Mining single-nucleotide polymorphisms from hexaploid wheat ESTs

Abstract

Single-nucleotide polymorphisms (SNPs) represent a new form of functional marker, particularly when they are derived from expressed sequence tags (ESTs). A bioinformatics strategy was developed to discover SNPs within a large wheat EST database and to demonstrate the utility of SNPs in genetic mapping and genetic diversity applications. A collection of >90 000 wheat ESTs was assembled into contiguous sequences (contigs), and 45 random contigs were then visually inspected to identify primer pairs capable of amplifying specific alleles. We estimate that homoeologue sequence variants occurred 1 in 24 bp and the frequency of SNPs between wheat genotypes was 1 SNP/540 bp (θ = 0.0069). Furthermore, we estimate that one diagnostic SNP test can be developed from every contig with 10-60 EST members. Thus, EST databases are an abundant source of SNP markers. Polymorphism information content for SNPs ranged from 0.04 to 0.50 and ESTs could be mapped into a framework of microsatellite markers using segregating populations. The results showed that SNPs in wheat can be discovered in ESTs, validated, and be applied to conventional genetic studies.