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数量遗传课题组 Quantitative Genetics Group |
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中国农业科学院 作物科学研究所
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数量遗传课题组 Quantitative Genetics Group |
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中国农业科学院 作物科学研究所
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We consider six QTL with different levels of dominance and a genome consisting of 8 chromosomes in our simulation studies (Tables 1, 2 and 3).
Each chromosome is of 140 cM , and evenly distributed with 15 codominant markers. QTL1 has additive effect 1, without dominance. QTL2 has dominance effect 1, without additive. QTL3 can be viewed as complete dominant, while QTL4 is complete recessive. Both QTL5 and QTL6 show overdominance, but with different directions. No interactions between QTL were considered. Each QTL was assumed to be located in the middle of a marker interval.
To investigate the effect of linkage on QTL mapping, we considered three QTL distribution models (Tables 2 and 3). QTL were distributed on different chromosomes in model I, and two QTL were linked on chromosomes 1, 2, and 3 for models II and III. In model I, QTL5 and QTL6 each explained 24.29% of the genotypic variation, and 17.00% of the phenotypic variance under heritability 0.7, respectively. QTL2 explained the least genotypic and phenotypic variation among the six defined QTL (Table 1).
F2 populations were simulated by the genetics and breeding simulation tool of QuLine, formerly called QuCim (Wang et al . 2004). QuLine is freely available from http://www.uq.edu.au/lcafs/qugene .
TABLE 1 QTL distribution model I
Note: The genetic variance of each QTL in F 2 is 
, and the heritability in the broad sense was set at 0.7 .
TABLE 2 QTL distribution model II
TABLE 3 QTL distribution model III
For convience, each population was given in three formats, which can be directly called by Carographer (extension name *.mcd), IciMapping (extension name *.qtl), and R/qtl and R/qtlbim (extension name *.csv).
We ran the 600 simulated F2 population on Cartographer one by one. For CIM, we applied “Model 6: Standard Model” and “3. Froward & Backward Method” available in Cartographer. The two probabilities for entering and removing variables were set at 0.01 and 0.02. To run Cartpower.exe to calculate powers after applying CIM on the 100 simulated populations. The LOD threshold can be changed by editing the resultoutrun.txt file. This file will be automatically called by Cartpower.exe.
To click the batch command (BatchIcim200.bat) to run the 100 simulated F2 populations. For ICIM, the same probability levels were adopted in the first step of stepwise regression. To run Powernew.exe to calculate powers after applying ICIM on the 100 simulated populations. The LOD threshold can be changed by editing the resultoutrun.txt file. This file will be automatically called by Powernew.exe.