The DOI matches its Crossref record; 56 of the 56 references it cites were found in a registry or an index.
CRISPR–Cas9 epigenome editing enables high-throughput screening for functional regulatory elements in the human genome
Open accessAbstract
Large genome-mapping consortia and thousands of genome-wide association studies have identified non-protein-coding elements in the genome as having a central role in various biological processes. However, decoding the functions of the millions of putative regulatory elements discovered in these studies remains challenging. CRISPR-Cas9-based epigenome editing technologies have enabled precise perturbation of the activity of specific regulatory elements. Here we describe CRISPR-Cas9-based epigenomic regulatory element screening (CERES) for improved high-throughput screening of regulatory element activity in the native genomic context. Using dCas9 KRAB repressor and dCas9 p300 activator constructs and lentiviral single guide RNA libraries to target DNase I hypersensitive sites surrounding a gene of interest, we carried out both loss- and gain-of-function screens to identify regulatory elements for the β-globin and HER2 loci in human cells. CERES readily identified known and previously unidentified regulatory elements, some of which were dependent on cell type or direction of perturbation. This technology allows the high-throughput functional annotation of putative regulatory elements in their native chromosomal context.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
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?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Activating domains (dCas9–VPR or dCas9–p300) have also been used to scan for poised enhancers in an approach termed CRISPR activation or ‘CRISPRa’92,208(Figure 2d).”
From Towards a comprehensive catalogue of validated and target-linked human enhancers (2020) · cites this paper as [208]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“When comparing Borzoi, Enformer and a distance-to-TSS baseline on their ability to classify measured positive from negative enhancer–gene interactions in data from previous works60–65, we find that Borzoi has superior average precision (AUPRC) and area under the receiver operating characteristic curve (AUROC) at all distances (Fig. 4c and Extended Data Fig. 5a).”
From Predicting RNA-seq coverage from DNA sequence as a unifying model of gene regulation (2025) · cites this paper as [62]
The cited source says what the claim attributes to it.
In the citing paper
“CRISPRi has subsequently been used in multiple single-gene screens of regulatory elements105,208,209.”
From Towards a comprehensive catalogue of validated and target-linked human enhancers (2020) · cites this paper as [208]
In the citing paper
“we validated 4 out of 5 enhancers identified in a CRISPRi screen for HBE1 enhancers using a fluorescent reporter22”
From Targeted Perturb-seq enables genome-scale genetic screens in single cells (2020) · cites this paper as [22]
In the citing paper
“15 gRNAs targeting the HBE1 TSS, and HS1–4 of the Globin LCR were chosen as validated from Klann et al. (2017) and Xie et al. (2017).”
From A Genome-wide Framework for Mapping Gene Regulation via Cellular Genetic Screens (2019) · cites this paper as Klann et al. (2017)
