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Cited by 316Genomics and Chromatin DynamicsCRISPR and Genetic EngineeringChromatin Remodeling and Cancer

Coupled Single-Cell CRISPR Screening and Epigenomic Profiling Reveals Causal Gene Regulatory Networks

Open access
Rubin, Adam J., Parker, Kevin R., Satpathy, Ansuman T., Qi, Yanyan, Wu, Beijing, Ong, Alvin J., Mumbach, Maxwell R., Ji, Andrew L. +6 more·2019·Cell
DOI 10.1016/j.cell.2018.11.022PMC PMC6329648

Published version of a preprint

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Abstract

Here, we present Perturb-ATAC, a method that combines multiplexed CRISPR interference or knockout with genome-wide chromatin accessibility profiling in single cells based on the simultaneous detection of CRISPR guide RNAs and open chromatin sites by assay of transposase-accessible chromatin with sequencing (ATAC-seq). We applied Perturb-ATAC to transcription factors (TFs), chromatin-modifying factors, and noncoding RNAs (ncRNAs) in ∼4,300 single cells, encompassing more than 63 genotype-phenotype relationships. Perturb-ATAC in human B lymphocytes uncovered regulators of chromatin accessibility, TF occupancy, and nucleosome positioning and identified a hierarchy of TFs that govern B cell state, variation, and disease-associated cis-regulatory elements. Perturb-ATAC in primary human epidermal cells revealed three sequential modules of cis-elements that specify keratinocyte fate. Combinatorial deletion of all pairs of these TFs uncovered their epistatic relationships and highlighted genomic co-localization as a basis for synergistic interactions. Thus, Perturb-ATAC is a powerful strategy to dissect gene regulatory networks in development and disease.

AI snapshot

Written from the paper’s full text.

TL;DR

The paper introduces Perturb-ATAC, a single-cell method that pairs CRISPR interference or knockout with ATAC-seq to link genetic perturbations to chromatin accessibility phenotypes. It applies the method in human B lymphoblasts and primary keratinocytes to map regulatory networks, differentiation modules, and epistatic interactions among transcription factors.

Key findings

  • Perturb-ATAC detected guide RNAs or guide barcodes together with chromatin accessibility in thousands of single cells: 2,936 B lymphoblasts and 1,356 primary keratinocytes, covering 63 genotype-phenotype relationships.
  • In GM12878 B cells, a 40-genotype screen across 2,627 cells identified accessibility changes at 10,103 open chromatin sites and 833 features; EZH2 depletion increased accessibility at H3K27me3-marked regions (chromVAR gain 0.78, FDR < 0.0001), while SPI1 depletion reduced SPI1-motif accessibility (loss 2.17, FDR < 0.0001).
  • In keratinocytes, single-cell ATAC-seq defined three sequential regulatory modules during differentiation, and a CRISPR knockout screen of JUNB, KLF4, ZNF750, CEBPA, and EHF in 279 single-sgRNA and 235 double-sgRNA cells identified 399 altered features and showed that CEBPA loss biased cells toward early differentiation while KLF4 loss shifted cells later.
  • Epistasis analysis classified 344 additive, 102 synergistic, and 101 buffering interactions; synergistic TF pairs showed greater target-region overlap (Spearman correlation = 0.4) and correlated expression across tissues (Spearman correlation = 0.358).

Methods

  • Perturb-ATAC was performed on microfluidic integrated fluidic circuits, combining cell lysis, Tn5 transposition, reverse transcription of sgRNAs or guide barcodes, and PCR amplification before sequencing of ATAC and guide libraries.
  • The B lymphoblast experiments used dCas9-KRAB CRISPRi targeting transcription factors, chromatin modifiers, and noncoding RNAs, with single- and dual-guide genotypes; the keratinocyte experiments used Cas9-mediated knockout of selected transcription factors, followed by differentiation and harvest at Day 3.
  • Analyses included chromVAR for transcription-factor motif accessibility, permutation-based false discovery rates for differential features, nucleosome-position inference from ATAC fragment sizes, pseudotime trajectory analysis, and epistasis scoring against an additive non-interaction model.

Limitations

  • The paper states that future screens should target fewer cells per genotype (about 20) while expanding the number of genotypes, and it anticipates technological improvements to increase throughput and design complexity.
  • The study is limited to two cell systems, GM12878 B lymphoblasts and primary human keratinocytes, so the generality of the inferred regulatory relationships to other cell types or tissues is not established in the text.
  • Evident from the text: Perturb-ATAC measures chromatin accessibility and guide identity, not transcript or protein levels directly, so inferred transcription-factor activity and network relationships rely on accessibility readouts rather than direct expression measurements.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1016/j.cell.2018.11.022

Cites

77 of 77 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

0 of 27 cited sources checked · 0 supported · 0 flagged

  • Findingown data

    In primary human epidermal cells, Perturb-ATAC revealed three sequential modules of cis-elements that specify keratinocyte fate.

