Genome-wide SNP identification in Fraxinus linking genetic characteristics to tolerance of Agrilus planipennis
Bibliographic record
Abstract
Abstract Background Ash ( Fraxinus spp.) is one of the most widely distributed tree genera in North America. Populations of ash in the United States and Canada have been decimated by the introduced pest, Agrilus planipennis (Coleoptera: Buprestidae; emerald ash borer), having both negative impacts on forest ecosystems and economic interests. The majority of trees succumb to attack by A. planipennis , but some trees have been found to be tolerant to infestation despite years of exposure. Restriction site-associated DNA (RAD) sequencing was used to sequence ash individuals, both tolerant and susceptible to A. planipennis attack, in order to identify SNP patterns related to tolerance and health declines.Results A de novo reference genome was assembled and single nucleotide polymorphisms (SNPs) were called using SAMtools. After filtering criteria were implemented, a set of 17,807 SNPs were generated. Principle component analysis (PCA) of SNPs aligned individual trees into clusters related to geography, however, five tolerant trees clustered together despite geographic diversity. A subset of 32 outlier SNPs identified within this group, as well as a subset of 17 SNPs identified based on vigor rating, are candidates for selection on host tolerance.Conclusions Identifying genetic markers associated with host tolerance through genome-wide association has the potential to restore populations with cultivars that are able to withstand A. planipennis infestation. This study was successful in using RAD-sequencing in order to identify SNPs that are potential candidates to identify tolerance to A. planipennis . This was a first step toward uncovering the genetic basis for host tolerance to A. planipennis . Future studies are needed to identify the functionality of the loci where these SNPs occur and how they may be related to tolerance of A. planipennis attack.
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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".