAs were designed to target each PER1 enhancer using CRISPick. From those nine crRNAs, 84 (9 choose 3) unique sets of three crRNAs were created to target each enhancer. Using those sets of crRNAs, a pool of 188 oligos, composed of two different groups, was designed (Twist). Group 1 was composed of oligos containing the 84 sets of three enhancer B-targeting crRNAs plus 10 sets of three non-targeting crRNAs, as well as a nested cloning site and a unique 8nt barcode sequence (Supplementary Fig. 12a). Group 2 was composed of oligos containing the 84 sets of three enhancer A-targeting crRNAs plus 10 sets of three non-targeting crRNAs, as well as the 5’ TruSeq adapter sequence for NGS and a unique 8nt barcode sequence. Barcode sequences were designed with a Hamming Distance of 3. Group 1 and group 2 oligos were amplified from the pool using separate PCR primer pairs (Supplementary Data 4). Then, Golden Gate cloning was used to insert the group 1 amplicons into the plasmid backbone. The plasmid was digested with Esp3I (NEB), while the PCR amplicon was digested with BsaI (NEB). These were purified using the DNA Clean and Concentrator Kit (Zymo). These DNA fragments were then input into eight ligation reactions using 120 fmol of PCR product and 40 fmol of digested plasmid. Ligated products were pooled and concentrated using the DNA Clean and Concentrator kit before being electroporated into Endura chemically competent cells (Lucigen). The 94-member library was purified using the MidiPlus kit (Qiagen). Group 2 amplicons were then cloned into the 94-member library using 8x one-pot Golden Gate cloning with Esp3I as described in plasmid generation methods. This library was electroporated and purified as before, resulting in a final library with six crRNAs per array and 8836 total crRNA arrays.

The non-targeting library was created by designing 50 non-targeting control crRNAs as well as three promoter-targeting crRNAs using CRISPick. To create a 10,000-member library, 200 sets of three crRNAs were randomly chosen from the 50 non-targeting crRNAs and broken up into 100 sets for group 1 and 100 sets for group 2. Three sets of three promoter-targeting crRNAs were also included with group 1. The non-targeting library was then cloned in the same way as the PER1 enhancer-targeting library. The three promoter-targeting crRNAs did not contain a nested cloning site and were therefore unchanged during the second round of cloning.

Cell culture
HEK293T (Cat. No. CRL-3216), A549 (Cat. No. CRM-CCL-185), and HepG2 (Cat. No. HB-8065) cell lines were obtained from ATCC. HEK293T and A549 cell lines were authenticated using STR profiling through the Duke Cell Culture and DNA Analysis facility. Mycoplasma testing was performed by Eurofins. All cell lines were grown in humidified incubators at 37°C and 5% CO2. Cells were cultured using the following media:
HEK293T: DMEM (Gibco) + 10% FBS + 1% penicillin-streptomycin
A549: F12K (Gibco) + 10% FBS + 1% penicillin-streptomycin
HepG2: EMEM (ATCC) + 10% FBS + 1% penicillin-streptomycin
The RVR-iPSC TUBB3-mCherry reporter cell line has been characterized in previously published work13. iPSCs were maintained on Matrigel (Corning) coated plates in mTESR supplemented with mTESR plus 5x Supplement (Stem Cell Technologies). For neuronal differentiation, media was changed to DMEM/F-12 Nutrient Mix (Gibco, 11320), 1x B-27 serum-free supplement (Gibco), 1x N-2 supplement (Gibco), and 25 μg/mL gentamicin (Gibco) 24 h post-transduction with pre-crRNA arrays.

Primary T cells were obtained by isolating CD3+ T cells from a leukopak (Stem Cell Technologies Cat No. 70500) using the EasySepTM Human T cell isolation kit (StemCell Technologies). Donor ID and information:
Donor 1: RG2959 (Male, Age 32)
Donor 2: 888588554 (Male, Age 47)
Donor 3: 889012042 (Female, Age 36)
The cells were activated with anti-CD3/CD28 Dynabeads (Gibco) at a 3:1 bead to cell ratio and maintained in PRIME-XV media (Fujifilm) supplemented with 100 U/mL of IL-2, 5% human platelet lysate (Compass Biomedical), 100 Uml−1 penicillin, and 100 μgml−1 streptomycin.

Transfection
For experiments performed in 24-well plates (Figs. 1a, 2–5 and Supplementary Figs. 3a, b and 2e), cells were co-transfected with 400 ng of dCas12a effector plasmid and 250 ng array plasmid 24 h after seeding using Lipofectamine 3000. For the experiments in Fig. 5 and Supplementary Fig. 6, cells were co-transfected with 250 ng of each dCas12a effector plasmid, and 250 ng of hybrid crRNA, or 125 ng of each control array (As and LbCas12a crRNAs). Forty-eight hours post-transfection, cells were either harvested for flow cytometry (Figs. 1a, 2–5 and Supplementary Figs. 6 and 2e), or RNA was extracted directly from bulk transfected cells (Supplementary Fig. 3a, b)

For experiments performed in 96-well plates (Figs. 1b, d, e, 4d, 7b and Supplementary Figs. 1, 2a–d, 3c–f) cells were reverse-transfected with 80 ng of dCas12a effector plasmid and 50 ng array plasmid using Lipofectamine 3000. For the low crRNA condition in Supplementary Fig. 1A, cells were transfected with 5 ng of array plasmid. RNA was harvested from cells 48 h post-transfection.

RT-qPCR
For all experiments except those specifically listed below, RNA extraction and cDNA synthesis were completed using the two-step Cells to Ct Kit (Thermo). About 2 μL of cDNA was used in each PCR reaction. Multiplexed qPCR was performed using TaqMan Gene Expression Master Mix (Thermo), a FAM-labeled Taqman assay (Thermo) for the appropriate target gene, and a VIC-labeled, primer-limited endogenous control assay (Thermo) for ACTB. qPCRs were performed with three technical replicates, except for the data presented in Figs. 1d-e, 7b and Supplementary Figs. 2e and 11, which were performed in technical duplicate. qPCR was performed on a StepOne Plus thermal cycler under the following conditions:
95°C for 10 min
40x
95°C for 15 s
60°C for 1 min
In instances where gene targets failed to amplify due to low/no expression, a Ct value of 40 was used.

For experiments in Figs. 2i, j and 4e and Supplementary Fig. 3a, b, qPCR was performed as above except that RNA was extracted using the RNeasy mini kit (Qiagen). cDNA was then created using the High-Capacity cDNA Reverse Transcription Kit (Applied Biosciences) or SuperScript III Reverse Transcription Kit (Thermo) using 500 ng–1 μg of RNA. About 1 μL of cDNA was used for qPCR.

For experiments to test dCas12a effector expression (Supplementary Fig. 2e), the Cells to Ct kit was used as above, and 2 μL of cDNA was used in the qPCR reaction. qPCR was performed using SYBR Green (Thermo) and primers to detect the Cas12a transcript or primers to detect ACTB. Primer sequences can be found in Supplementary Data 4. Thermal cycling conditions were as follows:
95°C for 10 min
40x
95°C for 15 s
60°C for 1 min
All nTPM values indicated for qPCR target genes are from the Human Protein Atlas (proteinatlas.org). All raw qPCR data were available in Supplementary Data 5.

Stable cell line generation
In order to create A549 and HepG2 cell lines that stably express a dCas12a effector, lentivirus was created by the Duke Viral Vectors Core using standard reagents (psPAX2 and MD2.G). A549 and HepG2 cells were transduced with lentivirus at 1x concentration in media containing 10 μg/mL polybrene (Thermo). The media was changed 24 h post-transduction. Cells were selected with 2.5 μg/mL Blasticidin-S-HCl. Once selection and expansion was complete, cell lines were validated by transduction or transfection of array constructs.

In order to create the stable crRNA array-expressing cell lines in Fig. 7b and Supplementary Figs. 2c, d, 4, and 11 and the Cas9 knockout cell lines in Supplementary Fig. 2c, we created lentivirus using standard reagents. Briefly, 90% confluent HEK293T cells in a six-well plate were transfected with 600 ng psPax2, 450 ng of the lentiviral vector of interest, and 150 ng of MD2.G using Lipofectamine 3000. Media was changed 24 h post-transfection, and supernatant was harvested 72 h post-transfection. A549 and HepG2 cells were transduced with lentivirus at 1x concentration in media containing 10 μg/mL polybrene. Media was changed 24 h post-transduction. HepG2 cells were selected with 0.75 μg/mL puromycin, while A549 cells were selected with 1.0 μg/mL puromycin. Once selection and expansion was complete, cell lines were validated by RT-qPCR.

In order to create iPSCs and T cells that stably express a dCas12a effector and pre-crRNA array, dCas12a and pre-crRNA array lentivirus were created based on a previously reported protocol for high-titer lentivirus production87. Specifically, 8×106 HEK293T cells were seeded in a T-75 flask in complete Opti-MEM: Opti-MEM (Gibco) supplemented with 1x GlutaMAX (Gibco), 5% FBS (Gibco), 1x NEAA (Gibco), and 1 mM sodium pyruvate (Gibco). The next day, 9.75 μg of psPAX2, 3.25 μg of MD2.G, and 4.3 μg of the transgene plasmid were transfected into the flask using Lipofectamine 3000 (Invitrogen). Plasmid DNA and 35 μL of P3000 were diluted in unsupplemented Opti-MEM to a total volume of 1.5 mL. Separately, 41 μL of Lipofectamine 3000 was mixed with 1459 μL of Opti-MEM and then added to the DNA/P3000 solution and mixed well. This was incubated at room temperature for 15 min and then added dropwise to the cells. Media was changed 6 hours post-transfection to 12 mL of complete Opti-MEM. Supernatant was then collected 24- and 48-hours post-transfection, and virus was concentrated 100x using Lenti-X concentrator (Takara Bio) according to manufacturer’s protocols.

T cells were transduced 24 h post-activation in a 24-well plate at a concentration of 1.0×106 cells/mL using 10% v/v of virus in cell culture media. Twenty-four hours post-transduction, cells were split evenly into five wells of a 96-well plate and transduced with pre-crRNA array lentivirus at a concentration of 10% v/v. Cells were expanded and selected using 4 μg/mL Blasticidin-S-HCl. Once expansion and selection was complete, RNA was harvested and qPCR was performed to assess levels of target gene activation or repression.

iPSCs were transduced with dHyperLbCas12a-VPR in single cell suspension in mTESR (Stem Cell Technologies) supplemented with Rock inhibitor (Y-27632, Stem Cell Technologies) at a concentration of 5×105 cells/mL. After 24 h, the media was changed to mTESR without Rock inhibitor. 30 h after transduction, 5 μg/mL Blasticidin-S-HCl was added directly to the media. Cells were selected and expanded to 10-cm dishes. Cells were single cells passaged for the first passage after transduction to facilitate complete selection. For neuronal differentiation experiments, 60,000 cells were seeded in a single cell suspension to each well of a matrigel-coated 24-well plate in mTESR supplemented with Rock inhibitor and 1 μL of pre-crRNA virus was added to each well (three independent transductions per pre-crRNA array construct). The next day, the media was changed to neurogenic media (see above). At 30 h post-transduction, puromycin was added directly to the media for a final concentration of 1 μg/mL. Daily media changes using neurogenic media plus 1 μg/mL puromycin were performed, and cells were harvested and analyzed via flow cytometry four days post-transduction.

A549, HepG2, and iPSCs with stably integrated dCas12a effectors, as well as the HKDC1 knockdown and overexpression cell lines, can be shared upon request after completing an MTA. Please contact the corresponding author with any such requests.

Flow cytometry
For studies involving transfected cells, live cells were harvested from a 24-well plate 48 h post-transfection and resuspended in 200 μL MACS Buffer (DPBS + 0.5% BSA + 2 mM EDTA). Cells were then sorted on a SONY SH800 sorter using a 100 μm chip. Populations were gated on FSC/SSC for single cells, and then gated for GFP-positive cells, a marker of Cas12a expression (Supplementary Fig. 18). Between 15,000 and 50,000 cells were sorted per sample, after which we proceeded with RNA extraction using the Cells to Ct kit.

For the iPSC studies, live cells were washed with PBS and harvested from a matrigel-coated 24-well plate four days post-transduction using Accutase (Stem Cell Technologies). Cells were resuspended in 150 μL MACS Buffer and analyzed on the Attune NxT Flow Cytometer (Thermo). Populations were gated on FSC/SSC to determine single cells, and then gated on mCherry using a threshold of ~1% mCherry positive cells in a population of cells transduced with a non-targeting control pre-crRNA array (Supplementary Fig. 5). This anaylsis was carried out with FlowJo v. 10.8.1. Raw data values for the plots in Fig. 3g, h are available in the Source Data and Supplementary Data 6 and the Source Data file.

To determine lentiviral titers for the CRISPRi libraries, A549 cells stably expressing dHyperLbCas12a-KRAB were transduced with serial dilutions of the lentiviral pre-crRNA libraries (either As or LbCas12a version). Media was changed 24 h post-transduction, and cells harvested 48 h post-transduction, resuspended in 150 μL MACS Buffer, and analyzed on the Attune NxT Flow Cytometer (Thermo). Single cells were gated on using FSC/SSC, and then mCherry positive population was determined by gating on untransduced cells (Supplementary Fig. 19). mCherry fluorescence was used as a marker of transduction and used for MOI calculations.

For the dHyperLbCas12a-KRAB screen, flow cytometry was performed by the flow cytometry core at the Duke Cancer Institute using an MoFlo Astrios EQ High Speed Sorter (Beckman Coulter). Cells were first gated on single cells using FSC/SSC. Next cells were gated on compensated mCherry, a marker of crRNA expression, and compensated FITC-488, a marker of PER1 transcripts by HCR. The top and bottom 12% of FITC-expressing cells were then sorted (Supplementary Fig. 15).

PER1 CRISPRi screen
First, lentivirus was created for the PER1-targeting and Non-Targeting crRNA libraries. For each library, two T-75s containing 90% confluent HEK293T cells were transfected with 4 μg of psPAX2, 3 μg of array plasmid, and 2 μg of MD2.G using 27 μL of PEI (1 mg/mL). Media was changed 24 h post-transfection, and supernatant was harvested 72 h post-transfection. For each library, 24 mL of supernatant was concentrated 10x using Lenti-X concentrator (Takara Bio) as directed.

