Marker and sequence information

Utilisation and conservation of farm animal genetic resources 87

Chapter 4. Genomics reveals domestication history and facilitates breed development

will be found. When a common origin is encountered for a pair of haplotypes, the number of ancestral lineages is decreased by one and again the common haplotype is paired with a third one to track an even older lineage and so on, inally ending in one common ancestor of the haplotypes. his genealogical process is called coalescence analysis reviewed by Rosenberg and Nordborg, 2002. he coalescence process can be used in detecting selection where the depth of the genealogy is indicating the type of selection. Positive selection sweeps an adaptive mutation to ixation leaving behind a shallow star-like genealogy and an excess of low-frequency haplotypes coupled with low π giving a negative value for Tajima’s test connected to a common ancestor with similar short branches. By contrast, balancing selection results in deep genealogies in which haplotype variants are found at intermediate frequencies with hitch-hiking variation at linked loci, and consequently a positive value for Tajima’s test statistic.

2.7. Establishing the hidden structure of a metapopulation by clustering methods

Phylogenetic techniques based on genetic distances have been the method of choice to assess the genetic diversity of livestock breeds chapter 5. he approach relies on the a priori deinition of populations and presents several problems. First, genetic variation within populations is completely ignored. Second, construction of trees using admixed populations, as oten happens in livestock, contradicts with the principles of phylogeny reconstruction. And third, it fails to take into account the fact that genetic distances vary greatly according to the marker used and the recent demographic history of the breed e.g. whether it has passed through a population bottleneck Toro and Caballero, 2005. Recent methods have been developed as a more lexible alternative to genetic distances. he new methods try to divide the total sample of genotypes of a population into an unknown number of subpopulations clusters. his allows the population structure or subdivision to be more lexibly inferred from the data. he clustering methods will separate a set of individuals into several populations when their genetic origin is unknown or to study the correspondence between inferred genetic clusters and known pre-deined population categorisations like breeds Pritchard et al., 2000. he individuals are assigned probabilistically to clusters or jointly to two or more clusters if their genotypes indicate that they are admixed. he methods also estimate, for each individual, the fraction of its genome that belongs to each cluster without any prior information on the structure of the population. hus, these methods allow to cluster data genetic mixture analysis either at group level or at individual level, and also to perform admixture analysis, in which the genome of an individual represents a mixture of alleles of diferent ancestries.