Applying functional genomics to the study of lamprey development and sea lamprey population control
Bibliographic record
Abstract
Lampreys are one of the few survivors of an ancient lineage of jawless vertebrates and have become an important study organism in numerous disciplines in the biological sciences, including evolutionary biology, embryology, ecology, physiology and biomedicine. At the same time, however, lampreys have created economic and ecological problems due, primarily, to the invasion of parasitic sea lamprey (Petromyzon marinus) into the North American Great Lakes and consequent negative impacts on local fish populations. Barriers, trapping and lampricide treatments have reduced these impacts, but concern for habitat restoration, non-target effects and possible evolution of resistance to lampricides suggests the need to develop additional strategies that supplement current control measures. The advent of functional genomics, and in particular CRISPR/Cas9 genome editing, offers a molecular approach to this on-going problem. Here, we review the successful application of functional genetic, transcriptomic, and CRISPR/Cas9 genome editing technologies in lampreys to address basic research questions in the fields of evolutionary and developmental biology. We then describe how these tools may be repurposed for use by fishery and conservation biologists to approach the problem of invasive sea lamprey from a molecular-genetic perspective.
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How this classification was reachedexpand
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 | 0.001 | 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) | 0.000 | 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 teacher head, 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".