Predicting polymorphic EST‐SSRs in silico |
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| Authors: | Chris Duran Richa Singhania Harsh Raman Jacqueline Batley David Edwards |
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| Institution: | 1. Melbourne eResearch Group, University of Melbourne, , Parkville, Vic, 3010 Australia;2. Centre for Integrative Legume Research, School of Agriculture and Food Science, University of Queensland, , Brisbane, QLD, 4072 Australia;3. School of Agriculture and Food Sciences, University of Queensland, , St Lucia, QLD, 4072 Australia;4. EH Graham Centre for Agricultural Innovation (an alliance between NSW Department of Primary Industries and Charles Sturt University), , Wagga Wagga, NSW, 2650 Australia;5. Australian Centre for Plant Functional Genomics, University of Queensland, , St Lucia, QLD, 4072 Australia |
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| Abstract: | The public availability of large quantities of gene sequence data provides a valuable resource of the mining of Simple Sequence Repeat (SSR) molecular genetic markers for genetic analysis. These markers are inexpensive, require minimal labour to produce and can frequently be associated with functionally annotated genes. This study presents the characterization of barley EST‐SSRs and the identification of putative polymorphic SSRs from EST data. Polymorphic SSRs are distinguished from monomorphic SSRs by the representation of varying motif lengths within an alignment of sequence reads. Two measures of confidence are calculated, redundancy of a polymorphism and co‐segregation with accessions. The utility of this method is demonstrated through the discovery of 597 candidate polymorphic SSRs, from a total of 452 642 consensus expressed sequences. PCR amplification primers were designed for the identified SSRs. Ten primer pairs were validated for polymorphism in barley and for transferability across species. Analysis of the polymorphisms in relation to SSR motif, length, position and annotation is discussed. |
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| Keywords: | Simple sequence repeats microsatellites polymorphic markers barley |
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