Next, for each library 1×108 cells in 500 cm2 dishes were transduced at low MOI using the concentrated lentivirus in media containing 10 μg/mL polybrene to achieve 1000x library coverage. After 48 h, cells were passaged 1:4 into media containing 0.75 μg/mL puromycin. Cells were passaged two more times (five more days) to ensure that selection was complete. In order to ensure good library coverage, at each passage, cells from all plates per library were pooled, and the number of cells passaged was at least 2000x library size. After three passages in puromycin (7 days post-transduction), cells from each of the two libraries were pooled in equal numbers and co-cultured. Ten days post-transduction, cells were treated for 3 h with 0.1% ethanol (vehicle), 200 pM dexamethasone, or 100 nM dexamethasone, with 2×108 cells per condition. 1.4×107 cells were taken from each condition, mixed, and pelleted in order to create a bulk sample to use as a comparison for crRNA enrichment. Additionally, 5×106 A549 dHyperLbCas12a-KRAB cells (untransduced) were harvested for use as flow cytometry controls.

Cells were harvested and HCR Flow-FISH was performed78. PER1 transcripts were detected using a custom set of 20 probe pairs containing the B3 amplifier. Probe was used at 2x concentration compared to the standard protocol. Amplification was performed for 22 h using the B3-488 amplifier. Flow cytometry controls were created as follows: negative control cells were taken from A549 cells that expressed dCas12a-KRAB but were not transduced with a crRNA library. They were hybridized with the probe but set aside after the probe wash step. mCherry single color controls were taken from cells transduced with the PER1 and Non-targeting libraries. They were hybridized with the probe but set aside after the probe wash step. FITC-488 single color controls were taken from A549 cells that expressed dCas12a-KRAB but were not transduced with a crRNA library. These cells went through the whole HCR protocol and had labeled PER1 transcripts. All cells were resuspended in MACS buffer and sorted as described above.

CRISPRi fitness screen
Lentivirus was created for the As and LbCas12a pre-crRNA array libraries using the same method as the PER1 screen. Next, since the pre-crRNA construct contains an mCherry marker, the titer was determined via flow cytometry as described above (under flow cytometry).

Next, for each A549 cell line expressing a dCas12a effector, 5×106 cells were seeded to a T-75 flask and transduced with the appropriate pre-crRNA array library at an MOI of 0.2. This was done in triplicate for each effector. Media was changed 24 h post-transduction. Forty-eight hours post-transduction, cells were passaged 1:4 into four new T-75s containing F12K media supplemented with 0.75 μg/mL puromycin. After selection (5 days post-transduction), an initial cell pellet was collected from each sample (2×106 cells/pellet). Cells were selected with puromycin for one week and then selected for one passage with 2.5 μg/mL Blasticidin-S-HCl to ensure that all cells continued to express the dCa12a repressor construct. Cell pellets were also collected at 7-, 14-, and 21-days post-transduction (1–2×106 cells/pellet) to compare pre-crRNA abundance at those times to the initial timepoint.

NGS library prep and sequencing
For the PER1 screen, genomic DNA was extracted from bulk-transduced cells that did not undergo HCR using the Puregene Cell Kit (Qiagen). Meanwhile, genomic DNA from cells sorted into high and low PER1 expression bins was extracted using the FFPE miniprep kit (Zymo). Genomic DNA purified using the FFPE miniprep kit was then cleaned using Axiprep Magnetic Beads (Axygen) at a ratio of 0.9x in order to remove any small DNA fragments. Genomic DNA was then analyzed on a TapeStation 4200 in order to confirm that DNA was high quality and the average fragment size was large (>20 kb).

Next, crRNAs were amplified from genomic DNA (primer sequences can be found in Supplementary Data 4 using Q5 2x Master Mix (NEB) in 100 μL reactions with the following thermal cycling parameters:
98°C for 45 s
27x
98°C for 15 s
60°C for 20 s
72°C for 1 min and 15 s
72°C for 5 min
We performed 18 PCR reactions for each sorted cell sample and 96 PCR reactions for the bulk unsorted sample. Axiprep magnetic beads were used at a 0.9x ratio to clean and size-select 200 μL of PCR product in order to remove any adapter dimer. PCR products were quantified using a qPCR standard curve (KAPA ABI Prism qPCR Master Mix). Preparation of libraries from plasmid DNA used the same PCR conditions, except with 12 cycles and 25 PCR reactions per plasmid library. In both cases, the number of cycles of PCR was determined empirically by first performing a qPCR using Q5 2x Master Mix and 1x EvaGreen (Thermo), and choosing the number of cycles that gave about one-half of the maximum signal. Libraries were run using a 600 cycle paired-end kit NextSeq 2000 at a concentration of 950 pM. Custom primers were used for sequencing (Read 1, Index 1, Index 2, and Read 2, Supplementary Data 4).

For the fitness screen, genomic DNA was extracted from cell pellets using the Puregene Cell Kit (Qiagen). Next, pre-crRNA arrays were amplified from genomic DNA using KAPA 2x PCR Master Mix (Roche) for 28–29 cycles. The plasmid libraries were also amplified using 13 cycles of PCR. We performed 8x 50 μL PCR reactions per sample. PCR cycle numbers were determined empirically by performing a qPCR using KAPA 2x PCR Master Mix with EvaGreen, similarly to the PER1 library. Axiprep magnetic beads were used at a 0.9x ratio to clean and size-select 200 μL of PCR product in order to remove any adapter dimer. PCR products were quantified using the Quant-It (Invitrogen). Libraries were run using a 300-cycle paired-end kit on the NextSeq 2000 at a concentration of 750 pM and with a 20% PhiX spike in. Standard Illumina primers were used for sequencing.

Sequencing data processing
For the PER1 screen, FastQ files were generated using BCL Convert in BaseSpace. To extract barcode sequences, reads containing the barcode were first trimmed using Cutadapt (version 4.4), aligned to a custom reference of barcode sequences using Bowtie2 (version 2.5.1), and counts for each barcode were generated using Samtools (version 1.17) with the following parameters:
cutadapt -a AGATCGGAAGAGCGTCGTGTAGGGAAAGAatctacacttagtagaaatt -m 20 --discard-untrimmed
bowtie2 -x new.primers.BC.only -p 12 --very-sensitive --nofw
samtools view -bS Input.umi.sam > Input.umi.bam
samtools sort Input.umi.bam -o Input.umi_Sorted.bam
samtools index Input.umi_Sorted.bam
samtools idxstats Input.umi_Sorted.bam > Input.umi.idxstats.txt
Only reads with a perfect match to a barcode sequence were considered. MaGeck (version 0.5.9.4) was then run, using control normalization to the non-targeting crRNAs, on the counts table to quantify barcode enrichment in high and low bins compared to bulk unsorted cells. High and low for each condition were analyzed separately. Raw read counts and log2 fold changes for each pre-crRNA can be found in Supplementary Data 2.

To assess whether barcode sequences were paired with the correct crRNA array sequences, barcode sequences were extracted from each read using UMI-tools (version 1.1.4). Reads were then trimmed using Cutadapt, and read 2 was aligned to a custom crRNA array reference using Bowtie2. Samtools was used to create a sorted bam file, and then UMI-tools was used to group reads by barcode sequence. The specific parameters used were
umi_tools extract --extract-method=regex --bc-pattern='^(?P<umi_1>.{8})(?P<discard_2>TCGG)(?P<umi_2>.{8})'
cutadapt -g ^NNNNNNNatcctggtattggtctgcgaaatttctactaagtgtagat -m 70 --discard-untrimmed
bowtie2 -x new.primers.array -p 12 --norc -N 0 --score-min C,0,0
samtools view -bS Input.umi.sam > Input.umi.bam
samtools sort Input.umi.bam -o Input.umi_Sorted.bam
samtools index Input.umi_Sorted.bam
samtools idxstats Input.umi_Sorted.bam > Input.umi.idxstats.txt
Umi_tools group -I Input.umi_Sorted.bam --group-out=Input.umi_counts.txt --output-bam -S Input.umi_grouped.bam

For each pre-crRNA array, the number of reads associated with the correct barcode was determined and the percentage of reads with the correct array was calculated as 100x (# of reads for correct array / # total reads).

For the fitness screen, FastQ files were generated using BCL Convert in BaseSpace. To align and count pre-crRNA array sequences, reads were first trimmed used cutadapt, aligned to a custom reference using Bowtie2, and then counted using samtools. Only perfect matches to the reference were considered. The specific parameters used were:
cutadapt -g ^NNNNNNNatcctggtattggtctgcgaaatttctactcttgtagat -m 70 --discard-untrimmed -G ^CGTAatctacaagagtagaaatta -m 70 --discard-untrimmed
bowtie2 -x As -p 12 --end-to-end -N 0 --score-min C,0,0 -I 152 -X 152
samtools view -bS As.Plasmid.sam > As.Plasmid.bam
samtools sort As.Plasmid.bam -o As_Sorted.Plasmid.bam
samtools index As_Sorted.Plasmid.bam
samtools idxstats As_Sorted.Plasmid.bam > As.Plasmid.idxstats.txt

To model changes in pre-crRNA array abundance over time, we used DESeq2 with the number of days in culture included as an independent variable in the model. We subtracted five from the number of days such that our initial observation at day 5 would serve as the intercept in the fit models. We evaluated statistical significance using a likelihood ratio test compared to a model without the day parameter. We estimated false discovery rates using the Benjamini–Hochberg method as implemented in DESeq2. We modeled each screen independently and plotted results using data where counts for all four screens were jointly normalized for differences in read depth by DESeq2. Code and examples for the analysis is available at https://github.com/ReddyLab/Cas12a_screen_analysis.

We also used our time course data in conjunction with the MAGeck MLE to determine which genes were essential and depleted over time using information from all pre-crRNAstargeting each gene. The associated beta scores and wald FDR values for each essential gene and cell surface control are reported in Supplementary Data 1 and Fig. 6. Gene effect score data in Supplementary Fig. 10 is from the DepMap Public 25Q1 dataset (depmap.org).

