DNA methylation dynamics during the interaction of wheat progenitor <i>Aegilops tauschii</i> with the obligate biotrophic fungus <i>Blumeria graminis</i> f. sp. <i>tritici</i>
Bibliographic record
Abstract
DNA methylation is dynamically involved in plant immunity, but little information is known about its roles in plant interactions with biotrophic fungi, especially in temperate grasses such as wheat (Triticum aestivum). Using wheat diploid progenitor Aegilops tauschii accession AL8/78, the genome of which has been sequenced, we assessed the extent of DNA methylation in response to infection with Blumeria graminis f. sp. tritici (Bgt), which causes powdery mildew. Upon Bgt infection, ARGONAUTE4a (AGO4a) was significantly downregulated in A. tauschii, which was accompanied by a substantial reduction in AGO4a-sorted 24-nt siRNA levels, especially for genes near transposable elements (TAGs). Bisulfite sequencing revealed abundant differentially methylated regions (DMRs) with CHH hypomethylation. TAGs bearing CHH-hypomethylated DMRs were enriched for 'response to stress' functions, including receptor kinase, peroxidase, and pathogenesis-related genes. Virus-induced gene silencing (VIGS) of a DOMAINS REARRANGED METHYLASE 2 (DRM2) homolog enhanced plant resistance to Bgt. The effect of CHH hypomethylation was exemplified by the upregulation of a pathogenesis-related β-1,3-glucanse gene implicated in Bgt defense. These findings support the idea that dynamic DNA methylation represents a regulatory layer in the complex mechanism of plant immunity, which could be exploited to improve disease resistance in common wheat.
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 | 0.001 | 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".