Recent Advances in Population Genomics of Plant-Parasitic Nematodes
Bibliographic record
Abstract
Plant-parasitic nematodes are a costly burden of crop production. Ubiquitous in nature, phytoparasitic nematodes are associated with nearly every important agricultural crop and represent a significant constraint on global food security. Population genetics is a key discipline in plant nematology to understand aspects of the life strategies of these parasites, in particular their modes of reproduction, geographic origins, evolutionary histories, and dispersion abilities. Advances in high-throughput sequencing technologies have enabled a recent but active effort in genomic analyses of plant-parasitic nematodes. Such genomic approaches applied to multiple populations are providing new insights into the molecular and evolutionary processes that underpin the establishment of these nematodes and into a better understanding of the genetic and mechanistic basis of their pathogenicity and adaptation to their host plants. In this review, we attempt to update information about genome resources and genotyping techniques useful for nematologists who are thinking about initiating population genomics or genome sequencing projects. This review is intended also to foster the development of population genomics in plant-parasitic nematodes through highlighting recent publications that illustrate the potential for this approach to identify novel molecular markers or genes of interest and improve our knowledge of the genome variability, pathogenicity, and evolutionary potential of plant-parasitic nematodes.
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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) | 0.001 | 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".