    “Perturb-ATAC in primary human epidermal cells revealed three sequential modules of c/s-elements that specify keratinocyte fate.”
    Quote in the paperSubstantial claim
  • Findingown data

    SPI1 motif-containing sites (51,862 sites) exhibited a significant loss of accessibility in SPI1-targeted cells compared to NT cells (FDR < 1e-3).

    “We found that SPI1 sites exhibited a significant loss of accessibility in SP/1-targeted cells compared to NT cells (FDR < 1e-3, permutation test; Methods), similar to bulk SP/1-targeting experiments (Figure 1G).”
    Quote in the paperSubstantial claim
  • Findingown data

    Cluster 2 included ncRNA 7SK and chromatin remodeler EZH2.

    “Cluster 2 included the ncRNA 7SK, which represses enhancer transcription (Flynn et al., 2016), and the chromatin remodeler EZH2 (Figure 2F).”
    Quote in the paperNot a substantial claim
  • Findingown data

    Module 5 features included specific regulators of B cell development, such as IKZF1, BCL11A, EBF1, NFKB, MEF2C, and AP-1 factors.

    “Module 4 contained homeobox domain TFs, and Module 5 features included specific regulators of B cell development, such as IKZF1 (also known as Ikaros), BCL11A, EBF1, NFKB, MEF2C and AP-1 factors.”
    Quote in the paperNot a substantial claim
  • Findingcitation

    Other altered TF motifs in SPI1-targeted cells included BCL11A, SPIB, and MEF2C, consistent with SPI1 function in regulating factors required for B cell lineage commitment.

    “Other altered TF motifs in SPI1-targeted cells included BCL11A, SPIB, and MEF2C factors, consistent with the function of SPI1 in regulating factors required for B cell lineage commitment (Figure 2E and Table S3) (Su et al., 1996; Liu et al., 2003; Stehling-Sun et al., 2009).”
    Quote in the paperNot a substantial claim
  • May combine two claims. 51
  • Classified as probably not a substantial claim. 25
  • The quote only partly states this claim. 2

  • May combine two claims.

    Findingown data

    Perturb-ATAC was applied to transcription factors, chromatin-modifying factors, and noncoding RNAs in about 4,300 single cells, covering more than 63 genotype-phenotype relationships.

    “We applied Perturb-ATAC to transcription factors (TFs), chromatin-modifying factors, and noncoding RNAs (ncRNAs) in ~4,300 single cells, encompassing more than 63 genotype-phenotype relationships.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    In human B lymphocytes, Perturb-ATAC identified regulators of chromatin accessibility, TF occupancy, and nucleosome positioning, and a hierarchy of TFs governing B cell state, variation, and disease-associated cis-regulatory elements.

    “Perturb-ATAC in human B lymphocytes uncovered regulators of chromatin accessibility, TF occupancy, and nucleosome positioning, and identified a hierarchy of TFs that govern B cell state, variation, and disease-associated c/s-regulatory elements.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingcitation

    NFKB1 and RELA showed overlapping and distinct effects, in line with prior studies demonstrating differences in NFκB subunit binding patterns.

    “Interestingly, two NFκB subunits, NFKB1 and RELA, showed overlapping and distinct effects, in line with prior studies demonstrating differences in the binding patterns of NFκB subunits through the formation of distinct protein complexes (Figures 2F and S3B; Zhao et al., 2014).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Loss of either EBER1 or EBER2 altered accessibility at EBF1 sites, consistent with these factors acting in the same pathway.

    “and loss of either factor altered accessibility at EBF1 sites, consistent with these factors acting in the same pathway (Figure S3B).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Depletion of EBF1 resulted in altered correlation of Module 2, as well as its own Module 5.

    “For example, depletion of EBF1 resulted in altered correlation of Module 2, as well as its own Module 5.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Depletion of either EBER1 or TET2 alone did not affect accessibility at IKZF1 binding sites, while dual depletion resulted in an unexpected increase in accessibility.

    “Conversely, depletion of either EBER1 or TET2 alone did not affect accessibility at IKZF1 binding sites, while dual depletion resulted in an unexpected increase in accessibility (Figure 4B).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Reads were almost exclusively assigned to one GBC, and multiple GBCs were detected in only 9 of 309 cells.

    “As expected, reads were almost exclusively assigned to one GBC (NT1, NT2, or SPI1); multiple GBCs were only detected in 9/309 cells.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Depletion of EZH2 alone primarily de-repressed regions commonly marked by H3K27me3 across cell types, which may not require additional targeting specificity.

    “Indeed, depletion of EZH2 alone primarily de-repressed regions commonly marked by H3K27me3 across cell types which may not require additional targeting specificity, while dual depletion of EZH2 and other factors de-repressed regions specifically active in alternate hematopoietic lineages (Figures 4G and 4H).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Cells passing filter yielded an average of 11.33 × 10^3 fragments mapping to the nuclear genome, and approximately 43.05% of reads were within bulk ATAC-seq peaks.

