Genome‐wide association implicates numerous genes underlying ecological trait variation in natural populations of <i>Populus trichocarpa</i>
Bibliographic record
Abstract
In order to uncover the genetic basis of phenotypic trait variation, we used 448 unrelated wild accessions of black cottonwood (Populus trichocarpa) from much of its range in western North America. Extensive data from large-scale trait phenotyping (with spatial and temporal replications within a common garden) and genotyping (with a 34 K Populus single nucleotide polymorphism (SNP) array) of all accessions were used for gene discovery in a genome-wide association study (GWAS). We performed GWAS with 40 biomass, ecophysiology and phenology traits and 29,355 filtered SNPs representing 3518 genes. The association analyses were carried out using a Unified Mixed Model accounting for population structure effects among accessions. We uncovered 410 significant SNPs using a Bonferroni-corrected threshold (P<1.7×10(-6)). Markers were found across 19 chromosomes, explained 1-13% of trait variation, and implicated 275 unique genes in trait associations. Phenology had the largest number of associated genes (240 genes), followed by biomass (53 genes) and ecophysiology traits (25 genes). The GWAS results propose numerous loci for further investigation. Many traits had significant associations with multiple genes, underscoring their genetic complexity. Genes were also identified with multiple trait associations within and/or across trait categories. In some cases, traits were genetically correlated while in others they were not.
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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 | 0.000 | 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".