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).

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Transcriptome sequencing catches bats’ immune systems napping

A little brown bat (Myotis lucifugans) infected with the white-nose fungus. (Flickr: US Fish and Wildlife Service)

Populations of multiple North American bat species have been more than decimated by white-nose syndrome, a fungal disease that spreads within roosting colonies and becomes deadly during hibernation. A paper just released online early at Molecular Ecology adds support to a hypothesis that the reason for the fungus’s virulence is that hibernation puts bats’ immune systems to sleep — and waking up to fight the fungus costs more than they can afford.

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Just So Stories addendum: How the stickleback keeps getting its stickles

Model organisms have been essential tools for genetics research since the field was formed.  Kelle Freel discussed the characteristics that make for a good model organism in a previous TME post.  Briefly, traits like short generation time, lots of offspring, and easy-to-track developmental stages have been exploited to answer questions about molecular mechanisms behind transmission, cyto-, developmental, population and quantitative genetics and comparative genomics.  A lesser-known model organism is the three spined stickleback, Gasterosteus aculeatus (though it has been mentioned or discussed in several previous TME posts).

Why? Because this fish has the rare honor of being an evolutionary and ecological model organism.  Sticklebacks occur holarctically in marine, estuarine, and freshwater (freshwater) habitats in Europe, Asia, and North America.  During the last retreat of the glaciers in the Pleistocene, this historically marine species began to invade freshwater habitats many times on different timescales in different places. What piqued researchers’ interests about these fish, in the pre-genomic age, was the striking phenotypic variation in various newly-formed freshwater populations and how quickly these divergences happened.  Even though freshwater morphs can differ markedly from each other, even in the same lake, there are certain morphological changes that consistently happen in the evolution from marine/anadromous to freshwater forms, like the loss of body armor.

Fig 1 from Cresko et al 2004. A-C) are freshwater-derived representatives while D) is an anadromous specimen.

This in situ replication lends itself to the study of adaptive radiation and parallel evolution in the wild – a rare treat for evolutionary biologists.  Furthermore, scientists have been able to perform genetic crosses between different morphs and produce viable offspring.  By coupling laboratory crosses between divergent phenotypes with genomic information such as SNP locations across the genome (i.e. QTL mapping) previous studies (reviewed here) managed to pin down regions of the genome likely responsible for a wealth of phenotypic differences observed between environments like body size, feeding traits, and color.

Again, technology lurches forward and in 2010, the first high density SNP-based genome scan (45000 SNPs, 100 fish) of sticklebacks was undertaken.  Applying those observations of intrapopulation diversity and interpopulation divergence patterns to hypotheses of evolution and adaptation the researchers found: 1) the repeated parallel evolution observed in this system relies upon “freshwater haplotypes” that nevertheless persist in oceanic populations at low frequencies, then become frequent in newly minted freshwater populations (aka parallel hard sweeps), as opposed to new mutations cropping up over and over in replicated freshwater populations; 2) both balancing and divergent selection play a role in stickleback evolution; 3) many of the genomic regions previously identified as having a QTL related to divergent phenotypes overlap with regions they found to have high FST values, and that newly-detected regions of the genome also contain patterns of divergence between populations; 4) their results lend more evidence to the biogeographic hypothesis that a large, panmictic oceanic population has repeatedly given rise to divergent freshwater populations.

Fast forward to the July issue of Genetics and the newest installment of RAD-seq/SNP discovery/stickleback research. What novel insights are to be gained? First of all, the authors were able to take advantage of a quite recent colonization event of freshwater habitat via the 1964 Alaska earthquake, which was so powerful that three islands were seismically uplifted, trapping some sticklebacks in newly-formed freshwater ponds.

Secondly, by training a general Hidden Markov model to segment the genome into regions of high and low divergence using genomic data from regions of known high and low FST values from other studies, and defining and classifying haplotypes (~100bp RAD loci, instead of individual SNPs) into different categories and analyzing the pattern between regions of high and low divergence across freshwater and marine populations, they were able to gain insight into mechanisms of evolution absent in other studies.

Fig 2 from Bassham et al 2018. I-XXI are linkage groups of the stickleback genome.  Each concentric circle, numbered outward, is a pairwise comparison of FST’ values.  “OC” indicates a marine population.  The complete lack of high FST’ (red; a measure of haplotype diversity) in ring 1 illustrates the low haplotype divergence between two oceanic populations.  Rings 2-5 are comparisons between a newly-formed freshwater population and 3 pooled marine populations. Note that regions with high FST’ values overlap across comparisons. Rings 4 and 5 represent the youngest of the populations and so have less marine-freshwater divergence.