    “Cells passing filter yielded an average of 11.33 × 103 fragments mapping to the nuclear genome, and approximately 43.05% of reads were within bulk ATAC-seq peaks, similar to previously published scATAC-seq as well as high-quality bulk ATAC-seq datasets (Buenrostro et al., 2015; Corces et al., 2017) (Figure 1C).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    NFKB1 and RELA exhibited distinct effects on Module 5, while altering Module 4 to a similar extent.

    “The two NFκB subunits, NFKB1 and RELA, exhibited distinct effects on Module 5, which includes NFKB1 and RELA, while altering Module 4 to a similar extent (Figures 3H, S4E).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Single-cell ATAC-seq in primary human epidermal cells identified three regulatory modules in keratinocyte differentiation, and a Perturb-ATAC CRISPR-deletion screen revealed key TF regulators of each module.

    “scATAC-seq in primary human epidermal cells identified three regulatory modules in keratinocyte differentiation, and a Perturb-ATAC CRISPR-deletion screen revealed key TF regulators of each module.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    SPI1 motif sites were unchanged in EBF1-depleted cells, while depletion of SPI1 strongly decreased accessibility of these sites.

    “For example, SPI1 motif sites were unchanged in EBF1 depleted cells, while depletion of SPI1 strongly decreased the accessibility of these sites (Figure 4B).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingcitation

    The 12 targeted trans-factors included transcription factors EBF1, IRF8, NFKB1, RELA, and SPI1; chromatin modifiers BRG1, DNMT3A, EZH2, and TET2; and noncoding RNAs 7SK, EBER1, and EBER2.

    “The 12 targeted trans-factors included transcription factors (EBF1, IRF8, NFKB1, RELA, and SPI1), chromatin modifiers (BRG1, DNMT3A, EZH2, and TET2), and noncoding RNAs (7SK, EBER1, and EBER2) that have previously been shown to impact normal and neoplastic B cell development and function (Nutt and Kee, 2007; Lunning and Green, 2015).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Cells passing filter yielded an average of 10.68 × 10^3 fragments mapping to the nuclear genome, and approximately 43.85% of reads were within peaks present in bulk profiles.

    “Cells passing filter yielded an average of 10.68 × 103 fragments mapping to the nuclear genome, and approximately 43.85% of reads were within peaks present in bulk profiles (Figure 2C).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingcitation

    Sub-nucleosome-sized fragments were enriched at the CTCF motif, indicating a central nucleosome-free region; nucleosome-sized fragments were enriched upstream and downstream, representing the +1 and −1 nucleosomes.

    “As expected, sub-nucleosome fragments were enriched at the CTCF motif, indicating a central nucleosome-free region. In contrast, nucleosome-sized fragments were enriched upstream and downstream relative to the CTCF motif, representing the +1 and −1 nucleosomes (Vierstra et al., 2014).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Module 3 (25 features) included target regions of ETS and IRF family factors and gained accessibility in late differentiation.

    “Finally, Module 3 (25 features) included target regions of ETS and IRF family factors, and gained accessibility in late differentiation.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingcitation

    ZNF750 target regions were not uniformly more or less accessible in ZNF750-targeted cells, consistent with its role as a positive and negative gene regulator.

    “Notably, ZNF750 target regions were not uniformly more or less accessible in ZNF750-targeted cells, consistent with the role of this factor as a positive and negative gene regulator (Boxer et al., 2014).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Cells largely separated by differentiation time point, but a few precocious differentiating cells were observed in the Day 0 population, and some Day 6 cells remained in a mid-differentiation state.

    “While cells largely separated by their differentiation time point, a few “precocious” differentiating cells were observed in the Day 0 population, and some Day 6 cells remained in a mid-differentiation state (Figure 5B).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Although perturbation of NFKB1 did not alter many other variant-enhancers in isolation, dual perturbation of NFKB1 and other factors modulated accessibility associated with several diseases.

    “Although perturbation of NFKB1 did not alter many other variant-enhancers in isolation, dual perturbation of NFKB1 and other factors modulated accessibility associated with several diseases, demonstrating that Perturb-ATAC uncovers epistatic interactions relevant to development and disease (Figure 4J).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    67 TFs with dynamic accessibility in differentiation clustered into three modules.

    “We identified 67 TFs with dynamic accessibility in differentiation, which clustered into three modules (Figures 5C and 5D).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    NFκB binding sites were enriched near causal variants associated with multiple sclerosis and systemic lupus erythematosus, and these sites demonstrated altered accessibility in cells where NFKB1 or RELA were depleted.

