When less might be more: The evolution of reduced genomes

Images courtesy of wiki commons

The advent of affordable genome sequencing has provided us with a wealth of data. Researchers have sequenced everything from Escherichia coli (4.6 Mbp genome size), to sea urchins (810 Mbp), chimpanzees (3.3 Gbp), and humans (3.2 Gbp). Then there are the massive genomes, which have been identified, including that of the rare Japanese flower (Paris japonica) with a genome of 149 Gbp. But, what does that mean? Maybe it’s more interesting to switch our focus from the large and in charge genomes to those of the small free living prokaryotes who have taken the opposite route.

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Molecular Ecologists at #Evol2017 —  see you in Portland!

The Portland skyline and Mt. Hood, as seen from the Portland Japanese Garden. (Flickr: Alan)

Evolution 2017 — the joint annual meeting of the American Society of Naturalists, the Society of Systematic Biologists, and the Society for the Study of Evolution — is already underway in Portland, Oregon, and it’s looking like a terrific week of science already. The program kicked off today with a symposium in honor of Joe Felsenstein, and gets fully underway tomorrow with a day of workshops capped by the traditional public outreach lecture, which will be given by Ann Reid, the Executive Director of the National Center for Science Education. Regular presentation sessions begin bright and early Saturday morning, and carry on through Tuesday.

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On hyRAD-X, another option for museum genomics

Last year, I profiled Suchan et al.’s “hyRAD” method for reduced-representation genome sequencing of degraded sources of DNA using RAD probes. While it’s too early to say whether hyRAD will be widely used by molecular ecologists looking to integrate historic samples into their work–in my own research, I found it effective, but not efficient–it remains a promising step forward for population genomics with a temporal dimension.

Now, the team behind hyRAD have published a major update to their protocol (“hyRAD-X”), replacing fragments from a RAD digest with messenger RNA as the basis for the probes in target capture. This, the authors argue, improves on the original method in several ways. First, as the reference used in bioinformatics steps is an assembled transcriptome from RNAseq of one high-quality tissue sample, both loci definition and SNP calling accuracy are improved. Second, the RNA probes in the method increase hybridization stringency — an important improvement for low-content DNA samples. (Arguably the main reason to apply hyRAD-X in the first place!)

So which method should you use? On the one hand, hyRAD-X’s advantages appear numerous, and address many of the problems inherent to the original protocol. Targeting the exome reduces the likelihood of capturing paralogous loci, as repetitive genomic regions are more frequently found in noncoding DNA. RNA probes are more thermodynamically stable, and eliminate the risk of contamination and chimera formation. Nor is hyRAD-X dramatically more complicated at the lab bench, deviating from hyRAD only in its probe generation step, where biotinylated RNA is synthesized from cDNA itself synthesized from a total RNA extract of a single high-quality sample. By integrating biotin-UTP during the in-vitro transcription stage of this process, the method also avoids the substantial probe material loss probably with the nick-labeling mechanisms proposed in Suchan et al. 2012. And in a comparison of the performance of both methods on an identical timeseries of conifer subfossils (spanning 7200 – 5800 years bp), Schmid et al. report significantly more SNPs from hyRAD-X than hyRAD with a de novo reference, and significantly greater mean read depth per site.

Figure 2 from Schmid et al. 2017, diagramming the hyRAD-X method.

On the other hand, these benefits are not abundantly clear from the author’s published results. Schmid et al. report no differences in percentage of missing data, overall mean read depth, or chimera production. Concerningly, they do report 2-8 times higher PCR duplicates in hyRAD-X compared to hyRAD alignments. (I found PCR duplicates to a be pervasive feature of my own hyRAD captures, and are an important consideration when deciding sequencing effort.) And when comparing hyRAD-X and hyRAD data aligned to an identical transcriptome, the original hyRAD protocol resulted in a higher percentage of mapped reads and a greater SNPs, suggesting its primary limitations may have been related to the inherent problems with de novo reference genomes. Finally, putatively neutral loci may be preferable to exome data in some cases where sites under selection violate the assumptions of population genetic models, or bias phylogenetic inference.