For example, marine sticklebacks have lower absolute haplotype diversity across divergent regions as opposed to non-divergent regions, which underscores the possibility of strong selection in both regimes, not just freshwater. Furthermore, most haplotypes in majority in freshwater occur in marine fish as well, but are rare. Therefore, greater purifying selection in marine sticklebacks across divergent genomic regions coupled with the fact that haplotypes that are more successful in freshwater habitats persist in marine fish at low frequencies could contribute to the magnitude of the divergence the authors observe as well as the speed with which freshwater morphotypes arise from oceanic stickleback when they colonize a new freshwater habitat. In fact, both population types could be acting as reservoirs of genetic diversity.

Another striking finding was the percentage of the genome deemed to be divergent, nearly 25%, which is a 30-fold increase from previous estimations. However, the authors argue deeper population genomic sampling will detect more changes in allele frequencies across loci as compared to previous methods.

So to reiterate: The remarkable thing about this system is that A) there is a powerful signal of divergent selection, more powerful than previously assumed, even in the presence of gene flow and B) this parallel evolution phenomenon has happened over and over, in the same regions in the genome, in a time period as short as 50 years, though the evolutionary history is much deeper.  Truly, the stickleback is a fascinating and powerful evolutionary and ecological model organism.

References

Bassham, S., Catchen, J., Lescak, E., von Hippel, F. A., Cresko, W. A. (2018) Repeated Selection of Alternatively Adapted Haplotypes Creates Sweeping Genomic Remodeling in Stickleback. GENETICS 209 (3) 921-939

Cresko, W. A., Amores, A., Wilson, C., Murphy, J., Currey, M., Phillips, P., Bell, M. A., Kimmel, C. B., Postlethwait, J. H. (2004) Parallel genetic basis for repeated evolution of armor loss in Alaskan threespine stickleback populations. Proceedings of the National Academy of Sciences, 101 (16) 6050-6055

Hohenlohe PA, Bassham S, Etter PD, Stiffler N, Johnson EA, Cresko WA (2010) Population Genomics of Parallel Adaptation in Threespine Stickleback using Sequenced RAD Tags. PLoS Genet 6(2)

Marques DA, Lucek K, Meier JI, Mwaiko S, Wagner CE, Excoffier L, Seehausen, O. (2016) Genomics of Rapid Incipient Speciation in Sympatric Threespine Stickleback. PLoS Genet 12(2)

Peichel, C.L. and Marques, D. A. Marques (2017) The genetic and molecular architecture of phenotypic diversity in sticklebacks. Philosophical Transactions of the Royal Society B-Biological Sciences 372 (1713)

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Robin Waples awarded the 2018 Molecular Ecology Prize

The 2018 Molecular Ecology prize has been awarded to Robin Waples for his work on conservation biology and management, particularly as the leading expert on approaches for using molecular markers to estimate and understand effective population size in natural populations, including subdivided and continuously distributed populations, and use of time series analyses. His studies of populations with overlapping generations have illuminated the evolution of life-history changes in species that are harvested by humans, and made important contributions to understanding fisheries populations. By adapting population genetic models to real-life situations, including structured populations with gene flow, and developing statistically rigorous analyses, his contributions have significantly advanced both conservation and evolutionary ecology.

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They joy of genome sequencing: when genomics meets natural history

When I have a massive pile of papers that I need to read, I can’t help but look at the ones with interesting natural history first. There’s something exceptionally satisfying about using modern tools to dig deeper into the features that make each species so interesting. Many molecular ecologists, myself included, started a career in biology because of a love of natural history, and I think it’s great when this passion can be captured in modern research. One area where an understanding of an organism’s natural history is perhaps surprisingly important is in whole genome sequencing. While it’s becoming increasingly common to sequence, assemble and annotate genomes (though I’d still argue it’s challenging to do it well), many papers do more than just generate a genomic resource, and relate genomic variants to unique properties of a species. Even better is when these interesting features of a species can be related to other experimental work, or sequencing additional natural populations, to gain deeper insights into organismal biology.

The pitcher plant Cephalotus follicularis (picture H. Zell for Wikipedia)

One example is the paper that describes the genome of the carnivorous pitcher plant Cephalotus (Fukushima et al. 2017). Carnivorous plants have evolved on multiple occasions and use a sophisticated range of traps to attract, catch and digest prey in nutrient-poor environments. The highlight of the paper is that the authors manage to induce the switch between pitcher trap and flat leaf by changing ambient temperature, and then use transcriptomic comparisons to pinpoint differentially expressed genes involved in leaf development. This neat trick reveals a number of candidate genes involved in pitcher formation, including AS2, YAB5, and WOX1 orthologues. They also looked at the digestive proteins in Cephalotus and other taxa representing independent origins of carnivory, and find shared proteins that are repeatedly co-opted in the evolution of this novel phenotype. I came away from reading the paper being even more intrigued about how these amazing plants have evolved, and thinking that there’s so much we can now address with careful genomic and transcriptomic analyses.

