Ancient drainage networks mediated a large‐scale genetic introgression in the East Asian freshwater snails
Bibliographic record
Abstract
Abstract Biogeography and genetic variation of freshwater organisms are influenced not only by current freshwater connections but also by past drainage networks. The Seto Inland Sea is a shallow enclosed sea in Japan, but geological evidence showed that a large freshwater drainage had intermittently appeared in this area between the late Pliocene and Pleistocene. Here, we demonstrated that this paleodrainage greatly affected the genetic variation of the East Asian freshwater snails,Semisulcospiraspp. We found that the mtDNA haplotypes originated in the Lake Biwa endemicSemisulcospiraspecies at the upstream side of the paleodrainage were frequently observed in the riverineSemisulcospiraspecies at its downstream side. The genome‐wide DNA and morphological analyses consistently showed that there was no clear evidence of nuclear introgression between the Lake Biwa endemics and riverine species. These results suggest that the large paleodrainage had facilitated mitochondrial introgression and had broadly spread the introgressed mtDNA haplotypes to its downstream region around the Seto Inland Sea. Our study highlights the role of paleodrainages in shaping the genetic variation of freshwater organisms.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".