Genetic Analyses of Discrete Geographic Samples of a Golden Chanterelle in Canada Reveal Evidence for Recent Regional Differentiation
Bibliographic record
Abstract
The wild edible mushroom Cantharellus enelensis is a recently described species of the golden chanterelles found in eastern North America. At present, the genetic diversity and population structure of C. enelensis are not known. In this study, we analyzed a total of 230 fruiting bodies of C. enelensis that were collected from three regions of Canada: near the east and west coasts of Newfoundland (NFLD), with 110 fruiting bodies each, and around Hamilton, Ontario (10 fruiting bodies). Among the 110 fruiting bodies from each coast in NFLD, 10 from 2009 were without specific site information, while 100 sampled in 2010 were from each of five patches separated by at least 100 m from each other. Each fruiting body was genotyped at three microsatellite loci. Among the total 28 multilocus genotypes (MLGs) identified, 2 were shared among all three regions, 4 were shared between 2 of the 3 regions, and the remaining 22 were each found in only 1 region. Minimal spanning network analyses revealed several region-specific MLG clusters, consistent with geographic specific mutation and expansion. Though the most frequently observed MLGs were shared among local (patch) and regional populations, population genetic analyses revealed that both local and regional geographic separations contributed significantly to the observed genetic variation in the total sample. All three regional populations showed excess heterozygosity; for the eastern NFLD population, we reject the null hypothesis of Hardy–Weinberg equilibrium (HWE) at all three loci. However, the analyses of clone-corrected samples revealed that most loci were in HWE. Together, our results suggest that the three discrete regional populations of C. enelensis were likely colonized from a common refugium since the last ice age. However, the local and regional populations are diverging from each other through mutation, drift, and selection at least partly due to heterozygous advantage.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 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".