QTL IciMapping: Integrated Software for Building Linkage Maps and Mapping Quantitative Trait Genes
In QTL IciMapping, kernel modules for building linkage maps were written by C#, those for QTL mapping were written by Fortran 90/95, and the interface was written by C#. QTL IciMapping runs on Windows XP/Vista/, with .NET Framework 2.0 (x86)/3.0/3.5. Genetic populations that can be handled were shown in Fig. 1. Six major functionalities are briefly described as follows, i.e. MAP, BIP, CSL, MET, NAM and SDL. IciMapping v3.1, which was released in May 2011. This software is freely available from ISBreeding.net.
1. MAP: Construction of Genetic Linkage Maps in Biparental Populations
There are three steps to build a linkage map: grouping, ordering and rippling. Grouping can be based on (i) anchored marker information, (ii) a threshold of LOD score, and (iii) a threshold of marker distance in cM.
Three ordering algorithms are (i) SER: SERiation (K. H. Buetow and A. Charavarti. 1987. Am. J. Hum. Genet. 41: 180-188), (ii) RECORD: REcombination Counting and ORDering (H. Van Os. 2005. Theor. Appl. Genet. 112: 30-40), and (iii) MF: an Multi-Fragment heuristic algorithm in travelling salesmen problem (TSP).
Five rippling criteria are (i) SARF (Sum of Adjacent Recombination Frequencies), (ii) SAD (Sum of Adjacent Distances), (iii) SALOD (Sum of Adjacent LOD scores), (iv) COUNT (number of recombination events), and (v) LogL (Logarithm Likelihood of the marker sequence).
2. BIP: Mapping of Additive and Digenic Epistasis Genes in 20 Biparental Populations (Fig. 1).
Five mapping methods are available.
SMA: Single Marker Analysis (K. Sax. 1923. Genetics 8: 552-560; M. Soller and T. Brody. 1976. Theor. Appl. Genet. 47: 35-39)
IM: the conventional Interval Mapping (E. S. Lander and D. Botstein. 1989. Genetics 121: 185-199)
ICIM-ADD: Inclusive Composite Interval Mapping of ADDitive (and dominant) QTL (H. Li et al. 2007. Genetics 175: 361-374; L. Zhang et al. 2008. Genetics 180: 1177-1190)
ICIM-EPI: Inclusive Composite Interval Mapping of digenic EPIstatic QTL (H. Li et al. 2008. 116: 243-260)
SGM: Selective Genotyping Mapping (R. L. Lebowitz et al. 1987 Theor. Appl. Genet. 73: 556-562; E. S. Lander and D. Botstein. 1989. Genetics 121: 185-199; Y. Sun et al. 2010. Mol. Breed.)
3. CSL: Mapping of Additive and Digenic Epistasis Genes with Chromosome Segment Substitution (CSS) Lines.
Three mapping methods are available.
SMA: Single Marker Analysis (K. Sax. 1923. Genetics 8: 552-560)
RSTEP-LRT-ADD: Stepwise regression based likelihood ratio tests of additive QTL (J. Wang et al. 2006. Genet. Res. 88: 93-104; J. Wang et al. 2007.Theor. Appl. Genet. 115: 87-100)
RSTEP-LRT-EPI: Stepwise regression based likelihood ratio tests of digenic epistasis QTL (J. Wang et al. 2006. Genet. Res. 88: 93-104; J. Wang et al. 2007.Theor. Appl. Genet. 115: 87-100)
4. MET: QTL by Environment Interaction in Biparental Populations (to be available in January 2011).
Two mapping methods are available.
ICIM-ADDbyE: ICIM of additive QTL by environment interaction
ICIM-EPIbyE: ICIM of digenic epistatic QTL by environment interaction
5. NAM: QTL Mapping in NAM Populations (to be available in January 2011)
JICIM: Joint Inclusive Composite Interval Mapping of additive QTL
6. SDL: Mapping of Segregation Distortion Loci in Biparental Populations (to be available in January 2011).* Two mapping methods are available.
SMA: Segregation Distortion Loci Mapping in biparental Mendelian populations based on single marker analysis
SMA: Segregation Distortion Loci Mapping in biparental Mendelian populations based on interval mapping.
7. Simulating Mapping
Simulation of the statistical power of QTL mapping has been fully implemented in QTL IciMapping v3.1. Twenty bi-parental populations (Fig. 1) can now be simulated. This allows users to define any number of chromosomes, marker densities, QTL numbers, linkage relationships, additive effects, and epistatic effects etc., so as to compare different QTL mapping methods, and study the effects of marker density, and population size etc. Power simulation can help to answer questions regarding population, marker density, and LOD threshold etc., and therefore allows more efficient genetic studies.
Incomplete List of Journal Articles Using the QTL IciMapping Software
Buckler, E.S., J.B. Holland, P.J. Bradbury, C.B. Acharya, P.J. Brown, et al. 2009. The genetic architecture of maize flowering time. Science 325: 714-718.