    “NFκB binding sites were shown to be enriched near causal variants associated with multiple sclerosis and system lupus erythematosus (Farh et al., 2015), and these sites demonstrated altered accessibility in cells where NFKB1 or RELA were depleted (Figure 4J).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The dual-knockout workflow identified 344 additive relationships, 102 synergistic interactions, and 101 buffering interactions.

    “This workflow identified 344 additive relationships, 102 synergistic interactions, and 101 buffering interactions.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    279 single sgRNA-expressing cells and 235 double sgRNA-expressing cells were identified, encompassing 23 distinct genotypes of all expected individual and double CRISPR perturbations.

    “Altogether, weidentified 279 single sgRNA-expressing cells and 235 double sgRNA-expressing cells, encompassing 23 distinct genotypes of all expected individual and doublé CRISPR perturbations (Figure 6B, Table S5).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Perturb-ATAC data permitted analysis of three levels of chromatin regulation: individual cis-regulatory elements, inferred transcription factor activity from cis-regulatory modules, and nucleosome occupancy and positioning.

    “Analysis of Perturb-ATAC data enabled the study of several layers of chromatin regulation: 1) individual c/s-regulatory elements, 2) inferred TF activity from cis-regulatory modules, and 3) nucleosome positioning and occupancy.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The ZNF750-bound enhancer of SPRR2E lost accessibility upon ZNF750 disruption, while other ZNF750 binding sites gained accessibility.

    “For example, the ZNF750-bound enhancer of the epidermal cornified envelope gene SPRR2E lost accessibility upon ZNF750 disruption, while other ZNF750 binding sites gained accessibility (Figure 6D and S7A).”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    After filtering for features significantly altered in at least one genotype and removing redundant annotations, 390 motif/ChIP features remained for correlation analysis.

    “Only features that were significantly altered in at least one genotype were considered, and redundant annotations were removed, resulting in 390 motif/ChIP feature annotations for analysis.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    ATAC-seq informs the identification of enhancers, nucleosome positioning, and inference of transcription factor binding.

    “This method informs the identification of enhancers, the positioning of nucleosomes, and the inference of transcription factor binding (Buenrostro et al., 2013; Schep et al., 2015, 2017).”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites Buenrostro et al., 2013 source

      Not checked in the free run.

    • cites Schep et al., 2015, 2017

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • May combine two claims.

    Interpretationown data

    Combinatorial deletion of all pairs of these TFs uncovered epistatic relationships and highlighted genomic co-localization as a basis for synergistic interactions.

    “Combinatorial deletion of all pairs of these TFs uncovered their epistatic relationships and highlighted genomic co-localization as a basis for synergistic interactions.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    ATAC-seq uses a hyperactive Tn5 transposase to measure the activity of regulatory DNA elements.

    “We recently developed the assay for transposase-accessible chromatin with sequencing (ATAC-seq), which utilizes a hyperactive transposase (Tn5) to measure the activity of regulatory DNA elements (Buenrostro et al., 2013).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Buenrostro et al., 2013 source

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    ATAC-seq can be performed in single cells, revealing cell-to-cell variability and rare epigenomic phenotypes.

    “Importantly, ATAC-seq can be performed in single cells (scATAC-seq), uncovering cell-to-cell variability and rare epigenomic phenotypes (Cusanovich et al., 2018; Satpathy et al., 2018; Buenrostro et al., 2018).”
    Quote in the paperSubstantial claim0 of 3 sources checked
    • cites Cusanovich et al., 2018 source

      Not checked in the free run.

    • cites Satpathy et al., 2018 source

      Not checked in the free run.

    • cites Buenrostro et al., 2018 source

      Not checked in the free run.

  • May combine two claims.

    Interpretationown data

    Perturb-ATAC consistently detects GBCs with high confidence and a low false positive rate.

    “These results demonstrate that Perturb-ATAC consistently detects GBCs with high confidence and a low false positive rate (Figures 1B, S1B and S1C).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data

    Loss of co-variation is not dependent on altered accessibility of each factor, decoupling two mechanisms of TF activity.

    “Of note, the loss of co-variation is not dependent on altered accessibility of each factor, decoupling two mechanisms of TF activity (Figures 3E and S4D).”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Premisecitation

    Single-cell ATAC-seq profiles can be paired with orthogonal measurements of RNA or protein expression in the same cell.

    “Additionally, scATAC-seq profiles can be paired with orthogonal measurements of RNA or protein expression in the same cell (Satpathy et al., 2018; Chen et al., 2018a).”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites Satpathy et al., 2018 source

      Not checked in the free run.

    • cites Chen et al., 2018a

      Not checked in the free run.

  • May combine two claims.

    Interpretationown data

    Regions losing accessibility upon depletion of 7SK exhibited stronger central nucleosome structure in 7SK-depleted cells, possibly indicating that 7SK interacts with nucleosome remodeling factors.

