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
Flagged first, then by citations
Cited by
Sorted by citations
Items 301–400 of 454
Li, J., Xu, L., Wang, X., Wang, X., Lin, Y., Zou, A., Ren, F., Wang, Y., Li, J., & Chang, Z. (2025) · Molecular Cancer · doi:10.1186/s12943-025-02361-3 · Cited by 5
Approches haut débit pour l’étude des séquences cis-régulatrices
España, A. P., Santiago‐Algarra, D., Pradel, L. C., & Spicuglia, S. (2017) · Biologie Aujourd hui · doi:10.1051/jbio/2018015 · Cited by 4
Application and prospects of high-throughput screening for in vitro neurogenesis
Zhang, S., Zhao, J., Ni, J.-J., Li, H., Quan, Z., & Qing, H. (2022) · World Journal of Stem Cells · doi:10.4252/wjsc.v14.i6.393 · Cited by 4
Contribution of CRISPRable DNA to human complex traits
Zhai, R., Zheng, C., Yang, Z., Li, T., Chen, J., & Shen, X. (2022) · Communications Biology · doi:10.1038/s42003-022-03969-7 · Cited by 3
A unifying statistical framework to discover disease genes from GWASs
McManus, J. N. J., Lovelett, R. J., Lowengrub, D., & Christensen, S. (2023) · Cell Genomics · doi:10.1016/j.xgen.2023.100264 · Cited by 5
Boulos, J., Golov, A. K., Keren, N., Erlich, I., Shehadeh, N., Avidan, N., Kariti, H., Sadeh, O., Haimovich-Caspi, L., Helms, A. S., et al. (2025) · iScience · doi:10.1016/j.isci.2025.114040 · Cited by 4
Advancing CRISPR-Based Programmable Platforms beyond Genome Editing in Mammalian Cells
Higashikuni, Y., & Lu, T. K. (2019) · ACS Synthetic Biology · doi:10.1021/acssynbio.9b00297 · Cited by 4
Dead Cas Systems: Types, Principles, and Applications
Brezgin, S., Kostyusheva, A., Kostyushev, D. S., & Chulanov, V. (2020) · Vide Leaf, Hyderabad eBooks · doi:10.37247/pamb.1.2020.14 · Cited by 5
McErlean, P. K., Kelly, A., Dhariwal, J., Kirtland, M., Watson, J., Ranz, I., Cousins, D. J., Solari, R. C. E., Edwards, M. R., Johnston, S. L., et al. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/282889 · Cited by 4
crisprQTL mapping as a genome-wide association framework for cellular genetic screensPreprint
Gasperini, M. J., Hill, A. J., McFaline‐Figueroa, J. L., Martin, B., Trapnell, C., Ahituv, N., & Shendure, J. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/314344 · Cited by 5
Glaser, L. V., Steiger, M., Fuchs, A., van Bömmel, A., Einfeldt, E., Chung, H.-R., Vingron, M., & Meijsing, S. H. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.06.04.446899 · Cited by 5
Discovery and engineering of hypercompact epigenetic modulators for durable gene activationPreprint
Carosso, G. A., Yeo, R. W., Gainous, T. B., Jawaid, M. Z., Yang, X., Cutillas, V., Daley, T., Hart, D. O., & Qi, L. S. (2023) · Research Square · doi:10.21203/rs.3.rs-3016082/v1 · Cited by 4
Genetic variants shape single-cell chromatin accessibility and disease risk
Xue, A., Fan, J., Dong, O. A., Huang, H. L., Chen, L., Allen, P. C., Spenceley, E., Sagi-Zsigmond, E., Bowen, B., Henry, A., et al. (2026) · Nature · doi:10.1038/s41586-026-11173-4 · Cited by 3
Moeckel, C. M., Mouratidis, I., Chantzi, N., Uzun, Y., & Georgakopoulos‐Soares, I. (2024) · BioEssays · doi:10.1002/bies.202300210 · Cited by 4
Techniques and strategies employing engineered transcription factors
Lawson, S., & Bleris, L. G. (2017) · Current Opinion in Biomedical Engineering · doi:10.1016/j.cobme.2017.10.009 · Cited by 3
