marker-assisted selection in wheat - ictsd

Chapter 8 – Marker-assisted selection in maize 135the opportunities for learning about andunderstanding the response to selectionwill increase dramatically. It may then bepossible to ameliorate some of the limitationsof MAS and truly breed by design.Limitations of MASWhile not truly an inherent limitation ofthe methods involved, one unavoidablelimitation of MAS is the cost of assemblingand integrating the necessary infrastructureand personnel. These can be substantial andbeyond the means of many programmes.For such programmes, implementation ofMAS could lead to a delusional or unbalancedreallocation of resources from vitalactivities such as high-quality phenotypicevaluation and selection in the target environment.Currently, only the largest maizebreeding programmes in a given market orregion have the scale of sales and diversityof products that can justify and supportMAS and withstand some of the financialburdens of establishing and replacing componentsof the system (e.g. changes in themethods and platforms for detecting DNApolymorphisms).Some inherent limitations to MAS arerelated to the estimates of QTL positionand genetic effects and the rates of falsepositives and negatives. Confidence intervalsfor QTL are typically 10–15 cM; agenetic region that should not be a majorbarrier for implementing MAS althoughit could become a limitation to achievinggenetic gain by preventing the selection ofdesired recombination events. The adventof association mapping and a growing poolof candidate genes should provide someresources needed to minimize problemsrelated to the estimation of QTL position.The genetic effects of QTL are overestimatedfor many reasons, some of whichare linked to experimental designs forphenotyping or population developmentwhile others are inherent to the process ofQTL detection (Lee, 1995; Beavis, 1998;Melchinger, Utz and Schön, 1998; Holland,2004). In addition, genetic effects relatedto epistasis are either poorly estimated orignored by programmes in the private sector(Holland, 2001; Crosbie et al., 2006).Such assessments of genetic effects willinflate predictions of genetic gain. Therelative merit of MAS will depend on thenature of predictions, actual results andcosts of alternative methods.A possible limitation of MAS withmaize is the structure and content of variousgene pools. Examples of maize genepools would include European flint anddent germplasm, United States dents andvarious heterotic groups within each ofthese and other larger pools. Surveys withDNA markers have established differencesamong such groups of germplasm (Smithand Smith, 1992; Niebur et al., 2004). Therelatively allele-rich maize gene pools coupledwith genetic heterogeneity for manytraits will hinder the ability to extrapolateinformation about genotype-phenotyperelationships across gene pools. Such transferof information is expected to be moresuccessful in relatively homogeneous andless diverse maize gene pools (e.g. sweetcornor popcorn) and with self-pollinatedplant species (Lee, 1995). There have beenundocumented reports of a few alleles atQTL that have relatively universal geneticeffects across a relatively broad range ofmaize populations and target environments,but details of such genetic factorshave not been publicly disclosed (Crosbieet al., 2006). More resources will need to bedevoted to discovering where genetic informationcannot be easily extrapolated acrossgene pools or even populations within agene pool compared with situations where