The QTL menus provide easy access to QTL analysis within Genstat. Two sources of data are required: phenotypic data (measurements of trait values) and genotypic/map data (evaluation of genotyping at markers and positions of markers on a genetic map). The description below gives a step-by-step approach to a QTL analysis for a single environment trial with individual observations.
Step 1. | Put trial data and all factors defining experimental structure into a Genstat spreadsheet. |
Step 2. | Load phenotypic (trait) data and all factors defining experimental structure into the QTL data space using the Stats | QTLs (Linkage/Association) | Data Import/Export | Load Phenotypic data menu item. Select the option for Plot or unit data and load all variates and factors relevant to analysis of the trial. The QTL data space Stats | QTLs (Linkage/Association) | View QTL Data Space should now show these variables under the Phenotypic raw data folder. |
Step 3. | Form phenotypic (trait) means from the trial data using the preliminary single environment analysis menu which can be opened by selecting the Stats | QTLs (Linkage/Association) | Phenotypic Analysis | Preliminary Single Environment Analysis menu item. This menu runs the specified model twice: first with genotypes random in order to estimate heritability and variance parameters, the second time with Genotypes fixed to get unshrunken means for QTL analysis. After running an analysis you can use the Save test line means button to put the predicted means to be used in QTL analysis into the correct format and QTL data space. The QTL data space will now show these saved data structures under the Phenotypic means folder.
Using the preliminary single environment analysis menu:
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Step 4. | Load genetic marker and map data using the Stats | QTLs (Linkage/Association | Data Import/Export | Load Genotypic (Marker and Map) data menu item. Choose the file type that contains the data (Flapjack text genotype/map, R/QTL csvs/csvsr and MapQTL loc/map file formats) and load the data. The QTL data space will now show these data structures under the Genotypic data folder.
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Step 5. | Check marker and map data using the display genetic map and genotype data plots menus (opened by selecting the Stats | QTLs (Linkage/Association) | Data Exploration | Genotypic Data | Display Genetic Map and Stats | QTLs (Linkage/Association) | Data Exploration | Genotypic Data | Genotype Data Plots respectively). |
Step 6. | Calculate genetic predictors for use in QTL interval mapping using the calculate genetic predictors menu opened using the Stats | QTLs (Linkage/Association) | Genotypic Analysis | Calculate Genetic Predictors menu item. The QTL data space will now show these data structures under Genetic predictors folder. Using the calculate genetic predictors menu:
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Step 7. | Run simple interval mapping using the Initial scan button on the Single Trait Linkage Analysis (Single Environment) menu (opened using the Stats | QTLs (Linkage/Association) | QTL Analysis | Single Trait Linkage Analysis (Single Environment) menu item). This does an initial scan for candidate QTLs, which are saved for further analysis. By default, the results of the scan are plotted and the candidates are displayed in the output.
Using the Single Trait Linkage Analysis (Single Environment) menu:
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Step 8. | Run composite interval mapping using the Scan with cofactors button on the Single Trait Linkage Analysis (Single Environment) menu. By default, the cofactors are set as the candidate QTLs from the previous scan. This does a scan for additional candidate QTLs in the presence of the cofactors, although cofactors within a set window (see Options) are ignored to avoid problems of collinearity. A modified set of candidate QTLs is saved. By default, the results of the scan are plotted and the candidates are displayed in the output.
Using the Single Trait Linkage Analysis (Single Environment) menu:
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Step 9. | Run composite interval mapping final model selection using the Select final QTL model button on the Single Trait Linkage Analysis (Single Environment) menu. By default, the full set of candidate QTLs are the set selected from the previous scan. The default first step is backwards selection from this candidate step, followed by estimation of the QTL effects for all QTLs retained in the selected model. |