Maximum-likelihood models for mapping genetic markers showing segregation distortion. 1. Backcross populations

Area of Science:

• Genetics
• Population Genetics
• Quantitative Genetics

Background:

• Segregation distortion, deviations from expected allele ratios, can complicate genetic mapping.
• Viability differences in gametes or zygotes due to selection are a common cause of segregation distortion.
• Accurate estimation of recombination fractions is crucial for constructing genetic maps.

Purpose of the Study:

• To develop and evaluate a maximum-likelihood approach for estimating recombination fractions in the presence of segregation distortion.
• To assess the performance of Bailey's (1949) estimate under more general assumptions.
• To investigate the impact of segregation distortion on linkage detection and marker order.

Main Methods:

• Utilizing a maximum-likelihood framework to estimate recombination fractions.
• Applying the method to backcross populations exhibiting segregation distortion.
• Comparing Bailey's estimate with the classical maximum-likelihood estimate.

Main Results:

• Bailey's estimate is shown to be consistent and efficient under broader conditions than previously assumed.
• The study demonstrates that segregation distortion can influence the detection of linkage.
• Marker order on linkage groups can be significantly affected by segregation distortion.

Conclusions:

• Bailey's estimate is a robust and recommended method for recombination fraction estimation in populations with segregation distortion.
• Segregation distortion poses challenges for accurate genetic mapping, potentially altering marker order.
• The findings have implications for genetic map construction and the study of selection in populations.