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Record W2155582980 · doi:10.1101/gr.137224.112

Targeted gene silencing in mouse germ cells by insertion of a homologous DNA into a piRNA generating locus

2012· article· en· W2155582980 on OpenAlexfundno aff
Yasuhiro Yamamoto, Toshiaki Watanabe, Yuko Hoki, Kenjiro Shirane, Yufeng Li, Kenji Ichiiyanagi, Satomi Kuramochi‐Miyagawa, Atsushi Toyoda, Asao Fujiyama, Masayuki Oginuma, Hitomi Suzuki, Takashi Sado, Toru Nakano, Hiroyuki Sasaki

Bibliographic record

VenueGenome Research · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicChromosomal and Genetic Variations
Canadian institutionsnot available
FundersInstitute of GeneticsNaito Foundation
KeywordsPiwi-interacting RNABiologyRetrotransposonTransposable elementGene silencingGeneticsGeneHomologous recombinationRNA interferenceRNACell biologyGenome

Abstract

fetched live from OpenAlex

In germ cells, early embryos, and stem cells of animals, PIWI-interacting RNAs (piRNAs) have an important role in silencing retrotransposons, which are vicious genomic parasites, through transcriptional and post-transcriptional mechanisms. To examine whether the piRNA pathway can be used to silence genes of interest in germ cells, we have generated knock-in mice in which a foreign DNA fragment was inserted into a region generating pachytene piRNAs. The knock-in sequence was transcribed, and the resulting RNA was processed to yield piRNAs in postnatal testes. When reporter genes possessing a sequence complementary to portions of the knock-in sequence were introduced, they were greatly repressed after the time of pachytene piRNA generation. This repression mainly occurred at the post-transcriptional level, as degradation of the reporter RNAs was accelerated. Our results show that the piRNA pathway can be used as a tool for sequence-specific gene silencing in germ cells and support the idea that the piRNA generating regions serve as traps for retrotransposons, enabling the host cell to generate piRNAs against active retrotransposons.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.031
Threshold uncertainty score0.399

Codex and Gemma teacher scores by category

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

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 head0.037
GPT teacher head0.278
Teacher spread0.241 · 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 teacher head, 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

Citations33
Published2012
Admission routes1
Has abstractyes

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