Statistics and reproducibility
For experiments where crRNAs were introduced into cells and then target gene expression was assessed using qPCR, we performed three independent transfections, three independent transductions, or extracted RNA from three separate wells of the same cell line in order to make comparisons between experimental and control samples. We performed one or two-sided Student’s T-tests with an assumption of equal variance to make comparisons between samples. When multiple experimental samples were compared to the sample control, we adjusted p values using the Benjamini–Hochberg (FDR) method. No statistical method was used to predetermine sample size. Data were excluded from the analyses in cases where a sample was physically lost (i.e., because a cell pellet was aspirated or the cell sorter encountered a technical issue) and/or RT-qPCR replicates where there was no amplification or where housekeeping gene Ct values were substantially different than all other samples. The experiments were not randomized. The Investigators were not blinded to allocation during experiments and outcome assessment.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "In this manuscript, Schuyler and colleagues explored the feasibility of expanding epigenome editing with newly created\ndCas12a-based epigenome editors. They thoroughly tested previously described dCas12a systems with various\nimprovements and benchmarked the editing efficiency at a wide range of target genes and different cell lines. Notably, the\nauthors leveraged Pol II-driven pre-crRNA transcription to expand usable crRNA usage due to the processivity of Pol II and\nthe dCas12a’s ability to cleave and load the final cRNAs. Leveraging the fact that AsCas12a and LbCas12a utilize different\nPAM sequences to find their target in the genome, the authors built a simultaneously activating and repressing system\nwhere the various versions of Cas12a cleverly facilitate the opposite role of gene regulation.\nOn a personal note, I would like to thank the authors for a beautifully written and well-edited manuscript, which was an\nabsolute pleasure to read – something that is unfortunately rare these days. Much thought went into the clarity of the figures\nand the accompanying manuscript text.\nMinor points:\n- Figures with box plots: Plotting the individual dots for each measurement would benefit from added jitter to identify each dot\nand prevent overplotting. This will enable viewers to see if there were dropouts (n=2 instead of n=3)\n- Figure 1 c -e: the use of red for the front and back cRNAs, the HBE1 gene, and the CAG promoter is very confusing. This\nfigure would benefit from consistency in color choice. For example, Fig 1c could have 4 constructs shown with U6 and CAG\nseparated, and the color would then be used in Fig 1d and 1e again.\n- Also, since some people might be color blind, the color for AS and LB in Figures 1a and 1b might be problematic\n- The main text could explain the choice of crRNA sequences or reference previously established sequences.\n- In Figure 2 f-g, which demonstrates multiplexed repression of multiple target genes - the 4xSID fusion represses slightly\nbetter than the KRAB fusion. This is compared to figures 2c and 2d, where it appears to be the other way around for\nRAB11A. Are the targeting crRNAs for RAB11A and VEGFA identical across Figures 2c-d and 2f-g? Does the positioning or\nthe multiplexing of the target crRNAs for Fig 2f-g attribute to differences in repression?\n- Fig 2 e-g: The authors chose to measure repression of RNA after 48h. Since repression of RNA is also dependent on RNA\nstability and KRAB vs Sin3A repression might have different dynamics, a time point at 72h or 96h post-transduction would\nhelp to understand if the repressive strength is time-dependent or not.\n- Figure 4: It would be helpful to have the statistical analysis depicted right in the figure (e.g. lines indicating the samples\ncompared and asterisk for levels of significance)\n- Figure 4: Labeling the target genes above the panels and not only using color to denote target genes helps clarity\n- In addition, to help the reader judge fold activation and repression, please add TPM (transcript per million from gene\nexpression data sets) for each target gene next to the gene label. 3,200-fold activation is likely only possible on non-\nexpressed genes vs 2-fold activation on a different target gene.\n- Figure 5: The two Cas12a orthologues have been shown to confer different transcriptional effects. Did the authors also test\nusing dHyperLbCas12a for activation and dEnAsCas12a for repression?\n- No comment or experiment has been performed to address the stability of the epigenome edits. While I wouldn’t expect this\nto be done for every cell and target gene presented, it would be interesting to know how quickly the enhancers of PER1 will\nbe reset after targeted repression, for example.\n- Figure 7 and the experiment screening crRNAs to repress PER1 enhancers: The analysis of which crRNAs were most\neffective at promoting enhancer silencing was not performed. It would be beneficial for the reader to understand if there are\nany rules or considerations for crRNA positioning relative to CREs.", "reviewer_2": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts.", "reviewer_3": "In the current manuscript, Melore et al. has combined dHyperLbCas12a with RNA Polymerase II expression of long crRNA for efficient highly-multiplexed epigenome editing. The authors have demonstrated that dHyperLbCas12a is compatible with different activation and repression domains. The authors further showed that this system can perform simultaneous activation and repression using a single crRNA array, and is effective for high-throught screens. Based on these, the authors use dHyperLbCas12a-KRAB and a barcoded library of crRNA arrays for dissecting the cis-regulatory architecture for a dose-dependent gene expression response to glucocorticoids.\nOverall, the study is interesting and the findings are useful to the multiplexed gene expression regulation subfield. However, the study is minimal on its novelty in terms of the methods it employed. The novelty and importance of dCas12a mediated the multiplexed activation and repression have been well-demonstrated already in previous publication. Perhaps, the authors can expand on some other high-throughput screening applications and . In addtion, some data are robust and not enough. Here are some comments and suggestions for the authors to improve the quality of the work.\n1.The authors state that they optimized the dCas12a epigenome editing system, but both the Cas protein and the regulatory elements have been reported before. Explain why chose these Cas12a variants, and not other variants or even other family such as Cas12i. And the statement that dHyperLbCas12a and dEnAsCas12a outperform the wild type dCas12a variants for epigenome editing, has been already reported. In addition, it is recommended to add more sites to compare the activity of encas12a and hypercas12a.\n2.It’s reported that RNA Pol II promoter CAG could improve the dCas12a pre-crRNA expression of long arrays, such as over 40 crRNAs. Explain or supplement experimental evidence for why CAG was chosen over other RNA Pol II promoters.\n3.Explain why chose the transcriptional regulatory elements VPR, P300, KRAB and 4xSID, not other such as SAM, Tet et al. It would be helpful to include more context on how this system compares to other multiplexed gene editing techniques, such as multiplexed CRISPRa or CRISPRi, particularly in terms of efficiency, cost, and ease of implementation.\n4.The data showed that dCas12a-VPR is significantly better than dCas12a-P300, but the author stated that dCas12a-P300 fusions robustly activate gene expression. Please explain this. The authors should add more sites to compare the activity of dCas12a-P300 and dCas12a-VPR when targeting a gene enhancer and/or promoter.\n5.Provide more detail on the hybrid pre-crRNA array strategy for simultaneous activation and repression, such as fornt or back combination of crRNA for activation and repression. Include a discussion on whether this approach could be extended to other types of dCas effectors, such as those for DNA methylation or histone modification.\n6.Expand the discussion on potential off-target effects, particularly when using multiplexed crRNA arrays. Although only at the cellular level of high throughput screening, include experiments or simulations that demonstrate the safety of the system in minimizing off-target interactions.\n7.In the figures section, appropriate statistical analysis should be conducted, and p-value indicated to assess the authors’ claim.\n8.The manuscript would benefit from a more detailed description of the statistical methods used to analyze gene expression changes, particularly in high-throughput screens. Specify how multiple hypothesis testing was corrected and how significant results were defined.\n9.In general, the biological replicates are 3 or over. Thus, it is recommended that for activity comparison of among these variants, while many group in this article only one set. This is not rigorous.", "reviewer_4": "This manuscript presents the development and characterization of dCas12a-based gene silencing and activation using two distinct dCas12a variants. The authors employed enhanced versions of dCas12a, enAsCas12a and HyperLbCas12a, along with crRNA arrays to modulate gene expression. They demonstrate that dCas12a can be coupled with the activation domain P300 and the repression domain SID. They show simultaneous activation and repression of target genes through a single crRNA array by co-expressing both enAsCas12a and HyperLbCas12a. Furthermore, they illustrate the platform's utility in screening applications using a barcoded library of crRNA arrays targeting two enhancers of a single gene.\nOverall, the study offers a side-by-side comparison of gene activation and repression across two different Cas12a systems. It provides a resource for using AsCas12a and LbCas12a variants in gene regulation. For example, the observation that dLbCas12a-P300 fusions exhibit stronger and more consistent activation than dAsCas12a-P300 fusions is interesting.\nWhile the fusion of Cas12a to P300 and SID is new, these tools do not outperform established systems such as VPR for activation and KRAB for repression.\nHowever, the manuscript raises major concerns that should be addressed before it can be considered for publication:\n1. The potential for crosstalk between the two Cas12a variants should be thoroughly evaluated. Both variants utilize the same PAM and share similar guide RNA structures. This raises concerns about their orthogonality. To confirm their suitability for simultaneous activation and repression, the authors should demonstrate that each Cas12a does not interact with the other's guide RNA. Additional experimental data are required to validate their orthogonality and crosstalk.\n2. The title, \"Highly multiplexed epigenome editing screens,\" is misleading and overstates the study's scope. The manuscript demonstrates the activation of four genes, and it remains unconvincing that all four genes are all activated in single cells. This falls short compared to prior studies that activated or repressed a greater number of genes. Additionally, the term \"epigenome editing\" is not fully substantiated, as the authors only present transcription-level activation or repression without characterizing epigenetic modifications. Moreover, the screens are limited to targeting two enhancers, which does not align with the claim of high multiplexing. The title should be revised to accurately reflect the data presented in the study.\n3. It is unclear how most data were collected. For example, how was flow cytometry gating defined? How many replicates were performed? How many biological or technical replicates were tested in each experimental group? Additionally, statistics are lacking in the figures, and p-values should be included.\n4. Although the authors tested a few cell lines for characterization, the study would have greater utility if additional cell types, particularly primary cells, were included. This would enhance the relevance and applicability of the findings for the community.\n5. The inclusion of a control library with 10,000 non-targeting six-crRNA arrays and three pre-crRNAs targeting the PER1 promoter seems excessive. The rationale for this large imbalance between non-targeting and targeting arrays should be clarified. How does this control design contribute to the study's objectives?\n6. The diagrams in Fig. 7b-d are confusing. Are these plots representing PER1-high cells or PER1-low cells? A more detailed explanation of how these plots were generated is necessary to help understanding.\n7. The purpose of testing the two enhancers using a large library is unclear. The authors should elaborate on why not use a few well-designed crRNA arrays to target individual or paired enhancers and measure the downstream gene expression? It is unclear if there is a necessity of performing library screening on two enhancers of one gene. Furthermore, the insights gained from testing PER1 enhancers can be strengthened.\n8. The manuscript would benefit from discussing specific design rules for guide RNA arrays.\n9. Citations 73-74: The manuscript does not appropriately cite work on Cas13. The authors should ensure they reference the most relevant studies."}, "author_response": "REVIEWER COMMENTS\nReviewer #1\nMinor comments:\n- Figures with box plots: Plotting the individual dots for each measurement would benefit from\nadded jitter to identify each dot and prevent overplotting. This will enable viewers to see if\nthere were dropouts (n=2 instead of n=3)\nThank you for the suggestion, we have added jitter to all boxplots in Figs. 1-5, Fig. 7, Supp. Fig. 1-6,\nand Supp. Fig. 10 so that readers can better see the spread of the data and number of replicates.\n- Figure 1 c -e: the use of red for the front and back cRNAs, the HBE1 gene, and the CAG\npromoter is very confusing. This figure would benefit from consistency in color choice. For\nexample, Fig 1c could have 4 constructs shown with U6 and CAG separated, and the color\nwould then be used in Fig 1d and 1e again.\nThank you for the feedback. We updated the diagram in figure 1c to show U6 and CAG separated,\ncolored them blue and orange, and then incorporated this color scheme in Fig. 1d-e. Red is now only\nused to represent HBE1 and the crRNAs that target it.\n- Also, since some people might be color blind, the color for AS and LB in Figures 1a and 1b\nmight be problematic\nWe have now changed the AsCas12a color in Figs. 1a and 1b from red to brown in this revised\nmanuscript in order to be more color blind friendly.\n- The main text could explain the choice of crRNA sequences or reference previously\nestablished sequences.\nThank you for the suggestion. In the revised manuscript, we have noted in the text when a crRNA\nsequence was originally reported in a previous study. This applies to the AR, HBB (Supp. Fig. 3),\nand\nPIK3C3 spacer sequences used in the study as well as one of the RAB5A spacer sequences used.\n- In Figure 2 f-g, which demonstrates multiplexed repression of multiple target genes - the\n4xSID fusion represses slightly better than the KRAB fusion. This is compared to figures 2c\nand 2d, where it appears to be the other way around for RAB11A. Are the targeting crRNAs for\nRAB11A and VEGFA identical across Figures 2c-d and 2f-g? Does the positioning or\nthe multiplexing of the target crRNAs for Fig 2f-g attribute to differences in repression?\nYes, the crRNAs are identical across these two arrays. Due to the design of the study, we cannot say\nwhether the multiplexing and/or position of the RAB11A-targeting crRNAs leads to the differences in\nactivity.\n- Fig 2 e-g: The authors chose to measure repression of RNA after 48h. Since repression of\nRNA is also dependent on RNA stability and KRAB vs Sin3A repression might have different\ndynamics, a time point at 72h or 96h post-transduction would help to understand if the\nrepressive strength is time-dependent or not.\nThank you for raising this point. We believe the reviewer is talking to transfection experiments and not\ntransduction experiments. The difficulty with studying time-dependent transfection effects is that\nchanges in repressive strength are confounded by intercellular plasmid abundance which changes\nover cell division. For that reason, we expect time dependence to vary across different models and\nrequire optimization for each experiment.\n- Figure 4: It would be helpful to have the statistical analysis depicted right in the figure (e.g.\nlines indicating the samples compared and asterisk for levels of significance)\nThank you for this comment, we have added asterisks to Fig. 2-7 and Supp. Figs 1, 2, 4, 6, and 11 to\ndenote significance where appropriate in this revised manuscript.\n- Figure 4: Labeling the target genes above the panels and not only using color to denote\ntarget genes helps clarity\nThank you for this suggestion, we have added target gene names to Fig. 2-4 in the revised\nmanuscript.