Part III

1. The map distance between loci does not equal the observed recombination between loci because double-crossovers result in the same amount of recombination as single crossovers. Double crossovers should be counted twice when determining the amount of recombination between loci. Unless there is a marker locus in the middle of the flanking markers, the double crossovers cannot be distinguished from the single crossovers. Double crossovers should be counted as two crossover events, but the recombination fraction appears the same as a single crossover event. Thus, the relative frequency of crossover events is underestimated by the observable recombination fraction. As a result the recombination fraction does not equal the map distance, except for chromosome segments less than 10cM.
   
   
2. Haldane's mapping function assumes that the coefficient of coincidence (C) is unity. Kosambi's map function assumes C = 2p.
   
   
3. To distinguish between two possible segregation ratios, the minimum number of individuals in the segregating progeny can be determined using a formula.
   
   
4. We can use a formula to determine the minimum number of plants to grow with a specified probability of failure to observe one plant with the desired genotype. This formula is useful to determine how many F₁ seeds must be grown to successfully transfer a trait by repeated backcrossing to the recurrent parent.
   
   
5. When planning experiments to estimate the 'p' value for recombination between two linked loci, the type of family evaluated, the type of linkage (coupling or repulsion), and the closeness of linkage - all influence the precision of the estimate of p.
   
   
6. Markers are not evenly distributed throughout the genome. The marker coverage of the genome is the ratio of the genomic map length to the total length of the genome. We can use a formula to determine the probability that n markers that are randomly distributed throughout the genome will be within a 2d cM distance of a QTL for a given genome length (L).
   
   
7. The lod score is the likelihood odds ratio. This is the Log₁₀ of the ratio of the likelihood that p is some value divided by the likelihood that p = 0.5
   
   
8. We can graph the lod score of p as varied. For discrete classes the maximum lod score will be the maximum likelihood estimate of p.