Genetic relatedness analysis: modern data and new challenges

Key Points Population and quantitative genetics theory is built with parameters that describe relatedness, and estimation of these parameters from genetic markers enables progress in fields as disparate as plant breeding, human disease gene mapping and forensic science. Relatedness can be described by the probabilities that two individuals share zero, one or two pairs of alleles that are identical-by-descent. More probabilities are needed if the individuals are inbred, meaning that their parents were related. Alternative hypotheses about the relationship between two individuals can be evaluated by dividing the probability of the observed genotypes of the individuals under one hypothesis by the probability of the genotypes under the other. The ratio of probabilities is called the likelihood ratio. In paternity testing, it is called the paternity index. The probabilities of patterns of identity-by-descent can be estimated by the method of maximum likelihood. Even for individuals whose parents are not related, and who are therefore not inbred, account needs to be taken of 'background relatedness' that is due to evolutionary history in a population. Even though the probabilities of identity-by-descent are defined by the family and population relatedness of two individuals, there is variation in actual identity-by-descent along the genome. This reflects the differences in actual genealogies at different loci, and it is influenced by recombination along with mutation and natural selection. Relationship is best estimated by highly polymorphic markers, to minimize the ambiguity between identity-in-state and identity-by-descent. However, reliable estimates can be obtained with a sufficiently large number of biallelic SNPs. The concept of relatedness is central to many fields, from human linkage analysis to forensics to animal and plant breeding. This review covers the statistical framework for studying relatedness, its applications and the challenges that the field faces. Individuals who belong to the same family or the same population are related because of their shared ancestry. Population and quantitative genetics theory is built with parameters that describe relatedness, and the estimation of these parameters from genetic markers enables progress in fields as disparate as plant breeding, human disease gene mapping and forensic science. The large number of multiallelic microsatellite loci and biallelic SNPs that are now available have markedly increased the prec