An assessment of the efficiency of fungal DNA extraction methods for maximizing the detection of medically important fungi using PCR.

To date, no single reported DNA extraction method is suitable for the efficient extraction of DNA from all fungal species. The efficiency of extraction is of particular importance in PCR-based medical diagnostic applications where the quantity of fungus in a tissue biopsy may be limited. We subjected 16 medically relevant fungi to physical, chemical and enzymatic cell wall disruption methods which constitutes the first step in extracting DNA. Examination by light microscopy showed that grinding with mortar and pestle was the most efficient means of disrupting the rigid fungal cell walls of hyphae and conidia. We then trialled several published DNA isolation protocols to ascertain the most efficient method of extraction. Optimal extraction was achieved by incorporating a lyticase and proteinase K enzymatic digestion step and adapting a DNA extraction procedure from a commercial kit (MO BIO) to generate high yields of high quality DNA from all 16 species. DNA quality was confirmed by the successful PCR amplification of the conserved region of the fungal 18S small-subunit rRNA multicopy gene.

Genetic diversity in Australian wheat varieties and breeding material based on RFLP data.

Restriction fragment length polymorphisms (RFLPs) have been used to characterise the genetic diversity of wheat (Triticum aestivum) germplasm. One hundred and twenty-four accessions comprising all major Australian wheat varieties and lines important for breeding purposes were assayed for RFLPs with clones of known genetic location and selected to give uniform genome coverage. The objectives of this study were to determine RFLP-based genetic similarity between accessions and to derive associations between agronomically significant traits and RFLP phenotypes. Ninety-eight probes screened against genomic DNA digested with five restriction endonucleases detected a total of 1968 polymorphic fragments. Genetic similarity (GS) calculated from the RFLP data ranged from 0.004 to 0.409 between accessions, with a mean of 0.18. Cluster analysis based on GS estimates produced four groupings that were generally consistent with available pedigree information. Comparisons of the RFLP phenotypes of accessions containing disease resistance genes present on introgressed alien segments enabled the identification of specific alleles characteristic of these regions. Associations were derived for a range of stem-rust, leaf-rust and yellow-rust resistance genes. These results suggest that RFLP analysis can be used for the characterisation and grouping of elite breeding material of wheat and RFLP profiling can identify chromosome segments associated with agronomic traits.