For flexible eDNA analysis, just capture whatever you want

This is a guest post by Taylor Wilcox and Katherine Zarn, whose article “Capture enrichment of aquatic environmental DNA: A first proof of concept” is online ahead of publication at Molecular Ecology Resources. Wilcox and Zarn wanted to elaborate on the usefulness of capture enrichment as an alternative to metabarcoding beyond what they could cover in that paper’s discussion, and this post is the result. — JBY

Environmental DNA sampling for multi-taxa species detection (i.e., the inference of species presence from genetic material in the environment) has been a hot topic lately. Some of the most exciting recent work has used high-throughput sequence (HTS) to simultaneously screen for the presence of large suites of taxa (Valentini et al. 2016), estimate relative species abundances (Ushio et al. 2018), and even make inferences about population structure (Sigsgaard et al. 2016). Most of these studies have relied on metabarcoding, which despite its obvious utility, has some real limitations. One fundamental limitation emerges from a reliance on shared primers for bulk amplification of mixed templates. This tends to generate skewed relative sequence abundances after enrichment and potential loss of species detection (Deiner et al. 2018, Piñol et al. 2018).

Capture enrichment, which has already been used for similar microbial and ancient DNA applications, represents a potential solution to the primer-bias problem (Jones and Good 2016, Taberlet et al. 2012). We recently tested this capability for detection of 40 aquatic, semi-aquatic, and riparian animals from water samples (Wilcox et al. 2018). To our knowledge, this study represents the first example of using capture enrichment for species detection from water samples (although other, complex templates have been enriched in the same way, e.g., Shokralla et al. 2017). Using mock community samples, we did in fact find that capture enrichment preserved initial, relative template abundances (Figure 3 in the paper). The sensitivity of our protocols was less than we were hoping for to use in eDNA analyses (sensitivity dropped off at < 0.1 ng genomic DNA in mock community trials), but we’re optimistic that this could easily be optimized given the success of capture for ancient DNA (e.g., Green et al. 2010)

Capture enrichment allows more flexible enrichment of targets for eDNA analysis than does metabarcoding. Shown is a hypothetical plot of interspecific divergence across the mitochondrial genome (based on a sliding window analysis of the fish genera Oncorhynchus and Micropterus). Probes can be designed to target either highly conserved regions (A) or highly variable regions (C) because no flanking primer sites are needed, as is the case for metabarcoding (B).

More importantly though, capture enrichment tool isn’t just a work-around for pesky primer-bias issues: It’s the perfect fit for targeting diverse marker sets across taxa to build up “multi-faceted” (Swift et al. 2018) datasets. Capture enrichment is exceedingly flexible because the targets within a single capture are not limited to “barcoding” loci bounded by conserved primer annealing sites or constrained to a single taxonomic group as they are in metabarcoding approaches. Thus, there is a really exciting potential to build boutique sets of capture probes to meet specific research needs, from broad biodiversity assessments to finer-scale multi-species presence / absence assays, or any combination in between (Figure 1). A single capture enrichment could target loci useful for a suite of applications. For example:

  • Detection of aquatic vertebrates as well as their parasites and pathogens (including fungal, bacterial, and viral)
  • Biomonitoring with markers for several key indicator species plus a suite of ultra-conserved regions to characterize previously undescribed diversity
  • Determining species composition and population structure simultaneously

Thus, although eDNA capture enrichment involves a high initial investment in probe development, it allows highly flexible analyses across taxa, but requires less sequencing effort than shotgun sequencing approaches (Table 1). There are a few different ways to generate probes for capture. For low-throughput of a few dozen loci and taxa, you might synthesize your own DNA-based probes as we did here. If you need more, you can buy custom capture kits with tens of thousands of probes (e.g., myBaits or SureSelect). For a more complete guide on capture experiment design, we suggest the recent review by Jones and Good (2016). Whatever the specific platform, we look forward to seeing more studies refine capture enrichment for eDNA analysis because we believe that it will open the door for a new level of flexibility in data acquisition and the types of ecological questions that can be explored.

