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Record W2289992440 · doi:10.1371/journal.pone.0150188

Homology Directed Knockin of Point Mutations in the Zebrafish tardbp and fus Genes in ALS Using the CRISPR/Cas9 System

2016· article· en· W2289992440 on OpenAlexafffund
Gary A.B. Armstrong, Meijiang Liao, Zhipeng You, Alexandra Lissouba, Brian E. Chen, Pierre Drapeau

Bibliographic record

VenuePLoS ONE · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsMcGill University Health CentreUniversité de Montréal
FundersCanadian Institutes of Health ResearchQuébec Consortium for Drug DiscoveryWeston Brain InstituteALS AssociationFondation Brain CanadaALS Society of Canada
KeywordsCRISPRGenome editingZebrafishBiologyGeneticsComputational biologyGeneCas9PalindromeGenomeHomology (biology)Homology directed repairDNA repairNucleotide excision repair

Abstract

fetched live from OpenAlex

The methodology for site-directed editing of single nucleotides in the vertebrate genome is of considerable interest for research in biology and medicine. The clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 type II (Cas9) system has emerged as a simple and inexpensive tool for editing genomic loci of interest in a variety of animal models. In zebrafish, error-prone non-homologous end joining (NHEJ) has been used as a simple method to disrupt gene function. We sought to develop a method to easily create site-specific SNPs in the zebrafish genome. Here, we report simple methodologies for using CRISPR/Cas9-mediated homology directed repair using single-stranded oligodeoxynucleotide donor templates (ssODN) for site-directed single nucleotide editing, for the first time in two disease-related genes, tardbp and fus.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.022
GPT teacher head0.267
Teacher spread0.245 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations136
Published2016
Admission routes2
Has abstractyes

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Same venuePLoS ONESame topicCRISPR and Genetic EngineeringFrench-language works237,207