Incorporating molecular data in fungal systematics: a guide for aspiring researchers

Abstract

The last twenty years have witnessed molecular data emerge as a primary research instrument in most branches of mycology. Fungal systematics, taxonomy, and ecology have all seen tremendous progress and have undergone rapid, far-reaching changes as disciplines in the wake of continual improvement in DNA sequencing technology. A taxonomic study that draws from molecular data involves a long series of steps, ranging from taxon sampling through the various laboratory procedures and data analysis to the publication process. All steps are important and influence the results and the way they are perceived by the scientific community. The present paper provides a reflective overview of all major steps in such a project with the purpose to assist research students about to begin their first study using DNA-based methods. We also take the opportunity to discuss the role of taxonomy in biology and the life sciences in general in the light of molecular data. While the best way to learn molecular methods is to work side by side with someone experienced, we hope that the present paper will serve to lower the learning threshold for the reader.

Insights into the genus Diaporthe: phylogenetic species delimitation in the D. eres species complex

“…In the last two decades much progress has been made in the ability to define fungal species through the use of molecular data (Hibbett and Taylor 2013;Hyde et al 2013). Circumscribing species within cryptic species complexes that have complicated life histories is essential for determining patterns of speciation and potential hyperdiversity within a genus (Bickford et al 2007;Silva et al 2012a;Fekete et al 2012;O'Donnell et al 2013).…”

Read quality-based trimming of the distal ends of public fungal DNA sequences is nowhere near satisfactory

“…The chromatograms, indicating the relative signal strength for each of the four purines/ pyrimidines C, T, A, and G for each position in the sequence, are a key resource in this pursuit. Brief guidelines for how chromatograms should be processed are available in Hyde et al (2013) and through various textbooks, online tutorials, and troubleshooting guides (e.g., Kearse et al 2012, Green andSambrook 2012). Trying to squeeze out extra information from chromatograms by progressing too far in the 5' or 3' ends is not a good idea, and researchers should make it a habit to crop sequence ends aggressively.…”

“…Finally, sequence similarity searches using BLAST may be used to get an idea of the technical quality of newly generated sequences (cf. Hyde et al 2013), including at least cursory inspection of whether the distal ends of sequences are trimmed well enough. BLAST is, however, a somewhat blunt tool when it comes to assessing the read quality of sequence ends and we recommend it as a complement to, rather than as a replacement of, manual inspection of chromatograms.…”

“…Similarly, sequences found to lack more than 50 bases of the 5' end of the ITS1 region, or more than 50 bases of the 3' end of the ITS2 region, were discarded. Alignments were adjusted manually, as needed, following Hyde et al (2013). Sequences found to be chimeric, taxonomically misidentified, or the subject of other severe technical complications were removed from the alignments prior to statistical analysis.…”

“…In addition to the lack of reference sequences for more than 99% of the estimated number of extant species of fungi, technical complications such as chimera formation and low read quality may introduce noise and bias to such efforts (Hyde et al 2013, Kõljalg et al 2013. To some extent, software tools are available to exercise some degree of control over these complications (e.g., Edgar et al 2011, Bengtsson-Palme et al 2013.…”