Data from: Genomic signature of successful colonization of Eurasia by the allopolyploid shepherd’s purse (Capsella bursa-pastoris)
Bibliographic record
Abstract
Polyploidization is a dominant feature of flowering plant evolution. However, detailed genomic analyses of the inter-population diversification of polyploids following genome duplication are still in their infancy, mainly because of methodological limits, both in terms of sequencing and computational analyses. The shepherd’s purse (Capsella bursa-pastoris) is one of the most common weed species in the world. It is highly self-fertilizing, and recent genomic data indicate that it is an allopolyploid, resulting from hybridization between the ancestors of the diploid species Capsella grandiflora and Capsella orientalis. Here, we investigated the genomic diversity of C. bursa-pastoris, its population structure and demographic history, following allopolyploidization in Eurasia. To that end, we genotyped 261 C. bursa-pastoris accessions spread across Europe, the Middle East and Asia, using genotyping-by-sequencing, leading to a total of 4,274 SNPs after quality control. Bayesian clustering analyses revealed three distinct genetic clusters in Eurasia: one cluster grouping samples from Western Europe and Southeastern Siberia, the second one centered on Eastern Asia and the third one in the Middle East. Approximate Bayesian computation (ABC) supported the hypothesis that C. bursa-pastoris underwent a typical colonization history involving low gene flow among colonizing populations, likely starting from the Middle East towards Europe and followed by successive human-mediated expansions into Eastern Asia. Altogether, these findings bring new insights into the recent multistage colonization history of the allotetraploid C. bursa-pastoris and highlight ABC and genotyping-by-sequencing data as promising but still challenging tools to infer demographic histories of selfing allopolyploids.
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 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".