Mating, random

Table 10.1 shows the seleetion of parents for mating from the initial population. If a random number generator is used to generate numbers between 0.0 and 1.0, then the eumulative probability values in Table 10.1 is used as follows ... 

The random number generator produeed the following values 0.326, 0.412, 0.862 and 0.067. Henee Parent 1 was seleeted twiee. Parents 2 and 4 onee and Parent 3 not at all. The seleeted parents were randomly mated with random ehoiee of erossover points. The fitness of the first generation of offsprings is shown in Table 10.2. 

If a population is large, and if individuals mate at random with respect to their genotypes at a locus, the population should be in Hardy-Weinberg equiUbrium, which means that there is a constant and predictable relationship between genotype frequencies and gene frequencies. This allows us to estimate genotype frequencies if we know gene frequencies, and vice versa. 

Assuming random mating, the Hardy-Weinberg principle specifies a predictable relationship between gene and genotype frequeicies in populations. It can be applied to estimate the frequency of heterozygous carriers of an autosomal recessive mutation. 

Consanguinity (choice A) affects Hardy-Weinberg eqinlibrium by increasing the number of homozygotes in the population above the equilibrium expectation (i.e., consanguinity results in a violation of the assumption of random mating). 

Only one generation of random mating is required to return a population to equilibrium (D). 

Matings are assumed to be random among persons within the population. 

The mated females are randomly allocated to treatment groups using a stratified procedure to ensure approximate equal mean body weights in all groups. 

When we are dealing with samples rather than populations, we cannot use the standard normal deviate, Z, to make predictions since this requires knowledge of the population mean and variance or standard deviation. In general, we do not know the value of these parameters. However, provided the sample is a random one, its mean 5 is a reliable estimate of the population mean p, and we can use the central limit theorem to provide an estimate of o. This esti mate, known as the standard error of the mean, is given by ... 

The control of mating type in yeast illustrates a specialized role of mobile or transposable genetic elements in which mobile elements hop from one site to another. Mobile genetic elements are commonly found in both prokaryotes and eukaryotes, but most of them show little site specificity. Indeed, their almost random insertion behavior has led to the proposal that their major function in most cases is to promote evolutionary change. 

The use of nuclear family data in association studies was initially developed to avoid possible ethnic mismatching between patients and randomly ascertained controls (76). The parental marker alleles not transmitted to an affected child, or never transmitted to an affected sib pair, form the so-called AFBAC population (19,20) (Fig. 1). In a random mating population, when there is a marker association with disease, the AFBAC population provides an unbiased estimate of the overall population (control) marker alleles when the recombination fraction between the marker and disease genes is sufficiently small that it can be taken as zero (0 = 0), and differences between patient and AFBAC frequencies can be tested for example by a contingency table analysis for heterogeneity. 

If mating is random, these genotypic frequencies are functions of p, the frequency of the allele A, and q, the frequency of the allele a, viz. 

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