Predicting polymorphic EST-SSRs in silico.
作者： Chris Duran , Richa Singhania , Harsh Raman , Jacqueline Batley , David Edwards
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摘要: The public availability of large quantities gene sequence data provides a valuable resource the mining Simple Sequence Repeat (SSR) molecular genetic markers for analysis. These are inexpensive, require minimal labour to produce and can frequently be associated with functionally annotated genes. This study presents characterization barley EST-SSRs identification putative polymorphic SSRs from EST data. Polymorphic distinguished monomorphic by representation varying motif lengths within an alignment reads. Two measures confidence calculated, redundancy polymorphism co-segregation accessions. utility this method is demonstrated through discovery 597 candidate SSRs, total 452 642 consensus expressed sequences. PCR amplification primers were designed identified SSRs. Ten primer pairs validated in transferability across species. Analysis polymorphisms relation SSR motif, length, position annotation discussed.
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