Population Genetics. Matthew B. Hamilton

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Population Genetics - Matthew B. Hamilton


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target="_blank" rel="nofollow" href="#ulink_e1d4b590-5c81-5ff2-b273-7d8448887d5d">Table 2.5 χ2 values and associated cumulative probabilities in the right‐hand tail of the distribution for one through five degrees of freedom.

Probability
df 0.5 0.25 0.10 0.05 0.01 0.001
1 0.4549 1.3233 2.7055 3.8415 6.6349 10.8276
2 1.3863 2.7726 4.6052 5.9915 9.2103 13.8155
3 2.3660 4.1083 6.2514 7.8147 11.3449 16.2662
4 3.3567 5.3853 7.7794 9.4877 13.2767 18.4668
5 4.3515 6.6257 9.2364 11.0705 15.0863 20.5150

       Assuming Hardy–Weinberg to test alternative models of inheritance

      Biologists are all probably familiar with the ABO blood group and are aware that mixing blood of different types can cause blood cell lysis and possibly result in death. Although we take this for granted now, there was a time when blood types and their patterns of inheritance defined an active area of clinical research. It was in 1900 that Karl Landsteiner of the University of Vienna mixed the blood of the people in his laboratory to study the patterns of blood cell agglutination (clumping). Landsteiner was awarded the Nobel Prize for Medicine in 1930 for his discovery of human ABO blood groups. Not until 1925, due to the research of Felix Bernstein, was the genetic basis of the ABO blood groups resolved (see Crow 1993a).

      Landsteiner observed the presence of four blood phenotypes A, B, AB, and O. A logical question was then, “what is the genetic basis of these four blood group phenotypes?” We will test two hypotheses (or models) to explain the inheritance of ABO blood groups that coexisted for 25 years. The approach will use the frequency of genotypes in a sample population to test the two hypotheses rather than an approach such as examining pedigrees. The hypotheses are that the four blood group phenotypes are explained by either two independent loci with two alleles each with one allele completely dominant at each locus (hypothesis 1) or a single locus with three alleles where two of the alleles show no dominance with each other but both are completely dominant over a third allele (hypothesis 2). Throughout, we will assume that Hardy–Weinberg expected genotype frequencies are met in order to determine which hypothesis best fits the available data.

Blood Genotype Expected genotype frequency Observed
Type Hypothesis 1 Hypothesis 2 Hypothesis 1 Hypothesis 2 (total = 502)
O aa bb OO fa2fb2 (fO)2 148
A A_ bb AA, AO (1‐fa2)(fb)2 fA2 + 2fAfO 212
B aa B_ BB, BO fa2(1‐fb2) fB2 + 2fBfO 103
AB A_ B_ AB (1‐fa2)(1‐fb2) 2fAfB 39

      The next step is to compare the expected genotype frequencies for the two hypotheses with observed genotype frequencies. To do this, we will need to estimate allele frequencies under each hypothesis and use these to compute the expected genotype frequencies. (Although these allele frequencies are parameter estimates, the “hat” notation is not used for readability.) For the hypothesis of two loci (hypothesis 1), fb2 =


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