\n- In addition, to help the reader judge fold activation and repression, please add TPM\n(transcript per million from gene expression data sets) for each target gene next to the gene\nlabel. 3,200-fold activation is likely only possible on non-expressed genes vs 2-fold activation\non a different target gene.\nThank you for this comment. We have added nTPM values from the Human Protein Atlas to the figure\nlegends so that readers can better contextualize activation or repression relative to baseline gene\nexpression level. The nTPMs are also listed all together as part of Supp. Table 1.\n- Figure 5: The two Cas12a orthologues have been shown to confer different transcriptional\neffects. Did the authors also test using dHyperLbCas12a for activation and dEnAsCas12a for\nrepression?\nThank you for this suggestion. To address that point in the revision, we performed experiments that\ntested the hybrid array system with dHyperLbCas12a activators and dEnAsCas12a repressors.\nThese data are presented in Supp. Fig 6c-f and summarized on lines 489-501. For convenience, that\nnew text is reproduced below:\nTo generalize this result, we also designed and tested a similar pre-crRNA containing the\nsame crRNA sequences, but with dHyperLbCas12a activators and dEnAsCas12a\nrepressors. As before, we first tested the ability of single dCas12a effectors to use the\npre-crRNA and found that dHyperLbCas12a-VPR and dEnAsCas12a-KRAB could\nsignificantly activate or repress the target genes when co-transfected with the hybrid\ncrRNA (Supp. Fig 6c-d). We next co-transfected a dHyperLbCas12a Cas12a activator\nand a dEnAsCas12a repressor along with the hybrid pre-crRNA into HEK293T cells. We\nfound that dHyperLbCas12-VPR was able to significantly activate both target genes (p <\n0.05, FDR-adjusted Student’s T-test), but dEnAsCas12a-KRAB was unable to repress\neither target gene (Supp. Fig 6e). Meanwhile, the combination of\ndHyperLbCas12a-P300 and dEnAsCas12a-SID was able to significantly activate HBE1\nand MYOD1 expression while significantly repressing RAB11A expression (p < 0.01,\nFDR-adjusted Student’s T-test), but not MYC expression (p = 0.172, FDR-adjusted\nStudent’s T-test) (Supp. Fig 6f).\n- No comment or experiment has been performed to address the stability of the epigenome\nedits. While I wouldn’t expect this to be done for every cell and target gene presented, it would\nbe interesting to know how quickly the enhancers of PER1 will be reset after targeted\nrepression, for example.\nThe stability of epigenome edits remains a major opportunity for study in the field. However, fully\naddressing this, e.g. with time course ChIP-Seq studies, we feel is beyond the scope of this\nmanuscript.\n- Figure 7 and the experiment screening crRNAs to repress PER1 enhancers: The analysis of\nwhich crRNAs were most effective at promoting enhancer silencing was not performed. It\nwould be beneficial for the reader to understand if there are any rules or considerations for\ncrRNA positioning relative to CREs.\nThank you for raising this point. We dug into our data and did find crRNAs that, when included in the\narray, led to significantly stronger or weaker repression. This data is shown in Supp. Fig. 17, and text\ndescribing these results on lines 705-714 and is reproduced below:\nWe did not find strong evidence for substantial heterogeneity in the effects of the\nindividual crRNAs. Specifically, we tested if, when targeting enhancer A or B individually,\nany of the crRNAs consistently increased or decreased the effect of the pre-crRNA array\n(Supp. Table 3). In the 100 nM Dex high bin, 2 of the 9 crRNAs targeting enhancer A\nhad significant effects and 6 of the 9 crRNAs targeting enhancer B had a significant\neffect (FDR < 0.05). Of those eight crRNAs with significant effects, four increased crRNA\narray activity, and four decreased that activity. However, the magnitude of those effects\nwere small, with changes in mean pre-crRNA enrichment of between 10% and 36%\nwhen those crRNAs were present (Supp. Fig 17a-c). The individual crRNA effects also\ndid not correlate with GC content or the on-target activity score predicted by CRISPick\n(Supp. Table 3).\nSince there are only 18 unique crRNAs in the screen, we feel that there is not sufficient\ndata to comment decisively about positioning or design rules.\nReviewer #2:\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the\nNature Communications initiative to facilitate training in peer review and to provide appropriate recognition for\nEarly Career Researchers who co-review manuscripts.\nReviewer #3:\nIn the current manuscript, Melore et al. has combined dHyperLbCas12a with RNA Polymerase II expression of\nlong crRNA for efficient highly-multiplexed epigenome editing. The authors have demonstrated that\ndHyperLbCas12a is compatible with different activation and repression domains. The authors further showed\nthat this system can perform simultaneous activation and repression using a single crRNA array, and is\neffective for high-throught screens. Based on these, the authors use dHyperLbCas12a-KRAB and a barcoded\nlibrary of crRNA arrays for dissecting the cis-regulatory architecture for a dose-dependent gene expression\nresponse to glucocorticoids.\nOverall, the study is interesting and the findings are useful to the multiplexed gene expression regulation\nsubfield. However, the study is minimal on its novelty in terms of the methods it employed. The novelty and\nimportance of dCas12a mediated the multiplexed activation and repression have been well-demonstrated\nalready in previous publication. Perhaps, the authors can expand on some other high-throughput screening\napplications and . In addtion, some data are robust and not enough. Here are some comments and\nsuggestions for the authors to improve the quality of the work.\n1.The authors state that they optimized the dCas12a epigenome editing system, but both the Cas protein and\nthe regulatory elements have been reported before. Explain why chose these Cas12a variants, and not other\nvariants or even other family such as Cas12i. And the statement that dHyperLbCas12a and dEnAsCas12a\noutperform the wild type dCas12a variants for epigenome editing, has been already reported.\nThank you for raising this point. While these variants have been previously reported, they have not\nbeen compared head-to-head in a single study, and AsCas12a Ultra had not been used for CRISPRi\nor CRISPRa before. Therefore, it was unclear which variant(s) had the strongest epigenome editing\nactivity. We have clarified this in text, on lines 97-102, which now reads:\nIn addition to the wild-type Cas12a from Acidaminococcus sp. BV3L6 (As) and\nLachnospiraceae bacterium (Lb), several engineered Cas12a versions with improved\nactivity have been recently published46–48. However, these variants have not all been\nused for epigenome editing, nor has their activation and repression strength been\ncompared head-to-head in a single study. We systematically compared the strength of\ngene activation and gene repression across five dCas12a variants…\nOne of the major outcomes of this work, that dHyperLbCas12a is suited for low MOI\nscreens, is a novel advance that came out of these comparisons.\nIn addition, it is recommended to add more sites to compare the activity of encas12a and\nhypercas12a.\nThank you for this suggestion. More comprehensively comparing dEnAsCas12a and\ndHyperLbCas12a was one of the major focuses of this revision. In order to compare dEnAsCas12a\nand dHyperLbCas12a over a large number of sites (n = 219), we performed for these revisions a low\nMOI fitness screen to target essential genes or olfactory receptor controls in A549 cells using\ndEnAsCas12a-KRAB, dEnAsCas12a-4xSID, dHyperLbCas12a-KRAB, and dHyperLbCas12a-4xSID.\nThis data is presented in Fig. 6 and Supp. Fig 7-9. That text is found on lines 548-591 of the text and\nreads:\nTo enable large-scale comparison of the dCas12a repressors described above and to\nassess their suitability for use in screening applications, we performed a screen of genes\nthat are predicted to impact cell proliferation. We created a library containing 171\npre-crRNAs targeting the promoters of 145 core essential genes71, 48 pre-crRNAs\ntargeting the promoters of 20 cell surface control genes45, 50 non-targeting pre-crRNAs,\nand 25 intergenic control crRNAs. Each pre-crRNA contained four crRNAs, and we\nrequired that all gene targets have at least four crRNAs with CRISPick on-target\nefficiency score of ≥ 30%. We created an As and Lb Cas12a version of this library using\nthe same spacer sequences but As- or Lb-specific direct repeats.\nNext, we transduced the appropriate library at an MOI of 0.2 into A549 cells stably\nexpressing either dHyperLbCas12a-KRAB, dHyperLbCas12a-4xSID,\ndEnAsCas12a-KRAB, or dEnAsCas12a-4xSID, with three replicates per cell line. Cells\nwere selected for crRNA expression using puromycin, and cell pellets were collected to\nassess relative pre-crRNA abundance at 5, 7, 14, and 21 days post-transduction (Fig.\n6a).\nThere was strong concordance in read counts between replicates for all Cas12a\nrepressor screens. Specifically, correlation between replicates at day 21 was R > 0.91\nfor the KRAB repressor screens and R > 0.79 for the SID repressor screens (Supp. Fig.\n7-8). The strongest and most consistent repressive effects occurred in the\ndHyperLbCas12a-KRAB screen. That screen had much higher correlation between\nreplicates for log fold changes of pre-crRNAs targeting essential genes (R > 0.8)\n2\ncompared to all the other repressors (-0.081 < R < 0.276). That screen also had greater\neffects compared to the other repressors (Fig. 6b-e, Supp. Fig. 9). Representative\nexamples for each system show genes that were significantly repressed by both\ndHyperLbCas12a repressors and dEnAsCas12-KRAB; by both dHyperLbCas12a\nrepressors but not the dEnAsCas12a repressors; and by dHyperLbCas12a-KRAB alone\n(Fig. 6h-j).\nOverall, we conclude that KRAB is a stronger repressor than 4x SID for targeting gene\npromoters, and that dHyperLbCas12a-KRAB is suitable for use in low MOI screens,\nwhile dEnAsCas12a is not. We based that conclusion on comparing effects across the\nfour screens. Using a linear model of change in log fold change over time and a\n2\nthreshold of FDR < 0.001, we detected 28 significantly depleted pre-crRNAs targeting\nessential genes in the dHyperLbCas12a-KRAB condition, five in the\ndHyperLbCas12a-4xSID condition, two in the dEnAsCas12a-KRAB condition, and zero\nin the dEnAsCas12a-4xSID condition using DeSeq2. We obtained similar results at the\ngene level when performing a time course analysis with the MAGeck MLE module and\nwald FDR < 0.05- 31 genes were significantly depleted in the dHyperLbCas12a-KRAB\ncondition, five in the dHyperLbCas12a-4xSID condition, one in the dEnAsCas12a-KRAB\ncondition, and zero in the dEnAsCas12a-4xSID condition (Supp. Table 2). Comparing\nthese hits to DepMap gene essentiality data for A549 cells, we find that the\ndHyperLbCas12a-KRAB hits are strongly enriched in highly essential genes (gene effect\n≤ -1)72 (Supp. Fig 10). Furthermore, we note that the effects of dHyperLbCas12a-4xSID\nwere stronger than those of either As repressor and the most closely correlated with\ndHyperLbCas12a-KRAB (R = 0.68 vs. R = 0.38 for dEnAsCas12a-KRAB and R = 0.13\nfor dEnAsCas12a-4xSID), even if they did not achieve significance.\nThe outcome of this screen strongly drives home the point that dHyperLbCas12a-KRAB has far\nstronger activity in high-throughput repression screens than other dCas12a repressors.\n2.It’s reported that RNA Pol II promoter CAG could improve the dCas12a pre-crRNA expression of\nlong arrays, such as over 40 crRNAs. Explain or supplement experimental evidence for why CAG\nwas chosen over other RNA Pol II promoters.\nCAG was chosen because it is widely used and well known to be a strong promoter that gives\nconsistent high transcription across many cell types and DNA delivery mechanisms (Ref. 49).\nHowever, we believe that any Pol II promoter would be effective for the transcription of Cas12a\ncrRNA arrays and not specifically dependent on CAG. This rationale for choosing CAG is now\nincluded in the text on lines 146-147 and reads:\nWe then expressed the pre-crRNAs via the RNA pol III promoter U6 or the RNA pol II\npromoter CAG, which was chosen due to its consistently high transcription across many\ncell types and DNA delivery mechanisms.\n3.Explain why chose the transcriptional regulatory elements VPR, P300, KRAB and 4xSID, not other\nsuch as SAM, Tet et al.\nVPR and KRAB were chosen due to their widespread use in the literature and demonstrated success when\nfused to dCas12a. 4xSID and P300 were chosen since they have previously been shown to strongly repress or\nactivate transcription, respectively, from enhancer elements. Additionally, P300 is a single subunit that is\ndirectly fused to the CRISPR protein (unlike SAM), and 4xSID had been shown to work with KRAB to strongly\nrepress genes as a 4xSID-dCas9-KRAB fusion. However, we believe it is possible to directly fuse other\nepigenetic modifying domains to dCas12a in order to repress or activate transcription.\nIt would be helpful to include more context on how this system compares to other multiplexed gene\nediting techniques, such as multiplexed CRISPRa or CRISPRi, particularly in terms of efficiency,\ncost, and ease of implementation.\nThank you for this suggestion. In this revised manuscript, we have added text to the discussion on how\ndCas12a compares to other multiplexed systems for CRISPRi and CRISPRa. That text is on lines 764-770\nand reads:\nWe believe that, compared to dCas9-based multiplexed epigenome editing strategies,\nthis type of combinatorial screening allows for much more highly-multiplexed\nexperiments, can enable more efficient gene activation or repression via multiple crRNAs\ntargeting the same promoter, and is cheaper to synthesize due to shorter crRNA length.\nAdditionally, while high MOI screens coupled with single cell sequencing technologies\ncan allow for delivery of many dCas9 gRNAs, these experiments limit library size and are\nmuch more expensive and technically complex than the screening strategy presented\nhere\n4.The data showed that dCas12a-VPR is significantly better than dCas12a-P300, but the author\nstated that dCas12a-P300 fusions robustly activate gene expression. Please explain this. The authors\nshould add more sites to compare the activity of dCas12a-P300 and dCas12a-VPR when targeting a\ngene enhancer and/or promoter.\nStudies using dCas9 have addressed this point, and found that both activators can be used to\nactivate gene expression. One challenge is that VPR has been more often used to target promoters,\nwhile P300 has been used more to activate gene expression from distal regulatory elements. We\nagree a systematic evaluation of the activity of these activators remains to be completed, but that\ndoing so would involve a dedicated study focused on evaluating these activators across many\npromoters and regulatory elements. Because of that, we feel that it’s beyond the scope of this paper.\n5.Provide more detail on the hybrid pre-crRNA array strategy for simultaneous activation and\nrepression, such as fornt or back combination of crRNA for activation and repression. Include a\ndiscussion on whether this approach could be extended to other types of dCas effectors, such as\nthose for DNA methylation or histone modification.\nThank you for this suggestion. In the revised manuscript, we performed an experiment to expand the\nhybrid pre-crRNA strategy to include using dEnAsCas12a repressors and dHyperLbCas12a\nactivators. This data is presented in. Supp. Fig 6c-f and summarized on lines 489-501. For\nconvenience, that new text is reproduced below:\nTo generalize this result, we also designed and tested a similar pre-crRNA containing the\nsame crRNA sequences, but with dHyperLbCas12a activators and dEnAsCas12a\nrepressors. As before, we first tested the ability of single dCas12a effectors to use the\npre-crRNA and found that dHyperLbCas12a-VPR and dEnAsCas12a-KRAB could\nsignificantly activate or repress the target genes when co-transfected with the hybrid\ncrRNA (Supp. Fig 6c-d). We next co-transfected a dHyperLbCas12a Cas12a activator\nand a dEnAsCas12a repressor along with the hybrid pre-crRNA into HEK293T cells. We\nfound that dHyperLbCas12-VPR was able to significantly activate both target genes (p <\n0.05, FDR-adjusted Student’s T-test), but dEnAsCas12a-KRAB was unable to repress\neither target gene (Supp. Fig 6e). Meanwhile, the combination of\ndHyperLbCas12a-P300 and dEnAsCas12a-SID was able to significantly activate HBE1\nand MYOD1 expression while significantly repressing RAB11A expression (p < 0.01,\nFDR-adjusted Student’s T-test), but not MYC expression (p = 0.172, FDR-adjusted\nStudent’s T-test) (Supp. Fig 6f).\nWe also added text to the discussion on possibilities for expanding this approach to the discussion.