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2
Love, M. I., Huber, W., & Anders, S. (2014) · Genome Biology · doi:10.1186/s13059-014-0550-8 · Cited by 95,106
Fast gapped-read alignment with Bowtie 2
Langmead, B., & Salzberg, S. L. (2012) · Nature Methods · doi:10.1038/nmeth.1923 · Cited by 56,400
An integrated encyclopedia of DNA elements in the human genome
The ENCODE Project Consortium (2012) · Nature · doi:10.1038/nature11247 · Cited by 18,072
A Programmable Dual-RNA–Guided DNA Endonuclease in Adaptive Bacterial Immunity
Jinek, M., Chylinski, K., Fonfara, I., Hauer, M., Doudna, J. A., & Charpentier, E. (2012) · Science · doi:10.1126/science.1225829 · Cited by 17,116
Multiplex Genome Engineering Using CRISPR/Cas Systems
Cong, L., Ran, F. A., Cox, D., Lin, S., Barretto, R., Habib, N., Hsu, P. D., Wu, X., Jiang, W., Marraffini, L. A., et al. (2013) · Science · doi:10.1126/science.1231143 · Cited by 15,339
Slamon, D. J., Leyland-Jones, B., Shak, S., Fuchs, H., Paton, V., Bajamonde, A., Fleming, T., Eiermann, W., Wolter, J., Pegram, M., et al. (2001) · New England Journal of Medicine · doi:10.1056/nejm200103153441101 · Cited by 11,500
RNA-Guided Human Genome Engineering via Cas9
Mali, P., Yang, L., Esvelt, K. M., Aach, J., Guell, M., DiCarlo, J. E., Norville, J. E., & Church, G. M. (2013) · Science · doi:10.1126/science.1232033 · Cited by 9,210
Improved vectors and genome-wide libraries for CRISPR screening
Sanjana, N. E., Shalem, O., & Zhang, F. (2014) · Nature Methods · doi:10.1038/nmeth.3047 · Cited by 5,239
Genome-scale CRISPR-Cas9 knockout screening in human cells
Shalem, O., Sanjana, N. E., Hartenian, E., Shi, X., Scott, D. A., Mikkelsen, T. S., Heckl, D., Ebert, B. L., Root, D. E., Doench, J. G., et al. (2014) · Science · doi:10.1126/science.1247005 · Cited by 5,234
Repurposing CRISPR as an RNA-Guided Platform for Sequence-Specific Control of Gene Expression
Qi, L. S., Larson, M. H., Gilbert, L. A., Doudna, J. A., Weissman, J. S., Arkin, A. P., & Lim, W. A. (2013) · Cell · doi:10.1016/j.cell.2013.02.022 · Cited by 5,016
Cited by
Sorted by citations
Items 401–454 of 454
CRISPR-Cas Fundamentals and Advancements in Translational Biotechnology
Kapoor, D. D., Yadav, S., & Gupta, R. K. (2023) · Springer eBooks · doi:10.1007/978-981-99-3126-2_12
eLife Assessment: Predicting the effect of CRISPR-Cas9-based epigenome editing
Khalil, A. S. (2023) · eLife · doi:10.7554/elife.92991.1.sa2
Neuropsychiatric Disorders and Epigenetics: summary and outlook
Peedicayil, J., & Grayson, D. R. (2024) · Elsevier eBooks · doi:10.1016/b978-0-443-18516-8.00012-0
Prediction of transcription factor binding using epigenomics and genome variation data
Baumgarten, N. (2023) · Publication Server of Goethe University Frankfurt am Main (Goethe University Frankfurt) · doi:10.21248/gups.82138
Feng, Y., Wang, Y., Wang, X., He, X., Chen, Y., Naseri, A., Pederson, T., Zheng, J., Zhang, S., Xiao, X., et al. (2020) · Figshare · doi:10.6084/m9.figshare.13352150
Feng, Y., Wang, Y., Wang, X., He, X., Chen, Y., Naseri, A., Pederson, T., Zheng, J., Zhang, S., Xiao, X., et al. (2020) · Figshare · doi:10.6084/m9.figshare.13352144
