Selection and use of genetically diverse genotypes are key factors in any crop breeding program to develop cultivars with a broad genetic base. Molecular markers play a major role in selecting diverse genotypes. In the present study, a reference set representing a wide range of sorghum genetic diversity was screened with 40 EST-SSR markers to validate both the use of these markers for genetic structure analyses and the population structure of this set. Grouping of accessions is identical in distance-based and model-based clustering methods. Genotypes were grouped primarily based on race within the geographic origins. Accessions derived from the African continent contributed 88.6 % of alleles confirming the African origin of sorghum. In total, 360 alleles were detected in the reference set with an average of 9 alleles per marker. The average PIC value was 0.5230 with a range of 0.1379-0.9483. Sub-race, guinea margaritiferum (Gma) from West Africa formed a separate cluster in close proximity to wild accessions suggesting that the Gma group represents an independent domestication event. Guineas from India and Western Africa formed two distinct clusters. Accessions belongs to the kafir race formed the most homogeneous group as observed in earlier studies. This analysis suggests that the EST-SSR markers used in the present study have greater discriminating power than the genomic SSRs. Genetic variance within the subpopulations was very high (71.7 %) suggesting that the germplasm lines included in the set are more diverse. Thus, this reference set representing the global germplasm is an ideal material for the breeding community, serving as a community resource for trait-specific allele mining as well as genome-wide association mapping. (Résumé d'auteur

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The sequencing and detailed comparative functional analysis of genomes of a number of select botanical models open new doors into comparative genomics among the angiosperms, with potential benefits for improvement of many orphan crops that feed large populations. In this study, a set of simple sequence repeat (SSR) markers was developed by mining the expressed sequence tag (EST) database of sorghum. Among the SSR-containing sequences, only those sharing considerable homology with rice genomic sequences across the lengths of the 12 rice chromosomes were selected. Thus, 600 SSR-containing sorghum EST sequences (50 homologous sequences on each of the 12 rice chromosomes) were selected, with the intention of providing coverage for corresponding homologous regions of the sorghum genome. Primer pairs were designed and polymorphism detection ability was assessed using parental pairs of two existing sorghum mapping populations. About 28% of these new markers detected polymorphism in this 4-entry panel. A subset of 55 polymorphic EST-derived SSR markers were mapped onto the existing skeleton map of a recombinant inbred population derived from cross N13 x E 36-1, which is segregating for Striga resistance and the stay-green component of terminal drought tolerance. These new EST-derived SSR markers mapped across all 10 sorghum linkage groups, mostly to regions expected based on prior knowledge of rice-sorghum synteny. The ESTs from which these markers were derived were then mapped in silico onto the aligned sorghum genome sequence, and 88% of the best hits corresponded to linkage-based positions. This study demonstrates the utility of comparative genomic information in targeted development of markers to fill gaps in linkage maps of related crop species for which sufficient genomic tools are not available.

Crop genome sequencing projects generate massive amounts of genomic sequence information, and the utilization of this information in applied crop improvement programs has been augmented by the availability of sophisticated bioinformatics tools. Here, we present the possible direct utilization of sequence data from a sorghum genome sequencing project in applied crop breeding programs. Based on sequence homology, we aligned all publicly available simple sequence repeat markers on a sequence-based physical map for sorghum. Linking this physical map with already existing linkage map(s) provides better options for applied molecular breeding programs. When a new set of markers is made available, the new markers can be first aligned on a sequence-based physical map, and those located near the quantitative trait locus (QTL) can be identified from this map, thereby reducing the number of markers to be tested in order to identify polymorphic flanking markers for the QTL for any given donor × recurrent parent combination. Polymorphic markers that are expected (on the basis of their position on the sequence-based physical map) to be closely linked to the target can be used for foreground selection in marker-assisted breeding. This map facilitates the identification of a set of markers representing the entire genome, which would provide better resolution in diversity analyses and further linkage disequilibrium mapping. Filling the gaps in existing linkage maps and fine mapping can be achieved more efficiently by targeting the specific genomic regions of interest. It also opens up new exciting opportunities for comparative mapping and for the development of new genomic resources in related crops, both of which are lagging behind in the current genomic revolution. This paper also presents a number of examples of potential applications of sequence-based physical map for sorghum. (Résumé d'auteur

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