    “Reflecting another distinct mechanism, regions losing accessibility upon depletion of 7SK exhibited stronger central nucleosome structure in 7SK-depleted cells, possibly indicating that 7SK interacts with nucleosome remodeling factors, as has been shown for the BAF complex (Figure S3F; Flynn et al.,”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationown data

    Multiplexed perturbations mapped epistatic relationships between TFs, and genomic co-localization and co-expression of TFs may predict genetic interaction.

    “We mapped epistatic relationships between TFs using multiplexed perturbations and suggest that genomic co-localization and co-expression of TFs may predict genetic interaction.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data

    SPI1 depletion increased accessibility of IRF motif regions, demonstrating that SPI1 exhibits activating and repressive functions.

    “In contrast, SPI depletion increased accessibility of IRF motif regions, demonstrating that SPI1 exhibits activating and repressive functions, as has been reported (van Riel and Rosenbauer, 2014).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data

    Trans-factors regulate nucleosome positioning in distinct ways, and Perturb-ATAC can read out nucleosome structure changes associated with perturbations.

    “Overall, these results demonstrate that trans-factors regulate nucleosome positioning in distinct ways and that Perturb-ATAC can read out nucleosome structure changes associated with perturbations.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Study design and conductown data

    Rare ATAC-seq reads mapping to the viral construct did not influence ATAC-seq profiles, and observed accessibility at potential sgRNA mismatch loci indicated no evidence of off-target repression.

    “Rare ATAC-seq reads mapping to the viral construct did not appear to influence ATAC-seq profiles, and observed accessibility at potential sgRNA mismatch loci indicated no evidence of off-target repression (Methods, Figure S2D).”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Study design and conductcitation

    Packaging steps were performed in separate cultures to eliminate the likelihood of recombination of sgRNAs and GBCs between vectors.

    “To eliminate the likelihood of recombination of sgRNAs and GBCs between vectors, as has been recently described (Adamson et al., 2018; Feldman et al., 2018; Hill et al., 2018; Xie et al., 2018), we performed packaging steps in separate cultures.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data

    The correlation between IKZF1 and FOS:JUN in NT cells (r = 0.420, p = 5.60e-6) was lost in IRF8-depleted cells (r = -0.051, p = 0.627), suggesting IRF8 coordinates these two factors.

    “In particular, the correlation between IKZF1 and FOS:JUN (AP-1) in NT cells (r = 0.420, p = 5.60e-6) was lost in IRF8 depleted cells (r = - 0.051, p=0.627), suggesting that IRF8 coordinates these two factors (Figures 3F and 3G).”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim. May combine two claims.

    Premisenone given

    Co-varying accessibility between sets of regions bound by two trans-factors may reflect common regulation, whereas inverse correlation may indicate that one factor controls the activity or expression of a negative regulator of the other set of regions.

    “For example, co-varying accessibility between sets of regions bound by two trans-factors may reflect common regulation. In contrast, inverse correlation may indicate that one factor controls the activity or expression of a negative regulator of the other set of regions.”
    Quote in the paperSubstantial claim
    • Rests on an assumption: Co-varying accessibility between sets of regions bound by two trans-factors reflects common regulation, and inverse correlation indicates one factor controls the activity or expression of a negative regulator of the other set.

  • Classified as probably not a substantial claim. May combine two claims.

    Study design and conductnone given

    CRISPRi guide RNAs were designed to maximize knockdown efficiency and minimize off-target effects.

    “CRISPRi guide RNAs were designed to maximize knockdown efficiency and minimize off-target effects (Figure S2A-C, Table S1).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data

    Regions that gained accessibility in DNMT3A-depleted cells exhibited a stronger central nucleosome, consistent with a model in which DNMT3A recruits negative regulatory factors to an open chromatin region.

    “However, regions that gained accessibility in DNMT3A-depleted cells exhibited a stronger central nucleosome, consistent with a model in which DMNT3A recruits negative regulatory factors to an open chromatin region.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationown data

    Regions marked by H3K27me3 exhibited a high degree of interaction, particularly involving EZH2, suggesting other factors may guide EZH2 recruitment or activity.

    “Similarly, regions marked by the repressive histone modification H3K27me3 exhibited a high degree of interaction, particularly involving EZH2, suggesting that other factors may guide EZH2 recruitment or activity (Figure 4F).”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Study design and conductown data

    Stringent cutoffs were used to assign the presence or absence of a GBC.

    “We used stringent cutoffs to assign the presence or absence of a GBC (Figure S1B).”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    CEBPA has a known role in murine epidermis.

    “We chose three Module 2 regulators: 1) KLF4, which induces epidermal differentiation genes, 2) ZNF750, a factor engaged in positive and negative gene regulation in epidermal differentiation, and 3) CEBPA, which has known role in murine epidermis (Lopez et al., 2009; Sen et al., 2012).”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites Lopez et al., 2009 source

      Not checked in the free run.

    • cites Sen et al., 2012 source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    KLF4 induces epidermal differentiation genes.

