marker-assisted selection in wheat - ictsd

214Marker-assisted selection – Current status and future perspectives in crops, livestock, forestry and fishthe flanking markers must be sufficientlyclose to the QTL so that it will be possibleto determine with relative certaintythat the QTL is in fact located betweenthe flanking markers. Although markerassistedintrogression does decrease thenumber of generations required to obtainfixation of the desired allele, it increasestwo key cost elements. First, with traditionalintrogression, half of the progenywill carry the donor allele for the introgressedgene, and all of these can be usedas parents in the next generation. However,if only a small fraction of the progeny isselected based on genetic markers, thenmany more individuals must be producedeach generation. Second, genotyping costsfor a large number of markers at each generationwill also be significant.Crosses between cattle breeds can alsobe used for QTL detection and they havebeen used in developing countries. In mostplant species, the parental lines are completelyinbred, and there will be completeLD in the F 2 or backcross generation.However, cattle are outbreeders and incrosses between breeds there will thereforeonly be partial LD between segregatingQTL and linked genetic markers. Song,Soller and Genizi (1999) proposed the fullsibintercross line (FSIL) design for QTLdetection and mapping for crosses betweenstrains of outcrossing species. They assumedthat the two parental strains differ in allelicfrequencies, but were not at fixation foralternative QTL alleles.For given statistical power, the FSILdesign requires only slightly more individualsthan an F 2 design derived from aninbred line cross, but six- to ten-fold fewerthan a half-sib or full-sib design. In addition,as the population is maintained bycontinued intercrossing, DNA samples andphenotypic information can be accumulatedacross generations. Continued intercrossingin future generations also leads to mapexpansion, and thus to increased mappingaccuracy in the later generations. AnFSIL can therefore be used for fine mappingof QTL and this is considered belowin detail.Although these methods have not as yetbeen applied to detect QTL related to milkproduction, they have been applied to QTLfor disease resistance. Trypanosomosis(sleeping sickness) is a major constrainton livestock productivity in sub-SaharanAfrica. Hanotte et al. (2003) mappedQTL affecting trypanotolerance in a crossbetween the “tolerant” N’Dama breed andthe susceptible Boran breed. Putative QTLaffecting 16 traits associated with diseasesusceptibility were mapped tentatively to18 autosomes. Excluding chromosomeswith ambiguous effects, the allele associatedwith resistance was derived from theN’Dama strain for nine QTL and from theBoran strain for five QTL. These results areconsistent with many plant crossbreedingexperiments in which the strain with overallphenotypic inferiority for the quantitativetrait nevertheless harbours QTL alleles thatare superior to the alleles present in thephenotypically superior strain (e.g. Weller,Soller and Brody, 1988).From QTL to QTN – theoryAs noted by Darvasi and Soller (1997),with a saturated genetic map, the resolvingpower for QTL will be a function of theexperimental design, number of individualsgenotyped and QTL effect. Weller andSoller (2004) computed that the 95 percentconfidence interval (CI) in percent recombinationfor half-sib designs, including thedaughter and granddaughter designs, was3073/d 2 N, where d is the QTL substitutioneffect in units of the standard deviation, and