Highlights from the Standalone Society of Systematic Biologists meeting – part 1

The 2017 standalone meeting of the Society of Systematic Biologists included expert-led debates on major issues in molecular systematics. Didn’t make it to Baton Rouge? Don’t worry – Bryan McLean and I report on the main points below, and highlight some of our favorite lightening talks of the day. We will post part two of our SSB summary next week.

Debate 1: What do we really know about gene tree variation? Led by Scott Edwards and Gavin Naylor, moderated by Jeremy Brown

In the early years of molecular systematics, there was a lot of focus on how to estimate a gene tree accurately from one or a few loci. After Maddison 1997, we started to expect (and often found) significant variation among gene trees. Now, our focus has shifted to understanding the sources of this variation and accommodating gene tree independence in our phylogenetic reconstructions.

In the phylogenomic era, we may be tempted to think that because we can collect so many data, we can solve all difficult phylogenetic problems. However, it is crucial to keep working to improve theory and methods. For example, while ILS is often accommodated by current models, other sources of gene tree variation (selection, horizontal transfer) are still harder to distinguish. The phylogenetic scale of the question (shallow vs. deep) should also inform models, as the relative importance of each process is somewhat scale-dependent.

Methods that identify gene tree outliers can be help identify patterns that are not consistent with model expectations. Posterior predictive simulations can also identify model inadequacies. Both of these approaches can be used to help us understand underlying biological processes. Still, another major need is in understanding how filtering different classes of outlier gene trees from analyses could bias results.

Put simply, there is a real need in molecular phylogenetics for ongoing theoretical and simulation work, as well as new ways to conceptualize phylogeny. Can we really keep considering phylogenies as bifurcating trees given the complexities of gene flow, horizontal gene transfer, hybridization, etc?

Debate 2: Species delimitation. Or is it? Led by Frank Burbrink and Robb Brumfield, moderated by Bryan Carstens

Species delimitation is still a developing field in molecular systematics. (This assumes, of course, that “species” are real things). Broad goals of delimitation are to identify groups, find the relationships among them, and estimate gene flow, migration, and divergence times. On our species delimitation wish list- a method/program that incorporates this multi-step process into one.

Would we feel more confident about delimitation if we thought about it as population delimitation? By a show of hands, many people said no! Delimitation of groups at lower levels is also a challenge.

Delimitation based on genetic signatures alone can get murky. Want less subjectivity? More integrative methods of delimitation such as iBPP (see our thoughts here and here) are attractive because they can incorporate rely on information other than just genes. Just beware of circularity when including other traits (e.g., those that have been previously defined by experts as taxonomically important).

The importance of species delimitation reverberates to higher levels as well. For example, does inaccurate species delimitation affect our other questions of trait evolution, for example? Must we put taxa into “species” bins? Or is a “tip” a “tip”? Luke Harmon thinks that the impacts of these issues on comparative studies are largely unknown.

Regardless of your view on species delimitation, there is no doubt that accurate delimitation is fundamental for conservation. Species are the unit recognized under the Endangered Species Act. Does that mean we should err on the side of delimiting more species? Or would this dilute conservation efforts?

Lightening Talks

Gustavo Bravo: Higher plumage brightness is associated with exposed habitats in dry regions in antbirds.

Laurel Yohe: Molecular evolution of the Trpc2 gene can predict olfactory morphology in bats.

Paul Hime: A single species hypothesis is rejected for the Hellbender, whose spatial patterns of gene flow and genetic diversity are non-random.

Laura Lagomarsino: Neotropical bellflowers show repeated evolution of bat and hummingbird pollination, but floral traits show differences in evolutionary mode.

Clare Brown: Long-distance migration has evolved multiple times in swallows (Hirundinidae) from an intermediate migrating ancestor.

From the Twittersphere

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Handling microbial contamination in NGS data

Until recently, I had given little thought to the potential for unwanted microbial contamination in high throughput sequence data. I suspect that if you’re a molecular ecologist who doesn’t primarily study microbes or work with ancient DNA, you’re in a similar boat: when I did a quick search of the documentation of three popular bioinformatics pipelines for handing the RADseq and UCE data most of us deal with (Pyrad, Phyluce, and Stacks) I found no hits for specific features dealing with exogenous microbial DNA.

Is it in your data? Photo credit Rocky Mountain Laboratories, NIAID, NIH

I was therefore surprised to learn — during a recent project involving DNA from both fresh tissues and historical museum specimens — that almost all my samples of both origins contained reads from Escherichia coli and other bacteria. Of course, it’s easy to see how this can occur, even with stringent wet-lab protocols. After all, the tissue we extract DNA from is rarely sterilized, samples may contain symbionts, errors are made, etc. Which may not be a big deal: while the potential for contamination to bias downstream analyses is well documented, it’s not clear how significant trace quantities of E. coli or other microbes are for the majority of studies of plants or vertebrates. But if you are concerned for one reason or other, are working with ancient DNA, or just want to follow best practices, what tools are available to you? Here’s what my collaborator Zach Hanna and I dug up:

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Friday action item: Put your Members of Congress on speed-dial

… but also, you know, know how to use the phone. (Image from Ghostbusters, 2016)

While the current administration is in office we’re posting small, concrete things you can do to help make things better, every Friday. Got a suggestion for an Action Item? E-mail us!

