ArticleRNA biology2019
Prediction and diversity of tracrRNAs from type II CRISPR-Cas systems.
Article in RNA biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 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
18 citing papers in PubMed.
- CoCas9 is a compact nuclease from the human microbiome for efficient and precise genome editing.Nature communications · 2024Article
- The CRISPR-Cas system inFrontiers in microbiology · 2024Article
- Novel and Engineered Type II CRISPR Systems from Uncultivated Microbes with Broad Genome Editing Capability.The CRISPR journal · 2023Article
- Single-Stranded DNA-Binding Proteins Mediate DSB Repair and Effectively Improve CRISPR/Cas9 Genome Editing inMicroorganisms · 2023Article
- CRISPR-Cas systems feature and targeting phages diversity inFrontiers in microbiology · 2023Article
- Applications of CRISPR/Cas technology against drug-resistant lung cancers: an update.Molecular biology reports · 2022Review
- Analysis of Probiotic Bacteria Genomes: Comparison of CRISPR/Cas Systems and Spacer Acquisition Diversity.Indian journal of microbiology · 2022Article
- Discovery in CRISPR-Cas9 system.Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2021Article
- The tracrRNA in CRISPR Biology and Technologies.Annual review of genetics · 2021Review
- Identification and Evolution of Cas9 tracrRNAs.The CRISPR journal · 2021Article
- Targeting cancer epigenetics with CRISPR-dCAS9: Principles and prospects.Methods (San Diego, Calif.) · 2021Review
- A compact Cas9 ortholog from Staphylococcus Auricularis (SauriCas9) expands the DNA targeting scope.PLoS biology · 2020Article
- Evolutionary classification of CRISPR-Cas systems: a burst of class 2 and derived variants.Nature reviews. Microbiology · 2020Review
- How CRISPR-Cas System Could Be Used to Combat Antimicrobial Resistance.Infection and drug resistance · 2020Review
- Genome-wide correlation analysis suggests different roles of CRISPR-Cas systems in the acquisition of antibiotic resistance genes in diverse species.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2019Article
- CRISPR-Cas: more than ten years and still full of mysteries.RNA biology · 2019Article
- Article
- CasPDB: an integrated and annotated database for Cas proteins from bacteria and archaea.Database : the journal of biological databases and curation · 2019Article
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
No grant is acknowledged in the PubMed record.
Abstract
Type II CRISPR-Cas9 systems require a small RNA called the trans-activating CRISPR RNA (tracrRNA) in order to function. The prediction of these non-coding RNAs in prokaryotic genomes is challenging because they have dissimilar structures, having short stems (3-6 bp) and non-canonical base-pairs e.g. G-A. Much of the tracrRNA is involved in base-pairing interactions with the CRISPR RNA, or itself, or in RNA-protein interactions with Cas9. Here we develop a new bioinformatic tool to predict tracrRNAs. On an experimentally verified test set the algorithm achieved a high sensitivity and specificity, and a low false discovery rate (FDR) on genome analysis. Analysis of representative RefSeq genomes (5462) detected 275 tracrRNAs from 165 genera. These tracrRNAs could be grouped into 15 clusters which were used to build covariance models. These clusters included Streptococci and Staphylococci tracrRNAs from the CRISPR-Cas9 systems which are currently used for gene editing. Compensating base changes observed in the models were consistent with the experimental structures of single guide RNAs (sgRNAs). Other clusters, for which there are not yet structures available, were predicted to form novel tracrRNA folds. These clusters included a large and divergent tracrRNA set from Bacteroidetes. These computational models contribute to the understanding of CRISPR-Cas biology, and will assist in the design of further engineered CRISPR-Cas9 systems. The tracrRNA prediction software is available through a galaxy web server.
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.