Using telomeric length measurements and methylation to understand the karyotype diversification of <i>Ctenomys minutus</i> (a small fossorial mammal)
Bibliographic record
Abstract
The genus Ctenomys has been widely used in karyotype evolution studies due to the variation in their diploid numbers. Ctenomys minutus is characterized by intraspecific variation in diploid number (2 n = 42, 46, 48, and 50), which makes it an interesting model to investigate genomic rearrangements mechanisms that could lead to different cytotypes in this species. Thereupon, it has been already shown that DNA methylation may participate in chromosome structure. Therefore, we aimed to investigate whether telomeres and global DNA methylation had a role in the genome rearrangements that led to this variation in C. minutus. We also realized an analysis for the presence of intrachromosomal telomeric repeats (ITRs) by fluorescence in situ hybridization. Our study demonstrated that neither telomere length nor DNA methylation had significant differences among the cytotypes. However, if only females were considered, there were significant differences for telomere length and methylation. Young individuals, regardless of their cytotypes, had the most methylated DNA. Regarding the ITRs, we found a signal on chromosome 1 in 2 n = 50b. No evidence was found that telomere length or methylation could have influenced chromosomal rearrangements, although new cytotypes seem to have emerged within the distribution of parental cytotypes by the accumulation of different chromosomal rearrangements.
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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 | 0.001 | 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".