Exploiting EST databases for the development and characterization of gene-derived SSR-markers in barley (Hordeum vulgare L.)
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A software tool was developed for the identification of simple sequence repeats (SSRs) in a barley (Hordeum vulgare L.) EST (expressed sequence tag) database comprising 24,595 sequences. In total, 1,856 SSR-containing sequences were identified. Trimeric SSR repeat motifs appeared to be the most abundant type. A subset of 311 primer pairs flanking SSR loci have been used for screening polymorphisms among six barley cultivars, being parents of three mapping populations. As a result, 76 EST-derived SSR-markers were integrated into a barley genetic consensus map. A correlation between polymorphism and the number of repeats was observed for SSRs built of dimeric up to tetrameric units. 3′-ESTs yielded a higher portion of polymorphic SSRs (64%) than 5′-ESTs did. The estimated PIC (polymorphic information content) value was 0.45 ± 0.03. Approximately 80% of the SSR-markers amplified DNA fragments in Hordeum bulbosum, followed by rye, wheat (both about 60%) and rice (40%). A subset of 38 EST-derived SSR-markers comprising 114 alleles were used to investigate genetic diversity among 54 barley cultivars. In accordance with a previous, RFLP-based, study, spring and winter cultivars, as well as two- and six-rowed barleys, formed separate clades upon PCoA analysis. The results show that: (1) with the software tool developed, EST databases can be efficiently exploited for the development of cDNA-SSRs, (2) EST-derived SSRs are significantly less polymorphic than those derived from genomic regions, (3) a considerable portion of the developed SSRs can be transferred to related species, and (4) compared to RFLP-markers, cDNA-SSRs yield similar patterns of genetic diversity.
- Exploiting EST databases for the development and characterization of gene-derived SSR-markers in barley (Hordeum vulgare L.)
Theoretical and Applied Genetics
Volume 106, Issue 3 , pp 411-422
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- Simple sequence repeats (SSRs) Polymorphism information content (PIC) Genetic mapping Diversity analysis
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