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Predicting polymorphic EST ‐ SSR s in silico
Author(s) -
Duran Chris,
Singhania Richa,
Raman Harsh,
Batley Jacqueline,
Edwards David
Publication year - 2013
Publication title -
molecular ecology resources
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.96
H-Index - 136
eISSN - 1755-0998
pISSN - 1755-098X
DOI - 10.1111/1755-0998.12078
Subject(s) - biology , in silico , genetics , microsatellite , computational biology , transferability , primer (cosmetics) , expressed sequence tag , gene , genome , allele , statistics , chemistry , mathematics , organic chemistry , logit
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 ‐ SSR s and the identification of putative polymorphic SSR s from EST data. Polymorphic SSR s are distinguished from monomorphic SSR s 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 SSR s, from a total of 452 642 consensus expressed sequences. PCR amplification primers were designed for the identified SSR s. 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.