Chen, P., L. Jiang, C. Yu, W. Zhang, J. Wang, and J. Wan. 2008. The identification and mapping of a tiller angle QTL on rice chromosome 9. Crop Science 48: 1799-1806.
Hamwieh, A., and D. Xu. 2008. Conserved salt tolerance quantitaive trait locus (QTL) in wild and cultivated soybeans. Breeding Science 58: 355-359.
Li, H., G. Ye and J. Wang. 2007. A modified algorithm for the improvement of composite interval mapping. Genetics 175: 361-374.
Li, H., Z. Li and J. Wang 2008. Inclusive composite interval mapping (ICIM) for digenic epistasis of quantitative traits in biparental populations. Theor. Appl. Genet. 116: 243-260.
Li, H., L. Zhang, and J. Wang. 2010. Analysis and answers to frequently asked questions in quantitative trait locus mapping. Acta Agronomica Sinica 36: 918-931.
Li, H., S. Hearne, M. Bänziger, Z. Li, and J. Wang. 2010. Statistical properties of QTL linkage mapping in biparental genetic populations. Heredity 105: 257-267.
Li, Y., J. Wang, L. Qiu, Y. Ma, X. Li, and J. Wan. 2010. Crop molecular breeding in China: Current status and perspectives. Acta Agronomica Sinica 36: 1425-1430.
Lu, Y., C. Lan, S. Liang, X. Zhou, D. Liu, G. Zhou, Q. Lu, J. Jing, M. Wang, X. Xia, and Z. He. 2009. QTL mapping for adult-plant resistance to stripe rust in Italian common wheat cultivars Libellula and Strampelli. Theoretical Applied Genetics 119: 1349-1359.
McMullen, M.D., S. Kresovich, H.S. Villeda, P.J. Bradbury, H. Li, et al. 2009. Genetic properties of the maize nested association mapping population. Science 325: 737-740.
Sun, Y., J. Wang, J. H. Crouch, and Y. Xu. 2010. Efficiency of selective genotyping for genetic analysis and crop improvement of complex traits. Mol. Breed. 26: 493-511.
Wan, X., J. Wan, L. Jiang, J. Wang, H. Zhai, J. Weng, H. Wang, C. Lei, J. Wang, X. Zhang, Z. Cheng, X. Guo. 2006. QTL analysis for rice grain length and fine mapping of an identified QTL with stable and major effects. Theoretical Applied Genetics 112: 1258-1270.
Wang, J., X. Wan, J. Crossa, J. Crouch, J. Weng, H. Zhai, and J. Wan. 2006. QTL mapping of grain length in rice (Oryza sativa L.) using chromosome segment substitution lines. Genetical Research 88: 93-104.
Wang, J., H. Li, X. Wan, W. Pfeiffer, J. Crouch, and J. Wan. 2007. Application of identified QTL-marker associations in rice quality improvement through a design breeding approach. Theor. Appl. Genet. 115: 87-100.
Wang J. 2009. Inclusive composite interval mapping of quantitative trait genes. Acta. Agron. Sin. 35: 3239-245.
Wang, J., W. Liu, H. Wang, L. Li, J. Wu, X. Yang, X. Li and A. Gao. 2010. QTL mapping of yield-related traits in the wheat germplasm 3228. Euphytica 177: 277-292.
Zhang, L., H. Li, Z. Li, and J. Wang. 2008. Interactions between markers can be caused by the dominance effect of QTL. Genetics 180: 1177-1190.
Zhang, Y., Y. Wu, Y. Xiao, Z. He, Y. Zhang, J. Yan, Y. Zhang, X. Xia, and C. Ma, (2009). QTL mapping for flour and noodle colour components and yellow pigment content in common wheat. Euphytica 165: 435-444.
Zhang, L., S. Wang, H. Li, Q. Deng, A. Zheng, S. Li, P. Li, Z. Li, J. Wang. 2010. Effects of missing marker and segregation distortion on QTL mapping in F2 populations. Theor. Appl. Genet. 121:1071-1082.
Zhang, Y., Z. Zhao, J. Zhou, L. Jiang, X. Bian, Y. Wang, C. Wang, Z. Zhong, J. Wang, D. Tao, J. Wan. 2010. Fine mapping of a gene responsible for pollen semi-sterility in hybrids between Oryza sativa L. and O. glaberrima Steud. Mol. Breed. (online).
Zhang, Y., J. Tang, Y. Zhang, J. Yan, Y. Xiao, Y. Zhang, X. Xia and Z. He. 2010. QTL mapping for quantities of protein fractions in bread wheat (Triticum aestivum L.) Theor. Appl. Genet. (online).
Zhou, L., L. Chen, L. Jiang, W. Zhang, L. Liu, X. Liu, Z. Zhao, S. Liu, L. Zhang, J. Wang, and J. Wan. 2009. Fine mapping of the grain chalkiness QTL qPGWC-7 in rice (Oryza sativa L.). Theor. Appl. Genet. 118: 581-590.
Figure 1 Genetic populations that can be handled in the QTL IciMapping software