CRISPR/Cas9 technology in neurological disorders: An update for clinicians
Srivastava, A. K., Swarup, V., Kumar, V., Faruq, M., Singh, H. N., & Singh, I. (2020) · Annals of Movement Disorders · doi:10.4103/aomd.aomd_39_19 · Cited by 4
How to find genomic regions relevant for gene regulation
Guo, X., Ohler, U., & Yildirim, F. (2021) · Medizinische Genetik · doi:10.1515/medgen-2021-2074 · Cited by 3
Deng, Y., Tang, L., Zhou, X., Wang, W., & Li, M. (2022) · iScience · doi:10.1016/j.isci.2022.105687 · Cited by 3
Dincer, T. U., & Ernst, J. (2025) · Genome biology · doi:10.1186/s13059-025-03579-6 · Cited by 3
Boosting, Not Breaking: CRISPR Activators Treat Disease Models
Gemberling, M. P., & Gersbach, C. A. (2018) · Molecular Therapy · doi:10.1016/j.ymthe.2018.01.004 · Cited by 3
Self-citationKey to Delivery: The (Epi-)genome Editing Vector Toolbox
Just, S., & Büning, H. (2018) · Methods in molecular biology · doi:10.1007/978-1-4939-7774-1_7 · Cited by 3
Transgenic mice for in vivo epigenome editing with CRISPR-based systemsPreprint
Gemberling, M. P., Siklenka, K., Rodriguez, E., Eisinger, K. R. T., Barrera, A., Liu, F., Kantor, A., Li, L., Cigliola, V., Hazlett, M. F., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.03.08.434430 · Cited by 3
Self-citationCompatibility logic of human enhancer and promoter sequencesPreprint
Bergman, D. T., Jones, T., Liu, V., Siraj, L., Kang, H., Nasser, J., Kane, M., Nguyen, T. H., Grossman, S. R., Fulco, C. P., et al. (2021) · bioRxiv · doi:10.1101/2021.10.23.462170 · Cited by 5
Enhancer Reprogramming in Melanoma Immune Checkpoint Therapy ResistancePreprint
Maitituoheti, M., Shi, A., Tang, M., Ho, L., Terranova, C. J., Galani, K., Keung, E. Z.-Y., Creasy, C. A., Wu, M., Chen, J., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.08.31.506051 · Cited by 3
Scaling perturbations: beyond genome-scale CRISPR screensPreprint
Tang, A., Ardy, R. C., Mendes, R., & Norman, T. M. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.01.16.699948 · Cited by 4
Targeted Modification of Epigenetic Marks Using CRISPR/dCas9-SunTag-Based Modular Epigenetic Toolkit
Song, M. K., & Kim, Y. (2024) · Methods in molecular biology · doi:10.1007/978-1-0716-3662-6_7 · Cited by 2
A Comprehensive Review on CRISPR-Based Screening and Its Applications
Sichani, A. S., Hassani, M., Gila, F., Shafieipour, N., Dabbaghipour, R., Heidari, Z., Sisakht, M., Hassani, M., & Fallahi, J. (2026) · Molecular Biotechnology · doi:10.1007/s12033-026-01562-5 · Cited by 2
Advances in single-cell epigenomics of the immune system
Schulte-Schrepping, J., Ferreira, H. J., Saglam, A., Hinkley, E. R., & Schultze, J. L. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-817964-2.00008-3 · Cited by 2
Editing the Epigenome in Neurodegenerative Diseases
Vetchinova, A. S., Fedotova, E. Y., & Illarioshkin, S. N. (2021) · Neurochemical Journal · doi:10.1134/s1819712421040152 · Cited by 2
High-throughput navigation of the sequence space
Choudhury, A. (2022) · Elsevier eBooks · doi:10.1016/b978-0-12-824469-2.00011-7 · Cited by 1
Zhang, E., Sun, Q., Zhang, C., Ma, H., Zhang, J., Ding, Y., Wang, G., Chen, J., Jin, C., Fu, Y., et al. (2024) · Cancer Letters · doi:10.1016/j.canlet.2024.216646 · Cited by 2
