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Finally, the available sequence data for these markers will contribute to a growing framework of genetic information that is relevant across related grass species and beyond.

In addition, the identification of new prognostic/predictive markers will contribute to more optimal patient sub-grouping and individualisation of treatment strategies (Hamilton and Piccart, 2000).

Therefore, these new markers will contribute to enrich existing genetic maps, generate more informative genetic and genomic tools and enable the identification of orthologous genes through genome synteny analysis [ 15].

These markers will contribute to determining the biological background of retaining floral color variation within a population, using parameters of gene flow, genetic variation (e.g., AMOVA), and genetic structure (e.g., STRUCTURE analysis) among different types of flower colors.

It is expected that dissection of the complex genome via evaluation of genome-wide allelic polymorphism of DNA markers, will contribute to our understanding of genomic diversity in soybean.

The developed markers will contribute to studies of the evolution of gynodioecy by facilitating estimation of the mating system (e.g., selfing ability and levels of pollen limitation), gene flow (e.g., pollen and seed dispersal), and population structure (e.g., spatial genetic structure) of this species.

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The microsatellite markers presented here will contribute to the control of Chagas disease in Venezuela and Colombia through the provision of population information that may allow the design of improved control strategies.

These markers will significantly contribute to research on ectomycorrhizal fungi, as they allow investigation of fungal populations from a species (and close relatives) from the Southern Hemisphere, from a previously unstudied host tree (N. cunninghamii) and ecosystem (cool temperate rainforest).

The development of SNP markers in plant species will contribute to the understanding of crop evolutionary history, to the positional cloning of QTLs, and to marker-assisted breeding (reviewed in [ 19]).

The identification of microsatellite and SNPs markers within turbot ESTs will contribute to extend the turbot genetic map [ 10] after linkage analysis in reference families.

In this situation, more integrated markers, such as metabolite levels, will contribute a decisive part of information, since they reflect the combined effect of many genes.

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