\nThe text is on line 787-792 and reads:\nHere, we demonstrate an alternative approach using a hybrid dCas12a pre-crRNA to\nsimultaneously activate two genes and repress two genes. That strategy can be\nexpanded in several ways. For example, it is likely, given the compatibility with\ndCas12a-VPR, P300, KRAB, and 4xSID, that the system could be expanded to other\ndCas12a epigenetic fusions or nuclease active Cas12a. It is also likely that other\nCRISPR proteins that process their own pre-crRNAs, such as Cas13a, could be added\n6.Expand the discussion on potential off-target effects, particularly when using multiplexed crRNA\narrays. Although only at the cellular level of high throughput screening, include experiments or\nsimulations that demonstrate the safety of the system in minimizing off-target interactions.\nThank you for raising this point. We agree that this is an important area of future study, and highlight\nthat in the discussion on line 805-808:\nA final challenge will be understanding the profile of off-target effects and how they scale\nwith the number of crRNAs contained in each array. We expect that a full understanding\nof those off-target events would require genome editing to stably record (Ref. 82-83).\n7.In the figures section, appropriate statistical analysis should be conducted, and p-value indicated to\nassess the authors’ claim.\nTo supplement the discussion of p values in the text, we have now added asterisks to Fig. 2-7 and\nSupp. Figs 1, 2, 4, 6, and 10 to denote significance where appropriate.\n8.The manuscript would benefit from a more detailed description of the statistical methods used to\nanalyze gene expression changes, particularly in high-throughput screens. Specify how multiple\nhypothesis testing was corrected and how significant results were defined.\nThank you for this suggestion. We have now added these details in the revised manuscript.\n9.In general, the biological replicates are 3 or over. Thus, it is recommended that for activity\ncomparison of among these variants, while many group in this article only one set. This is not\nrigorous.\nThank you for your comment. We have ensured that all data represent at least two biological\nreplicates. However, some of our boxplots were previously overplotted, and in this revised manuscript\nwe have increased jitter in Fig. 2-7 to more clearly show the number of data points represented for\neach condition. A full summary of statistical tests performed is available in Supp. Table 1.\nReviewer #4:\nThis manuscript presents the development and characterization of dCas12a-based gene silencing\nand activation using two distinct dCas12a variants. The authors employed enhanced versions of\ndCas12a, enAsCas12a and HyperLbCas12a, along with crRNA arrays to modulate gene expression.\nThey demonstrate that dCas12a can be coupled with the activation domain P300 and the repression\ndomain SID. They show simultaneous activation and repression of target genes through a single\ncrRNA array by co-expressing both enAsCas12a and HyperLbCas12a. Furthermore, they illustrate\nthe platform's utility in screening applications using a barcoded library of crRNA arrays targeting two\nenhancers of a single gene.\nOverall, the study offers a side-by-side comparison of gene activation and repression across two\ndifferent Cas12a systems. It provides a resource for using AsCas12a and LbCas12a variants in gene\nregulation. For example, the observation that dLbCas12a-P300 fusions exhibit stronger and more\nconsistent activation than dAsCas12a-P300 fusions is interesting. While the fusion of Cas12a to P300\nand SID is new, these tools do not outperform established systems such as VPR for activation and\nKRAB for repression.\nHowever, the manuscript raises major concerns that should be addressed before it can be considered\nfor publication:\n1. The potential for crosstalk between the two Cas12a variants should be thoroughly evaluated. Both\nvariants utilize the same PAM and share similar guide RNA structures. This raises concerns about\ntheir orthogonality. To confirm their suitability for simultaneous activation and repression, the authors\nshould demonstrate that each Cas12a does not interact with the other's guide RNA. Additional\nexperimental data are required to validate their orthogonality and crosstalk.\nThank you for this comment, we have performed additional experiments to address these concerns.\nThe data is shown in Supp. Fig. 6g-h and the text on lines 510-531 describing them reads:\nTo evaluate crosstalk in such a setting, we co-transfected dHyperLbCas12a-VPR with\nthe hybrid pre-crRNA containing AsCas12a crRNAs for activation as well as either\ndEnAsCas12a or Cas9 as a transfection control for number and size of plasmids. We\nfound that, by itself, dHyperLbCas12a-VPR can use AsCas12a crRNAs but with less\nefficacy than homologous LbCas12a crRNAs. Specifically, when dHyperLbCas12a-VPR\nwas cotransfected with Cas9, there was 150-fold activation of HBE1 and no significant\nactivation of MYOD1 (Supp. Fig 6g). The observed activation of HBE1 was ~30-fold\nless than when dHyperLbCas12a-VPR was co-transfected with its homologous hybrid\npre-crRNA array (Supp. Fig 6a).\nHowever, that crosstalk is alleviated when dHyperLbCas12a and dEnAsCas12a are both\npresent and competing for crRNAs. Specifically, when dHyperLbCas12a-VPR was\nco-transfected with dEnAsCas12a, we observed no significant activation of either gene,\nand relative HBE1 expression dropped to a 1.25-fold change over non-targeting control\n(Supp. Fig 6g).\nThat result was essentially similar when we tested dEnAsCas12a-VPR in the same way.\nSpecifically, dEnAsCas12a-VPR was able to significantly activate HBE1 by ~6.5 fold\nusing LbCas12a crRNAs when co-transfected with Cas9. However, there was no effect\nwhen dEnAsCas12a-VPR was co-transfected with dHyperLbCas12a (Supp. Fig 6h).\nTogether, these results confirm that while dEnAsCas12a and dHyperLbCas12a can use\northologous crRNAs for activation, they are not able to do so when the homologous\nCas12a is also present and competing for crRNAs, such as in the hybrid pre-crRNA\nsystem developed here.\n2. The title, \"Highly multiplexed epigenome editing screens,\" is misleading and overstates the study's\nscope. The manuscript demonstrates the activation of four genes, and it remains unconvincing that all\nfour genes are all activated in single cells. This falls short compared to prior studies that activated or\nrepressed a greater number of genes. Additionally, the term \"epigenome editing\" is not fully\nsubstantiated, as the authors only present transcription-level activation or repression without\ncharacterizing epigenetic modifications. Moreover, the screens are limited to targeting two enhancers,\nwhich does not align with the claim of high multiplexing. The title should be revised to accurately\nreflect the data presented in the study.\nThank you for this comment, we have revised the title to “HyperCas12a enables multiplexed CRISPRi\nscreens”, which we believe better reflects the scope of the study.\n3. It is unclear how most data were collected. For example, how was flow cytometry gating defined?\nHow many replicates were performed? How many biological or technical replicates were tested in\neach experimental group? Additionally, statistics are lacking in the figures, and p-values should be\nincluded.\nFlow cytometry gating is described in the methods and now shown in Supp. Figs 5, 16, and 18.\nBiological replicates are described in figure legends and p values are described in the text, and we\nhave now added asterisks to Fig. 2-7 and Supp. Figs 1, 2, 4, 6, and 10 to denote significance where\nappropriate. We also increased jitter in Fig. 2-7 so that the number of replicates can be more clearly\nseen in the figures. A full summary of statistical tests performed is available in Supp. Table 1.\n4. Although the authors tested a few cell lines for characterization, the study would have\ngreater utility if additional cell types, particularly primary cells, were included. This would\nenhance the relevance and applicability of the findings for the community.\nThank you for this comment. Addressing this comment was one of the major focuses of our revised\nmanuscript. We performed numerous additional experiments to address these concerns. We tested\nthe effects of stably expressed dCas12a effectors and pre-crRNA arrays in primary human T Cells\nand iPSCs. The results of these experiments are displayed in Fig. 2h-j and Fig. 4e-h. The text related\nto the T cell repression results in on line 284-292 and reads:\nNext, we co-transduced human T cells from three independent donors with\ndHyperLbCas12a-KRAB or dEnAsCas12a-KRAB and either a pre-crRNA targeting the\npromoters of SLA2, GATA3, MAP4K1, GRAP, and LAT2 or a control pre-crRNA\ncontaining ten non-targeting crRNAs (Fig. 2h). We observe similar trends for both\nCas12a orthologues. For example, both dEnAsCas12a- and dHyperLbCas12a-KRAB\nshowed the strongest repression of GRAP and LAT2, though dHyperLbCas12a showed\nstronger repression (mean log fold change across donors of -0.89 and -0.87 vs. -0.47\n2\nand -0.42) consistent with our previous findings (Fig. 2i-j). While we do not observe\neffects for all target genes in this cell type, these results indicate the potential of using\ndCas12a for multiplexed repression in primary cells.\nThe text related to activation experiments in T Cells and iPSCs reads is on lines 397-440 and reads:\nModel systems for studying primary cell differentiation commonly involve controlling the\nexpression of several genes at once16,69. As a key step towards such highly multiplexed\ncontrol of gene regulation in primary cells, we focused on demonstrating dCas12a-based\ngene activation in T cells and in an human induced pluripotent stem cell (iPSC)-based\nmodel of neuronal differentiation.\nTo demonstrate multiplexed control of gene expression in T cells, we co-transduced\ndHyperLbCas12a-VPR along with the pre-crRNA targeting AR, HBE1 and MYOD1 into\nprimary human CD3+ T cells from three different donors. The results were similar to\nthose observed in cell lines, namely that there was significant activation (p < 0.05,\nOne-Sided Student's Paired T-Test) of HBE1 and MYOD1, with effects ranging from\n~45-350-fold upregulation (Fig.4e). Also as in the cell lines, there was little or no\nactivation of AR gene expression.\nTo demonstrate multiplexed control of gene expression in iPSC cell differentiation, we\nused an iPSC cell line that had previously been modified to express mCherry\ncotranslationally with TUBB3A, a marker of neuronal differentiation13. We further\nmodified the line to stably express dHyperLbCas12a-VPR. We designed a pre-crRNA\narray of three crRNAs to target the promoter of NGN3, a strong driver of neuronal\ndifferentiation, to act as a positive control. We also designed a pre-crRNA array\ncontaining seven crRNAs that target three core neurogenic transcription factors (deemed\n“Core”): NGN1, NGN2, and NGN3. We designed a pre-crRNA array containing seven\ncrRNAs that target four accessory genes that have been shown to enhance neuronal\ndifferentiation when co-activated in tandem with a core factor (deemed “Accessory”):\nLHX6, LHX8, SOX2, and E2F713. Lastly, we designed a pre-crRNA array containing all\n14 crRNAs and targeting both core and accessory factors together (deemed\n“Core+Accessory”) (Fig. 4f).\nWe transduced the dHyperLbCas12a-VPR cell line with these pre-crRNAs and then\nmeasured the percentage of cells that were mCherry positive when gating such that ~1%\nof cells transduced with a pre-crRNA array containing non-targeting control crRNAs are\nmCherry positive (Fig. 4g, Supp. Fig 5). We find that ~4% of cells that received the\nNGN3 targeting array are mCherry positive, while ~1.25% of cells that received the\n“core” pre-crRNA array and ~3.5% of cells that received the “Core+Accessory”\npre-crRNA array are mCherry positive. As expected, activation of the accessory factors\nalone did not lead to an increase in mCherry positive cells over control (Fig. 4h). While\nwe did not observe higher rates of mCherry positive cells in the Core or Core+Accessory\nconditions vs. the NGN3-targeting array, we do observe an (~3x) increase in mCherry\npositive cells between Core and Core+Accessory conditions, suggesting increased\ndifferentiation efficiency due to multiplexed activation. Furthermore, we observe\nincreased (~2x) MFI of the mCherry positive population in the Core+Accessory condition\nvs. both the NGN3 and core conditions, suggesting higher TUBB3A expression in these\ncells (Fig. 4i).\nTogether, these results demonstrate that dCas12a activators are capable of multiplexed\nactivation of gene expression in multiple primary cell systems in which dCas12a\neffectors have been integrated and remain stably expressed.\n5. The inclusion of a control library with 10,000 non-targeting six-crRNA arrays and three pre-crRNAs\ntargeting the PER1 promoter seems excessive. The rationale for this large imbalance between\nnon-targeting and targeting arrays should be clarified. How does this control design contribute to the\nstudy's objectives?\nSince most of the targeting library is composed of pre-crRNA arrays targeting both enhancers, it\nwould be difficult to detect depletion from the high (top 12.5%) PER1 expression bin and enrichment\nin the low (bottom 12.5%) PER1 expression bin if only a small fraction of the library was composed of\nnon-targeting pre-crRNA arrays. We included many non-targeting pre-crRNA arrays so that we could\ndetect whether the pre-crRNA arrays targeting both enhancers were well separated from negative\ncontrols and conservatively designed our library to contain ~50% non-targeting pre-crRNAs arrays\nand ~50% dual-targeting pre-crRNA arrays.\nWe have added text to the manuscript to justify this design choice on lines 648-652. It reads:\nIn parallel, we separately constructed a control library of 10,000 non-targeting six-crRNA\narrays and three pre-crRNAs targeting the PER1 promoter (Supp. Fig 13). Since most\n(80%) of the PER1-targeting library consists of pre-crRNAs targeting both enhancers,\nthis large control library will enable better separation between cells with high and low\nPER1 expression.\n6. The diagrams in Fig. 7b-d are confusing. Are these plots representing PER1-high cells or\nPER1-low cells? A more detailed explanation of how these plots were generated is necessary to help\nunderstanding.\nThank you for this comment. We originally showed the average of the two bins, but have revised Fig.\n8 (previously Fig. 7) to show the high and low bin separately since this is how we refer to the data in\nthe text.\n7. The purpose of testing the two enhancers using a large library is unclear. The authors should\nelaborate on why not use a few well-designed crRNA arrays to target individual or paired enhancers\nand measure the downstream gene expression? It is unclear if there is a necessity of performing\nlibrary screening on two enhancers of one gene. Furthermore, the insights gained from testing PER1\nenhancers can be strengthened.\nIdentifying interactions between gene regulatory elements remains a major challenge for numerous\ntechnical, biological, and statistical reasons. Specifically, experimental noise, potentially weak\nbiological effects, and the compounding of those factors in statistical analyses typically leaves studies\nof genetic interactions highly underpowered. Using rough estimates of how those factors would\nimpact the new dCas12a systems developed here, we developed a screen where we were highly\nconfident in our statistical power. Indeed, we feel that the depth of analysis in this screen can serve\nas a starting point for more formal power analyses to guide future study designs.\nTo clarify that point to readers, we added the following text to the discussion on lines 813-816:\nA key observation from our screen of the PER1 locus is that identifying epistatic\ninteractions in gene regulation requires a great degree of replication, and we\nexpect that the outcomes of our study can be useful for power analyses to design\nfuture such screens.\n8. The manuscript would benefit from discussing specific design rules for guide RNA arrays.\nWe believe that we address this concern throughout the manuscript. Specifically, we observed that\ncrRNAs towards the end of an array have low activity, but that this can be rescued by using an RNA\nPol II promoter. We do not observe clear evidence of positional effects in the PER1 enhancer screen.\nWe looked further into that screen data and did find crRNAs that, when included in the array, led to\nsignificantly stronger or weaker repression. This data is shown in Supp. Fig. 17, and text describing\nthese results on lines 705-714 and is reproduced below:\nWe did not find strong evidence for substantial heterogeneity in the effects of the\nindividual crRNAs. Specifically, we tested if, when targeting enhancer A or B individually,\nany of the crRNAs consistently increased or decreased the effect of the pre-crRNA array\n(Supp. Table 3). In the 100 nM Dex high bin, 2 of the 9 crRNAs targeting enhancer A\nhad significant effects and 6 of the 9 crRNAs targeting enhancer B had a significant\neffect (FDR < 0.05). Of those eight crRNAs with significant effects, four increased crRNA\narray activity, and four decreased that activity. However, the magnitude of those effects\nwere small, with changes in mean pre-crRNA enrichment of between 10% and 36%\nwhen those crRNAs were present (Supp. Fig 17a-c). The individual crRNA effects also\ndid not correlate with GC content or the on-target activity score predicted by CRISPick\n(Supp. Table 3).