GENOPARFUM : Création de ressources et d'outils moléculaires pour la mise en place d'une stratégie de sélection sur la lavande.
Bibliographic record
Abstract
Fine lavender (Lavandula angustifolia) and lavandin (Lavandula x intermedia) are emblematic species of France and of great economic interest. Thanks to the cost reduction of sequencing technologies and to the development of suitable bioinformatics tools, Iteipmai, with the help of its partners (INRAE, CRIEPPAM and CNPMAI), was able to set up a project to develop molecular tools on lavender and lavandin, in order to improve the efficiency of breeding programs. Thus, the GenoParfum project was set up to create the genomic resources necessary for the development of these new strategies using next-generation sequencing technologies. This general objective is declined in three axes: (i) to develop a catalog of reference lavender genes, (ii) to identify SNP (Single Nucleotide Polymorphism) polymorphism for lavender and lavandin and (iii) to test the validity of this polymorphism within the scope of an analysis of genetic diversity (clonal varieties and natural populations of lavender). This article presents the work carried out in axis 3 (the results from axes 1 and 2 are presented in an associated article (Fopa Fomeju et al., 2018)). A pooled sequencing approach was used to study SNP-type polymorphism in 21 natural populations from 6 geographic regions of southeastern France and northwestern Italy. These populations were collected at altitudes ranging from 200 meters to 1500 meters. To these populations, 3 population varieties selected by Iteipmai (Rapido, Carla and Saralia) were added. The results indicated that genetic diversity was structured according to the geographical origin of the populations and not according to their altitude. The rate of polymorphism in improved populations was similar to that observed in natural populations. This approach also made it possible to highlight the relevance of molecular tools for the management of genetic resources. The results will be used to build a core collection to initiate association genetics studies and to identify markers associated with agronomic traits of interest to lavender.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".