Comparative whole-genome analysis reveals genetic adaptation of the invasive pinewood nematode
Bibliographic record
Abstract
Abstract Genetic adaptation to new environments is essential for invasive species. To explore the genetic underpinnings of invasiveness of a dangerous invasive species, the pinewood nematode (PWN) Bursaphelenchus xylophilus , we analysed the genome-wide variations of a large cohort of 55 strains isolated from both the native and introduced regions. Comparative analysis showed abundant genetic diversity existing in the nematode, especially in the native populations. Phylogenetic relationships and principal component analysis indicate a dominant invasive population/group (DIG) existing in China and expansion beyond, with few genomic variations. Putative origin and migration paths at a global scale were traced by targeted analysis of rDNA sequences. A progressive loss of genetic diversity was observed along spread routes. We focused on variations with a low frequency allele (<50%) in the native USA population but fixation in DIG, and a total of 25,992 single nuclear polymorphisms (SNPs) were screened out. We found that a clear majority of these fixation alleles originated from standing variation. Functional annotation of these SNP-harboured genes showed that adaptation-related genes are abundant, such as genes that encode for chemoreceptors, proteases, detoxification enzymes, and proteins involved in signal transduction and in response to stresses and stimuli. Some genes under positive selection were predicted. Our results suggest that adaptability to new environments plays essentially roles in PWN invasiveness. Genetic drift, mutation and strong selection drive the nematode to rapidly evolve in adaptation to new environments, which including local pine hosts, vector beetles, commensal microflora and other new environmental factors, during invasion process.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".