However these issues come out in the wash, I think the decision to apply hyRAD, hyRAD-X, or another probe-based method for reduced representation sequencing historic samples is more likely to be based on your project’s goals and your lab’s contingencies than any clear advantages of a particular protocol. But while there may not yet be a silver bullet for population genomics with degraded DNA, it’s undoubtedly an exciting time to be working in the field, and hyRAD-X represents a creative solution to its many challenges.


Schmid, S., Genevest, R., Gobet, E., Suchan, T., Sperisen, C., Tinner, W., Alvarez, N. 2017. HyRAD-X, a versatile method combining exome capture and RAD sequencing to extract genomic information from ancient DNA. DOI: 10.1111/2041-210X.12785

Suchan, T., Pitteloud, C., Gerasimova, N.S., Kostikova, A., Schmid, S., Arrigo, N., Pajkovic, M., Ronikier, M., Alvarez, N. 2016. Hybridization Capture Using RAD Probes (hyRAD), a New Tool for Performing Genomic Analyses on Collection Specimens. PLoS One. DOI: 10.1371/journal.pone.0151651

Posted in genomics, methods, natural history, next generation sequencing, phylogenetics, phylogeography, population genetics, RNAseq, selection, transcriptomics | Tagged , , , | Leave a comment

Shared patterns of genomic diversity across populations of distantly related taxa

Genomic diversity is shaped by the complex interplay between the effects of genetic drift and natural selection among populations. Several of these effects, especially those of linked selection at neutral sites, adaptive introgression, and barriers to migration (often called “genomic islands”) have been discussed on our blog before, all of which compare diversity within species, or among closely related species.

In a recent study, Vijay et al. 2017 propose a “macro-level comparative approach”, comparing genomic diversity across taxa, under the hypothesis that shared patterns of diversity across distantly related taxa are characteristic of shared demographic history (here characterized by the effective population size, Ne, and variants of it) across syntenic regions.

Genome-wide patterns of summary statistics measured across whole genomes of three species of birds – Darwin’s finches, flycatchers, and American crows. Figure from Fig. 2 of Vijay et al. 2017 (http://dx.doi.org/10.1111/mec.14195)

Vijay et al. (2017) analyzed shared polymorphisms across publicly available genomes of three disparate clades of Darwin’s finches, flycatchers, and American crows, with ~50 million years of evolution between them. Thereon, summary statistics including population recombination rates, nucleotide diversities, divergences, and Fst were computed in 50 Kb windows. Similarities within and among clades were then computed using Pearson correlations. Results indicated several interesting findings: (1) strong correlations within clades among all summary statistics computed, as expected – for example, dxy is expected to be negatively correlated with Fst under the effects of linked selection (2) high levels of between clade correlations, particularly in dxy estimates, and recapitulation of the negative correlation between dxy and Fst when comparing across clades, and (3) significant correlation across estimates of summary statistics concentrated around sub-telomeric regions, rather than in peri-centromeric regions (which also had reduced diversity, elevated differentiation), indicative of the influence of chromosomal recombination rates in mitigating the effects of linked selection/differential introgression.

These results suggest that syntenic genomic regions evolving putatively due to linked natural selection experience similar effects across millions of years of evolution.

The degree of correlation among clades was remarkable considering divergence times of several million generations, gaps in syntenic alignments and the statistical error associated with population genetic estimates from moderate samples sizes. With recombination rate being the key mediator of linked selection, an explanation of genomic parallelism in Ne through linked selection requires conserved recombination landscapes among the clades under investigation.



Genome-wide patterns of variation in genetic diversity are shared among populations, species and higher order taxa, Nagarjun Vijay, Matthias Weissensteiner, Reto Burri, Takeshi Kawakami, Hans Ellegren and Jochen B. W. Wolf, Molecular Ecology, DOI: 10.1111/mec.14195


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Friday action item: It’s time to go local

Screencap of weather.com, which is not having this. (Twitter: Eric Holthaus)

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

This Thursday was not a good day for the world, or for the standing of the United States in the world:

President Trump has announced that the U.S. will be withdrawing from the Paris accord — the historic global agreement reached by 195 countries in 2015 to set targets for reducing greenhouse gas emissions and limiting the rise in average global temperatures.

