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Record W4280493960 · doi:10.1186/s12896-022-00744-8

Introduction of loxP sites by electroporation in the mouse genome; a simple approach for conditional allele generation in complex targeting loci

2022· article· en· W4280493960 on OpenAlexafffund
Guillaume Bernas, Mariette Ouellet, Andréa Barrios, Hélène Jamann, Catherine Larochelle, Émile Lévy, Jean-François Schmouth

Bibliographic record

VenueBMC Biotechnology · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsUniversité de MontréalCentre Hospitalier de l’Université de Montréal
FundersUniversity of California, IrvineMultiple Sclerosis SocietyMultiple Sclerosis Society of CanadaEuropean Genomic Institute for Diabetes
KeywordsBiologyCre-Lox recombinationElectroporationAlleleGeneticsGenomeComputational biologySimple (philosophy)GeneTransgene

Abstract

fetched live from OpenAlex

BACKGROUND: The discovery of the CRISPR-Cas9 system and its applicability in mammalian embryos has revolutionized the way we generate genetically engineered animal models. To date, models harbouring conditional alleles (i.e. two loxP sites flanking an exon or a critical DNA sequence of interest) are amongst the most widely requested project type that are challenging to generate as they require simultaneous cleavage of the genome using two guides in order to properly integrate the repair template. An approach, using embryo sequential electroporation has been reported in the literature to successfully introduce loxP sites on the same allele. Here, we describe a modification of this sequential electroporation procedure that demonstrated the production of conditional allele mouse models for eight different genes via one of two possible strategies: either by consecutive sequential electroporation (strategy A) or non-consecutive sequential electroporation (strategy B). This latest strategy originated from using the by-product produced when using consecutive sequential electroporation (i.e. mice with a single targeted loxP site) to complete the project. RESULTS: By using strategy A, we demonstrated successful generation of conditional allele models for three different genes (Icam1, Lox, and Sar1b), with targeting efficiencies varying between 5 and 13%. By using strategy B, we generated five conditional allele models (Loxl1, Pard6a, Pard6g, Clcf1, and Mapkapk5), with targeting efficiencies varying between 3 and 25%. CONCLUSION: Our modified electroporation-based approach, involving one of the two alternative strategies, allowed the production of conditional allele models for eight different genes via two different possible paths. This reproducible method will serve as another reliable approach in addition to other well-established methodologies in the literature for conditional allele mouse model generation.

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)0.001
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: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.002
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 head0.014
GPT teacher head0.264
Teacher spread0.250 · 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
GenreMethods

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

Citations6
Published2022
Admission routes2
Has abstractyes

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