Fitting genetic mapping functions based on sperm typing: results for three chromosomal segments in cattle

Area of Science:

• Genetics
• Bioinformatics
• Computational Biology

Background:

• Genetic mapping functions are essential for converting recombination rates into map distances.
• Multiple crossover events can influence the accuracy of different mapping functions.
• The optimal mapping function can vary depending on the specific genetic data and organism.

Purpose of the Study:

• To determine the most suitable genetic mapping functions for cattle chromosomes 6, 23, and the sex chromosome.
• To evaluate the performance of various mapping functions using real genetic data from Norwegian bulls.
• To assess the multilocus feasibility of identified optimal mapping functions.

Main Methods:

• Utilized genetic data from 2214 sperm samples of 37 Norwegian bulls, genotyped for 11 markers.
• Applied maximum likelihood, likelihood ratio tests, and empirical discriminant analysis to derive optimal functions.
• Assessed mapping functions for their ability to handle multiple crossover events and multilocus feasibility.

Main Results:

• Identified chromosome-specific optimal mapping functions: Rao et al. for chromosome 6, Goldgar & Fain for chromosome 23, and Felsenstein for the sex chromosome.
• Demonstrated that commonly used functions like Haldane and Kosambi were suboptimal for this dataset.
• Found the optimal function for chromosome 23 to be multilocus feasible, while those for chromosomes 6 and the sex chromosome were not.

Conclusions:

• The selection of an appropriate genetic mapping function significantly impacts the accuracy of genetic mapping studies, especially when accounting for double recombinations.
• No single mapping function is universally optimal; chromosome-specific parameter estimation is recommended.
• Utilizing simple parametric functions with estimated parameters, such as Felsenstein's function, can improve mapping accuracy for specific datasets.