Enhancer‐dependent gene regulation in space, time, and malignancies
Blum, B., Dachtler, V., & Feldmann, A. (2025) · International Journal of Cancer · doi:10.1002/ijc.35350 · Cited by 2
Pulling the genome in opposite directions to dissect gene networks
Gersbach, C. A., & Barrangou, R. (2018) · Genome biology · doi:10.1186/s13059-018-1425-1 · Cited by 2
Self-citationEpigenetic Therapies in the Precision Medicine Era
Leite, M. L., de Oliveira, K. B. S., Cunha, V. A., Dias, S. C., da Cunha, N. B., & Costa, F. F. (2020) · Advanced Therapeutics · doi:10.1002/adtp.201900184 · Cited by 1
CRISPR-Cas9 in cancer therapeutics
Randhawa, S. (2021) · Progress in molecular biology and translational science · doi:10.1016/bs.pmbts.2021.01.016 · Cited by 2
The transformational impact of site-specific DNA modifiers on biomedicine and agriculture
Polkoff, K. M., & Piedrahita, J. A. (2018) · Animal Reproduction · doi:10.21451/1984-3143-ar2018-0065 · Cited by 2
DNA Methylation in Multiple Sclerosis
Kular, L., & Jagodic, M. (2019) · RNA technologies · doi:10.1007/978-3-030-14792-1_8 · Cited by 2
CRISPR/Cas9 technologies in epigenetics research
Schoelz, J. M., & Riddle, N. C. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-819414-0.00027-6 · Cited by 2
Loop competition and extrusion model predicts CTCF interaction specificity
Wang, X., & Beer, M. (2021) · RePEc: Research Papers in Economics · Cited by 2
Computational prediction of CRISPR-impaired non-coding regulatory regions
Baumgarten, N., Schmidt, F., Wegner, M., Hebel, M., Kaulich, M., & Schulz, M. H. (2021) · Biological Chemistry · doi:10.1515/hsz-2020-0392 · Cited by 2
Reversible inhibition of specific transcription factor-DNA interactions using CRISPRPreprint
Shariati, A., Dominguez, A. A., Wernig, M., Qi, L. S., & Skotheim, J. M. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/282681 · Cited by 2
Adkar, S. S., Wu, C., Willard, V. P., Dicks, A. R., Ettyreddy, A. R., Steward, N. S., Bhutani, N., Gersbach, C. A., & Guilak, F. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/252767 · Cited by 2
Self-citationGenome Variation, the Epigenome and Cellular Phenotypes
Baumann, M., Klanert, G., Vcelar, S., Weinguny, M., Marx, N., & Borth, N. (2019) · Wiley eBooks · doi:10.1002/9783527811410.ch5 · Cited by 2
Maybury‐Lewis, S. Y., Brown, A. K., Yeary, M. D., Sloutskin, A., Dhakal, S., McCarthy-Sinclair, B., Juven‐Gershon, T., & Webb, A. E. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.01.24.918664 · Cited by 2
Loop competition and extrusion model predicts CTCF interaction specificityPreprint
Xi, W., & Beer, M. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.07.02.185389 · Cited by 2
Discovery and Functional Characterization of Pro-growth Enhancers in Human Cancer CellsPreprint
Chen, P.-S. B., Fiaux, P. C., Li, B., Zhang, K., Kubo, N., Jiang, S., Hu, R., Wu, S.-H., Wang, M.-C., Wang, W., et al. (2021) · bioRxiv · doi:10.1101/2021.02.04.429675 · Cited by 3
Comparative Analysis and Rational Design of dCas9-VP64 Variants for CRISPR ActivationPreprint
Omachi, K., & Miner, J. H. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.08.13.456279 · Cited by 2
Glaser, L. V., Steiger, M., Fuchs, A., van Bömmel, A., Einfeldt, E., Chung, H. R., Vingron, M., & Meijsing, S. H. (2021) · MDC Repository (Max-Delbrueck-Center for Molecular Medicine) · Cited by 2
