An efficient single nucleotide polymorphism assay to diagnose the genomic identity of poplar species and hybrids on the Canadian prairies
Bibliographic record
Abstract
Hybridization frequently occurs among poplars, both naturally and artificially, hindering identification. Over 32 million clonal poplars, predominantly hybrids, have been planted throughout the Canadian prairies over the past century, making confirmation of genomic identity important. We developed a genotyping assay that rapidly diagnoses four compatible Populus species ( Populus balsamifera L. and Populus deltoides Bartr. ex Marsh.: indigenous, Populus laurifolia Ledeb. and Populus nigra L.: exotics) and their hybrids found throughout this ecozone. First, we sequenced 23 genes from representative provenances of the four Populus species to discover single nucleotide polymorphisms (SNPs). Second, we developed and validated a medium-throughput genotyping assay of 26 diagnostic SNPs within these genes. We used this assay to genotype 198 trees from natural populations as well as 30 clones (pure species and hybrids), including those broadly distributed by Agriculture and Agri-Food Canada’s Agroforestry Development Centre since 1910. This suite of SNPs has the resolving power to correctly identify pure species and hybrids of Populus. We confirmed the identity of clones of well-documented origin, complex hybrids with exotic components, and paternity of open-pollinated progenies from breeding programs. This diagnostic tool should prove useful for efficient molecular fingerprinting of breeding material and for further studies of interspecific gene flow on the Canadian prairies.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".