MétaCan
Menu
Back to cohort
Record W2048709308 · doi:10.1083/jcb.200811138

Sam68 regulates translation of target mRNAs in male germ cells, necessary for mouse spermatogenesis

2009· article· en· W2048709308 on OpenAlexafffund
Maria Paola Paronetto, Valeria Messina, Enrica Bianchi, Marco Barchi, Gillian Vogel, Costanzo Moretti, Fioretta Palombi, Mario Stefanini, Raffaele Geremia, Stéphane Richard, Claudio Sette

Bibliographic record

VenueThe Journal of Cell Biology · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsMcGill UniversityJewish General Hospital
FundersArmstrong FoundationCanadian Institutes of Health ResearchLance Armstrong Foundation
KeywordsBiologyMessenger RNACell biologyTranslation (biology)RNA-binding proteinPolyadenylationSpermatogenesisGerm cellProtein biosynthesisMolecular biologyGeneticsGeneEndocrinology

Abstract

fetched live from OpenAlex

Sam68 is a KH-type RNA-binding protein involved in several steps of RNA metabolism with potential implications in cell differentiation and cancer. However, its physiological roles are still poorly understood. Herein, we show that Sam68(-/-) male mice are infertile and display several defects in spermatogenesis, demonstrating an essential role for Sam68 in male fertility. Sam68(-/-) mice produce few spermatozoa, which display dramatic motility defects and are unable to fertilize eggs. Expression of a subset of messenger mRNAs (mRNAs) is affected in the testis of knockout mice. Interestingly, Sam68 is associated with polyadenylated mRNAs in the cytoplasm during the meiotic divisions and in round spermatids, when it interacts with the translational machinery. We show that Sam68 is required for polysomal recruitment of specific mRNAs and for accumulation of the corresponding proteins in germ cells and in a heterologous system. These observations demonstrate a novel role for Sam68 in mRNA translation and highlight its essential requirement for the development of a functional male gamete.

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 score0.002
Threshold uncertainty score0.225

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.013
GPT teacher head0.266
Teacher spread0.253 · 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

Citations137
Published2009
Admission routes2
Has abstractyes

Explore more

Same venueThe Journal of Cell BiologySame topicRNA Research and SplicingFrench-language works237,207