Methods

Fungal molecular ecology

Determining the diversity of fungi in an ecosystem, then using this information to understand the links between specific fungi and their particular ecosystem roles and to predict their responses to global changes are especially challenging objectives. This challenge stems from the fact that the identification of fungi and their activities is hampered by their cryptic nature as diffuse, ubiquitous networks of filamentous cells that hide in substrates such as soil.

In this area, my research focuses on finding ways to identify fungi with DNA based methods. I pioneered some of the methods for faster and larger scale fragment analysis prior to the advent of accessible high throughput next generation sequencing:

Avis P.G. and Feldheim K. A. 2005. A method to size DNA fragments from 50 to 800 base pairs on a DNA analyzer. Molecular Ecology Notes 5:969–970

Dickie I.D., Avis P.G., Reich P.B, and McLaughlin D.J. 2003. GERM: Good Enough RFLP Matching Program. Mycorrhiza 13:171-172.

Improved molecular technology made rapid and accurate fungal identification possible and we all used these tools to understand fungal diversity better. But, a major contribution of my work has been to show the limitations of these tools (as well as their promise):

Avis P.G., I.A. Dickie, and G.M. Mueller. 2006. A “dirty” business: Testing the limitations of terminal restriction fragment length polymorphism (TRFLP) analysis of soil fungi. Molecular Ecology 15:873-882.

Bidartondo et al. (P.G. Avis one of 256 authors of the letter to the editor). 2008. Preserving Accuracy in GenBank. Science 319:616.

Avis P.G., Branco S., Tang Y.*, Mueller, G. 2010. Pooled samples bias fungal community descriptions. Molecular Ecology Resources 10:135-141. This latter paper was quickly cited and highlighted as having an “immediate impact on the literature.” (Molecular Ecology Resources (2011) 11, 1–4).

I continue to work on ways to link various molecular approaches. Currently, I am testing the relationship between sequence read abundance generated by MiSeq metabarcoding (an uncertain measure of organismal abundance) with the actual biomass of fungi in the same soil samples. This test uses a novel qPCR test and a specific set of unique primers for fungi known to exist in the samples. At least for some fungi tested, sequence reads may be useful.