And who can forget the passenger pigeon genome papers? The passenger pigeon (Ectopistes migratorius) was at one point perhaps the most abundant bird species on earth, with a census population size in the billions, before its unprecedented extinction in the 19th century due to over-hunting. Two papers, one lead by Chih-Ming Hung published in PNAS, and one by Gemma Murray published in Nature, produced genome data from museum specimens and from related extant pigeon species. Both studies showed surprisingly low genomic diversity indicative of a low effective population size. They differ in what they think caused this low diversity, with Hung et al. (2014) pointing to population fluctuations, and Murray et al. (2017) inferring pervasive natural selection. I haven’t looked at the details to decide which is more likely to be correct, but either way, this is a remarkable example of low diversity in a high abundance species, and a great use of museum sequencing.

Genomes come in all sizes and levels of complexity, and I think there’s something to learn from sequencing them all. From tiny desiccation-tolerant bdelloid rotifers (Nowell et al. 2018) and wonderful water bears (Koutsovoulos et al. 2016), to enigmatic Gnetum (one to look up, plant fans, see Wan et al. 2018) and giant lilly genomes (Kelly et al. 2015), each with their own fascinating biology. The next time whole genome sequencing fatigue sets in as you see the boiler plate title “the genome of XXX reveals YYY”, remember that genome sequencing is a superb tool to make amazing discoveries about the natural world.

References

Fukushima K, Fang X, Alvarez-Ponce D, et al. (2017) Genome of the pitcher plant Cephalotus reveals genetic changes associated with carnivory. Nature ecology & evolution 1, 0059.

Hung C-M, Shaner P-JL, Zink RM, et al. (2014) Drastic population fluctuations explain the rapid extinction of the passenger pigeon. Proceedings of the National Academy of Sciences 111, 10636-10641.

Kelly LJ, Renny‐Byfield S, Pellicer J, et al. (2015) Analysis of the giant genomes of Fritillaria (Liliaceae) indicates that a lack of DNA removal characterizes extreme expansions in genome size. New Phytologist 208, 596-607.

Koutsovoulos G, Kumar S, Laetsch DR, et al. (2016) No evidence for extensive horizontal gene transfer in the genome of the tardigrade Hypsibius dujardini. Proceedings of the National Academy of Sciences, 201600338.

Murray GG, Soares AE, Novak BJ, et al. (2017) Natural selection shaped the rise and fall of passenger pigeon genomic diversity. Science 358, 951-954.

Nowell RW, Almeida P, Wilson CG, et al. (2018) Comparative genomics of bdelloid rotifers: Insights from desiccating and nondesiccating species. PLoS biology 16, e2004830.

Wan T, Liu Z-M, Li L-F, et al. (2018) A genome for gnetophytes and early evolution of seed plants. Nature Plants 4, 82.

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The eyes have it!

Eyes are pretty darn complicated, which makes them cool models for studying complex trait evolution.  Maybe the first time I realized how interesting eyes are when I saw this by the oatmeal about the amazing-ness of the mantis shrimp (are they your new favorite too?), or when I first listened to Colors (or the update) by Radiolab (which also mentions the majestic and clearly magical mantis shrimp).

Graphical Abstract (Picciani et al., 2018).

Eyes exist at different levels of complexity, at their most basic they might have some photoreceptors, pigments, or maybe even lenses or mirrors. As Picciani et al., (2018) from the Oakley lab at UC Santa Barbara, point out, many researchers focus (no pun intended) on the evolution of eyes in bilaterian animals, essentially the animals that have a right and left side (like us). As you might imagine, these visual systems are incredibly intricate, and unraveling their evolution is quite the challenge.

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Metabarcoding for every body, every habitat, every time

The immediate reason why I wanted to write about Boosting DNA metabarcoding for biomonitoring with phylogenetic estimation of operational taxonomic units’ ecological profiles is its usefulness for the scientific community and the effort of the authors to make their study reproducible. All their code and data are online and publicly available. It was even accessible before the paper got accepted!

