Accurate estimation of map distance between markers is important for the construction of large-scale linkage maps because it provides reliable and useful linkage information of markers on chromosomes. How to improve accuracy of estimating map distances depends on an appropriate mapping function. We used the coefficient of coincidence to integrate the Haldane function, in which crossovers are assumed to be independent and the Morgan function, in which crossovers are assumed to be interfered, and produce a new mapping function. The mapping function based on positive interference is referred to as the positive function and that on negative interference as the negative function. In these two mapping functions, map distances between loci are determined by both recombination frequencies and the coefficient of coincidence. We applied our mapping functions to four examples and show that our map estimates have much higher goodness-of-fit to the observed mapping data than the Haldane and Kosambi functions. Therefore, they can provide much more precise estimates of map distances than the two conventional mapping functions. Furthermore, our mapping functions produced almost linear (additive) map distances.
KeywordsMap Function Linkage Recombination Coefficient of coincidence Map distance
This study was supported by grant (39870568) from Natural Science Foundation of China and grants from the U.S. National Institutes of Health (NS41466 and HL69126) to M. F. We thank anonymous reviewers for their helpful comments and constructive suggestions and also specially acknowledge Dr. W. J. Etges for his valuable revision suggestions on this paper.
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