Identifying parental chromosomes and genomic rearrangements in animal hybrid complexes of species with small genome size using Genomic In Situ Hybridization (GISH)
Bibliographic record
Abstract
Genomic In Situ Hybridization (GISH) is a powerful tool to identify and to quantify genomic constituents in allopolyploids, and is mainly based on hybridization of highly and moderate repetitive sequences. In animals, as opposed to plants, GISH has not been widely used in part because there are technical problems in obtaining informative results. Using the allopolyploid Squalius alburnoides Steindachner, 1866 fish complex as a model system, we succeeded in overcoming methodological constraints when dealing with parental species with a small genome size. This hybridogenetic complex has biotypes with different genome compositions and ploidy levels, but parental chromosomes are small, morphologically very similar and therefore cannot be distinguished by conventional cytogenetic approaches. Specimens have a small genome (C-value1.2 pg) with a low level of highly and moderate repetitive sequences, mainly located at pericentromeric chromosome regions. Since it is well known that probe annealing depends on probe concentration and hybridization time to obtain uniform hybridization signals along the chromosome arms, we progressively increased the amount of labeled probes from 100ng up to 1µg and the incubation time from overnight up to 5 days. We also made other smaller improvements. Results showed a clear enhancement of signals with respect to previous data, allowing an accurate and reproducible assignment of the parental genomes in both diploid and triploid fish.It was thus evidenced that high probes' concentrations and long incubation time are the key to obtain, without extra image editing, uniform and reliable hybridization signals in metaphase chromosomes of animal hybrids from species with small genome size.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".