Ribosomal RNA Genes Contribute to the Formation of Pseudogenes and Junk DNA in the Human Genome
Bibliographic record
Abstract
Approximately 35% of the human genome can be identified as sequence devoid of a selected-effect function, and not derived from transposable elements or repeated sequences. We provide evidence supporting a known origin for a fraction of this sequence. We show that: 1) highly degraded, but near full length, ribosomal DNA (rDNA) units, including both 45S and Intergenic Spacer (IGS), can be found at multiple sites in the human genome on chromosomes without rDNA arrays, 2) that these rDNA sequences have a propensity for being centromere proximal, and 3) that sequence at all human functional rDNA array ends is divergent from canonical rDNA to the point that it is pseudogenic. We also show that small sequence strings of rDNA (from 45S + IGS) can be found distributed throughout the genome and are identifiable as an "rDNA-like signal", representing 0.26% of the q-arm of HSA21 and ∼2% of the total sequence of other regions tested. The size of sequence strings found in the rDNA-like signal intergrade into the size of sequence strings that make up the full-length degrading rDNA units found scattered throughout the genome. We conclude that the displaced and degrading rDNA sequences are likely of a similar origin but represent different stages in their evolution towards random sequence. Collectively, our data suggests that over vast evolutionary time, rDNA arrays contribute to the production of junk DNA. The concept that the production of rDNA pseudogenes is a by-product of concerted evolution represents a previously under-appreciated process; we demonstrate here its importance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 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) | 0.000 | 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 teacher head, 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".