# 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 100 kg of flowers per hectare, but processors have managed to require that the average sepmetin content of commercial lots be above 15 per thousand.

## Biology and ecology

Apimeta simulans is annual, hermaphrodite and autogamous. It is commercially available as pure lines, and crosses easily. Up to 3 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 10 chromosomes, all of the same size ( 1 Mb). A physical map is also available. Two microarrays were constructed from the de novo sequencing of 20 individuals: a high-density chip with 10000 SNP markers and a low-density one with 5000 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 825 lines were derived.

## Available data

These lines were planted and phenotyped on the only experimental site consisting of 300 plots. Starting in 2005 , 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 525 lines tested the last years, genotypic data on the high-density chip are already available. Moreover, phenotypes of the 5 controls used at the end of the game are also provided ( 4 years, 5 plots per control).

## Experimental and financial means

Experimental site : the only experimental site, Agrom-sur-Lez (AZ), has 300 plots. Planting a plot should be requested before May 31 , and requires about 500 seeds. The cost of a single plot (seeding, phenotyping of the three traits and harvesting) is 50 Mendels , and is used as a reference for all other costs. Phenotypic data are available 4 months after, that is not before October 01 .

Greenhouse : it can be used all year long to phenotype P. psychedelica , as well as perform crosses (allofecundation and autofecundation). Rust phenotyping has a 3 -month delay and costs 0.1 plot ( 5 Mendels). Allofecundation has a 4 -month delay and costs 0.1 plot ( 5 Mendels). Autofecundation has a 4 -month delay and costs 0.04 plot ( 2 Mendels).

Laboratory : it can be used to perform haplodiploidisation (similar as for maize), and genotype samples on the various SNP chips. Haplodiploidisation has a 12 -month delay, costs 1 plot ( 50 Mendels), and a maximum of 700 can be requested at once. High-density genotyping has a 1 -month delay and costs 1 plot ( 50 Mendels). Low-density genotyping has a 1 -month delay and costs 0.33 plot ( 17 Mendels). Single-SNP genotyping has a 1 -month delay and costs 0.02 plot ( 1 Mendels).

Budget : each team starts with a total budget of 195000 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 five). The registration fee is 200 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 103 % of the flower production of the control lines (known at the beginning of the program). Varieties below the 15 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!

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

Depending on your status, you are granted with different permissions:

• game-master (such as breeder 'admin'): has the highest privileges. Has access to the "Admin" and "Evaluation" tabs. Data files available without any time restriction.
• tester (such as breeder 'test'): used to test the game without needing a password. Has access to the "Evaluation" tab. Data files available without any time restriction.
• player: used when playing in a common session. Has access neither to the "Admin" nor "Evaluation" tabs. Data files available under time restriction.

### 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: $$R = \mu_1 - \mu_0$$

### 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

2015-2019: INRA , Montpellier SupAgro

### Authors

Timothée Flutre, Julien Diot, Jacques David.

### 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).

Code: repository ; current version: b1fbd36