Applications of CRISPRi and CRISPRa in Drug Discovery
Gilbert, L. A. (2022) · Wiley eBooks · doi:10.1002/9781119671404.ch10 · Cited by 2
Enhancer-driven gene regulatory network of forebrain human development provides insights into autismPreprint
Jourdon, A., Mariani, J., Natu, A., Wu, F., Li, B., Capauto, D., Hagy, K. T., Norton, S., Tomasini, L., Safi, A., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.09.06.555206 · Cited by 2
Self-citationGene regulatory activity associated with PCOS revealed DENND1A -dependent testosterone productionPreprint
Sankaranarayanan, L., Brewer, K., Johnson, G. D., Barrera, A., Venukuttan, R., Sisk, R. K., Dunaif, A. E., & Reddy, T. E. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.05.23.595551 · Cited by 2
Self-citationPredicting 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. (2024) · eLife · doi:10.7554/elife.92991.2 · Cited by 2
Self-citationFunctional Annotation of the Major Histocompatibility Complex LocusPreprint
Bounds, L. R., Barrera, A., ter Weele, M. A., Liu, S., Wu, E. Y., Li, S., Venukuttan, R., Rai, R., Mu, W., Iglesias, N., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.02.01.703124 · Cited by 3
Self-citationUnwind to the beat: chromatin and cardiac conduction
Chapski, D. J., & Vondriska, T. M. (2023) · Journal of Clinical Investigation · doi:10.1172/jci165663 · Cited by 1
Patel, A., & Dharap, A. A. (2025) · Stroke · doi:10.1161/strokeaha.125.050915 · Cited by 2
Antiviral and Mutagenic Effects of APOBEC Deaminases A3C, A3D, and A3H in a Hepatitis B Virus Model
Karandashov, I., Brezgin, S., Ponomareva, N. I., Tikhonov, A., Chulanov, V. P., Kostyushev, D. S., & Kostyusheva, A. (2026) · Biochemistry (Moscow) · doi:10.1134/s0006297925603326 · Cited by 1
Shariati, A., Homaei, A., Khezrpour, A., Azizi, N., Khani, P., Shariati, F. S., Rafiee, M., Afkhami, H., Yousefi, M. H., Saeidi, F., et al. (2026) · Current Research in Biotechnology · doi:10.1016/j.crbiot.2026.100382 · Cited by 1
Gold Nanorod-Affibody Conjugates Mediate Cancer Photothermal Therapy under 808 nm LED Irradiation
Martínez, M. C. N., Wieczerzak, E., Lobo, C. S., Pieve, C. D., Kreft, D., Grzegorczyk, M., Mahlik, S., Narajczyk, M., Rodziewicz‐Motowidło, S., Werner, J. H., et al. (2026) · ACS Applied Nano Materials · doi:10.1021/acsanm.6c00865 · Cited by 1
As 5mC enters a programmable era: charted avenues for cancer understanding and intervention
Shi, Q., Liu, P., Zhu, J.-K., & Sun, S. (2026) · Oral Science and Homeostatic Medicine · doi:10.26599/oshm.2026.9610044 · Cited by 1
Epigenetic Biomarkers and Their Therapeutic Applications in Colorectal Cancer
Hartley, A.-V., Martin, M., & Lu, T. (2019) · IntechOpen eBooks · doi:10.5772/intechopen.82572 · Cited by 1
Tumor-promoting function and regulatory landscape of PD-L2 in B-cell lymphoma
Shingaki, S., Koya, J., Yuasa, M., Saito, Y., Tabata, M., McClure, M. B., Ogawa, S., Katayama, K., Togashi, Y., Imoto, S., et al. (2022) · Leukemia · doi:10.1038/s41375-022-01772-1 · Cited by 1
Using Synthetic DNA Libraries to Investigate Chromatin and Gene Regulation
Kleinschmidt, H., Xu, C., & Bai, L. (2023) · Chromosoma · doi:10.1007/s00412-023-00796-5 · Cited by 2
