Functional Characterization of a Phf8 Processed Pseudogene in the Mouse Genome
Bibliographic record
Abstract
Most pseudogenes are generated when an RNA transcript is reverse-transcribed and integrated into the genome at a new location. Pseudogenes are often considered as an imperfect and silent copy of a functional gene because of the accumulation of numerous mutations in their sequence. Here we report the presence of Pfh8-ps, a Phf8 retrotransposed pseudogene in the mouse genome, which has no disruptions in its coding sequence. We show that this pseudogene is mainly transcribed in testis and can produce a PHF8-PS protein in vivo. As the PHF8-PS protein has a well-conserved JmjC domain, we characterized its enzymatic activity and show that PHF8-PS does not have the intrinsic capability to demethylate H3K9me2 in vitro compared to the parental PHF8 protein. Surprisingly, PHF8-PS does not localize in the nucleus like PHF8, but rather is mostly located at the cytoplasm. Finally, our proteomic analysis of PHF8-PS-associated proteins revealed that PHF8-PS interacts not only with mitochondrial proteins, but also with prefoldin subunits (PFDN proteins) that deliver unfolded proteins to the cytosolic chaperonin complex implicated in the folding of cytosolic proteins. Together, our findings highlighted PHF8-PS as a new pseudogene-derived protein with distinct molecular functions from PHF8.
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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".