Genomic insights into wheatgrass: unravelling genetic diversity, population structure, and evolutionary dynamics in Pseudoroegneria species
Bibliographic record
Abstract
Pseudoroegneria species are outcrossing perennial grasses with significant ecological and agricultural value due to its resilience in challenging environmental conditions in the temperate regions. Understanding the extent and pattern of genetic diversity and population structure is essential for the breeding improvement and conservation of these species. In the current research, we analyzed genomic variations of 145 genotypes representing seven species (P. spicata, P. tauri, P. geniculata, P. libanotica, P. strigosa, P. stipifolia, and P. cognata) from major global lineages, using genotyping-by-sequencing. Different metrics including nucleotide diversity, observed heterozygosity, and Tajima's D were used to evaluate genetic diversity among populations revealing significant variation among species, with P. stipifolia exhibiting the highest diversity and P. spicata the lowest. Population structure analyses, including principal component analysis, admixture inference, and phylogenetic reconstruction, identified six distinct genetic clusters, with P. spicata (a North American species) clearly separated from the other six species underscoring its unique genetic identity. In contrast, the Eurasian species exhibit mixed ancestry, indicating intricate genetic relationships and widespread exchange of genetic material. Furthermore, no single species tree fully captures the relationships among them, implying interactions such as hybridization or gene flows between closely related species. To investigate the evolutionary history of Eurasian Pseudoroegneria species, we reconstructed the species tree topology based on the SNV (single nucleotide variants) matrix, and f-branch statistics confirmed close relationships among P. spicata, P. libanotica, and P. tauri, with evidence of unidirectional gene flow between P. stipifolia, P. geniculata, and P. strigosa. These findings highlight the importance of high genetic variation in the P. stipifolia population, suggesting its potential to be a reservoir of valuable alleles for resilient genotypes.
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) | 0.000 | 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".