Transcriptomics of host-specific interactions in natural populations of the parasitic plant purple witchweed (<i>Striga hermonthica</i>)
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Host-specific interactions can maintain genetic and phenotypic diversity in parasites that attack multiple host species. Host diversity, in turn, may promote parasite diversity by selection for genetic divergence or plastic responses to host type. The parasitic weed purple witchweed [ Striga hermonthica (Delile) Benth.] causes devastating crop losses in sub-Saharan Africa and is capable of infesting a wide range of grass hosts. Despite some evidence for host adaptation and host-by- Striga genotype interactions, little is known about intraspecific Striga genomic diversity. Here we present a study of transcriptomic diversity in populations of S. hermonthica growing on different hosts (maize [ Zea mays L.] vs. grain sorghum [ Sorghum bicolor (L.) Moench]). We examined gene expression variation and differences in allelic frequency in expressed genes of aboveground tissues from populations in western Nigeria parasitizing each host. Despite low levels of host-based genome-wide differentiation, we identified a set of parasite transcripts specifically associated with each host. Parasite genes in several different functional categories implicated as important in host–parasite interactions differed in expression level and allele on different hosts, including genes involved in nutrient transport, defense and pathogenesis, and plant hormone response. Overall, we provide a set of candidate transcripts that demonstrate host-specific interactions in vegetative tissues of the emerged parasite S. hermonthica . Our study shows how signals of host-specific processes can be detected aboveground, expanding the focus of host–parasite interactions beyond the haustorial connection.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it