fundamentals of eDNA

Collection & extraction methods were the topic of the week. Our class came to the conclusion that research questions across the Maine-eDNA program are too different for effective standardisation in most cases. The best techniques to use can differ greatly based on a host of factors, such as environmental parameters (e.g. salinity), sample type (e.g. water vs sediment), taxa of interest (e.g. inhibitor-rich taxa sich as plants, or slimy organisms such as molluscs), and the nature of the study (e.g. detection of specific taxa vs community-level studies). Other classmates brought up the point that index sites sampling and other standardised protocols are not useful for their own research questions, as steps such as pre-filtering can eliminate taxa of interest from the sample, and that may apply to some of the meiofauna and microfauna I am interested in as well.

Standardisation might only be feasible when it comes to looking at similar taxa across similar environmental conditions, but standardisation with the methods of past studies may be critical when it comes to making use of long-term datasets, in order to ensure consistency. In addition, even if methods improve over time, provided the difference in efficiency is marginal, the statistical wizadry needed to ensure validity between the two approaches is unlikely to be worth the effort (e.g. randomisation and cross-validation). Under most circumstances, I feel it would be better to just use what works well enough, save for some specific research questions where detection efficiency is the main factor (e.g. detection of specific rare species)

The challenge with our projects, then, is to determine what parts of our protocols are critical, and what we can be more flexible with. Based on Rene’s pilot studies, it would seem that sample collection methods have a greater impact on obtained SVs compared to the extraction kits used, but it remains to be seen if this observation holds true in a wider context.

I was always aware of how metabarcoding presents a skewed picture of true alpha biodiversity, but I hadn’t thought of it specifically as being good for measuring beta diversity, even though it seems rather evident in hindsight. Erin brought up a great point about being especially careful about primer design and sequencing depth when it comes to metabarcoding, as these factors are pretty much what will make-or-break a potentially interesting study. For example, if one will be working across a large spectrum of taxa, as my future project on microbes and meiofauna will be, primer design is likely to be the most important consideration. For well-understood taxa such as fish, with well-established primers, sampling methods, followed by extraction methods may be more important.

Another salient point was brought up about proper documentation of metadata on online databases. In my own taxonomic work thus far, I am admittedly ashamed to admit that my metadata on the collection details and processing of my specimens is woefully inadequate! A lesson learned, I guess….

Finally, it was interesting to read about the early days of eDNA, and while we nowadays scoff at aspects of their methodologies, such the use of such small volumes of water, it does remind me to be a little bit more grateful about how far eDNA has come since then, when we can take things like filters for granted, and even complain about their performanc. Reading some of the older eDNA studies has also made me a little wistful. I dismissed my undergraduate eDNA work as unpublishable, but if I had been a bit more thorough with my statistics, it would still have made for a reasonable story by the standards of its era.