Spatial analysis of fungicide resistance mutations in Botrytis spp. populations
Bibliographic record
Abstract
The objectives of this project were: 1) to study the spatial interactions of single nucleotide polymorphisms (SNPs) related to fungicide resistance within Botrytis cinerea populations isolated from grapes; 2) to study the spatial distribution patterns of SNPs related to fungicide resistance within B. cinerea populations in grape and within B. squamosa populations in onion; and 3) to compute sampling curves relative to mean SNP incidence estimation. In a first experiment, B. cinerea isolates were collected following a quadrat-based design (100 10x10m quadrats) in two commercial vineyards. The presence of 9 SNPs related to resistance to iprodione, boscalid, azoxystrobin and fenhexamid were detected using PCR-RFLP, PIRA-PCR and RT-qPCR assays. These data were spatially referenced and considered as a multivariate point pattern in a given vineyard. Spatial point patterns were analyzed by pairs, using an extension of Diggle's procedure for the analysis of nearest-neighbor distances. In this randomization testing procedure, the cumulative relative frequency distribution of the inter-SNP distances was used to characterize the spatial relationship between SNPs related to fungicide resistance. In the second experiment, two SNPs known to be responsible for boscalid resistance and one SNP known to be responsible for dicarboximide resistance in B. cinerea on grape were studied, in addition to one SNP responsible for dicarboximide resistance in B. squamosa on onion. One onion field was sampled in 2009 and another one was sampled in 2010 for B. squamosa, and two vineyards were sampled in 2011 for B. cinerea, for a total of four sampled sites. Sampling was carried following the same design as in the first experiment, except 10 samples were collected in each quadrat. Samples were analyzed by RFLP-PCR. The characterization of spatial distribution patterns was made through the fitting of discrete probability distributions. The level of mutations obtained in the first experiment was 90%, 64%, 67%, 33% and 1% for G143A, I86S, H272R, H272Y and N230I, respectively. Our results show that three spatial relationships can arise when spatial point patterns representing the presence of SNPs related to fungicide resistance are compared by pairs: spatial exclusiveness (12%), spatial co-existence (31%) and absence of a spatial relationship (56%). Despite the fact that more than one half of the pairs of SNPs tested showed no spatial relationship, the presence of about a third of inclusive spatial relationships supports the models of co-existence between sensitive and resistant strains postulated in the literature, but suggests a higher level of complexity in the resistant-sensitive interactions. In the second experiment, the beta-binomial distribution was found to fit the data better than the binomial distribution for all data sets. This indicates local SNP aggregation among sampling units, as supported by estimates of the parameter θ of the beta-binomial distribution ranging from 0.09 to 0.23, with an overall median value of 0.20. On the basis of the spatial distribution patterns of SNP incidence that we found in Botrytis populations, sampling curves were developed for various levels of precision, emphasizing the importance of sampling for early detection of fungicide resistance in plant disease epidemiology.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".