ReviewMethods (San Diego, Calif.)2014
Tools for TAL effector design and target prediction.
Review in Methods (San Diego, Calif.), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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
9 citing papers in PubMed.
- Epigenetic features improve TALE target prediction.BMC genomics · 2021Article
- ThePlant communications · 2021Article
- PrediTALE: A novel model learned from quantitative data allows for new perspectives on TALE targeting.PLoS computational biology · 2019Article
- A Pathovar ofFrontiers in plant science · 2019Article
- Engineering altered protein-DNA recognition specificity.Nucleic acids research · 2018Review
- Efficient enrichment cloning of TAL effector genes fromMethodsX · 2018Article
- TALEN based HPV-E7 editing triggers necrotic cell death in cervical cancer cells.Scientific reports · 2017Article
- The genome of the cotton bacterial blight pathogenStandards in genomic sciences · 2017Article
- QueTAL: a suite of tools to classify and compare TAL effectors functionally and phylogenetically.Frontiers in plant science · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
TAL effectors are transcription factors injected into plant cells by pathogenic bacteria during infection. They find their specific DNA targets via a string of contiguous, structural repeats that individually recognize single nucleotides (with some degeneracy) by virtue of polymorphisms at residue 13. The number of repeats and sequence of the amino acids at position 13 determine the nucleotide sequence of the DNA target. Due to this modularity, TAL effectors are readily engineered and have been used alone or as molecular fusions for targeted gene activation, gene repression, chromatin modification, chromatin tagging, and most broadly, for genome editing as TAL effector nucleases (TALENs). Several moderate and high-throughput cloning methods are in place for assembling TAL effector-based genetic constructs. Targeting is complicated to an extent by a general requirement for thymine to precede the DNA target, a requirement of TALENs to bind paired opposing sites separated by a defined range of distances, differential contributions of different repeat types to overall affinity, and a polarity to mismatch tolerance. Several computational tools are available online to aid in design and the identification of candidate off-target binding sites, as well as assembly and implementation. These tools vary in their approaches, capabilities, and relative utility for different types of TAL effector applications. Accuracy of off-target prediction is not well characterized yet for any of the tools and will require a better understanding of the qualitative and quantitative variation in the nucleotide preferences of individual repeats.
Indexed as
Identifiers
What OpenQuestion holds
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.