    “We chose three Module 2 regulators: 1) KLF4, which induces epidermal differentiation genes, 2) ZNF750, a factor engaged in positive and negative gene regulation in epidermal differentiation, and 3) CEBPA, which has known role in murine epidermis (Lopez et al., 2009; Sen et al., 2012).”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites Lopez et al., 2009 source

      Not checked in the free run.

    • cites Sen et al., 2012 source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    JUNB, an AP-1 family member, controls epidermal homeostasis and tumorigenesis.

    “For a candidate Module 1 regulator, we selected JUNB, an AP-1 family member which controls epidermal homeostasis and tumorigenesis (Eckert et al., 2013).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Eckert et al., 2013

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductnone given

    Guides were designed with CRISPOR and selected to reduce genomic loci with 0-4 mismatches, aiming to limit off-target CRISPRi activity.

    “Guides were designed using the CRISPOR online tool (http://crispor.tefor.net/) and chosen to minimize the number of genomic loci with 0–4 mismatches, with the intention of minimizing the chance for any off-target CRISPRi activity.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim. May combine two claims.

    Premisecitation

    The human epidermis is a constantly renewing stratified epithelial tissue, and thousands of genes change in expression during terminal epidermal differentiation as progenitor cells migrate from the basal layer, begin keratinization, and undergo cornification.

    “The human epidermis is a constantly renewing stratified epithelial tissue, and thousands of genes change in expression during terminal epidermal differentiation as progenitor cells migrate from the basal layer, begin keratinization, and undergo cornification to form the outer layer of the skin. (Lopez-Pajares et al., 2015).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Lopez-Pajares et al., 2015 source

      Not checked in the free run.

  • May combine two claims.

    Interpretationown data

    The study identified both regulatory factors responsible for distinct epidermal states and rerouted differentiation trajectories in response to TF perturbation.

    “Together, we identified both the regulatory factors responsible for distinct epidermal states as well as rerouted differentiation trajectories in response to TF perturbation.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Study design and conductown data

    Cells with high background reads (greater than 1%) were excluded, and remaining cells clearly separated into single or double sgRNA-expressing populations.

    “Cells with high background reads (greater than 1%) were excluded, and the remaining cells clearly separated into single or double sgRNA-expressing populations (Figure S6D-F).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationreasoning

    CEBPA knockout cells lost accessibility of Module 2 features but gained Module 1 accessibility, indicating they were unable to fully engage the mid-differentiation program.

    “Correspondingly, CEBPA knockout cells lost accessibility of Module 2 features but gained Module 1 accessibility, indicating that CEBPA knockout cells were unable to fully engage the mid-differentiation program.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    EHF is an ETS factor implicated in controlling epidermal differentiation.

    “As a Module 3 regulator, we chose EHF, an ETS factor implicated in controlling epidermal differentiation (Rubin et al., 2017).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Rubin et al., 2017 source

      Not checked in the free run.

  • Classified as probably not a substantial claim. May combine two claims.

    Study design and conductown data

    A second Perturb-ATAC protocol was developed to directly detect sgRNA rather than a GBC and to assess CRISPR gene knockouts rather than CRISPR interference.

    “We developed a second Perturb-ATAC protocol to achieve two goals: 1) to directly detect the sgRNA rather than a GBC, and 2) to assess CRISPR gene knockouts rather than CRISPR interference.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    TP63 serves as a key regulator of epidermal homeostasis and differentiation.

    “TP63, a master regulator of epidermal homeostasis and differentiation”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Bao et al., 2015 source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing). The quote only partly states this claim.

    Study design and conductnone given

    All samples had consent obtained under the NIH genomic data sharing policy.

    “Consent for all samples were obtained in accordance with the NIH genomic data sharing policy.”
    Quote in the paperNot a substantial claim

  • The quote only partly states this claim.

    Interpretationown data

    EHF and JUNB act antagonistically in controlling accessibility at CEBP motif sites.

    “reflecting a negative interaction between EHF and JUNB”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    Gene expression knockdown was confirmed using qRT-PCR.

    “gene expression knockdown was confirmed using the Agilent Brilliant II qRT-PCR 1-Step kit.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationreasoning

    Perturb-ATAC is a high-throughput platform linking genotypes to epigenetic phenotypes and can reveal molecular mechanisms that control cell fate and function through chromatin state changes.

    “Perturb-ATAC provides a high-throughput platform to link genotypes with epigenetic phenotypes iand ultimately reveal molecular mechanisms that govern cell fate and function through modulation of the chromatin state.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    All plasmid sgRNA and GBC sequences were verified by Sanger sequencing.

    “The sgRNA sequences and GBC sequences of all plasmids were confirmed by Sanger sequencing.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    ZNF750 is engaged in positive and negative gene regulation in epidermal differentiation.

