Genome-wide identification of microsatellites in white clover (<it>Trifolium repens </it>L.) using FIASCO and phpSSRMiner

Abstract

Abstract Background Allotetraploid white clover (Trifolium repens L.) is an important forage legume widely cultivated in most temperate regions. Only a small number of microsatellite markers are publicly available and can be utilized in white clover breeding programs. The objectives of this study were to develop an integrated approach for microsatellite development and to evaluate the approach for the development of new SSR markers for white clover. Results Genomic libraries containing simple sequence repeat (SSR) sequences were constructed using a modified Fast Isolation by AFLP of Sequences COntaining repeats (FIASCO) procedure and phpSSRMiner was used to develop the microsatellite markers. SSR motifs were isolated using two biotin-labeled probes, (CA)17 and (ATG)12. The sequences of 6,816 clones were assembled into 1,698 contigs, 32% of which represented novel sequences based on BLASTN searches. Approximately 32%, 28%, and 16% of these SSRs contained hexa-, tri-, and di-nucleotide repeats, respectively. The most frequent motifs were the CA and ATG complementary repeats and the associated compound sequences. Primer pairs were designed for 859 SSR loci based on sequences from these genomic libraries and from GenBank white clover nucleotide sequences. A total of 191 SSR primers developed from the two libraries were tested for polymorphism in individual clones from the parental genotypes GA43 ('Durana'), 'SRVR' and six F1 progeny from a mapping population. Ninety two percent produced amplicons and 66% of these were polymorphic. Conclusion The combined approach of identifying SSR-enriched fragments by FIASCO coupled with the primer design and in silico amplification using phpSSRMiner represents an efficient and low cost pipeline for the large-scale development of microsatellite markers in plants. The approach described here could be readily adapted and utilized in other non-related species with none or limited genomic resources.