Question

Ecologists use molecular biological methods to measure genetic relatedness.

How can we measure relatedness?

Answer 1

The measurement of relatedness is of vital importance. The estimation is based on the pedigree connections between individuals. Relatedness is an general term for level of genetic similarity between individuals in terms of their sharing alleles identical by descent. Some coefficients that are used for this study is the coefficient of kinship is the probability that a randomly chosen allele from each will be identical by descent, given a particular set of genealogical order. An offspring I, of X and Y will have an inbreeding coefficient FI which is equal to coefficient of kinship

The coefficient of relationship between X and Y can be defined as,

Where Fx and Fy are inbreeding coefficients of X and Y respectively.

The pedigree coefficient of relationship, Gyx , is the proportion of Ys gene identical by descent with genes present in X

The above three coefficients measure the identity by descent using pedigree connections. in populations in which pedigree connections are unknown these parameters have to be replaced with terms relating to distribution of alleles and genotypes in population concerned. they measure the relatedness of an individual relative to population average.

The regression coefficient of relatedness, is analogous to pedigree coefficient,

where the numerator is the genotypic covariance and the denominator the variance.

Relatedness estimates can be obtained from scattered nests in different populations, and considerable precision can be achieved by using multi-allelic data and the distribution of multi-locus genotypes.

Coefficient of relatedness

The characteristic to be used in the regression analysis is the frequency of allele A. Assuming an infinite sample size, we can calculate the regression coefficient between the frequencies for individuals (X) and the average for the nest (Y). In a given nest, there are three possible values for X (1 for AA, 0.5 for Aa, and 0.0 for aa), but only a single value for Y (which is D + H/2). The regression coefficient within any one nest is, of course, zero, and hence the regression coefficient of relatedness can be estimated only from population data, using inter nest differences

When samples of finite size are taken from the nests, the above procedure over-estimates b, because the inclusion of each individual within Y as well as within X boosts the apparent genetic similarity of the nest as a whole to each such individual. As the sample size per nest, n. increases, the biased estimate 6” approaches the expected value, E(b), asymptotically according to