Reconstructing the Phylogenetic Relationships of Scomberomorus spp.: Evolutionary History from Whole-Genome Data
Bibliographic record
Abstract
The genus Scomberomorus (mackerels) includes several important marine fish species of high economic value in global fisheries and aquaculture, particularly across Asia. However, due to the large number of species and their morphological similarity, traditional taxonomy has been ambiguous, hindering efforts in genetic improvement and resource conservation. In recent years, with the advancement of high-throughput sequencing technologies, phylogenetic studies have entered the "whole-genome era." This paper provides a comprehensive review of the latest developments in reconstructing the phylogeny of Scomberomorus , highlighting the application of whole-genome data in species classification, lineage delimitation, speciation mechanisms, and evolutionary timescales. Case studies on farmed populations in Asia are also discussed, evaluating the genetic structure of hatchery and released stocks relative to wild lineages, and proposing lineage-based population optimization strategies. Further analysis indicates that phylogenetic research contributes not only to the identification of genetic resources and resistance traits but also offers scientific support for molecular breeding, broodstock selection, and genetic improvement. The paper concludes by recommending expanded global sampling, multi-omics integration, and the application of phylogenetic findings in aquaculture management, aiming to bridge foundational evolutionary research with practical breeding applications.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".