marker-assisted selection in wheat - ictsd

124Marker-assisted selection – Current status and future perspectives in crops, livestock, forestry and fishand become more stable so that start-upand operating costs, while still high forsome programmes, are more predictable.Statistical methods and related softwarehave also been areas of significant development,especially for the detection anddescription of putative QTL. QTL, whichare nothing more than associations betweenmarkers and traits, were first describedusing simple association tests betweentrait values and marker genotypes (Stuberand Moll, 1972). These tests consider eachmarker locus independently and neitherrequire nor take advantage of the existenceof genetic maps. Statistical methods havebeen developed that take advantage of theexistence of genetic maps (see review byManly and Olson, 1999). These statisticalmethods, simple interval mapping (Landerand Botstein, 1989) and composite intervalmapping (Jansen, 1993; Zeng, 1993, 1994),test the existence of associations betweenhypothetical marker genotypes and traitvalues at several points in intervals betweenpairs of adjacent marker loci on the geneticmap, allowing the positioning of QTL onthese genetic maps. All of the previousmethods are based on single QTL models.Other statistical methods have been developedthat simultaneously test the presenceof several QTL in the genome (Kao, Zengand Teasdale, 1999).Many software packages are availablefor QTL mapping and based on one orseveral of the statistical methods developedto date. No two packages are exactly alikeand all have specific strengths and weaknesseswith respect to particular situations,making it sometimes beneficial to use morethan one package to perform QTL mappinganalyses. The software packages mostcommonly used for QTL mapping in maizeinclude QTL Cartographer (Basten, Weirand Zeng, 1994), MapQTL (van Ooijen andMaliepaard, 1996), and PLABQTL (Utz andMelchinger, 1996). All of these only handlebi-allelic populations, while MCQTL(Jourjon et al., 2005) also performs QTLmapping in multi-allelic situations, includingbi-parental populations made fromsegregating parents, or sets of bi-parental,bi-allelic populations.More recently, methods based onBayesian analysis (Jansen, Jannink andBeavis, 2003; Gelman et al., 2004) andassociation (Varshney, Graner and Sorrels,2005) or in silico mapping (Parisseaux andBernardo, 2004) have been proposed asmore powerful and refined approaches toassess the relationships between genotypeand phenotype that are needed for MAS.Methods of Bayesian analysis should beless affected by the uncertainties of QTLeffects and locations and produce betterestimates of those parameters in MAS.Association mapping approaches are particularlyuseful to validate the relevanceof genes and alleles in specific germplasmsuch as that used by maize breeders. Insilico mapping takes advantage of the pedigreerelationships among individuals tostructure the population used to establishmarker-trait associations. This approach,which is highly complex due to the populationstructure resulting from pedigreebreeding, is particularly appropriate formaize where data across many years andenvironments are available for large setsof related individuals. Certainly, as theannotation of genomes gradually improves,such methods will be common componentsof breeding programmes. Currently, theapplications of methods such as associationmapping for MAS are hindered by thefact that a very low percentage of the genesin crop plants have a function assigned tothem on the basis of direct experimentation.However, this impoverished situation