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Record W2898407871 · doi:10.1016/j.gene.2018.10.061

Both male and female gamete generating cells produce processed pseudogenes in the human genome

2018· article· en· W2898407871 on OpenAlexafffund
Vincent Maranda, Frédérick G. Sunstrum, Guy Drouin

Bibliographic record

VenueGene · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and Clinical Aspects of Sex Determination and Chromosomal Abnormalities
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPseudogeneBiologyGeneticsRetrotransposonGenomeChromosomeGeneHuman genomeAutosomeX chromosomeY chromosomeTransposable element

Abstract

fetched live from OpenAlex

The human genome contains an unusually large number of processed pseudogenes. The fact that processed pseudogenes are roughly 33% more abundant in our X chromosome than in our autosomes suggests that this overabundance is the result of the fact that human oogenesis is much longer than that of non-mammalian species. Here, we analyze the origins of the processed pseudogenes found on the human Y chromosome to determine whether human spermatogenesis also contribute to this overabundance. Our results show that human processed pseudogenes not only retrotranspose to the Y chromosome, but are also produced by genes on the Y chromosome. Furthermore, the fact that X chromosomes are three times more abundant than Y chromosomes likely explains why the euchromatic density of processed pseudogenes is three times higher in the X chromosome than in the Y chromosome. The large number of processed pseudogenes found in our genome is therefore due to the low substrate specificity of the L1 reverse transcriptase responsible for the reverse transcription of germline mRNA molecules into processed pseudogenes, as well as the life-long production of both male and female gametes.

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)0.000
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 score0.022
Threshold uncertainty score0.386

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.018
GPT teacher head0.269
Teacher spread0.250 · 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

Citations7
Published2018
Admission routes2
Has abstractyes

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