Feng, Y., Wang, Y., Wang, X., He, X., Chen, Y., Naseri, A., Pederson, T., Zheng, J., Zhang, S., Xiao, X., et al. (2020) · Figshare · doi:10.6084/m9.figshare.13352153
Feng, Y., Wang, Y., Wang, X., He, X., Chen, Y., Naseri, A., Pederson, T., Zheng, J., Zhang, S., Xiao, X., et al. (2020) · Figshare · doi:10.6084/m9.figshare.13352147
Application of CRISPR in Cancer Research and Treatment
Singh, A. K., Kapoor, V., & Gupta, R. K. (2024) · Springer eBooks · doi:10.1007/978-981-99-3746-2_7
Rojhannezhad, M., Mowla, S. J., Soltani, B. M., Vasei, M., Taghizadeh, S., & Mirsadeghi, L. (2022) · ملیون. · doi:10.61186/sjrm.7.3.177
An overview of epigenetics and cancer
Pangeni, R. P. (2024) · Elsevier eBooks · doi:10.1016/b978-0-443-13209-4.00011-8
Modification and Screening of Antibiotic-producing Strains
Sun, B. (2024) · Innovation & Technology Advances · doi:10.61187/ita.v2i2.130
Narayanan, A., & West, A. E. (2024) · Springer eBooks · doi:10.1007/978-3-031-68550-7_7
Functional enhancers: concept, screening, and validation
Lin, H., Chen, F., & Huang, J. (2025) · Scientia Sinica Vitae · doi:10.1360/ssv-2025-0113
Predicting the effect of CRISPR-Cas9-based epigenome editingPreprint
Batra, S. S., Cabrera, A., Spence, J. P., Goell, J., Anand, S. S., Hilton, I. B., & Song, Y. S. (2025) · eLife · doi:10.7554/elife.92991.3
Self-citationMultifaceted roles of CRISPR technology in blood cancer research
Solayappan, M., Azlan, A., Khor, K. Z., Yik, M. Y., Jaishanker, A., Thevendran, R., Saleem, M. T. S., Yusoff, N. M., & Moses, E. J. (2025) · Current Opinion in Hematology · doi:10.1097/moh.0000000000000855
CRISPR Technologies for Precise Epigenome Editing and Current Applications
Abdallah, N. A., Hamwieh, A., Radwan, K. H., Fouad, N., & Baum, M. (2025) · CABI climate change series. · doi:10.1079/9781800626102.0001
CRISPR/Cas technologies in epigenetics research
Zheng, C., Hu, K., Li, J., Wang, Y., & Zhang, J. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-26759-8.00020-5
Ray-Jones, H. F., Duffus, K., McGovern, A., Martin, P., Shi, C., Hankinson, J., Gough, O., Yarwood, A., Morris, A. P., Adamson, A. D., et al. (2020) · Figshare · doi:10.6084/m9.figshare.12246839
Ray-Jones, H. F., Duffus, K., McGovern, A., Martin, P., Shi, C., Hankinson, J., Gough, O., Yarwood, A., Morris, A. P., Adamson, A. D., et al. (2020) · Figshare · doi:10.6084/m9.figshare.12246902
Ray-Jones, H. F., Duffus, K., McGovern, A., Martin, P., Shi, C., Hankinson, J., Gough, O., Yarwood, A., Morris, A. P., Adamson, A. D., et al. (2020) · Figshare · doi:10.6084/m9.figshare.12246926
He, Z., Dong, C., Song, T., Zhou, J., Xu, T., He, R., & Li, S. (2024) · Figshare · doi:10.6084/m9.figshare.26716933
Ray-Jones, H. F., Duffus, K., McGovern, A., Martin, P., Shi, C., Hankinson, J., Gough, O., Yarwood, A., Morris, A. P., Adamson, A. D., et al. (2020) · Figshare · doi:10.6084/m9.figshare.12246872
Additional file 1 of Mechanisms of enhancer action: the known and the unknown
Panigrahi, A., & O’Malley, B. W. (2021) · Figshare · doi:10.6084/m9.figshare.14429176
Ray-Jones, H. F., Duffus, K., McGovern, A., Martin, P., Shi, C., Hankinson, J., Gough, O., Yarwood, A., Morris, A. P., Adamson, A. D., et al. (2020) · Figshare · doi:10.6084/m9.figshare.12246908