The new Congress is just getting started, and its to-do list is already full of worrying items — from repealing the Affordable Care Act with an extra dose of cutting off women’s healthcare access to reviving an 1876 rule that lets Congress eliminate the pay for individual civil servants — which includes a lot of government scientists. The outlook is grim, but now’s a good time to take advantage of one nice thing about members of Congress — they all have offices you can call.

Telephoning is simultaneously a big effort — you have to talk to a real person in real time! — and often under-estimated. But consider that a just dozen or so calls on the same subject to congressional representative’s local office are a lot, and you start to see why it’s worth the awkwardness. It is certainly more effective than Twitter or Facebook posting (though those can help organize people to take more effective action), and it’s more direct than a letter, even a non-form letter. In fact, phoning Congress has already won a small victory for better governance. The House of Representatives was set to dramatically reduce the independence and power of the Office of Congressional Ethics, which investigates allegations of corruption against members of the House — but has backed down (for now, at least) in the face of “a blizzard of angry constituent calls”.

So go find the contact information for your Representative and both Senators, and prepare now to use it when you have a good reason, which will probably be soon. Here’s some tips informed by advice from former Congressional staffers:

  • Call a local office, if it’s at all possible — not the District of Columbia.
  • Call from a local number, and make sure to mention where you live. Calls from constituents get noticed; calls from people who won’t vote for the member’s reelection, not so much.
  • Take time to jot down a script. It doesn’t have to be long. It helps.
  • Pick one thing to ask for, preferably something nice and concrete, like a bill to vote for or against.
  • Round up some friends to coordinate calls with. Maybe even find a bigger local group to join.
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Unbalanced population sampling and STRUCTURE

The utility and intuition offered by the program STRUCTURE, and more generally, the ‘admixture’ model of Pritchard et al. (2000) are unquestioned – with tens of thousands of citations, it retains its lead among the most popular population genetics software. However, much like any method, STRUCTURE comes with its caveats, which recent works have pointed to using simulations and meta-analyses (see here, and also the studies of Gilbert et al. 2012, Evanno et al. 2005, Puechmaille 2016). In a recent manuscript, Wang (2016) quantifies the effect of unbalanced sampling and specification of ancestry priors on STRUCTURE’s estimates.

Ancestry priors (specified by the term ‘alpha’ in STRUCTURE) follows a Dirichlet distribution on the number of ancestral populations (often denoted as ‘K’). STRUCTURE allows two modes of specifying alpha (here a) – it either assumes a uniform prior (i.e. each individual’s multi-locus genotype is assumed to be sampled uniformly from ‘K’ populations with a probability of 1/K), or can be inferred per population (such that a1a2≠…≠aK).

Wang (2017) performed a series of simulations to formally assess the effect of the two ancestry prior specification methods on analyses of unbalanced populations. He varied the number of sampled loci (L = 10, 20, 40, 50), and the number of ancestral populations (K = 3, 6, 12, 24, 48), and levels of differentiation (Fst = 0.05, 0.1, 0.2), and performed long, and 20 replicated runs of STRUCTURE by varying the initial a (set to 1.0 by default). He notes that for greater number of ancestral populations (K), values of a lower than 1.0 are required to deliver accurate inferences. Accuracy was estimated at two levels – in estimation of the number of ancestral populations (as ascertained by the method of Evanno et al. 2005, and Pritchard 2000), and in estimates of admixture proportions (assignment probabilities).

Accuracy, measured here as average assignment errors (AAEs), as a function of the extent of unbalanced among populations. Figure 1 from Wang (2016). Dft = default value of alpha = 1.0 in STRUCTURE, Alt = alternative priors, and L quantifies the number of sampled loci. Simulated data comprised of three populations under the island model.

His key findings include (1) inaccurate estimates of both K and assignment probabilities due to unbalanced population sizes while using the default prior of a = 1.0, (2) accurate estimates of assignment probabilities while using the alternative prior (except at large values of K, or in highly unbalanced populations), (3) the estimator of Pritchard et al. (2000) is more accurate in recapitulating ancestral populations than the estimator of Evanno et al. (2005).

This study is important in that it emphasizes the need to perform your STRUCTURE analyses using the alternative prior model of a, rather than using the default value of 1.0. Wang (2016) recommends that you set the initial value of a to be equal to 1/K (i.e. much less than 1.0) for improved accuracy.