    “We chose three Module 2 regulators: 1) KLF4, which induces epidermal differentiation genes, 2) ZNF750, a factor engaged in positive and negative gene regulation in epidermal differentiation, and 3) CEBPA, which has known role in murine epidermis (Lopez et al., 2009; Sen et al., 2012).”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites Lopez et al., 2009 source

      Not checked in the free run.

    • cites Sen et al., 2012 source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductnone given

    qRT-PCR was run in duplicate, and each sample's expression values were normalized to 18S.

    “qRT-PCR was performed in duplicate, and expression values for each sample were normalized against 18S.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Study design and conductreasoning

    For epistasis interaction categorization, the null distribution was generated separately for each feature to account for differences in scale and variability.

    “This procedure was performed separately for each feature to account for differences in scale and variability across features.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    Cas9 nuclease activity was tested by PCR amplification of ~800bp cDNA fragments around sgRNA binding sites followed by Sanger sequencing.

    “Cas9 nuclease activity was assessed by PCR amplifying ~800bp fragments of cDNA surrounding sgRNA binding sites and analyzing the resulting fragments by Sanger sequencing”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Study design and conductnone given

    Cells with more than 1% background-associated reads were removed from analysis.

    “Cells with greater than 1% of reads associated with background were excluded from analysis.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Study design and conductcitation

    The keratinocyte feature deviation matrix was processed to remove plate and experiment batch effects.

    “The feature deviation matrix including unperturbed and CRISPR knockout cells was first processed using Seruat 2.0.1 (Butler et al., 2018) to regress out plate andexperiment batch effects.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Butler et al., 2018 source

      Not checked in the free run.

  • May combine two claims.

    Study design and conductown data

    ATAC reads matching the CRISPR viral construct were very rare (median 0.0049%), and the abundance of such reads did not appear to affect epigenomic profiles.

    “We observed an extremely low rate of ATAC reads matching the CRISPR viral construct (median 0.0049%) and found no evidence of the abundance of CRISPR construct matching reads influencing epigenomic profiles.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Study design and conductown data

    38/40 GM12878 genotypes and 23/23 keratinocyte genotypes had more than five cells.

    “indeed 38/40 genotypes for GM12878 cells and 23/23 genotypes for keratinocytes consist of greater than five cells.”
    Quote in the paperSubstantial claim
69 of 69

  • The paper relies on this without support.

    Epigenetic assays require large amounts of cellular material and are difficult to couple with genetic perturbations at scale.

    “However, it is challenging to characterize each trans-factor or c/s-element, since epigenetic assays require large amounts of cellular material and are difficult to couple with genetic perturbations at scale.”

  • The paper relies on this without support.

    Most studies are limited to measuring how single genetic perturbations affect chromatin state in bulk cell populations.

    “Therefore, most studies are limited to measuring how single genetic perturbations affect chromatin state in bulk cell populations.”

  • The paper relies on this without support.

    Co-varying accessibility between sets of regions bound by two trans-factors reflects common regulation, and inverse correlation indicates one factor controls the activity or expression of a negative regulator of the other set.

    “For example, co-varying accessibility between sets of regions bound by two trans-factors may reflect common regulation. In contrast, inverse correlation may indicate that one factor controls the activity or expression of a negative regulator of the other set of regions.”

  • The paper relies on this without support.

    Previous high-throughput genetic screens have mostly introduced genetic variants into cell populations and then selected for a narrow set of phenotypes.

    “Previous high-throughput genetic screens have largely relied on the introduction of genetic variants in a population of cells (for example, using CRISPR/Cas9), followed by the selection of cells containing variants that confer a limited set of cellular phenotypes, such as increased cell growth or viability.”

  • The paper relies on this without support.

    Finding genetic variants that control genome-wide chromatin states is difficult with standard selection and needs focused experiments that perturb candidate factors one at a time.

    “identifying genetic variants that regulate genome-wide chromatin states, which are challenging to isolate with standard selection protocols, requires focused experiments, where candidate factors are perturbed one-by-one.”

  • The authors state this as an assumption.

    The expected accessibility change for a double perturbation under non-interaction is the product of the single perturbation effects, equivalent to adding their log2 fold changes.

    “The additive expectation was based on a multiplicative model of non-interaction, (i.e., CRISPR AB = CRISPR A x CRISPR B), which we calculated by adding the single perturbation fold changes in log2-space.”
6 of 6

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Experimental manipulations of TF levels or mutagenesis of natural enhancers demonstrate that single TFs cause non-trivial increases and decreases of the activity of TF-bound enhancers.

