The ribose methylation enzyme FTSJ1 has a conserved role in neuron morphology and learning performance
Bibliographic record
Abstract
ABSTRACT FTSJ1 is a conserved human 2’-O-methyltransferase (Nm-MTase) that modifies several transfer RNAs (tRNAs) at position 32 and the wobble position 34 in the AntiCodon Loop (ACL). Its loss of function has been linked to Non-Syndromic X-Linked Intellectual Disability (NSXLID), and more recently to cancers. However, the molecular mechanisms underlying these pathologies are currently unclear. Here we report a novel FTSJ1 pathogenic variant from a NSXLID patient. Using blood cells derived from this patient and other affected individuals carrying FTSJ1 mutations, we performed an unbiased and comprehensive RiboMethSeq analysis to map the ribose methylation (Nm) on all human tRNAs and identify novel targets. In addition, we performed a transcriptome analysis in these cells and found that several genes previously associated with intellectual disability and cancers were deregulated. We also found changes in the miRNA population that suggest potential cross-regulation of some miRNAs with these key mRNA targets. Finally, we show that differentiation of FTSJ1-depleted human neuronal progenitor cells (NPC) into neurons displays long and thin spine neurites compared to control cells. These defects are also observed in Drosophila and are associated with long term memory deficit in this organism. Altogether, our study adds insight into FTSJ1 pathologies in human and flies by the identification of novel FTSJ1 targets and the defect in neuron morphology.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".