Reference:

Wang, J., 2016. The computer program Structure for assigning individuals to populations: easy to use but easier to misuse. Molecular Ecology Resources.  http://dx.doi.org/10.1111/1755-0998.12650

Posted in bioinformatics, genomics, howto, methods, population genetics, software, STRUCTURE | Tagged , , | 1 Comment

For these birds, isolation-by-distance is (almost) all in the family

A Florida scrub jay (Flickr: Candace Martino)

Isolation by distance is one of the most fundamental processes of molecular ecology. In any finite population, the frequency of a genetic variant will change from generation to generation due to random sampling effects, which we call genetic drift. In two separate populations a genetic variant can drift to different frequencies — but migration between the two can keep them “synchronized.” Across a larger landscape, if migration becomes more difficult between more distant pairs of populations, this isolation, by distance, can allow them to evolve measurable genetic differences.

This process is important for molecular ecologists because we study the genetic differences between populations, and IBD creates those differences as a simple consequence of time and space. If you don’t take IBD into account, you can mistake its results for local adaptation, which is the very thing we’re most often interested in — genetic differences between populations that reflect adaptation to different environments.

As important as IBD is, though, we don’t usually study it directly. Instead, we test for its consequences, by comparing genetic differences between pairs of populations at different distances, to see whether genetic differences increase with geographic distance. To see how migration across a landscape creates those genetic differences, we’d have to track the movement of multiple generations of individuals across a region — no trivial task. Precisely that kind of data, though, has just been released as a preprint on bioRxiv.

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Friday Action Item: Science

The Greek goddess Athena, patron of knowledge, craft, wisdom — and strategy. (Flickr: Ed Lim)

Now that we’ve posted a few of these Action Items, I want to step back and add an important caveat to this idea of small things to do in the wake of a devastating political reversal. These posts are intended to highlight things we think our readers may not already be doing — and we definitely want everyone to do all the things. It’s important to remember, though, that those of us who work in science, education, and science communication have already committed our daily lives to opposing the incoming administration.

In the last few weeks, I’ve returned several times to history professor Timothy Snyder’s list of principles for life under an authoritarian presidency, published just after the election. This one, in particular, has been helpful:

Defend an institution. Follow the courts or the media, or a court or a newspaper. Do not speak of “our institutions” unless you are making them yours by acting on their behalf. Institutions don’t protect themselves. They go down like dominoes unless each is defended from the beginning.

If you’re a scientist or a science educator, you’re already part of an institution that needs defending — maybe a university campus, a whole field of inquiry, or a single classroom. Continuing to do and teach science in the coming years will be, in itself, an act of resistance.

Do you study part of the living world threatened by climate change or habitat destruction? When the EPA is run by one of its most dogged enemies and the Secretary of the Interior wants to cut Federal power to protect wilderness, you’re a voice for the voiceless.

Will your research help make the world greener, more equitable, or kinder? When the Secretary of State is a billionaire oil company CEO with a history of buttering up dictators, you’re a subversive.

Do you design experiments, organize data, and build systems to separate real patterns from statistical noise? When the president reimagines reality to better suit his wishes, you’re a revolutionary.

Are you figuring out how to keep a research program going without any certainty of Federal funding? You’ll be rebelling against the leadership of the House Science Committee and the White House itself.

Do you teach students how to find and evaluate evidence, and to practice critical thinking? In the era of fake news, the hope of the future is in your hands.

As California Governor Jerry Brown said in a recent, rousing speech to the American Geophysical Union, all of us working in science are “foot soldiers of change, and understanding, and scientific collaboration.” So that’s the Action Item for this week, and every week: keep right on sciencing.

See you in 2017.

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Friday Action Item: Have a science conversation with a non-scientist

In the wake of the recent U.S. election, we’ve started these “Friday Action Item” posts with ideas about specific things you can do to support science — from calling Congress to helping crowd-fund a cool new research project. Got a suggestion for a future Action Item? E-mail and tell us all about it!

This time of year many of us take time off to visit friends and family but that doesn’t mean our work as scientists should stop. Now more than ever, we must be advocates for science through effective communication, outreach, and engagement with the general public. Unfortunately, when we spend most of our time caught up in the nitty gritty details of a complicated analysis or sophisticated theory, it can be difficult to switch gears and talk with a “non-scientist”* about why our work, and science in general, is broadly important (and super cool!). Below are a few resources that will help you engage your sister/father/aunt/in-law/neighbor/uber driver/person sitting next to you on the plane/etc in a productive, accessible conversation about science.

9 Tips For Communicating Science To People Who Are Not Scientists

  • Don’t use jargon, get to the point, and “flip the script” as in the figure above.

Science Communication as a Moral Imperative

  • “[Your job] really isn’t to land big grants for your university, crank out obscure academic publications by the dozens, and amass a long list of peer citations. As scientists, your real job should be to make great discoveries and share them with the world.”

Effective Communication, Better Science

  • “Know your audience. Who are they? You always need to know who you are trying to reach, as it affects everything else you do.”

*I put the term ‘non-scientist’ in quotes because I would argue that everyone is a scientist in some way, shape, or form!

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