marker-assisted selection in wheat - ictsd

40Marker-assisted selection – Current status and future perspectives in crops, livestock, forestry and fishcharacters that breeders are concernedabout in population or variety improvementprogrammes. Given the complexity ofquantitative traits, many different lines orcrosses must be carefully analysed overdifferent years and environments to unravelimportant components of gene interaction.In a breeding context, understanding thegenetic basis of genotype by genotypeinteraction (G x G) and genotype byenvironment interaction (G x E) is criticalas the basis for predicting how QTL arelikely to behave. Information from a largenumber of studies addressing each of thesepoints must then be assembled into adatabase that offers easy access to users andallows many different kinds of data to beintegrated with a simple query.The Gramene database represents abeginning in the quest to serve this usercommunity. Gramene is a comparativegenome database for grasses and currentlyoffers a complete inventory of all publishedQTL that have been identified in rice (www.gramene.org/qtl/index.html), allowing usersto find information about where along thechromosome a QTL is located, what phenotypeis associated with the QTL, how itwas measured, what germplasm was used,what molecular markers reside nearby, whatthe corresponding position is on a comparativemap of another grass species and withwhat statistical significance the QTL wasdetected. The database also provides a linkto the published article so that users canreadily find more information on the subject.Similar inventories and databases arebeing assembled for other families of plantsand are critical to the implementation ofeffective molecular breeding strategies.Comparative genome methods takeadvantage of the fact that some specieshave more developed genetic systems thanothers. Examples of well studied “model”organisms with available genomic sequenceinclude species such as Arabidopsis andrice for plants, Populus (Taylor, 2002) andEucalyptus (Poke et al., 2005) specificallyfor forestry, and Fugu (Aparicio et al.,2002) and zebrafish (Guryev et al., 2006)for fisheries. Relying heavily on the useof comparative maps and comparativesequence analysis, genome databases allowresearchers to make predictions about thelocation and phenotypic consequences ofhomologous genes in related species. Thus,understanding how a gene or QTL behavesin one species can potentially shortcutthe process of identifying a related geneor QTL in the genetic system of anotherspecies. This approach underscores thesearch for QTL associated with abioticstress tolerance in cereals. A global effortto identify loci associated with droughttolerance has recently been initiated underthe umbrella of the Generation ChallengeProgramme (www.generationcp.org).Markers associated with tolerance fora variety of environmental stresses rank asimportant targets for molecular MAS incereal breeding because these complex traitsare often prohibitively difficult to screenusing classical selection techniques. Effortsto identify QTL associated with tolerance todrought, salt and mineral deficiencies or toxicities(Champoux et al., 1995; Flowers et al.,2000; Nguyen et al., 2002; Kamoshita et al.,2002; Price et al., 2002; Gregorio, 2002) ina number of genetic backgrounds representan important first step towards achievingthis goal. Additional studies have specificallyaddressed the problems associated withG x G and G x E (Zheng et al., 2000; Li etal., 2003; Hittalmani et al., 2003).In the area of biotic stress, several geneshave been cloned and characterized forresistance to major diseases such as bacterialblight and blast (Song et al., 1995;