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.
88 Utilisation and conservation of farm animal genetic resources
Miguel Toro and Asko Mäki-Tanila
he algorithms are based on multi-locus genotypes and solved adopting a Bayesian approach computed using Monte Carlo Markov Chain methods and assuming multi-
locus genotypes in Hardy-Weinberg and linkage equilibrium within each randomly mating subpopulation. he procedure consists of simultaneously itting the allele
frequencies and assigning individuals to the populations where some individuals may descent from more than one population. his complex calculation is carried out
numerically using a Monte Carlo Markov Chain MCMC approach. hree programs are available until now: STRUCTURE Pritchard
et al., 2000, PARTITION Dawson and Belkhir, 2001 and BAPS Corander
et al., 2003 and their diferences are summarised by Pearse and Crandall 2004.
his approach was irst applied by Rosenberg et al. 2001 in 20 chicken breeds and later
it has been applied to pigs, cattle, sheep, goat, dogs and horses. Rosenberg et al. 2001
argued that genetically distinctive populations can be identiied on the basis of the lack of diiculties encountered in separating them from others. When some populations can
easily be separated with only a small number of markers, this could indicate the presence of distinctive multi-locus genetic combinations in those populations. herefore they
suggest that the relative number of loci required for the ‘correct’ clustering of several populations can be used as a way of identifying those that are genetically distinctive
with respect to a collection. In an example in Box 4.3., only six independent loci are enough to separate the two more distinct strains.
3. Utilisation of breed differences
his section is devoted to implementation of the knowledge on breed diferences in genetic improvement schemes. he emphasis is on the utilisation of genomic tools for
the prediction of heterosis in crosses, for detection of interesting genes in diferent situations, for introgressing useful genes from one breed to another and for assigning
individuals and products to breeds.
3.1. Prediction of heterosis using genetic distances
It is well know in quantitative genetics that crosses between genetically diferent breeds present hybrid vigour or heterosis especially for traits related to itness.
Heterosis requires directional dominance for the majority of loci the recessive allele has an unfavourable efect and diferences in frequencies between the lines used in
crossing. However, crosses do not always enhance itness. Crosses between very distant populations may fail to show heterosis and may sufer a reduction in itness in the F2
generation
recombination loss usually attributed to a break-down of a co-adapted gene complex of favourable epistatic interactions Dickerson, 1969.
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