\nSince there are only 18 unique crRNAs in the screen, we feel that there is not sufficient data to\ncomment decisively about positioning or design rules.\n9. Citations 73-74: The manuscript does not appropriately cite work on Cas13. The authors should\nensure they reference the most relevant studies.\nThank you for this comment, we now cite:\nEast-Seletsky, A., O’Connell, M., Knight, S. et al. Two distinct RNase activities of CRISPR-C2c2 enable\nguide-RNA processing and RNA detection. Nature 538, 270–273 (2016).\nhttps://doi.org/10.1038/nature19802\nTo substantiate our claim that Cas13a can process its own crRNA array."}, {"round": 2, "reviewer_comments": {"reviewer_1": "This is a well-executed and thoughtfully revised manuscript. I commend the authors for incorporating targeted gene activation in primary cells, which adds significant value beyond standard cell line models. Their acknowledgment of the differences in performance compared to HEK293T cells provides important perspective. I also appreciate the authors’ transparency in noting that not all target genes respond equally to activation—an important consideration for future studies, particularly those with therapeutic aims.", "reviewer_2": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts.", "reviewer_3": "“The data showed that dCas12a-VPR is significantly better than dCas12a-P300, but the author stated that dCas12a-P300 fusions robustly activate gene expression. Please explain this. The authors should add more sites to compare the activity of dCas12a-P300 and dCas12a-VPR when targeting a gene enhancer and/or promoter.”\nRegarding this question, the authors did not provide a reasonable response. The authors state that \"dCas12a-P300 fusions robustly activate gene expression\", but this conclusion cannot be drawn from their data, which instead shows that dCas12a-VPR has higher activity. Moreover, while the authors claim dCas12a-P300 is more suitable for gene activation expression from distal regulatory elements, the data indicates that dCas12a-VPR exhibits higher activity targeting MYOD1 distal regulatory region (DRR). The authors need to clarify the purpose of comparing the activity between enAsCas12a and LbCas12a, not dhyperCas12a in the Supp Fig. 3c-f. Similarly, the statement \"dCas12a-P300 fusions enable multiplexed gene activation in human cell lines\" is problematic. We recommend the authors revise the title and provide clearer descriptions.\nThe authors have appropriately supplemented the data or reasonably addressed other comments.", "reviewer_4": "This revised manuscript introduces the simultaneous regulation of multiple genes, by expressing crRNA arrays from an RNA polymerase II promoter, using engineered dCas12a variants, dHyperLbCas12a and dEnAsCas12a. In addition to activation domain VPR and repression domain KRAB, they demonstrated that dCas12a can be coupled with activation domain P300 and repression domain 4xSID. They showed the platform’s capability with multiple cell lines: cancer cell lines, human T cells, and iPSCs. They further validate their approach in two screenings: a low MOI fitness screen and an enhancer screen that assessed dose-dependent control of PER1 by two glucocorticoid-responsive enhancers. This side-by-side comparison of dHyperLbCas12a-KRAB, dHyperLbCas12a-4xSID, dEnAsCas12a-KRAB, and dEnAsCas12a-4xSID in low MOI fitness screen illustrated that dHyperLbCas12a-KRAB carries stronger activity. While the revision represents a clear improvement over the prior submission, several issues remain and should be addressed before the work is considered for publication.\nMajor comments:\n1. In Figure 2, authors show data for the simultaneous repression of 4 genes in HEK cells and 5 genes in primary T cells. However, in primary T cells, repression is not statistically significant across all target genes and donors. This suggests that multiplex repression is cell-type dependent, which is a limitation to their screening application. This cell-type dependent and gene-dependent performance should be acknowledged in the text.\n2. This sentence is ambiguous: \"While we do not observe effects for all target genes in this cell type, these results indicate the potential of using dCas12a for multiplexed repression in primary cells.\" The authors should clarify and revise this text.\n3. Authors showed activation of core and accessory neuronal differentiation genes can induce moderate expression of TUBB3. However, what is the benefit or advantage of using this system for cell differentiation? TUBB3 is an early marker for differentiation; it doesn’t indicate full neuronal identity.\n4. Improving the visualization in Figure 8 to more clearly distinguish between enhancer level and shift would help convey the message more effectively. For example, adding a bar indicating the mean value for each group and statistical tests.\n5. What has been learned from their enhancer screening? The manuscript would benefit from biological insights learned from their screening.\n6. In their qPCR method, it is important to clarify how many technical replicates were performed.\n7. P-values are noted in the caption of Figure 2. The authors didn't label any P-values in the figures. In Figure 1, there is no statistical comparison between the control and experimental groups.\n8. The authors should include clear explanation why in Fig. 4g “Core+Accessory” shows similar or slightly weaker mCherry+ cells% compared to “NGN3”, but in Fig. 4h mCherry MFI is higher for “Core+Accessory”. This is a discrepancy that should be explained.\n9. The authors should pay close attention to statistics and clearly label them in the figure or caption. Raw flow cytometry and qPCR data and screening results should be made publicly available.\nMinor comments:\n1. The way authors labeled supplementary data is inconsistent. Some are Supp Fig xx, some are Supp. Fig xx and Supplementary Fig. xx.\n2. In Figure 4, does dHyperLbCas12a-P300 work in primary T cells?\n3. The title said “HyperCas12a enables multiplexed CRISPRi screens”, but to be precise, they used HyperdCas12a, the catalytically dead version.\n4. Fig S6g-h: the figure legend or the figure itself should clearly state which crRNA these diagrams use.\n5. Line 486: duplicate words", "reviewer_5": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts."}, "author_response": "REVIEWER COMMENTS\nReviewer #1\nMinor comments:\n- Figures with box plots: Plotting the individual dots for each measurement would benefit from\nadded jitter to identify each dot and prevent overplotting. This will enable viewers to see if\nthere were dropouts (n=2 instead of n=3)\nThank you for the suggestion, we have added jitter to all boxplots in Figs. 1-5, Fig. 7, Supp. Fig. 1-6,\nand Supp. Fig. 10 so that readers can better see the spread of the data and number of replicates.\n- Figure 1 c -e: the use of red for the front and back cRNAs, the HBE1 gene, and the CAG\npromoter is very confusing. This figure would benefit from consistency in color choice. For\nexample, Fig 1c could have 4 constructs shown with U6 and CAG separated, and the color\nwould then be used in Fig 1d and 1e again.\nThank you for the feedback. We updated the diagram in figure 1c to show U6 and CAG separated,\ncolored them blue and orange, and then incorporated this color scheme in Fig. 1d-e. Red is now only\nused to represent HBE1 and the crRNAs that target it.\n- Also, since some people might be color blind, the color for AS and LB in Figures 1a and 1b\nmight be problematic\nWe have now changed the AsCas12a color in Figs. 1a and 1b from red to brown in this revised\nmanuscript in order to be more color blind friendly.\n- The main text could explain the choice of crRNA sequences or reference previously\nestablished sequences.\nThank you for the suggestion. In the revised manuscript, we have noted in the text when a crRNA\nsequence was originally reported in a previous study. This applies to the AR, HBB (Supp. Fig. 3),\nand\nPIK3C3 spacer sequences used in the study as well as one of the RAB5A spacer sequences used.\n- In Figure 2 f-g, which demonstrates multiplexed repression of multiple target genes - the\n4xSID fusion represses slightly better than the KRAB fusion. This is compared to figures 2c\nand 2d, where it appears to be the other way around for RAB11A. Are the targeting crRNAs for\nRAB11A and VEGFA identical across Figures 2c-d and 2f-g? Does the positioning or\nthe multiplexing of the target crRNAs for Fig 2f-g attribute to differences in repression?\nYes, the crRNAs are identical across these two arrays. Due to the design of the study, we cannot say\nwhether the multiplexing and/or position of the RAB11A-targeting crRNAs leads to the differences in\nactivity.\n- Fig 2 e-g: The authors chose to measure repression of RNA after 48h. Since repression of\nRNA is also dependent on RNA stability and KRAB vs Sin3A repression might have different\ndynamics, a time point at 72h or 96h post-transduction would help to understand if the\nrepressive strength is time-dependent or not.\nThank you for raising this point. We believe the reviewer is talking to transfection experiments and not\ntransduction experiments. The difficulty with studying time-dependent transfection effects is that\nchanges in repressive strength are confounded by intercellular plasmid abundance which changes\nover cell division. For that reason, we expect time dependence to vary across different models and\nrequire optimization for each experiment.\n- Figure 4: It would be helpful to have the statistical analysis depicted right in the figure (e.g.\nlines indicating the samples compared and asterisk for levels of significance)\nThank you for this comment, we have added asterisks to Fig. 2-7 and Supp. Figs 1, 2, 4, 6, and 11 to\ndenote significance where appropriate in this revised manuscript.\n- Figure 4: Labeling the target genes above the panels and not only using color to denote\ntarget genes helps clarity\nThank you for this suggestion, we have added target gene names to Fig. 2-4 in the revised\nmanuscript.\n- In addition, to help the reader judge fold activation and repression, please add TPM\n(transcript per million from gene expression data sets) for each target gene next to the gene\nlabel. 3,200-fold activation is likely only possible on non-expressed genes vs 2-fold activation\non a different target gene.\nThank you for this comment. We have added nTPM values from the Human Protein Atlas to the figure\nlegends so that readers can better contextualize activation or repression relative to baseline gene\nexpression level. The nTPMs are also listed all together as part of Supp. Table 1.\n- Figure 5: The two Cas12a orthologues have been shown to confer different transcriptional\neffects. Did the authors also test using dHyperLbCas12a for activation and dEnAsCas12a for\nrepression?\nThank you for this suggestion. To address that point in the revision, we performed experiments that\ntested the hybrid array system with dHyperLbCas12a activators and dEnAsCas12a repressors.\nThese data are presented in Supp. Fig 6c-f and summarized on lines 489-501. For convenience, that\nnew text is reproduced below:\nTo generalize this result, we also designed and tested a similar pre-crRNA containing the\nsame crRNA sequences, but with dHyperLbCas12a activators and dEnAsCas12a\nrepressors. As before, we first tested the ability of single dCas12a effectors to use the\npre-crRNA and found that dHyperLbCas12a-VPR and dEnAsCas12a-KRAB could\nsignificantly activate or repress the target genes when co-transfected with the hybrid\ncrRNA (Supp. Fig 6c-d). We next co-transfected a dHyperLbCas12a Cas12a activator\nand a dEnAsCas12a repressor along with the hybrid pre-crRNA into HEK293T cells. We\nfound that dHyperLbCas12-VPR was able to significantly activate both target genes (p <\n0.05, FDR-adjusted Student’s T-test), but dEnAsCas12a-KRAB was unable to repress\neither target gene (Supp. Fig 6e). Meanwhile, the combination of\ndHyperLbCas12a-P300 and dEnAsCas12a-SID was able to significantly activate HBE1\nand MYOD1 expression while significantly repressing RAB11A expression (p < 0.01,\nFDR-adjusted Student’s T-test), but not MYC expression (p = 0.172, FDR-adjusted\nStudent’s T-test) (Supp. Fig 6f).\n- No comment or experiment has been performed to address the stability of the epigenome\nedits. While I wouldn’t expect this to be done for every cell and target gene presented, it would\nbe interesting to know how quickly the enhancers of PER1 will be reset after targeted\nrepression, for example.\nThe stability of epigenome edits remains a major opportunity for study in the field. However, fully\naddressing this, e.g. with time course ChIP-Seq studies, we feel is beyond the scope of this\nmanuscript.\n- Figure 7 and the experiment screening crRNAs to repress PER1 enhancers: The analysis of\nwhich crRNAs were most effective at promoting enhancer silencing was not performed. It\nwould be beneficial for the reader to understand if there are any rules or considerations for\ncrRNA positioning relative to CREs.\nThank you for raising this point. We dug into our data and did find crRNAs that, when included in the\narray, led to significantly stronger or weaker repression. This data is shown in Supp. Fig. 17, and text\ndescribing these results on lines 705-714 and is reproduced below:\nWe did not find strong evidence for substantial heterogeneity in the effects of the\nindividual crRNAs. Specifically, we tested if, when targeting enhancer A or B individually,\nany of the crRNAs consistently increased or decreased the effect of the pre-crRNA array\n(Supp. Table 3). In the 100 nM Dex high bin, 2 of the 9 crRNAs targeting enhancer A\nhad significant effects and 6 of the 9 crRNAs targeting enhancer B had a significant\neffect (FDR < 0.05). Of those eight crRNAs with significant effects, four increased crRNA\narray activity, and four decreased that activity. However, the magnitude of those effects\nwere small, with changes in mean pre-crRNA enrichment of between 10% and 36%\nwhen those crRNAs were present (Supp. Fig 17a-c). The individual crRNA effects also\ndid not correlate with GC content or the on-target activity score predicted by CRISPick\n(Supp. Table 3).\nSince there are only 18 unique crRNAs in the screen, we feel that there is not sufficient\ndata to comment decisively about positioning or design rules.\nReviewer #2:\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the\nNature Communications initiative to facilitate training in peer review and to provide appropriate recognition for\nEarly Career Researchers who co-review manuscripts.\nReviewer #3:\nIn the current manuscript, Melore et al. has combined dHyperLbCas12a with RNA Polymerase II expression of\nlong crRNA for efficient highly-multiplexed epigenome editing. The authors have demonstrated that\ndHyperLbCas12a is compatible with different activation and repression domains. The authors further showed\nthat this system can perform simultaneous activation and repression using a single crRNA array, and is\neffective for high-throught screens. Based on these, the authors use dHyperLbCas12a-KRAB and a barcoded\nlibrary of crRNA arrays for dissecting the cis-regulatory architecture for a dose-dependent gene expression\nresponse to glucocorticoids.\nOverall, the study is interesting and the findings are useful to the multiplexed gene expression regulation\nsubfield. However, the study is minimal on its novelty in terms of the methods it employed. The novelty and\nimportance of dCas12a mediated the multiplexed activation and repression have been well-demonstrated\nalready in previous publication. Perhaps, the authors can expand on some other high-throughput screening\napplications and . In addtion, some data are robust and not enough. Here are some comments and\nsuggestions for the authors to improve the quality of the work.\n1.The authors state that they optimized the dCas12a epigenome editing system, but both the Cas protein and\nthe regulatory elements have been reported before. Explain why chose these Cas12a variants, and not other\nvariants or even other family such as Cas12i. And the statement that dHyperLbCas12a and dEnAsCas12a\noutperform the wild type dCas12a variants for epigenome editing, has been already reported.\nThank you for raising this point. While these variants have been previously reported, they have not\nbeen compared head-to-head in a single study, and AsCas12a Ultra had not been used for CRISPRi\nor CRISPRa before. Therefore, it was unclear which variant(s) had the strongest epigenome editing\nactivity. We have clarified this in text, on lines 97-102, which now reads:\nIn addition to the wild-type Cas12a from Acidaminococcus sp. BV3L6 (As) and\nLachnospiraceae bacterium (Lb), several engineered Cas12a versions with improved\nactivity have been recently published46–48. However, these variants have not all been\nused for epigenome editing, nor has their activation and repression strength been\ncompared head-to-head in a single study. We systematically compared the strength of\ngene activation and gene repression across five dCas12a variants…\nOne of the major outcomes of this work, that dHyperLbCas12a is suited for low MOI\nscreens, is a novel advance that came out of these comparisons.