    “Experimental manipulations of TF levels24,25,26 or mutagenesis of natural enhancers27 demonstrate that single TFs cause non-trivial increases and decreases of the activity of TF-bound enhancers”

    From Design principles of cell-state-specific enhancers in hematopoiesis (2025) · cites this paper as [25]

    In Results, ‘Perturb-ATAC screen for TF control of cellular differentiation trajectories’ (page unavailable), ZNF750 disruption decreases accessibility at one ZNF750-bound enhancer and increases it at other ZNF750 binding sites. The Introduction describes ATAC-seq as measuring regulatory-element activity, but the Results do not establish that the sites gaining accessibility are enhancers; that part of the claim is less directly supported. (LLM, conf=0.83)

    Experimental — accuracy not yet measured

  • Methods to capture changes in the epigenome following CRISPR perturbations have limited throughput.

    “However, methods to capture changes in the epigenome following CRISPR perturbations have limited throughput6.”

    From Profiling the genetic determinants of chromatin accessibility with scalable single-cell CRISPR screens (2021) · cites this paper as [6]

  • Some biological processes are better assayed using alternative modalities (splicing, chromatin, protein, imaging).

    “In addition, some biological processes are better assayed using alternative modalities, including mRNA splicing, chromatin state, protein level, and imaging, all of which are now being studied at scale with single cell CRISPR screens39-44.”

    From Transcriptome-wide analysis of differential expression in perturbation atlases (2025) · cites this paper as [39]

  • Perturb-ATAC combines genome-wide chromatin accessibility profiling in single cells based on simultaneous detection of CRISPR guide RNAs and open chromatin sites by ATAC-seq and multiplexed CRISPR interference or knockout.

    “Additionally, Perturb-ATAC [19] combines genome-wide chromatin accessibility profiling in single cells based on the simultaneous detection of CRISPR guide RNAs and open chromatin sites by assaying transposase-accessible chromatin with sequencing (ATAC-seq) and multiplexed CRISPR interference or knockout (KO).”

    From A mini-review on perturbation modelling across single-cell omic modalities (2024) · cites this paper as [19]

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • Synergy example switches transcription-factor pairs

    Minor

    The text identifies EHF-ZNF750 as the high-synergy pair, then presents a dual EHF-JUNB knockout as an example of "this synergy." It is therefore unclear which pair the TP63 example is intended to support.

  • RT primer mix has incompatible concentrations

    Minor

    The same RT primer mix is described as 6 pM and as containing each sequencing oligo at 6 μM. A mix containing an oligo at 6 μM cannot have a total primer concentration of 6 pM.

2 of 2

Cites

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1 of the 78 references couldn’t be matched to a known paper.

Cited by

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Related

Authors
Rubin, A. J., Parker, K. R., Satpathy, A. T., Qi, Y., Wu, B., Ong, A. J., Mumbach, M. R., Ji, A. L., Kim, D. S., Cho, S. W., Zarnegar, B. J., Greenleaf, W. J., Chang, H. Y., & Khavari, P. A.
Affiliations
  • Stanford Medicine (US)
  • Chan Zuckerberg Biohub San Francisco (US)
  • Howard Hughes Medical Institute (US)
  • VA Palo Alto Health Care System (US)
Corresponding author
  • Chang, Howard Y.
  • Khavari, Paul A.
ORCID
Venue
Cell
Publisher
Elsevier BV
Published
2019-01
Volume
176
Issue
1-2
Pages
361-376.e17
ISSN
0092-8674 (ISSN-L)
DOI
10.1016/j.cell.2018.11.022
PMC
PMC6329648
OpenAlex
W2950195808
Cited by
314
References
78
Citations by year
2026: 31 · 2025: 50 · 2024: 40 · 2023: 37 · 2022: 52 · 2021: 44 · 2020: 42 · 2019: 17 · 2012: 1
FWCI
9.16
Type
journal article
Language
en
Open access
Licence
Locations
  • Cell (publishedVersion)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nd)
  • PubMed (publishedVersion)
  • Europe PMC (PubMed Central) (acceptedVersion)
  • PubMed Central (acceptedVersion)
  • Scholarworks@UNIST (Ulsan National Institute of Science and Technology) (submittedVersion)
Funders
  • Veterans Affairs Office of Research and Development
  • NIH (AR45192, AR43799, P50-HG007735, R35-CA209919)
  • Parker Institute for Cancer Immunotherapy
  • Scleroderma Research Foundation
  • Stanford Bio-X
  • Stanford
  • Burroughs Wellcome Fund
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › CRISPR and Genetic Engineering
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Chromatin Remodeling and Cancer
Keywords
CRISPR interference, CRISPR knockout, chromatin accessibility, gene regulatory networks, transcription factor occupancy, nucleosome positioning, cis-regulatory elements, B cells, epidermal cells, non-coding RNA, genotype-phenotype correlation
MeSH terms
Chromatin, Humans, Transcription Factors, Sequence Analysis, DNA, Chromatin Assembly and Disassembly, Gene Regulatory Networks, Epigenomics, Single-Cell Analysis, High-Throughput Nucleotide Sequencing, Clustered Regularly Interspaced Short Palindromic Repeats

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-04.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-04.

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