Secondly, I like observing how the field of metabarcoding eukaryotes is developing. I feel at home in the field of metabarcoding prokaryotes, that is archaea and bacteria. Hence, many of the approaches are familiar. People who study prokaryotes and very small eukaryotes could not just go out and observe their objects interacting in the wild. Because these tiny microorganisms are difficult to see. One very successful way to work around this obstacle was to use genetics and study microbial DNA instead. The 16S rRNA gene has become extremely useful to bacteriologists. This gene is part of the prokaryotic ribosome. It is a very essential gene – most prokaryotic organisms have it. Highly conserved regions of this genes serve as primer binding sites for universal primers and variable regions in between them can be used to reconstruct bacterial phylogenies. 16S amplicons give us a glance at the distribution of bacteria and archaea, the oldest, most diverse and abundant species on this earth (more about this here). Most environments, from remote volcanic hot springs to human genitalia have been characterized using next-generation sequencing of 16S amplicons. While most people refer to it as 16S amplicon studies, it is basically a form of metabarcoding. Eukaryotes have a similar gene, the 18S. Hence, people studying small eukaryotes like fungi and protists have been using 18S amplicon studies for the same purpose.

Only recently, it has become very fashionable to apply metabarcoding techniques to larger multicellular organisms and entire systems. I am excited to see how this scientific community is adopting methods from 16S amplicon microbiologists and bringing them to a new level. The paper by François Keck et al. that came out in Molecular Ecology Resources is a big step towards this direction. I hope that the metabarcoding leaders and whiz kids learn from the success and failures of microbiologists without re-inventing the wheel.

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Support the Molecular Ecologist with all-new evolution and ecology-themed merch!

We don’t often make a big deal about it, but The Molecular Ecologist has long offered merchandise for purchase to help cover our operating expenses, which are chiefly web hosting and small stipends for contributors. The platform we’d used for that was less than ideal, though — and we’ve finally set up shop on Redbubble, which offers a wider range of products at better pricing.

Molecular Ecologist-supporting shirts, images by Redbubble

You can now purchase our “heliboot” logo on a wide array of apparel, mugs, and other accessories, get a poster print of the Molecular Ecology Flowchart, or pick a side in the eternal struggle between genetic drift and natural selection. Prices start at less than $20 for a tee (before shipping and sales tax), and all proceeds benefit the blog — so check out the whole range.

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Population genetic simulation … in Lego

Julien Yann Dutheil, of the Institut des Sciences de l’Évolution de Montpellier, has a long track record of work in population genetics and genomics methods, particularly in the C++ programming language. He recently posted a video to YouTube, though, which suggests he’s trying out a new simulation platform: Lego bricks.

The video shows a robot built using the Lego Mindstorms system, which connects a programmable computing unit to motors and sensors built into Lego bricks. The robot moves along a rack of colored balls representing a population of haploid, clonally reproducing individuals bearing one of two possible color genotypes. The robot randomly selects individuals to remove, simulating their deaths, and draws colored balls from two hoppers to replace dead individuals with ones “cloned” from one of the balls neighboring the empty space in the population. This is a physical model of Patrick Moran’s 1958 description of evolution by drift in a fixed, finite population, and while it’s not very computationally efficient, Dutheil speeds up the video to show how the random birth-death process eventually leads to the loss of diversity, and that this loss happens more quickly when the population is smaller. I’ll definitely be keeping this one in my pocket for my fall evolutionary biology class.

Hat tip to Will Shoemaker, who posted the video to Twitter.

Reference

Moran P. 1958. Random processes in genetics. Mathematical Proceedings of the Cambridge Philosophical Society, 54(1), 60-71. doi: 10.1017/S0305004100033193

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Nominations open for the Harry Smith Prize in Molecular Ecology

Posted on behalf of the Harry Smith Prize Selection Committee.

The editorial board of the journal Molecular Ecology has established a new prize to recognize the best paper published in Molecular Ecology in the previous year by graduate students or early career scholars with no more than five years of postdoctoral or fellowship experience. The prize comes with a cash award of US$1000 and an announcement in the journal. The winner will also be asked to join a junior editorial board for the journal to offer advice on changing research needs and potentially serve as a guest editor. As with the Molecular Ecology Prize, the winner of this annual prize will be selected by an independent award committee.

The prize is named after Professor Harry Smith FRS, who founded the journal and served as both its Chief and Managing Editor during the journal’s critical early years. He continued as the journal’s Managing Editor until 2008, and he went out of his way to encourage early career scholars. In addition to his editorial work, Harry was one of the world’s foremost researchers in photomorphogenesis, where he determined how plants respond to shading, leading to concepts such as “neighbour detection” and “shade avoidance”; which are fundamental to understanding plant responses to crowding and competition. More broadly his research provided an early example of how molecular data could inform ecology, and in 2008 he was awarded the Molecular Ecology Prize that recognized both his scientific and editorial contributions to the field.

Please send your nomination with a short supporting statement (no more than 250 words; longer submissions will not be accepted) directly to Rose Andrew (randre20@une.edu.au) by Tuesday 31 July 2018.

With thanks on behalf of the Harry Smith Prize Selection Committee

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