Information
Apimeta simulans , a species with a bright future!
Recently discovered on the borders of the upper valley of the Aghromonpe, Apimeta simulans belongs to the Statisticeae genus. It produces flowers which contain an alkaloid compound, named sepmetin , which is consumed by students to avoid headaches during excessive intellectual effort. The market is therefore very important and growing rapidly. Producers are paid for the quantity produced, with yields in the order of kg of flowers per hectare, but processors have managed to require that the average sepmetin content of commercial lots be above per thousand.
Biology and ecology
Apimeta simulans is annual, hermaphrodite and autogamous. It is commercially available as pure lines, and crosses easily. Up to generations per year can be produced in greenhouses to accelerate fixation until homozygosity. It is also possible to produce doubled haploids via haplodiploidisation. The multiplication rate of the species is very high, each plant being able to produce more than 1000 seeds. However, A. simulans is susceptible to various fungi, most notably the dreaded fluorescent rust, Putrida psychedelica .
Genomic and genetic resources
The species is diploid, with chromosomes, all of the same size ( Mb). A physical map is also available. Two microarrays were constructed from the de novo sequencing of individuals: a high-density chip with SNP markers and a low-density one with SNP markers. KASPar genotyping can also be developed for single SNPs.
The species was domesticated recently. Despite the dangers in the uninhabited Aghromonpe valley, several sampling campaigns were conducted. As a result, numerous accessions were gathered into a genetic resources collection, from which lines were derived.
Available data
These lines were planted and phenotyped on the only experimental site consisting of plots. Starting in , each year for 10 years, 150 lines were planted, in 2 plots each. In addition, most lines were planted two successive years. Each year, the trial hence includes 75 lines already tested in the previous year, and 75 new lines.
The data collected are flower production in kg/ha (
trait1
),
sepmetin
content in g/kg (
trait2
), and the presence of symptoms caused by
P. psychedelica
(
trait3
).
For
lines tested the last years, genotypic data on the high-density chip are already available.
Moreover, phenotypes of the
controls used at the end of the game are also provided (
years,
plots per control).
Download the data at the bottom of this page.
Experimental and financial means
Experimental site : the only experimental site, Agrom-sur-Lez (AZ), has plots. Planting a plot should be requested before , and requires about 500 seeds. The cost of a single plot (seeding, phenotyping of the three traits and harvesting) is Mendels , and is used as a reference for all other costs. Phenotypic data are available months after, that is not before .
Greenhouse : it can be used all year long to phenotype P. psychedelica , as well as perform crosses (allofecundation and autofecundation). Rust phenotyping has a -month delay and costs plot ( Mendels). Allofecundation has a -month delay and costs plot ( Mendels). Autofecundation has a -month delay and costs plot ( Mendels).
Laboratory : it can be used to perform haplodiploidisation (similar as for maize), and genotype samples on the various SNP chips. Haplodiploidisation has a -month delay, costs plot ( Mendels), and a maximum of can be requested at once. High-density genotyping has a -month delay and costs plot ( Mendels). Low-density genotyping has a -month delay and costs plot ( Mendels). Single-SNP genotyping has a -month delay and costs plot ( Mendels).
Budget : each team starts with a total budget of Mendels , fully available from the start.
Final trial
At the end of the game, each team will have to propose to register their best genotypes (up to ). The registration fee is Mendels per genotype.
Each of them must meet the DHS criteria, which will be assessed primarily on their heterozygosity: < 3%. They must also meet the VATE criteria corresponding to a minimum of % of the flower production of the control lines (known at the beginning of the program). Varieties below the per thousand of sepmetin will be eliminated. Resistant varieties will have a bonus.
Availability of seed should be sufficient. The proposed genotype must therefore have been tested at least once in a plot to ensure that sufficient seed is available to send to the evaluators.
Usage
Before making any request, such as phenotyping, you need to log in (tab 'Identification'). To get a sense of how the interface works, you can use the 'test' breeder with the 'tester' status. If you are playing in a common session, ask your game master to create a breeder for you. Once you are all set, start to devise your strategy and then... let's play!
Advice
For your selection to work, you better analyze the initial data carefully: the 'Theory' tab can be helpful.
Key concepts: heritability, breeding values, additive genetic variance, expected selection gain, selection intensity, genetic architecture, QTL detection, genomic prediction
Softwares: beanplot , lme4 , MM4LMM , SpATS , breedR , MuMIn , QTLRel , rrBLUP , BGLR , glmnet , varbvs , mlmm.gwas , cvTools , caret
Initial data
Notations
Phenotypic mean and variance without selection: \(\mu_0\) and \(\sigma_0^2\)
Phenotypic mean of selected parents: \(\mu^{(s)}\)
Differential of selection: \(S = \mu^{(s)} - \mu_0\)
Selection intensity: \(i = \frac{S}{\sigma_0} = \frac{z}{\alpha}\) where \(\alpha\) is the selection rate (proportion of selected parents)
Phenotypic mean of offsprings from selected parents: \(\mu_1\)
Response to selection: \(R = \mu_1 - \mu_0\)
Parameters
Breeder's equation: \(R = h^2 S\)
Context
This is the
PlantBreedGame
software implementing a serious game to teach selective breeding via the example of a fictitious annual plant species to students at the master level.
Citation
Flutre, T., Diot, J., and David, J. (2019). PlantBreedGame: A Serious Game that Puts Students in the Breeder's Seat. Crop Science. DOI 10.2135/cropsci2019.03.0183le
Copyright
2015-2019: INRA , Montpellier SupAgro
Authors
Timothée Flutre, Julien Diot, Jacques David.
Website
https://sourcesup.renater.fr/plantbreedgame/
Sources
The software takes the form of a Shiny application, benefiting from the R programming language and software environment for statistical computing. It is available under a free software license, the GNU Affero General Public License (version 3 and later).
Source code: GitHub repository
Version
Current version: 1.1.2