Metabolomics deciphers quantitative resistance mechanisms in diploid potato clones against late blight
Bibliographic record
Abstract
Resistance to late blight in potato is either qualitative or quantitative in nature. The quantitative resistance is durable, but the molecular and biochemical mechanisms underlying quantitative resistance are poorly understood, and are not efficiently utilised in potato breeding. A non-targeted metabolomics, using high resolution hybrid mass spectrometry, was applied to decipher the mechanisms of resistance in the advanced breeding diploid potato genotypes (Solanum tuberosum L. Group Phureja), with valuable sources of genetic diversity. The metabolomics profiles of resistant genotypes (AC04 and AC09) were compared with a susceptible commercial genotype (Criolla Colombia), following Phytophthora infestans or mock-inoculation, to identify the resistance related (RR) metabolites. Metabolites belonging to phenylpropanoids, flavonoid and alkaloid chemical groups were highly induced in resistant genotypes relative to susceptible. Concurrently, the biosynthetic genes, tyrosine decarboxylase (TyDC) and tyramine hydroxycinnamoyl transferase (THT), involved in the biosynthesis of hydroxycinnamic acid amides (HCAAs), and chalcone synthase (CHS) and flavonol synthase (FLS), involved in flavonoid biosynthesis, were also upregulated, as confirmed by quantitative real-time PCR. Probable genes coding for these enzymes were sequenced and nonsynonymous single-nucleotide polymorphisms (nsSNPs) were identified. The resistance to late blight observed in this study was mainly associated with cell wall thickening due to deposition of HCAAs, flavonoids and alkaloids.
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 | 0.000 | 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) | 0.001 | 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 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".