This administration has done plenty of awful things, but this move is a kind of nexus of everything that came before — disdainful of hard-won international cooperation, short-sighted even from a purely business-oriented perspective, deliberately ignorant of scientific consensus, and likely to visit its greatest harms on the poorest people on the planet. The Paris Agreement was, to some extent, a symbol — the Trump Administration was already merrily gutting the infrastructure of environmental protection before today, and formal withdrawal could take almost four years to complete — but the announcement makes crystal clear that the U.S. Federal Government is abdicating any role it could have in facing the global threat that defines our generation.

Even without Federal leadership, though, we have options at the local level. Because today’s announcement was hardly a surprise, some of them are already set to go. The states of Washington, California, and New York, which together account for about a fifth of the U.S. population and GDP have announced an alliance to coordinate carbon emissions reductions without D.C., with the explicit goal of meeting the Paris commitments. The new organization is billed as an extension of the Under2 Coalition, an international coalition of cities, states, and other “sub-national” governments that signed a memo of understanding for joint action on carbon emissions starting in 2015. A number of other states’ governors pledged independent action in anticipation of Thursday’s announcement — so one thing you can do today is call up your governor’s office and your state representatives to ask, why isn’t my state in the U.S. Climate Alliance already?

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Nancy Moran awarded the 2017 Molecular Ecology Prize

Nancy Moran’s most cited paper used metagenomics to identify a possible cause of honeybee colony collapse disorder. (Flickr: Rachel Bonoan)

The 2017 Molecular Ecology Prize will go to Professor Nancy Moran of the University of Texas at Austin. The Prize is awarded by the Editorial Board of Molecular Ecology to recognize “an outstanding scientist who has made significant contributions to Molecular Ecology,” as selected by an independent award committee. Professor Moran’s nomination statement particularly highlights her extensive work on symbiosis and microbial community genetics:

Nancy Moran, from her Google Scholar citations page.

The 2017 Molecular Ecology Prize has been awarded to Professor Nancy Moran for her pioneering studies of symbiosis and bacterial genome evolution. Her discoveries provide a clear link between bacterial lifestyle and population size with rates of evolution and genome degradation. Her work has also provided some of the most convincing demonstrations of the molecular basis for ecologically important traits, including defense, nutrition, and thermotolerance, inclucing remarkable examples of convergence mediated via symbiosis. Professor Moran’s more recent work on the honeybee system is now setting the standard for molecular studies of complex symbiotic gut communities.

Previous Molecular Ecology Prize recipients include Godfrey Hewitt, John Avise, Pierre Taberlet, Harry Smith, Terry Burke, Josephine Pemberton, Deborah Charlesworth, Craig Moritz, Laurent Excoffier, Johanna Schmitt, Fred Allendorf and Louis Bernatchez.

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Friday action item: An awful budget, now with detail

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

There’s a detailed Federal budget proposal out this week, covering the Trump administration’s plans for the 2018 fiscal year. Have you called Congress about it? You should.

Detailed breakdowns have identified cruel cuts to the social safety net and a multi-trillion-dollar arithmetic error that make excellent reasons to oppose the plan all on their own. But there’s also piles of bad news for science:

We’ve also, for the first time, got a concrete proposal for the National Science Foundation’s budget — more than 11% lower than what it had in 2016 — to the lowest it’s been, in inflation un-adjusted dollars, since 2008. The spending plan NSF has prepared with that number in mind would reduce funding for graduate research fellowships, EPSCoR support for institutions in states that otherwise receive less NSF funding, and the research at undergraduate institutions (RUI) program, among others.

As we saw with the Trump proposal for continuing funding in 2017, this will almost certainly not pass Congress in its current state; but Congress can use every bit of encouragement we give it. Call!

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