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Record W2095144494 · doi:10.1186/1472-6750-8-77

A construct with fluorescent indicators for conditional expression of miRNA

2008· article· en· W2095144494 on OpenAlexfundno aff
Linghua Qiu, Hongyan Wang, Xu‐Gang Xia, Hongxia Zhou, Zuoshang Xu

Bibliographic record

VenueBMC Biotechnology · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Interference and Gene Delivery
Canadian institutionsnot available
FundersNational Institute of Neurological Disorders and StrokeUniversity of TorontoALS AssociationJohns Hopkins UniversityNational Institute on AgingNational Institutes of Health
KeywordsBiologyConstruct (python library)microRNAExpression (computer science)Computational biologyGeneticsGeneComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: Transgenic RNAi holds promise as a simple, low-cost, and fast method for reverse genetics in mammals. It may be particularly useful for producing animal models for hypomorphic gene function. Inducible RNAi that permits spatially and temporally controllable gene silencing in vivo will enhance the power of transgenic RNAi approach. Furthermore, because microRNA (miRNA) targeting specific genes can be expressed simultaneously with protein coding genes, incorporation of fluorescent marker proteins can simplify the screening and analysis of transgenic RNAi animals. RESULTS: We sought to optimally express a miRNA simultaneously with a fluorescent marker. We compared two construct designs. One expressed a red fluorescent protein (RFP) and a miRNA placed in its 3' untranslated region (UTR). The other expressed the same RFP and miRNA, but the precursor miRNA (pre-miRNA) coding sequence was placed in an intron that was inserted into the 3'-UTR. We found that the two constructs expressed comparable levels of miRNA. However, the intron-containing construct expressed a significantly higher level of RFP than the intron-less construct. Further experiments indicate that the 3'-UTR intron enhances RFP expression by its intrinsic gene-expression-enhancing activity and by eliminating the inhibitory effect of the pre-miRNA on the expression of RFP. Based on these findings, we incorporated the intron-embedded pre-miRNA design into a conditional expression construct that employed the Cre-loxP system. This construct initially expressed EGFP gene, which was flanked by loxP sites. After exposure to Cre recombinase, the transgene stopped EGFP expression and began expression of RFP and a miRNA, which silenced the expression of specific cellular genes. CONCLUSION: We have designed and tested a conditional miRNA-expression construct and showed that this construct expresses both the marker genes strongly and can silence the target gene efficiently upon Cre-mediated induction of the miRNA expression. This construct can be used to increase the efficiency of making cell lines or transgenic animals that stably express miRNA targeting specific genes.

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)0.001
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: none
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.003

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 head0.013
GPT teacher head0.231
Teacher spread0.218 · 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

Citations41
Published2008
Admission routes1
Has abstractyes

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