Genome - wide variation and demographic history of small cats with a focus on Felis species
Bibliographic record
Abstract
Majority of the 38 known cat species are classified as small and they inhabit five of the seven continents. They survive in a vast range of habitats but still 12 out of the 18 threatened felids are small cats. However, there has not been enough progress in the field of small cat research as they generally get overshadowed by the charismatic big cats. Here we attempt to create a resource for small cat research especially of the genus Felis which has six species out of which two are classified as vulnerable by IUCN and at least one more is at risk. We collected tissue samples of four Felis chaus (Jungle cat) from central India and used available whole genome sequences of nine individuals from four other Felis species, two individuals of Prionailurus bengalensis and an Otocolobus manul. These whole genome sequences were filtered and aligned with the already published domestic cat (Felis catus) genome assembly. Felids are closely related species and reads from all species in our study aligned with the domestic cat genome with a rate of at least 93%. We estimated the existing genomic variation by calculating heterozygous SNP encounter rate. So far, it seems that all wild cats have more genetic variation than Felis catus species. This can be attributed to the inbreeding in these cats. Among the wild cats, Felis silvestris seems to have the highest level of genetic variation. To understand the reasons behind the distribution of genetic variation in small cats, we estimated the demographic histories of each of the species using PSMC. This method can only detect demographic changes more than 1000 generations ago. We observe that roughly all species share a parallel history in terms of population increase. The most interesting and important feature might be that all wild small cat population sizes increased exponentially around twenty thousand years ago as opposed to domestic cat and big cats which declined around this time. Another interesting feature of the demographic history is all the small cats seem to have recovered from the effects of Toba Volcano eruption which had triggered a glacial maximum leading a decline in big cat population. Thus it seems the partitioning of genetic variation has happened less than ten thousand years ago owing to anthropogenic activities?
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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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".