\nIn addition, it is recommended to add more sites to compare the activity of encas12a and\nhypercas12a.\nThank you for this suggestion. More comprehensively comparing dEnAsCas12a and\ndHyperLbCas12a was one of the major focuses of this revision. In order to compare dEnAsCas12a\nand dHyperLbCas12a over a large number of sites (n = 219), we performed for these revisions a low\nMOI fitness screen to target essential genes or olfactory receptor controls in A549 cells using\ndEnAsCas12a-KRAB, dEnAsCas12a-4xSID, dHyperLbCas12a-KRAB, and dHyperLbCas12a-4xSID.\nThis data is presented in Fig. 6 and Supp. Fig 7-9. That text is found on lines 548-591 of the text and\nreads:\nTo enable large-scale comparison of the dCas12a repressors described above and to\nassess their suitability for use in screening applications, we performed a screen of genes\nthat are predicted to impact cell proliferation. We created a library containing 171\npre-crRNAs targeting the promoters of 145 core essential genes71, 48 pre-crRNAs\ntargeting the promoters of 20 cell surface control genes45, 50 non-targeting pre-crRNAs,\nand 25 intergenic control crRNAs. Each pre-crRNA contained four crRNAs, and we\nrequired that all gene targets have at least four crRNAs with CRISPick on-target\nefficiency score of ≥ 30%. We created an As and Lb Cas12a version of this library using\nthe same spacer sequences but As- or Lb-specific direct repeats.\nNext, we transduced the appropriate library at an MOI of 0.2 into A549 cells stably\nexpressing either dHyperLbCas12a-KRAB, dHyperLbCas12a-4xSID,\ndEnAsCas12a-KRAB, or dEnAsCas12a-4xSID, with three replicates per cell line. Cells\nwere selected for crRNA expression using puromycin, and cell pellets were collected to\nassess relative pre-crRNA abundance at 5, 7, 14, and 21 days post-transduction (Fig.\n6a).\nThere was strong concordance in read counts between replicates for all Cas12a\nrepressor screens. Specifically, correlation between replicates at day 21 was R > 0.91\nfor the KRAB repressor screens and R > 0.79 for the SID repressor screens (Supp. Fig.\n7-8). The strongest and most consistent repressive effects occurred in the\ndHyperLbCas12a-KRAB screen. That screen had much higher correlation between\nreplicates for log fold changes of pre-crRNAs targeting essential genes (R > 0.8)\n2\ncompared to all the other repressors (-0.081 < R < 0.276). That screen also had greater\neffects compared to the other repressors (Fig. 6b-e, Supp. Fig. 9). Representative\nexamples for each system show genes that were significantly repressed by both\ndHyperLbCas12a repressors and dEnAsCas12-KRAB; by both dHyperLbCas12a\nrepressors but not the dEnAsCas12a repressors; and by dHyperLbCas12a-KRAB alone\n(Fig. 6h-j).\nOverall, we conclude that KRAB is a stronger repressor than 4x SID for targeting gene\npromoters, and that dHyperLbCas12a-KRAB is suitable for use in low MOI screens,\nwhile dEnAsCas12a is not. We based that conclusion on comparing effects across the\nfour screens. Using a linear model of change in log fold change over time and a\n2\nthreshold of FDR < 0.001, we detected 28 significantly depleted pre-crRNAs targeting\nessential genes in the dHyperLbCas12a-KRAB condition, five in the\ndHyperLbCas12a-4xSID condition, two in the dEnAsCas12a-KRAB condition, and zero\nin the dEnAsCas12a-4xSID condition using DeSeq2. We obtained similar results at the\ngene level when performing a time course analysis with the MAGeck MLE module and\nwald FDR < 0.05- 31 genes were significantly depleted in the dHyperLbCas12a-KRAB\ncondition, five in the dHyperLbCas12a-4xSID condition, one in the dEnAsCas12a-KRAB\ncondition, and zero in the dEnAsCas12a-4xSID condition (Supp. Table 2). Comparing\nthese hits to DepMap gene essentiality data for A549 cells, we find that the\ndHyperLbCas12a-KRAB hits are strongly enriched in highly essential genes (gene effect\n≤ -1)72 (Supp. Fig 10). Furthermore, we note that the effects of dHyperLbCas12a-4xSID\nwere stronger than those of either As repressor and the most closely correlated with\ndHyperLbCas12a-KRAB (R = 0.68 vs. R = 0.38 for dEnAsCas12a-KRAB and R = 0.13\nfor dEnAsCas12a-4xSID), even if they did not achieve significance.\nThe outcome of this screen strongly drives home the point that dHyperLbCas12a-KRAB has far\nstronger activity in high-throughput repression screens than other dCas12a repressors.\n2.It’s reported that RNA Pol II promoter CAG could improve the dCas12a pre-crRNA expression of\nlong arrays, such as over 40 crRNAs. Explain or supplement experimental evidence for why CAG\nwas chosen over other RNA Pol II promoters.\nCAG was chosen because it is widely used and well known to be a strong promoter that gives\nconsistent high transcription across many cell types and DNA delivery mechanisms (Ref. 49).\nHowever, we believe that any Pol II promoter would be effective for the transcription of Cas12a\ncrRNA arrays and not specifically dependent on CAG. This rationale for choosing CAG is now\nincluded in the text on lines 146-147 and reads:\nWe then expressed the pre-crRNAs via the RNA pol III promoter U6 or the RNA pol II\npromoter CAG, which was chosen due to its consistently high transcription across many\ncell types and DNA delivery mechanisms.\n3.Explain why chose the transcriptional regulatory elements VPR, P300, KRAB and 4xSID, not other\nsuch as SAM, Tet et al.\nVPR and KRAB were chosen due to their widespread use in the literature and demonstrated success when\nfused to dCas12a. 4xSID and P300 were chosen since they have previously been shown to strongly repress or\nactivate transcription, respectively, from enhancer elements. Additionally, P300 is a single subunit that is\ndirectly fused to the CRISPR protein (unlike SAM), and 4xSID had been shown to work with KRAB to strongly\nrepress genes as a 4xSID-dCas9-KRAB fusion. However, we believe it is possible to directly fuse other\nepigenetic modifying domains to dCas12a in order to repress or activate transcription.\nIt would be helpful to include more context on how this system compares to other multiplexed gene\nediting techniques, such as multiplexed CRISPRa or CRISPRi, particularly in terms of efficiency,\ncost, and ease of implementation.\nThank you for this suggestion. In this revised manuscript, we have added text to the discussion on how\ndCas12a compares to other multiplexed systems for CRISPRi and CRISPRa. That text is on lines 764-770\nand reads:\nWe believe that, compared to dCas9-based multiplexed epigenome editing strategies,\nthis type of combinatorial screening allows for much more highly-multiplexed\nexperiments, can enable more efficient gene activation or repression via multiple crRNAs\ntargeting the same promoter, and is cheaper to synthesize due to shorter crRNA length.\nAdditionally, while high MOI screens coupled with single cell sequencing technologies\ncan allow for delivery of many dCas9 gRNAs, these experiments limit library size and are\nmuch more expensive and technically complex than the screening strategy presented\nhere\n4.The data showed that dCas12a-VPR is significantly better than dCas12a-P300, but the author\nstated that dCas12a-P300 fusions robustly activate gene expression. Please explain this. The authors\nshould add more sites to compare the activity of dCas12a-P300 and dCas12a-VPR when targeting a\ngene enhancer and/or promoter.\nStudies using dCas9 have addressed this point, and found that both activators can be used to\nactivate gene expression. One challenge is that VPR has been more often used to target promoters,\nwhile P300 has been used more to activate gene expression from distal regulatory elements. We\nagree a systematic evaluation of the activity of these activators remains to be completed, but that\ndoing so would involve a dedicated study focused on evaluating these activators across many\npromoters and regulatory elements. Because of that, we feel that it’s beyond the scope of this paper.\n5.Provide more detail on the hybrid pre-crRNA array strategy for simultaneous activation and\nrepression, such as fornt or back combination of crRNA for activation and repression. Include a\ndiscussion on whether this approach could be extended to other types of dCas effectors, such as\nthose for DNA methylation or histone modification.\nThank you for this suggestion. In the revised manuscript, we performed an experiment to expand the\nhybrid pre-crRNA strategy to include using dEnAsCas12a repressors and dHyperLbCas12a\nactivators. This data is presented in. Supp. Fig 6c-f and summarized on lines 489-501. For\nconvenience, that new text is reproduced below:\nTo generalize this result, we also designed and tested a similar pre-crRNA containing the\nsame crRNA sequences, but with dHyperLbCas12a activators and dEnAsCas12a\nrepressors. As before, we first tested the ability of single dCas12a effectors to use the\npre-crRNA and found that dHyperLbCas12a-VPR and dEnAsCas12a-KRAB could\nsignificantly activate or repress the target genes when co-transfected with the hybrid\ncrRNA (Supp. Fig 6c-d). We next co-transfected a dHyperLbCas12a Cas12a activator\nand a dEnAsCas12a repressor along with the hybrid pre-crRNA into HEK293T cells. We\nfound that dHyperLbCas12-VPR was able to significantly activate both target genes (p <\n0.05, FDR-adjusted Student’s T-test), but dEnAsCas12a-KRAB was unable to repress\neither target gene (Supp. Fig 6e). Meanwhile, the combination of\ndHyperLbCas12a-P300 and dEnAsCas12a-SID was able to significantly activate HBE1\nand MYOD1 expression while significantly repressing RAB11A expression (p < 0.01,\nFDR-adjusted Student’s T-test), but not MYC expression (p = 0.172, FDR-adjusted\nStudent’s T-test) (Supp. Fig 6f).\nWe also added text to the discussion on possibilities for expanding this approach to the discussion.\nThe text is on line 787-792 and reads:\nHere, we demonstrate an alternative approach using a hybrid dCas12a pre-crRNA to\nsimultaneously activate two genes and repress two genes. That strategy can be\nexpanded in several ways. For example, it is likely, given the compatibility with\ndCas12a-VPR, P300, KRAB, and 4xSID, that the system could be expanded to other\ndCas12a epigenetic fusions or nuclease active Cas12a. It is also likely that other\nCRISPR proteins that process their own pre-crRNAs, such as Cas13a, could be added\n6.Expand the discussion on potential off-target effects, particularly when using multiplexed crRNA\narrays. Although only at the cellular level of high throughput screening, include experiments or\nsimulations that demonstrate the safety of the system in minimizing off-target interactions.\nThank you for raising this point. We agree that this is an important area of future study, and highlight\nthat in the discussion on line 805-808:\nA final challenge will be understanding the profile of off-target effects and how they scale\nwith the number of crRNAs contained in each array. We expect that a full understanding\nof those off-target events would require genome editing to stably record (Ref. 82-83).\n7.In the figures section, appropriate statistical analysis should be conducted, and p-value indicated to\nassess the authors’ claim.\nTo supplement the discussion of p values in the text, we have now added asterisks to Fig. 2-7 and\nSupp. Figs 1, 2, 4, 6, and 10 to denote significance where appropriate.\n8.The manuscript would benefit from a more detailed description of the statistical methods used to\nanalyze gene expression changes, particularly in high-throughput screens. Specify how multiple\nhypothesis testing was corrected and how significant results were defined.\nThank you for this suggestion. We have now added these details in the revised manuscript.\n9.In general, the biological replicates are 3 or over. Thus, it is recommended that for activity\ncomparison of among these variants, while many group in this article only one set. This is not\nrigorous.\nThank you for your comment. We have ensured that all data represent at least two biological\nreplicates. However, some of our boxplots were previously overplotted, and in this revised manuscript\nwe have increased jitter in Fig. 2-7 to more clearly show the number of data points represented for\neach condition. A full summary of statistical tests performed is available in Supp. Table 1.\nReviewer #4:\nThis manuscript presents the development and characterization of dCas12a-based gene silencing\nand activation using two distinct dCas12a variants. The authors employed enhanced versions of\ndCas12a, enAsCas12a and HyperLbCas12a, along with crRNA arrays to modulate gene expression.\nThey demonstrate that dCas12a can be coupled with the activation domain P300 and the repression\ndomain SID. They show simultaneous activation and repression of target genes through a single\ncrRNA array by co-expressing both enAsCas12a and HyperLbCas12a. Furthermore, they illustrate\nthe platform's utility in screening applications using a barcoded library of crRNA arrays targeting two\nenhancers of a single gene.\nOverall, the study offers a side-by-side comparison of gene activation and repression across two\ndifferent Cas12a systems. It provides a resource for using AsCas12a and LbCas12a variants in gene\nregulation. For example, the observation that dLbCas12a-P300 fusions exhibit stronger and more\nconsistent activation than dAsCas12a-P300 fusions is interesting. While the fusion of Cas12a to P300\nand SID is new, these tools do not outperform established systems such as VPR for activation and\nKRAB for repression.\nHowever, the manuscript raises major concerns that should be addressed before it can be considered\nfor publication:\n1. The potential for crosstalk between the two Cas12a variants should be thoroughly evaluated. Both\nvariants utilize the same PAM and share similar guide RNA structures. This raises concerns about\ntheir orthogonality. To confirm their suitability for simultaneous activation and repression, the authors\nshould demonstrate that each Cas12a does not interact with the other's guide RNA. Additional\nexperimental data are required to validate their orthogonality and crosstalk.\nThank you for this comment, we have performed additional experiments to address these concerns.\nThe data is shown in Supp. Fig. 6g-h and the text on lines 510-531 describing them reads:\nTo evaluate crosstalk in such a setting, we co-transfected dHyperLbCas12a-VPR with\nthe hybrid pre-crRNA containing AsCas12a crRNAs for activation as well as either\ndEnAsCas12a or Cas9 as a transfection control for number and size of plasmids. We\nfound that, by itself, dHyperLbCas12a-VPR can use AsCas12a crRNAs but with less\nefficacy than homologous LbCas12a crRNAs. Specifically, when dHyperLbCas12a-VPR\nwas cotransfected with Cas9, there was 150-fold activation of HBE1 and no significant\nactivation of MYOD1 (Supp. Fig 6g). The observed activation of HBE1 was ~30-fold\nless than when dHyperLbCas12a-VPR was co-transfected with its homologous hybrid\npre-crRNA array (Supp. Fig 6a).\nHowever, that crosstalk is alleviated when dHyperLbCas12a and dEnAsCas12a are both\npresent and competing for crRNAs. Specifically, when dHyperLbCas12a-VPR was\nco-transfected with dEnAsCas12a, we observed no significant activation of either gene,\nand relative HBE1 expression dropped to a 1.25-fold change over non-targeting control\n(Supp. Fig 6g).\nThat result was essentially similar when we tested dEnAsCas12a-VPR in the same way.\nSpecifically, dEnAsCas12a-VPR was able to significantly activate HBE1 by ~6.5 fold\nusing LbCas12a crRNAs when co-transfected with Cas9. However, there was no effect\nwhen dEnAsCas12a-VPR was co-transfected with dHyperLbCas12a (Supp. Fig 6h).\nTogether, these results confirm that while dEnAsCas12a and dHyperLbCas12a cannorthologous crRNAs for activation, they are not able to do so when the homologous\nCas12a is also present and competing for crRNAs, such as in the hybrid pre-crRNA\nsystem developed here.\n2. The title, \"Highly multiplexed epigenome editing screens,\" is misleading and overstates the study's\nscope. The manuscript demonstrates the activation of four genes, and it remains unconvincing that all\nfour genes are all activated in single cells. This falls short compared to prior studies that activated or\nrepressed a greater number of genes. Additionally, the term \"epigenome editing\" is not fully\nsubstantiated, as the authors only present transcription-level activation or repression without\ncharacterizing epigenetic modifications. Moreover, the screens are limited to targeting two enhancers,\nwhich does not align with the claim of high multiplexing. The title should be revised to accurately\nreflect the data presented in the study.\nThank you for this comment, we have revised the title to “HyperCas12a enables multiplexed CRISPRi\nscreens”, which we believe better reflects the scope of the study.\n3. It is unclear how most data were collected. For example, how was flow cytometry gating defined?