Ray-Jones, H. F., Duffus, K., McGovern, A., Martin, P., Shi, C., Hankinson, J., Gough, O., Yarwood, A., Morris, A. P., Adamson, A. D., et al. (2020) · Figshare · doi:10.6084/m9.figshare.12246866
Ray-Jones, H. F., Duffus, K., McGovern, A., Martin, P., Shi, C., Hankinson, J., Gough, O., Yarwood, A., Morris, A. P., Adamson, A. D., et al. (2020) · Figshare · doi:10.6084/m9.figshare.12246851
He, Z., Dong, C., Song, T., Zhou, J., Xu, T., He, R., & Li, S. (2024) · Figshare · doi:10.6084/m9.figshare.26716936
Ray-Jones, H. F., Duffus, K., McGovern, A., Martin, P., Shi, C., Hankinson, J., Gough, O., Yarwood, A., Morris, A. P., Adamson, A. D., et al. (2020) · Figshare · doi:10.6084/m9.figshare.12246932
Ray-Jones, H. F., Duffus, K., McGovern, A., Martin, P., Shi, C., Hankinson, J., Gough, O., Yarwood, A., Morris, A. P., Adamson, A. D., et al. (2020) · Figshare · doi:10.6084/m9.figshare.12246887
Additional file 1 of MAUDE: inferring expression changes in sorting-based CRISPR screens
de Boer, C. G., Ray, J., Hacohen, N., & Regev, A. (2020) · Figshare · doi:10.6084/m9.figshare.12421364
Feng, Y., Wang, Y., Wang, X., He, X., Yang, C., Naseri, A., Pederson, T., Zheng, J., Zhang, S., Xiao, X., et al. (2020) · Figshare · doi:10.6084/m9.figshare.13352156
Ray-Jones, H. F., Duffus, K., McGovern, A., Martin, P., Shi, C., Hankinson, J., Gough, O., Yarwood, A., Morris, A. P., Adamson, A. D., et al. (2020) · Figshare · doi:10.6084/m9.figshare.12246896
Feng, Y., Wang, Y., Wang, X., He, X., Yang, C., Naseri, A., Pederson, T., Zheng, J., Zhang, S., Xiao, X., et al. (2020) · Figshare · doi:10.6084/m9.figshare.13352162
Feng, Y., Wang, Y., Wang, X., He, X., Yang, C., Naseri, A., Pederson, T., Zheng, J., Zhang, S., Xiao, X., et al. (2020) · Figshare · doi:10.6084/m9.figshare.13352159
He, Z., Dong, C., Song, T., Zhou, J., Xu, T., He, R., & Li, S. (2024) · Figshare · doi:10.6084/m9.figshare.26716939
Luo, S., Lin, L., Zhang, H., Yang, Y., Liu, Y., Han, Y., Chen, F., Liang, R., Niang, X., Dai, J., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.02.02.703403
Distinguishing causal from tagging enhancers using single-cell multiome dataPreprint
Dorans, E., & Price, A. L. (2026) · medRxiv · doi:10.64898/2026.02.15.26346353
Development of targeted methylome modifications in mammal cells
Lleida, A. A. (2018) · theses.fr (ABES) · doi:10.70675/6e05a7d8z70caz4650zb774z4d6156ab4205
de Freitas, J. A. N. L. F. (2020) · theses.fr (ABES) · doi:10.70675/0e6e3614z3915z4fb8za2cdz24b40b9679b2
Caractérisation des enhancers dérégulés dans la leucémie aiguë lymphoblastique de type T
España, A. P. (2019) · theses.fr (ABES) · doi:10.70675/5c13bdf2zac72z45c4z91e7z396bdaa5ddc4
Gene coregulation in cis within the 3D genome – A single-molecule imaging study
Kerlin, M. A. (2021) · theses.fr (ABES) · doi:10.70675/95774cf6z713dz4df5z92b1z76204ad8b669
Yu, W., Chen, J., Guo, J. Z., Yu, F., Wang, G. G., Lin, J., Dai, X., Tan, X., Ma, P., Wu, L., et al. (2026) · Nature Communications · doi:10.1038/s41467-026-74520-z
ATLAS-Evo: An Evidence-Tiered Benchmark Framework for Condition-Aware Cis-Regulatory PredictionPreprint
Jafari, A., Jayervand, P., & Ederth, T. (2026) · Research Square · doi:10.21203/rs.3.rs-10120522/v1
Tuning epigenetics to enhance cancer virotherapy
Wang, Y., Zhang, L., Che, Y., Fu-hua, Y., & Sun, Z. (2026) · Acta Pharmaceutica Sinica B · doi:10.1016/j.apsb.2026.06.045 · Cited by 1
