Microsatellite loci are increasingly used as markers in the human, animal and plant genomes. Being highly mutable, microsatellite regions are able to differentiate between related taxa, even at the level of individual isolates in a single species. Studies on mushroom population structure, gene flow and dispersal between natural and cultivated species have become central in breeding programmes and the knowledge of new polymorphic, codominant markers will be a promising avenue to exploit wild genetic resources. The molecular phylogeny in 50 different commercial cultivated strains of Pleurotus eryngii using PCR amplification with URP primers and mitochondrial microsatellite primer was studed. The sizes of the polymorphic fragments obtained were in the range of 200 to 2000 bp. RAPD analysis techniques were able to detect genetic variation among the tested strains. With these isolated PCR amplification with URP primers we intend to analyse the population structure of the P. eryngii species complex and investigate the structure of the basidiomycete genome which deserves. A few single-locus microsatellite markers have been isolated in Pleurotus eryngii and Pleurotus ferulae. This technique is useful in those species where microsatellite loci are rare in the mitochondria.

The mating-type genes control formation of the dikaryon from two haploid strains. These genes are now used in mating-type-assisted breeding programs for economically important mushrooms, especially the oyster mushroom, Pleurotus ostreatus, aiming at high-yield and high-quality standard mushroom production. However, it improves the breeding program when the breeder is able to quickly identify compatible strains in a given set of progeny. The two mating factors with their mating-type loci are used as markers for breeding and have been incorporated in a chromosome mapping investigation. The linkage maps include not only genetic markers such as the mating types that can be cored, but also molecular markers such as PCR-assisted approaches, e.g. RAPD analyses, or RFLP markers. Once mating-type genes within progeny may be more easily identified by the use of PCR-directed cloning of partial mating-type genes. We analyzed homeodomain (HD1 and HD2) and pheromone receptor(rcb1, 2 and 3) genes as molecular markers for breeding using mating type A and B of Pleurotus eryngii and Pleurotus ferulae by direct PCR.

Discovery, identification, and informatics of low molecular weight peptide are extensively rising in the field of proteomics research. In this study, we analyzed protein profiles to discover peptide based biomarker for twelve different soybean seeds with three different agronomic types using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS). For optimization of SELDI-TOF MS in soybean seed proteome analysis, four different extraction buffers were tested with urea solubilization buffer, thiourea/urea solubilization buffer, phenol extraction buffer, and modified trichloroacetic acid (TCA)/acetone precipitation/urea solubilization extraction buffer. Two different type of ProteinChip arrays, cation exchange (CM10) and anion exchange (Q10), applied to profile peptides. Among the four different extraction buffers, phenol extraction was selected to protein extraction methodology. Numbers of detected peak cluster in twelve soybean seeds were 125 at CM10 and 90 at Q10 array in the mass range from 2 to 40 kDa. Among them, 82 peak clusters at CM10 and 33 peak clusters at Q10 array showed significantly different peak clusters at p<0.00004 (CM10) and p<0.00005 (Q10) among twelve different soybean cultivars. Moreover, 29 peak clusters at CM10 and 17 peak clusters at Q10 array were detected in all cultivars as an ‘universally existed peptide’. In comparison with three different agronomic types, total of 55 peak clusters (CM10) and 23 peak clusters (Q10) were significantly different peak clusters at p<0.00004 and p<0.0001, respectively. In these probability levels, soybean seeds were well discriminated into different cultivar and different type with each other. Also we could find several specific peptide biomarkers for agronomic type.