Population structure and history of North Atlantic Blue whales (Balaenoptera musculus musculus) inferred from whole genome sequence analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Knowledge of genetic diversity and structure is essential for developing conservation strategies for endangered species. Blue whales were hunted to near extinction in the mid-twentieth century. Not-withstanding almost 380,000 animals killed globally, much remains unknown about their population structure and migration patterns. Herein, we use whole genome sequencing to elucidate the poorly understood population genetics of North Atlantic (NA) blue whales. We generated a de novo genome assembly for a NA blue whale to analyze 19 other whole genomic sequences and 31 complete mitochondrial genomes. Present-day and historical samples (earliest from 1876) from the Atlantic and Antarctic Oceans were included to understand the impact of whaling on the genetic diversity of this species. We found low but statistically significant population structuring and high genetic diversity. Demographic modeling using fastsimcoal2 rejected an absence of gene flow between eastern and western NA blue whales and suggested an asymmetric west to east gene flow. Introgression estimated using D-statistics between blue and fin whales ( Balaenoptera physalus ), was observed in all present-day samples. This gene flow was found to be unidirectional from fin whales to blue whales and accounts for ~ 3.5% of the NA blue whale’s genome. Our sequencing and population structure analyses provide a genomic baseline to inform ongoing conservation strategies for this iconic species.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 it