Wei, Z., Liu, C., Liang, J., Zhou, X., Xue, K., Wang, K., & Zhang, X. (2024) · IUBMB Life · doi:10.1002/iub.2818 · Cited by 1
Reader-Effectors as Actuators of Epigenome Editing
Kim, S. H., & Haynes, K. A. (2024) · Methods in molecular biology · doi:10.1007/978-1-0716-4051-7_5 · Cited by 1
Geny, S., Hosseini, E. S., Concordet, J., & Giovannangeli, C. (2019) · Royal Society of Chemistry eBooks · doi:10.1039/9781788015714-00400 · Cited by 1
Stem Cell Epigenetics and Human Disease
Larijani, L., & Rancourt, D. E. (2018) · Elsevier eBooks · doi:10.1016/b978-0-12-812215-0.00029-7 · Cited by 1
Physiological Traits Based Breeding to Achieve Higher Yield in Soybean Crop
Singh, M., Nagar, S., Singh, A., & SATPUTE, G. K. (2022) · Springer eBooks · doi:10.1007/978-981-16-9848-4_12 · Cited by 1
Velegzhaninov, I. O., Игоревна, П. Я., Rybak, A. V., Шадрин, Д. М., Belykh, E. S., & Klokov, D. Y. (2018) · Preprints.org · doi:10.20944/preprints201812.0117.v1 · Cited by 1
Interrogation of Enhancer Function by Enhanced CRISPR Epigenetic EditingPreprint
Li, K., Liu, Y., Cao, H., Zhang, Y., Gu, Z., Liu, X., Yu, A., Kaphle, P., Dickerson, K. E., Ni, M., et al. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/761247 · Cited by 1
Kang, Y., & Brent, M. R. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.12.15.422864 · Cited by 1
Mitochondrial Phenotypes Distinguish Pathogenic MFN2 Mutations by Pooled Functional Genomics ScreenPreprint
Yenkin, A. L., Bramley, J. C., Kremitzki, C. L., Waligorski, J. E., Liebeskind, M. J., Xu, X. E., Vakaki, M. A., Chandrasekaran, V. D., Mitra, R. D., Milbrandt, J., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.03.12.434746 · Cited by 1
Repurposing the CRISPR-Cas9 System for Targeted Chromatin O-linked β-N-acetylglucosamine EditingPreprint
Parker, M. P., Dias, W. B., Brautman, W., Lowe, N., Fedosyuk, H., Peterson, K. R., & Slawson, C. M. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.10.27.514044 · Cited by 1
Alda-Catalinas, C., Ibarra-Soria, X., Flouri, C., Gordillo, J. E., Cousminer, D. L., Hutchinson, A., Krejčí, A., Cortés, A., Acevedo, A., Malla, S., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.05.14.540711 · Cited by 1
MethNet: a robust approach to identify regulatory hubs and their distal targets in cancerPreprint
Sakellaropoulos, T., Do, C., Jiang, G., Cova, G., Meyn, P., Dimartino, D., Ramaswami, S., Heguy, A., Tsirigos, A., & Skok, J. A. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.07.07.548142 · Cited by 1
Predicting the effect of CRISPR-Cas9-based epigenome editingPreprint
Batra, S. S., Cabrera, A., Spence, J. P., Hilton, I. B., & Song, Y. S. (2023) · eLife · doi:10.7554/elife.92991.1 · Cited by 1
Self-citationCRISPRing the Human Genome for Functional Regulatory Elements
Lopes, R. (2018) · RePub (Erasmus University Rotterdam)
Cas-CLIP: a method for customizing pooled CRISPR librariesPreprint
Kweon, J., Kim, J., Jang, A.-H., & Kim, Y. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/187757
Discovering functional sequences with RELICS, an analysis method for tiling CRISPR screensPreprint
Fiaux, P. C., Chen, H. V., Chen, A. R., Chen, P. B., & McVicker, G. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/687293
Identification of Essential Genes in Hepatocellular Carcinomas using CRISPR Screening
