Snipping polymorphisms from large EST collections in barley (Hordeum vulgare L.)

Area of Science:

• Plant genomics
• Bioinformatics
• Molecular biology

Background:

• Public expressed sequence tag (EST) databases are vast, heterogeneous resources containing valuable sequence data from diverse plant species and varieties.
• High redundancy in EST collections offers potential for rapid identification of candidate sequence polymorphisms.
• Barley (Hordeum vulgare L.) genetic research can benefit from efficient methods for discovering single nucleotide polymorphisms (SNPs).

Purpose of the Study:

• To develop and present a strategy for the rapid identification of candidate SNPs in barley using publicly available EST databases.
• To assess the efficiency and cost-effectiveness of this strategy for SNP discovery and marker development.

Main Methods:

• Analysis of 271,630 barley EST sequences from 23 varieties to generate tentative consensus sequences (unigenes).
• Application of a novel SNP detection algorithm (SNiPpER) to identify candidate inter-varietal SNPs within unigene clusters.
• Validation of candidate SNPs through direct sequencing and mapping to the barley genome.

Main Results:

• Generated 56,302 tentative consensus sequences from 271,630 ESTs.
• Identified 3069 candidate inter-varietal SNPs using the SNiPpER algorithm on 8171 unigene clusters.
• Validated 86% (54 out of 63) of selected candidate SNPs via direct sequencing.
• Demonstrated significantly higher polymorphism information content (PIC) and nucleotide diversity (pi) for SNiPpER-identified SNPs compared to random sequencing.

Conclusions:

• The developed strategy enables rapid and cost-efficient identification of candidate SNPs in barley from public EST databases.
• The SNiPpER algorithm proves effective for detecting high-quality SNPs with significant genetic variation.
• This approach facilitates the development of EST-based SNP markers for barley genetic studies and breeding programs.