Elasmobranch genome sequencing reveals evolutionary trends of vertebrate karyotype organization
Bibliographic record
Abstract
Abstract Genomic studies of vertebrate chromosome evolution have long been hindered by the scarcity of chromosome-scale DNA sequences of some key taxa. One of those limiting taxa has been the elasmobranchs (sharks and rays), which harbor species often with numerous chromosomes and enlarged genomes. Here, we report the chromosome-scale genome assembly for the zebra shark Stegostoma tigrinum , an endangered species that has the smallest genome sequenced to date among sharks (3.71 Gb), as well as for the whale shark Rhincodon typus . Our analysis employing a male–female comparison identified an X chromosome, the first genomically characterized shark sex chromosome. The X chromosome harbors a Hox C cluster whose intact linkage has not been shown for an elasmobranch fish. The sequenced shark genomes exhibit a gradualism of chromosome length with remarkable length-dependent characteristics—shorter chromosomes tend to have higher GC content, gene density, synonymous substitution rate, and simple tandem repeat content as well as smaller gene length, which resemble the edges of longer chromosomes. This pattern of intragenomic heterogeneity, previously recognized as peculiar to species with so-called microchromosomes, occurs in more vertebrates including elasmobranchs. We challenge the traditional binary classification of karyotypes as with and without microchromosomes, as even without microchromosomes, shorter chromosomes tend to have higher contents of GC and simple tandem repeats and harbor shorter and more rapid-evolving genes. Such characteristics also appear on the edges of longer chromosomes. Our investigation of elasmobranch karyotypes underpins their unique characteristics and provides clues for understanding how vertebrate karyotypes accommodate intragenomic heterogeneity to realize a complex readout.
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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 | 0.001 |
| 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".