marker-assisted selection in wheat - ictsd

174Marker-assisted selection – Current status and future perspectives in crops, livestock, forestry and fishIncorporating marker informationin genetic evaluation programmesThe value of genotypic information forpredicting the genetic merit of animals isdependent on the predictive ability of themarker genotypes. The three types of molecularloci described previously differ not onlyin methods of detection but also in methodsof their incorporation in genetic evaluationprocedures. Whereas direct and, to alesser degree, LD markers, allow selectionon genotype across the population, use ofLE markers must allow for different linkagephases between markers and QTL fromfamily to family, i.e. LE markers are familyspecific and family specific information mustbe derived. As discussed later in this chapter,this makes LE markers a lot less attractivefor use in breeding programmes. In thissection, the different types of models thathave been proposed for genetic evaluationbased on marker information are describedand this is followed by a brief description ofsome practical issues regarding implementationof such methods and the likely routestowards achieving that goal.Modelling QTL effects in geneticevaluationBy using QTL information in genetic evaluation,in principle, part of the assumedpolygenic variation is substituted by a separateeffect due to a genetic polymorphismat a known locus. This has the immediateeffect of having a much better handle onthe Mendelian sampling process, as phenotypicco-variance can be evaluated basedon specific genetic similarity rather thanon an average relationship. For example,on average two full sibs share 50 percentof their alleles, but at a specific locus it isnow possible to know whether these fullsibs carry exactly the same complete genotype(both paternal and maternal alleles arein common), or actually have a completelydifferent genotype. The actual degree ofsimilarity of full sibs at a QTL can thusvary between 0 and 1. This additional informationhelps to better evaluate the geneticmerit due to specific QTL, and to betterpredict offspring that do not yet have phenotypicmeasurements.A number of different approaches havebeen described to accommodate markerinformation in genetic evaluation. Roughly,these methods can be distinguishedthrough their modelling of the QTL effectand through the type of genetic markerinformation used. The QTL effect can bemodelled as random or fixed, while themolecular information comes from LE, LDor direct markers.With a fixed QTL model, regression ongenotype probabilities would be used ingenetic evaluation to account for the effectof QTL polymorphisms. In the simplestadditive QTL model, suitable for estimatingbreeding values, simple regressionscould be included on the probability of carryingthe favourable mutation. Regressioncan be on known genotypes (class variables),or probabilities can be derived forungenotyped animals in a general complexpedigree (Kinghorn, 1999). A fixed QTLmodel is sensible if few alleles are knownto be segregating, and where dominanceand/or epistasis are important. The modelalso assumes effects being the same acrossfamilies. The effects of various genotypescould be fitted separately, giving power toaccount for dominance and epistasis in caseof multiple QTL. For selection purposes,a fixed QTL effect, if additive, would beadded to the polygenic estimated breedingvalues (EBVs), similar to breed effects inacross-breed evaluations. The advantage ofa fixed QTL model is the limited number ofeffects that need to be fitted.