Advances and clinical potential of epigenome editing
Choi, I., Kim, S., & Baek, I. (2026) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-026-06311-0
Region-Level Design and Analysis of CRISPR Perturbation Screens with FRACTELPreprint
Doty, R. W., ter Weele, M. A., Barrera, A., Bounds, L. R., Gersbach, C. A., & Allen, A. S. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.07.06.736794
Self-citationYin, D., Chang, Z., Yz, L., Dai, J., Qu, T., Su, J., Lu, X., Pf, W., Han, L., & Zhang, E. (2026) · Oncogene · doi:10.1038/s41388-026-03817-6
From epigenetic mark detection to rational design of epigenetic editing strategies
Faiq, A., Haider, S., & Nitschke, R. (2026) · Molecular Therapy Advances · doi:10.1016/j.omta.2026.201831
Zhu, W., Tian, M., Duan, Y., Reisman, S. J., Miller, S. E., Corden, E., ter Weele, M. A., Song, L., Blount, J., Safi, A., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.08.10.743836
Self-citationFunctional identification of non-coding regulatory regions that drive breast and skin carcinogenesis
Oh, R. H., Cheng, K. C. L., Serafimova, E., Langille, E. R., Pérez‐Castro, M. A., Lowden, C., Nurtanto, J., Dessapt, J., Fotiadou, I., Haider, S., et al. (2026) · Cell Reports · doi:10.1016/j.celrep.2026.118111
Role of Chromatin-Associated RNAs in Eye Physiology and Pathology
Savickyte, I., & Lapinaitė, A. (2026) · Methods in molecular biology · doi:10.1007/978-1-0716-5627-3_1
Metadata
- Authors
- Klann, T. S., Black, J. B., Chellappan, M., Safi, A., Song, L., Hilton, I. B., Crawford, G. E., Reddy, T. E., & Gersbach, C. A.
- Affiliations
- Duke University (US)
- Corresponding author
- Crawford, Gregory E
- Reddy, Timothy E
- Gersbach, Charles A
- ORCID
- Venue
- Nature Biotechnology
- Published
- 2017-04-03
- Volume
- 35
- Issue
- 6
- Pages
- 561-568
- ISSN
- 0733-222X (ISSN-L)
- 1087-0156
- 1546-1696
- PMC
- PMC5462860
- OpenAlex
- W2604130415
- Cited by
- 447
- References
- 56
- Citations by year
- 2026: 23 · 2025: 24 · 2024: 37 · 2023: 39 · 2022: 53 · 2021: 57 · 2020: 70 · 2019: 64 · 2018: 55 · 2017: 24
- FWCI
- 24.45
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Biotechnology (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (1dp2od008586-01)
- National Institute on Drug Abuse (R01DA036865)
- National Human Genome Research Institute (U01HG007900)
- National Institute of General Medical Sciences (T32GM008555, R41GM119914)
- National Institute of Arthritis and Musculoskeletal and Skin Diseases (P30AR066527)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › CRISPR and Genetic Engineering
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Chromatin Remodeling and Cancer
- Keywords
- regulatory elements, high-throughput screening, Ceres, DNase I hypersensitive sites, loss-of-function screen, gain-of-function screen, beta-globin locus, non-coding genome
- MeSH terms
- Gene Editing, Chromosome Mapping, Humans, Genome, Human, Sequence Analysis, DNA, Regulatory Elements, Transcriptional, Epigenomics, High-Throughput Nucleotide Sequencing, Clustered Regularly Interspaced Short Palindromic Repeats, CRISPR-Cas Systems, CRISPR-Associated Proteins
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.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
