Intrapopulation genomics in a model mutualist: Population structure and candidate symbiosis genes under selection in <i>Medicago truncatula</i>
Bibliographic record
Abstract
Bottom-up evolutionary approaches, including geographically explicit population genomic analyses, have the power to reveal the mechanistic basis of adaptation. Here, we conduct a population genomic analysis in the model legume, Medicago truncatula, to characterize population genetic structure and identify symbiosis-related genes showing evidence of spatially variable selection. Using RAD-seq, we generated over 26,000 SNPs from 191 accessions from within three regions of the native range in Europe. Results from STRUCTURE analysis identify five distinct genetic clusters with divisions that separate east and west regions in the Mediterranean basin. Much of the genetic variation is maintained within sampling sites, and there is evidence for isolation by distance. Extensive linkage disequilibrium was identified, particularly within populations. We conducted genetic outlier analysis with FST-based genome scans and a Bayesian modeling approach (PCAdapt). There were 70 core outlier loci shared between these distinct methods with one clear candidate symbiosis related gene, DMI1. This work sets that stage for functional experiments to determine the important phenotypes that selection has acted upon and complementary efforts in rhizobium populations.
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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 | 0.001 |
| 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 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".