Severe Bottleneck Impacted the Genomic Structure of Egg-Eating Cichlids in Lake Victoria
Bibliographic record
Abstract
Within 15,000 years, the explosive adaptive radiation of haplochromine cichlids in Lake Victoria, East Africa, generated 500 endemic species. In the 1980s, the upsurge of Nile perch, a carnivorous fish artificially introduced to the lake, drove the extinction of more than 200 endemic cichlids. The Nile perch predation particularly harmed piscivorous cichlids, including paedophages, cichlids eat eggs and fries, which is an example of the unique trophic adaptation seen in African cichlids. Here, aiming to investigate past demographic events possibly triggered by the invasion of Nile perch and the subsequent impacts on the genetic structure of cichlids, we conducted large-scale comparative genomics. We discovered evidence of recent bottleneck events in 4 species, including 2 paedophages, which began during the 1970s to 1980s, and population size rebounded during the 1990s to 2000s. The timing of the bottleneck corresponded to the historical records of endemic haplochromines" disappearance and later resurgence, which is likely associated with the introduction of Nile perch by commercial demand to Lake Victoria in the 1950s. Interestingly, among the 4 species that likely experienced bottleneck, Haplochromis sp. "matumbi hunter," a paedophagous cichlid, showed the most severe bottleneck signatures. The components of shared ancestry inferred by ADMIXTURE suggested a high genetic differentiation between matumbi hunter and other species. In contrast, our phylogenetic analyses highly supported the monophyly of the 5 paedophages, consistent with the results of previous studies. We conclude that high genetic differentiation of matumbi hunter occurred due to the loss of shared genetic components among haplochromines in Lake Victoria caused by the recent severe bottleneck.
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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 | 0.001 | 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".