Identifying Diagnostic Genetic Markers for a Cryptic Invasive Agricultural Pest: A Test Case Using the Apple Maggot Fly (Diptera: Tephritidae)
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 Insect pests destroy ~15% of all U.S. crops, resulting in losses of $15 billion annually. Thus, developing cheap, quick, and reliable methods for detecting harmful species is critical to curtail insect damage and lessen economic impact. The apple maggot fly, Rhagoletis pomonella, is a major invasive pest threatening the multibillion-dollar apple industry in the Pacific Northwest United States. The fly is also sympatric with a benign but morphologically similar and genetically closely related species, R. zephyria, which attacks noncommercial snowberry. Unambiguous species identification is essential due to a zero-infestation policy of apple maggot for fruit export. Mistaking R. zephyria for R. pomonella triggers unnecessary and costly quarantines, diverting valuable control resources. Here we develop and apply a relatively simple and cost-effective diagnostic approach using Illumina sequencing of double-digest restriction site-associated DNA markers. We identified five informative single-nucleotide polymorphisms (SNPs) and designed a diagnostic test based on agarose gel electrophoresis of restriction enzyme-digested polymerase chain reaction amplification products (RFLPs) to distinguish fly species. We demonstrated the utility of this approach for immediate, 1-d species identification by scoring apple- and snowberry-infesting flies from known hosts, reared from fruit collected at 11 sites throughout Washington. However, if immediate diagnosis is not required, or hundreds to thousands of specimens must be assessed, then a direct Illumina-based sequencing strategy, similar to that used here for diagnostic SNP identification, can be powerful and cost-effective. The genomic strategy we present is effective for R. pomonella and also transferable to many cryptic pests.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it