\nHow many replicates were performed? How many biological or technical replicates were tested in\neach experimental group? Additionally, statistics are lacking in the figures, and p-values should be\nincluded.\nFlow cytometry gating is described in the methods and now shown in Supp. Figs 5, 16, and 18.\nBiological replicates are described in figure legends and p values are described in the text, and we\nhave now added asterisks to Fig. 2-7 and Supp. Figs 1, 2, 4, 6, and 10 to denote significance where\nappropriate. We also increased jitter in Fig. 2-7 so that the number of replicates can be more clearly\nseen in the figures. A full summary of statistical tests performed is available in Supp. Table 1.\n4. Although the authors tested a few cell lines for characterization, the study would have\ngreater utility if additional cell types, particularly primary cells, were included. This would\nenhance the relevance and applicability of the findings for the community.\nThank you for this comment. Addressing this comment was one of the major focuses of our revised\nmanuscript. We performed numerous additional experiments to address these concerns. We tested\nthe effects of stably expressed dCas12a effectors and pre-crRNA arrays in primary human T Cells\nand iPSCs. The results of these experiments are displayed in Fig. 2h-j and Fig. 4e-h. The text related\nto the T cell repression results in on line 284-292 and reads:\nNext, we co-transduced human T cells from three independent donors with\ndHyperLbCas12a-KRAB or dEnAsCas12a-KRAB and either a pre-crRNA targeting the\npromoters of SLA2, GATA3, MAP4K1, GRAP, and LAT2 or a control pre-crRNA\ncontaining ten non-targeting crRNAs (Fig. 2h). We observe similar trends for both\nCas12a orthologues. For example, both dEnAsCas12a- and dHyperLbCas12a-KRAB\nshowed the strongest repression of GRAP and LAT2, though dHyperLbCas12a showed\nstronger repression (mean log fold change across donors of -0.89 and -0.87 vs. -0.47\n2\nand -0.42) consistent with our previous findings (Fig. 2i-j). While we do not observe\neffects for all target genes in this cell type, these results indicate the potential of using\ndCas12a for multiplexed repression in primary cells.\nThe text related to activation experiments in T Cells and iPSCs reads is on lines 397-440 and reads:\nModel systems for studying primary cell differentiation commonly involve controlling the\nexpression of several genes at once16,69. As a key step towards such highly multiplexed\ncontrol of gene regulation in primary cells, we focused on demonstrating dCas12a-based\ngene activation in T cells and in an human induced pluripotent stem cell (iPSC)-based\nmodel of neuronal differentiation.\nTo demonstrate multiplexed control of gene expression in T cells, we co-transduced\ndHyperLbCas12a-VPR along with the pre-crRNA targeting AR, HBE1 and MYOD1 into\nprimary human CD3+ T cells from three different donors. The results were similar to\nthose observed in cell lines, namely that there was significant activation (p < 0.05,\nOne-Sided Student's Paired T-Test) of HBE1 and MYOD1, with effects ranging from\n~45-350-fold upregulation (Fig.4e). Also as in the cell lines, there was little or no\nactivation of AR gene expression.\nTo demonstrate multiplexed control of gene expression in iPSC cell differentiation, we\nused an iPSC cell line that had previously been modified to express mCherry\ncotranslationally with TUBB3A, a marker of neuronal differentiation13. We further\nmodified the line to stably express dHyperLbCas12a-VPR. We designed a pre-crRNA\narray of three crRNAs to target the promoter of NGN3, a strong driver of neuronal\ndifferentiation, to act as a positive control. We also designed a pre-crRNA array\ncontaining seven crRNAs that target three core neurogenic transcription factors (deemed\n“Core”): NGN1, NGN2, and NGN3. We designed a pre-crRNA array containing seven\ncrRNAs that target four accessory genes that have been shown to enhance neuronal\ndifferentiation when co-activated in tandem with a core factor (deemed “Accessory”):\nLHX6, LHX8, SOX2, and E2F713. Lastly, we designed a pre-crRNA array containing all\n14 crRNAs and targeting both core and accessory factors together (deemed\n“Core+Accessory”) (Fig. 4f).\nWe transduced the dHyperLbCas12a-VPR cell line with these pre-crRNAs and then\nmeasured the percentage of cells that were mCherry positive when gating such that ~1%\nof cells transduced with a pre-crRNA array containing non-targeting control crRNAs are\nmCherry positive (Fig. 4g, Supp. Fig 5). We find that ~4% of cells that received the\nNGN3 targeting array are mCherry positive, while ~1.25% of cells that received the\n“core” pre-crRNA array and ~3.5% of cells that received the “Core+Accessory”\npre-crRNA array are mCherry positive. As expected, activation of the accessory factors\nalone did not lead to an increase in mCherry positive cells over control (Fig. 4h). While\nwe did not observe higher rates of mCherry positive cells in the Core or Core+Accessory\nconditions vs. the NGN3-targeting array, we do observe an (~3x) increase in mCherry\npositive cells between Core and Core+Accessory conditions, suggesting increased\ndifferentiation efficiency due to multiplexed activation. Furthermore, we observe\nincreased (~2x) MFI of the mCherry positive population in the Core+Accessory condition\nvs. both the NGN3 and core conditions, suggesting higher TUBB3A expression in these\ncells (Fig. 4i).\nTogether, these results demonstrate that dCas12a activators are capable of multiplexed\nactivation of gene expression in multiple primary cell systems in which dCas12a\neffectors have been integrated and remain stably expressed.\n5. The inclusion of a control library with 10,000 non-targeting six-crRNA arrays and three pre-crRNAs\ntargeting the PER1 promoter seems excessive. The rationale for this large imbalance between\nnon-targeting and targeting arrays should be clarified. How does this control design contribute to the\nstudy's objectives?\nSince most of the targeting library is composed of pre-crRNA arrays targeting both enhancers, it\nwould be difficult to detect depletion from the high (top 12.5%) PER1 expression bin and enrichment\nin the low (bottom 12.5%) PER1 expression bin if only a small fraction of the library was composed of\nnon-targeting pre-crRNA arrays. We included many non-targeting pre-crRNA arrays so that we could\ndetect whether the pre-crRNA arrays targeting both enhancers were well separated from negative\ncontrols and conservatively designed our library to contain ~50% non-targeting pre-crRNAs arrays\nand ~50% dual-targeting pre-crRNA arrays.\nWe have added text to the manuscript to justify this design choice on lines 648-652. It reads:\nIn parallel, we separately constructed a control library of 10,000 non-targeting six-crRNA\narrays and three pre-crRNAs targeting the PER1 promoter (Supp. Fig 13). Since most\n(80%) of the PER1-targeting library consists of pre-crRNAs targeting both enhancers,\nthis large control library will enable better separation between cells with high and low\nPER1 expression.\n6. The diagrams in Fig. 7b-d are confusing. Are these plots representing PER1-high cells or\nPER1-low cells? A more detailed explanation of how these plots were generated is necessary to help\nunderstanding.\nThank you for this comment. We originally showed the average of the two bins, but have revised Fig.\n8 (previously Fig. 7) to show the high and low bin separately since this is how we refer to the data in\nthe text.\n7. The purpose of testing the two enhancers using a large library is unclear. The authors should\nelaborate on why not use a few well-designed crRNA arrays to target individual or paired enhancers\nand measure the downstream gene expression? It is unclear if there is a necessity of performing\nlibrary screening on two enhancers of one gene. Furthermore, the insights gained from testing PER1\nenhancers can be strengthened.\nIdentifying interactions between gene regulatory elements remains a major challenge for numerous\ntechnical, biological, and statistical reasons. Specifically, experimental noise, potentially weak\nbiological effects, and the compounding of those factors in statistical analyses typically leaves studies\nof genetic interactions highly underpowered. Using rough estimates of how those factors would\nimpact the new dCas12a systems developed here, we developed a screen where we were highly\nconfident in our statistical power. Indeed, we feel that the depth of analysis in this screen can serve\nas a starting point for more formal power analyses to guide future study designs.\nTo clarify that point to readers, we added the following text to the discussion on lines 813-816:\nA key observation from our screen of the PER1 locus is that identifying epistatic\ninteractions in gene regulation requires a great degree of replication, and we\nexpect that the outcomes of our study can be useful for power analyses to design\nfuture such screens.\n8. The manuscript would benefit from discussing specific design rules for guide RNA arrays.\nWe believe that we address this concern throughout the manuscript. Specifically, we observed that\ncrRNAs towards the end of an array have low activity, but that this can be rescued by using an RNA\nPol II promoter. We do not observe clear evidence of positional effects in the PER1 enhancer screen.\nWe looked further into that screen data and did find crRNAs that, when included in the array, led to\nsignificantly stronger or weaker repression. This data is shown in Supp. Fig. 17, and text describing\nthese results on lines 705-714 and is reproduced below:\nWe did not find strong evidence for substantial heterogeneity in the effects of the\nindividual crRNAs. Specifically, we tested if, when targeting enhancer A or B individually,\nany of the crRNAs consistently increased or decreased the effect of the pre-crRNA array\n(Supp. Table 3). In the 100 nM Dex high bin, 2 of the 9 crRNAs targeting enhancer A\nhad significant effects and 6 of the 9 crRNAs targeting enhancer B had a significant\neffect (FDR < 0.05). Of those eight crRNAs with significant effects, four increased crRNA\narray activity, and four decreased that activity. However, the magnitude of those effects\nwere small, with changes in mean pre-crRNA enrichment of between 10% and 36%\nwhen those crRNAs were present (Supp. Fig 17a-c). The individual crRNA effects also\ndid not correlate with GC content or the on-target activity score predicted by CRISPick\n(Supp. Table 3).\nSince there are only 18 unique crRNAs in the screen, we feel that there is not sufficient data to\ncomment decisively about positioning or design rules.\n9. Citations 73-74: The manuscript does not appropriately cite work on Cas13. The authors should\nensure they reference the most relevant studies.\nThank you for this comment, we now cite:\nEast-Seletsky, A., O’Connell, M., Knight, S. et al. Two distinct RNase activities of CRISPR-C2c2 enable\nguide-RNA processing and RNA detection. Nature 538, 270–273 (2016).\nhttps://doi.org/10.1038/nature19802\nTo substantiate our claim that Cas13a can process its own crRNA array."}, {"round": 3, "reviewer_comments": {"reviewer_3": "The authors provided explanations and revisions to the manuscript reasonably addressed my comments. I have no further questions.", "reviewer_4": "Thank you for the thoughtful revision. The manuscript is improved, and many of our earlier concerns are addressed in the text. That said, a few key issues remain around robustness in primary T cells. Most of the changes are textual rather than experimental, so the main uncertainty is still how well the system performs in a more complex, physiologically relevant setting.\nMajor points:\n• Particularly, P300 is described as part of the toolkit but is not shown in primary T cells. Even a small pilot (e.g., n=2 donors) would help establish whether P300 is workable in this context. If those data aren’t feasible now, the authors should at least say so explicitly and acknowledge that P300 remains untested in primary T cells and reduce the claim of broad applicability.\n• Not all target genes were repressed is a main issue for robustness. Primary cell experiments can be variable, but this highlights that the system isn't a simple \"plug-and-play\" tool. It requires target-specific optimization. The authors should clearly explain in the main text that its application in primary T cells appears more preliminary and would benefit from further optimization.\nMinor points:\n• In earlier rounds of reviews, we’ve requested the authors to add numerical P-values. The request for P-values was not for significance thresholds (indicated by asterisks), but for the exact numerical P-values.\n• While the authors corrected most of the supplementary figure labeling inconsistencies (Supplementary Fig. xx), there is still one missed at line 424.\n• The sentence on line 291 remains ambiguous. We suggest the authors consider: 'Although not all target genes showed measurable effects in this cell type, these findings demonstrate the potential of dCas12a for multiplexed repression in primary cells.’", "reviewer_5": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts."}, "author_response": "We thank the reviewers for taking their time to review our revised manuscript. Below we address each of the remaining concerns from Reviewer #4.\nReviewer #3 (Remarks to the Author):\nThe authors provided explanations and revisions to the manuscript reasonably addressed my comments. I have\nno further questions.\nReviewer #4 (Remarks to the Author):\nThank you for the thoughtful revision. The manuscript is improved, and many of our earlier concerns are\naddressed in the text. That said, a few key issues remain around robustness in primary T cells. Most of the changes\nare textual rather than experimental, so the main uncertainty is still how well the system performs in a more\ncomplex, physiologically relevant setting.\nMajor points:\n• Particularly, P300 is described as part of the toolkit but is not shown in primary T cells. Even a small pilot (e.g.,\nn=2 donors) would help establish whether P300 is workable in this context. If those data aren’t feasible now,\nthe authors should at least say so explicitly and acknowledge that P300 remains untested in primary T cells and\nreduce the claim of broad applicability.\nWe thank the reviewer for this suggestion. It is currently not feasible for us to complete that study. We have\ntherefore added the following text to lines 824-826 of the discussion per the reviewer's recommendation:\nWe also did not evaluate dCas12a-P300 fusions in primary T cells, and the efficacy of\nsuch approaches has remains to be evaluated.\n• Not all target genes were repressed is a main issue for robustness. Primary cell experiments can be variable, but\nthis highlights that the system isn't a simple \"plug-and-play\" tool. It requires target-specific optimization. The\nauthors should clearly explain in the main text that its application in primary T cells appears more preliminary\nand would benefit from further optimization.\nIn the previous revision, we included discussion to highlight the importance of additional optimization for primary\nT cell studies. We have further updated that section per the reviewer's suggestion. Specifically, lines 820-824 now\nread (with additional text in bold):\nWhile we found that dCas12a epigenome effectors can drive multiplexed gene regulation in\ndifferent cell types including T cells, the effects in T cells were variable across genes and donors.\nThat variability likely has a combination of causes including the efficacy of crRNA targeting,\nsmaller effects when delivering to primary cells, and reduced statistical power when accounting\nfor donor variability. As a result, we expect additional target-specific optimization will be\nneeded for primary cell applications.\nMinor points:\n• In earlier rounds of reviews, we’ve requested the authors to add numerical P-values. The request for P-values\nwas not for significance thresholds (indicated by asterisks), but for the exact numerical P-values.\nIncluding all of the p-values in each figure made the figures very busy and overwhelming to read. We therefore\nhave included all p-values in Supplementary Dataset 1 where we feel they will be more useful to the interested\nreader.\n• While the authors corrected most of the supplementary figure labeling inconsistencies (Supplementary Fig. xx),\nthere is still one missed at line 424.\nThank you. We corrected that.\n• The sentence on line 291 remains ambiguous. We suggest the authors consider: 'Although not all target genes\nshowed measurable effects in this cell type, these findings demonstrate the potential of dCas12a for multiplexed\nrepression in primary cells.’\nWe revised the text on line 291 to now read: \"Although not all genes were repressed in this cell type, these results\nindicate the potential of using dCas12a for multiplexed repression in primary cells. \"\nReviewer #5 (Remarks to the Author):\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature\nCommunications initiative to facilitate training in peer review and to provide appropriate recognition for Early\nCareer Researchers who co-review manuscripts."}]

Decision letter