Identifying Novel Polymorphic Microsatellites from Cultivated Flax (Linum usitatissimum L.) Following Data Mining

One of the major concerns in genetic characterization and breeding of cultivated flax is the lack of informative microsatellite markers (SSRs). In this regard, the development of SSRs using molecular methods might be time-consuming, laborious, and expensive. On the other hand, using bioinformatics to mine sequences in public databases enables a cost-effective discovery of SSRs. A total of 3,242 Linum usitatissimum genomic sequences were surveyed for the identification of SSRs. Among them, 118 non-redundant sequences containing repeats were selected for designing primers. The most abundant motifs were tri- (72.4%) and dinudeotide (16.6%), within which AGG/CCT and AG/CT were predominant. Primers were tested for polymorphism in 60 L. usitatissimum cultivars/accessions including 57 linseed and three fiber flax. Eighty-eight pairs gave amplifications within the expected size range while 60 pairs were found to be polymorphic. The mean number of alleles amplified per primer was 3.0 (range, 2–8; 180 total alleles). The mean polymorphism information content (PIC) value was 0.39 (range, 0.06–0.87), and the highest average PIC was observed in dinucleotide SSRs (0.41). The SSR data mining presented here demonstrates the usefulness of in silico development of microsatellites. These novel genomic SSR markers could be used in genetic diversity studies, the development of genetic linkage maps, quantitative trait loci mapping, association mapping, and marker-assisted selection.