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Available scientific literature reports very few microsatellite markers   derived from tetraploid genomes using de novo transcriptome sequencing,   mostly because their gain usually represents a major computational challenge   due to complicated combinatorics during assembly of sequence reads. Here we   present a novel approach for mining polymorphic microsatellite loci from   transcriptome data in a tetraploid species with no reference genome   available. Pairs of 114 bp long de novo sequenced transcriptome reads of   Centaurium erythraea were merged into short contigs of 170-200 bp each. High   accuracy assembly of the pairs of reads was accomplished by a minimum of 14   bp overlap. Sequential bioinformatics operations involved fully free and   open-source software and were performed using an average personal computer.   Out of the 13 150 candidate contigs harboring SSR motifs obtained in a final   output, we randomly chose 16 putative markers for which we designed primers.   We tested the effectiveness of the established bioinformatics approach by   amplifying them in eight different taxa within the genus Centaurium having   various ploidy levels (diploids, tetraploids and hexaploids). Nine markers   displayed polymorphism and/or transferability among studied taxa. They   provided 54 alleles in total, ranging from 2 to 14 alleles per locus. The   highest number of alleles was observed in C. erythraea, C. littorale and a   hybridogenic taxon C. pannonicum. The developed markers are qualified to be   used in genetic population studies on declining natural populations of   Centaurium species, thus providing valuable information to evolutionary and   conservation biologists. The developed cost-effective methodology provides   abundant de novo assembled short contigs and holds great promise to mine   numerous additional EST-SSR-containing markers for possible use in genetics   population studies of tetraploid taxa within the genus Centaurium.

Pursuit for est microsatellites in a tetraploid model from de novo transcriptome sequencing