Some trade-offs associated with different types of eDNA analysis tools. Taxon-specific qPCR, metabarcoding, capture enrichment, and shotgun sequencing vary in terms of initial development cost, per sample cost, sensitivity (ability to detect rare templates), number of taxa that can be assessed in parallel, and question flexibility. (Some general characteristics summarized here could vary substantially depending on the specific protocol. For example, capture enrichment sensitivity might be substantially improved, as evidence of good success in aDNA systems, and shotgun sequencing sensitivity is only listed as ‘low’ only because sequencing effort and the availability of reference libraries are typically limiting.)

References

Deiner, K., H. M. Bik, E. Mächler, M. Seymour, A. Lacoursière-Roussel, F. Altermatt, S. Creer, et al. 2017. Environmental DNA metabarcoding: Transforming how we survey animal and plant communities. Molecular Ecology 26:5872–5895. doi: 10.1111/mec.14350

Green, R. E., J. Krause, A. W. Briggs, T. Maricic, U. Stenzel, M. Kircher, N. Patterson, et al. 2010. A Draft Sequence of the Neandertal Genome. Science 328:710–722. doi: 10.1126/science.1188021

Jones, M. R., and J. M. Good. 2015. Targeted capture in evolutionary and ecological genomics. Molecular Ecology 25:185–202. doi: 10.1111/mec.13304

Piñol, J., M. A. Senar, and W. O. C. Symondson. 2018. The choice of universal primers and the characteristics of the species mixture determine when DNA metabarcoding can be quantitative. Molecular Ecology. doi: 10.1111/mec.14776

Ushio M, Murakami H, Masuda R, Sado T, Miya M, Sakurai S, Yamanaka H, Minamoto T, Kondoh M 2018. Quantitative monitoring of multispecies fish environmental DNA using high-throughput sequencing. Metabarcoding and Metagenomics 2: e23297. doi: 10.3897/mbmg.2.23297

Shokralla, S., J. Gibson, I. King, D. Baird, D. Janzen, W. Hallwachs, and M. Hajibabaei. 2016. Environmental DNA Barcode Sequence Capture: Targeted, PCR-free Sequence Capture for Biodiversity Analysis from Bulk Environmental Samples. bioRxiv doi: 10.1101/087437

Sigsgaard, E. E., I. B. Nielsen, S. S. Bach, E. D. Lorenzen, D. P. Robinson, S. W. Knudsen, M. W. Pedersen, et al. 2016. Population characteristics of a large whale shark aggregation inferred from seawater environmental DNA. Nature Ecology & Evolution 1:0004. doi: 10.1038/s41559-016-0004

Swift, J. F., R. F. Lance, X. Guan, E. R. Britzke, D. L. Lindsay, and C. E. Edwards. 2018. Multifaceted DNA metabarcoding: Validation of a noninvasive, next-generation approach to studying bat populations. Evolutionary Applications 11:1120–1138. doi: 10.1111/eva.12644

Taberlet, P., E. Coissac, F. Pompanon, C. Brochmann, and E. Willerslev. 2012. Towards next-generation biodiversity assessment using DNA metabarcoding. Molecular Ecology 21:2045–2050. doi: 10.1111/j.1365-294X.2012.05470.x

Valentini, A., P. Taberlet, C. Miaud, R. Civade, J. Herder, P. F. Thomsen, E. Bellemain, et al. 2016. Next-generation monitoring of aquatic biodiversity using environmental DNA metabarcoding. Molecular Ecology 25:929–942. doi: 10.1111/mec.13428

Wilcox, T. M., K. E. Zarn, M. P. Piggott, M. K. Young, K. S. McKelvey, and M. K. Schwartz. 2018. Capture enrichment of aquatic environmental DNA: A first proof of concept. Molecular Ecology Resources. doi: 10.1111/1755-0998.12928

About Jeremy Yoder

Jeremy B. Yoder is an Associate Professor of Biology at California State University Northridge, studying the evolution and coevolution of interacting species, especially mutualists. He is a collaborator with the Joshua Tree Genome Project and the Queer in STEM study of LGBTQ experiences in scientific careers. He has written for the website of Scientific American, the LA Review of Books, the Chronicle of Higher Education, The Awl, and Slate.
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