Breeding Simulation Tools
1. QuLine: a breeding simulation tool for inbred line breeding programs
QuLine was firstly designed in 2002-2003 for simulating CIMMYT's Wheat Program, one of the most successful programs of its kind in the world. It can integrate enormous amounts of data from widely different sources, process them in many ways, and produce alternative theoretical but realistic scenarios that the breeder can draw on to make a decision. QuLine can simulate almost all breeding activities in CIMMYT's wheat breeding program, including male master selection, female master selection, parental selection, single cross, backcross, top cross, double cross, doubled haploid, marker-assisted selection, pedigree breeding and selected bulk etc. QuLine can simulate other breeding programs for selecting inbred lines, which means all major food cereals in the world, plus basically all leguminous crops.
2. QuHybrid: a breeding simulation tool for hybrid breeding programs
Taking advantage of the advanced state of QuLine, QuHybrid was developed in 2008-2009. The major development required for QuHybrid is the implementation of test crossing and hybrid performance prediction. To make the testcrosses, an additional population defining all the testers was added. When the "testcross" functionality is activated, testcrosses will be made between all families and testers. Among-family selection is conducted based on the mean performance of all testcrosses in each family, and within-family selection is conducted based on the mean performance of each individual across all testers.
3. QuMARS:* *a breeding simulation tool for marker assisted recurrent selection
MARS (marker assisted recurrent selection) was proposed to overcome the disadvantages when using markers in selecting complex traits. It has been commercially used for selecting complex traits in maize, sunflower and soybean breeding programs. QuMARS was developed in 2009-2010. With QuMARS, we will be able to investigate various issues when using MARS. For example, how many cycles of recurrent selection are suitable? How many markers should be used in MARS? How much gains can be acquired if genome-wide selection is used instead? How can the breeding values of lines under development be best predicted?
Simulation of mapping populations and power of QTL mapping is also available in the QTL IciMapping software.
Incomplete List of Journal Articles Using the Above Simulation Tools
Kuchel, H., G. Ye, R. Fox, and S. Jefferies. 2005. Genetic and genomic analysis of a targeted marker-assisted wheat breeding strategy. Mol. Breed. 16: 67-78.
Wang, J., M. van Ginkel, D. Podlich, G. Ye, R. Trethowan, W. Pfeiffer, I. H. DeLacy, M. Cooper, and S. Rajaram. 2003. Comparison of two breeding strategies by computer simulation. Crop Science 43: 1764-1773.
Wang, J., M. van Ginkel, R. Trethowan, G. Ye, I. DeLacy, D. Podlich, and M. Cooper. 2004. Simulating the effects of dominance and epistasis on selection response in the CIMMYT Wheat Breeding Program using QuCim. Crop Science 44: 2006-2018.
Wang, J., H. A. Eagles, R. Trethowan, and M. van Ginkel. 2005. Using computer simulation of the selection process and known gene information to assist in parental selection in wheat quality breeding. Aus. J. Agric. Res. 56: 465-473.
Wang, J., and W. H. Pfeiffer. 2007. Principle of simulation modeling with applications in plant breeding. Scientia Agricultura Sinica 40: 1-12.
Wang, J., S.C. Chapman, D.B. Bonnett, G.J. Rebetzke, and J. Crouch. 2007. Application of population genetic theory and simulation models to efficiently pyramid multiple genes via marker-assisted selection. Crop Science 47: 580-588.
Wang, J., X. Wan, H. Li, W. Pfeiffer, J. Crouch, J. Wan. 2007. Application of identified QTL-marker associations in rice quality improvement through a design breeding approach. Theor. Appl. Genet. 115: 87-100.
Ye, G., D. Moody, L. Emebiri, and M. van Ginkel. 2007. Designing an optimal marker-based pedigree selection strategy for parent building in barley in the presence of repulsion linkage, using computer simulation. Aus. J. Agric. Res. 58: 243-251.
Wang, J., S. C. Chapman, D. G. Bonnett, and G. J. Rebetzke. 2009. Simultaneous selection of major and minor genes: use of QTL to increase selection efficiency of coleoptile length of wheat (Triticum aestivum L.). Theor. Appl. Genet. 119: 65-74.
Wang, J., R. P. Singh, H.-J. Braun, and W. H. Pfeiffer. 2009. Investigating the efficiency of the single backcrossing breeding strategy through computer simulation. Theor. Appl. Genet. 118: 683-694.
Wei, X., L. Liu, J. Xu, L. Jiang, W. Zhang, J. Wang, H. Zhai, J. Wan. 2010. Breeding strategies for optimum heading date using genotypic information in rice. Mol. Breed. 25:287-298.
Wei, X., L. Liu, J. Xu, L. Jiang, W. Zhang, J. Wang, H. Zhai, J. Wan. 2009. Breeding strategies for optimum heading date using genotypic information in rice. Mol. Breed. 25: 287-298.