ArticleNature communications2015
Context influences on TALE-DNA binding revealed by quantitative profiling.
Article in Nature communications, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
21 citing papers in PubMed.
- Unconstrained Precision Mitochondrial Genome Editing with αDdCBEs.Human gene therapy · 2024Article
- Designer TALEs enable discovery of cell death-inducer genes.Plant physiology · 2024Article
- Targeted DNA Demethylation: Vectors, Effectors and Perspectives.Biomedicines · 2023Review
- Review
- A single promoter-TALE system for tissue-specific and tuneable expression of multiple genes in rice.Plant biotechnology journal · 2022Article
- Epigenetic Editing in Prostate Cancer: Challenges and Opportunities.Epigenetics · 2022Review
- Flexible TALEs for an expanded use in gene activation, virulence and scaffold engineering.Nucleic acids research · 2022Article
- Engineering protein and DNA tools for creating DNA-dependent protein switches.Methods in enzymology · 2022Article
- DNA features beyond the transcription factor binding site specify target recognition by plant MYC2-related bHLH proteins.Plant communications · 2021Article
- The genetic arms race between plant and Xanthomonas: lessons learned from TALE biology.Science China. Life sciences · 2021Review
- Epigenome engineering: new technologies for precision medicine.Nucleic acids research · 2020Article
- Annotations capturing cell type-specific TF binding explain a large fraction of disease heritability.Human molecular genetics · 2020Article
- Context and number of noncanonical repeat variable diresidues impede the design of TALE proteins with improved DNA targeting.Protein science : a publication of the Protein Society · 2020Article
- PrediTALE: A novel model learned from quantitative data allows for new perspectives on TALE targeting.PLoS computational biology · 2019Article
- Engineering altered protein-DNA recognition specificity.Nucleic acids research · 2018Review
- Engineered promoters enable constant gene expression at any copy number in bacteria.Nature biotechnology · 2018Article
- RNA-binding specificity landscapes of designer pentatricopeptide repeat proteins elucidate principles of PPR-RNA interactions.Nucleic acids research · 2018Article
- Engineering and Application of Zinc Finger Proteins and TALEs for Biomedical Research.Molecules and cells · 2017Review
- The effect of increasing numbers of repeats on TAL effector DNA binding specificity.Nucleic acids research · 2017Article
- Exploiting the sequence diversity of TALE-like repeats to vary the strength of dTALE-promoter interactions.Synthetic biology (Oxford, England) · 2017Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Transcription activator-like effector (TALE) proteins recognize DNA using a seemingly simple DNA-binding code, which makes them attractive for use in genome engineering technologies that require precise targeting. Although this code is used successfully to design TALEs to target specific sequences, off-target binding has been observed and is difficult to predict. Here we explore TALE-DNA interactions comprehensively by quantitatively assaying the DNA-binding specificities of 21 representative TALEs to ∼5,000-20,000 unique DNA sequences per protein using custom-designed protein-binding microarrays (PBMs). We find that protein context features exert significant influences on binding. Thus, the canonical recognition code does not fully capture the complexity of TALE-DNA binding. We used the PBM data to develop a computational model, Specificity Inference For TAL-Effector Design (SIFTED), to predict the DNA-binding specificity of any TALE. We provide SIFTED as a publicly available web tool that predicts potential genomic off-target sites for improved TALE design.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.