Sheel, A. (2019) · The Journal of the American Medical Association (JAMA) Network (American Medical Association) · doi:10.13028/hv7r-q398
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. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/822304
REMY: A platform for the rapid interrogation of epigenome modifications on yeastPreprint
Waldman, A. C., Rao, B. M., & Keung, A. J. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.02.24.432679
鍼灸の免疫応答、特にTh1、Th2バランスに与える影響について(平成17年度共同研究報告)
栗林, 恒., 田原, 壮., 笠原, 由., 奥田, 学., & 岡田, 圭. (2007)
Development and Vision of CRISPR-Based Technology
Zhang, Z., Wang, P., & Liu, J. (2022) · Springer eBooks · doi:10.1007/978-981-16-8504-0_1
Riegel, D., Romero-Fernández, E., Simon, M., Adenugba, A. R., Singer, K., Mayr, R., Weber, F., Imbusch, C. D., Kreutz, M. P., Brors, B., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.03.16.484513
Gianni, D., & Escudero‐Ibarz, L. (2022) · Wiley eBooks · doi:10.1002/9781119671404.ch9
Glucocorticoid Receptor Regulated KCNA5 Mediates Cell Proliferation in Human Fetal MembranesPreprint
Cunningham, S. J., Barrera, A., Sankaranarayanan, L., Allen, T. K., & Reddy, T. E. (2022) · Research Square · doi:10.21203/rs.3.rs-1594481/v1
Self-citationSharrocks, A. D. (2019) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.735667505.793560965
Saitsu, H. (2020) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.737001613.793572920
Mefford, H. C. (2020) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.736437709.793571951
NON-CHROMATOGRAPHIC OLIGONUCLEOTIDE PURIFICATION AND AUTOMATED POLYETHYLENEGLYCOL SYNTHESIS
Eriyagama, D. N. A. M. (2022) · doi:10.37099/mtu.dc.etdr/1396
Glucocorticoid Receptor Regulated KCNA5 Mediates Cell Proliferation in Human Fetal MembranesPreprint
Cunningham, S. J., Barrera, A., Sankaranarayanan, L., Allen, T. K., & Reddy, T. E. (2022) · Research Square · doi:10.21203/rs.3.rs-1594481/v2
Self-citationSAM-based Genome Editing to Obtain Isogenic Cell Lines Overexpressing Human CD5 Protein
Istomina, P. V., Kulemzin, S. V., Yamabhai, M., & Gorchakov, A. A. (2022) · Russian Journal for Personalized Medicine · doi:10.18705/2782-3806-2022-2-4-56-62
Host Cell Transcriptional Tuning with CRISPR/dCas9 to Mitigate the Effects of Toxin Exposure
Metzger, D., Miller, K., Lyon, W. J., Migliozzi, R., Pangburn, H. A., & Saldanha, R. (2022) · ACS Synthetic Biology · doi:10.1021/acssynbio.2c00214
Kang, E.-H., Kim, J., Noh, H., Park, S., Park, H., Yoon, S., & Kim, H. (2022) · Stem Cell Research · doi:10.1016/j.scr.2022.102986
CRISPR-Cas Functional Genetic Screening: Traditional Review
Kara, H. G., Kosova, B., Doğan, E., Çetintaş, V. B., & Şentürk, Ş. (2022) · Turkiye Klinikleri Journal of Medical Sciences · doi:10.5336/medsci.2022-88507
CRISPR technology and its potential role in treating rare imprinting diseases
Nickl, P., Syding, L. A., & Sedláček, R. (2023) · Principles of Gender-Specific Medicine · doi:10.1016/b978-0-323-88534-8.00044-4
CRISPR, epigenetics, and cancer
Martella, A. (2023) · Elsevier eBooks · doi:10.1016/b978-0-323-91367-6.00007-6
Advances towards personalized therapies for Stargardt disease
Huang, D., McLenachan, S., & Chen, F. K. (2023) · Expert Review of Ophthalmology · doi:10.1080/17469899.2023.2268289
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