New paper: Understanding mutualism with population genomics

Comparing metrics of diversity (x axis) and geographic differentiation (y axis) for thousands of genes in the Medicago truncatula genome (gray points) reveals that some symbiosis genes (red points) are genome-wide outliers — but they are not all the same kind of outlier (crosses and triangles). Yoder (2016), Figure 1.

Comparing metrics of diversity (x axis) and geographic differentiation (y axis) for thousands of genes in the Medicago truncatula genome (gray points) reveals that some symbiosis genes (red points, crosses, and triangles) are genome-wide outliers — but they are not all the same kind of outlier. Yoder (2016), Figure 1.

My very latest scientific publication is now online at the American Journal of Botany. It’s sort of an odd paper — something of a review, or an opinion piece, discussing how population genomic data can help us understand why mutualisms stay stable [PDF] in spite of the risk of “cheating” by partners, with a “worked example” with data from the Medicago HapMap Project. Here’s some key bits from the abstract:

Different hypothesized models of mutualism stability predict different forms of coevolutionary selection, and emerging high-throughput sequencing methods allow examination of the selective histories of mutualism genes and, thereby, the form of selection acting on those genes. … As an example of the possibilities offered by genomic data, I analyze genes with roles in the symbiosis of Medicago truncatula and nitrogen-fixing rhizobial bacteria, the first classic mutualism in which extensive genomic resources have been developed for both partners. Medicago truncatula symbiosis genes, as a group, differ from the rest of the genome, but they vary in the form of selection indicated by their diversity and differentiation — some show signs of selection expected from roles in sanctioning noncooperative symbionts, while others show evidence of balancing selection expected from coevolution with symbiont signaling factors.

The paper is my contribution to a Special Section on “The Ecology, Genetics, and Coevolution of Intimate Mutualisms”, which I co-edited with Jim Leebens-Mack. You can view the whole Special Section here, and download my paper here [PDF].

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Coming soon: Crowd-funding a Joshua tree genome

Joshua trees at Tikaboo Valley, Nevada (Flickr: jby)

Joshua trees at Tikaboo Valley, Nevada (Flickr: jby)

I’m very excited to announce a new project, with a new model for doing science: The Joshua Tree Genome Project, in which I’m working with a bunch of smart, accomplished folks to sequence the genome of my favourite spiky desert plant. A sequenced Joshua tree genome will provide the framework to understand how coevolution with highly specialized pollinators has shaped the history of Joshua trees, and to use the landscape genomics skills I’ve developed with the Medicago HapMap Project and AdapTree to understand how the trees cope with extreme desert climates — and how to ensure they have a future in a climate-changed world.

Perhaps most excitingly (terrifyingly?) we’re going to raise some of the funds to do the genome sequencing by crowdfunding, using the Experiment.com platform. So please keep an eye on the project site, follow our Twitter feed, and Like our Facebook page to make sure you don’t miss your chance to help understand Joshua trees’ evolutionary past and ensure their future.

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The Molecular Ecologist: Fishing for genetic signals of adaptation

Atlantic Salmon

Adult Atlantic salmon. (Flickr: Matt Hintsa)

Over at The Molecular Ecologist, I discuss a new paper that exemplifies how we’re going to be studying the genetics of adaptation in the age of high-throughput DNA sequencing—even if it doesn’t quite live up to that promise. It’s a study of adaptation in Atlantic salmon, whose lifestyle makes them uniquely suitable for a particuar sampling design:

Salmon hatch in freshwater rivers, and spend at least their first year in that environment before swimming downstream to the ocean, where they develop into reproductively mature adults. When they’re ready to mate, they migrate back from the ocean, up the river where they hatched to spawn at the site of their birth. Those major migrations and the transitions between freshwater and salt-water are likely to be major selective events for salmon, and they offer convenient times to catch and study salmon from roughly the same age-cohort: when they migrate downstream to the ocean, and when they return to their birth-river.

By taking genetic samples of juvenile salmon on their way out to sea, and then adults on swimming upstream to breed, you can test for genetic changes—adaptation—that has occurred over the course of the fishes’ life in the ocean. And that’s exactly what the authors of this paper did—go read the whole post to find out how it worked.

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Chris Smith takes on that Troublesome book

Cain and Abel

Cain and Abel, in medieval stained glass. Photo by Fr Lawrence Lew.

Over at Nothing in Biology Makes Sense, Chris Smith has been writing a series of posts digging deep into the evolutionary claims made in Nicholas Wade’s book A Troublesome Inheritance. Last week, Chris debunked the claim that human population genetics naturally sorts into “races”—this week, he’s taking on Wade’s claim that variation at a particular gene has made some human populations more prone to violence than others:

Although some studies have found genetic variants in the MAO-A promoter region that are more common in some ethnic groups than in others (Sabol et al. 1998; Widom & Brzustowicz 2006; Reti et al. 2011) it is likely that these genetic variants are not –on their own– associated with violent or impulsive behavior (Caspi et al. 2002; Widom & Brzustowicz 2006). Instead, genetic variation in the MAO-A promoter seems to make some children less able to recover from abuse and childhood trauma, and therefore more likely to act out later in life (Caspi et al. 2002; Widom & Brzustowicz 2006). Simply carrying the ‘low expression’ allele in the MAO-A promoter does not have any effect at all on impulsivity or aggression.

Chris co-teaches a class on exactly the topics covered in A Troublesome Inheritance, so I highly recommend you read the whole thing, and follow the series to its conclusion.

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The Molecular Ecologist: I read A Troublesome Inheritance so you don’t have to

World Map - Abstract Acrylic Image by Lara Mukahirn.

Over at The Molecular Ecologist I’ve done an in-depth review of the population genetics data cited by Nicholas Wade in his book A Troublesome Inheritance, which argues that social, cultural, and economic differences between human populations are all in our genes. Digging into the book’s endnotes, it didn’t take me long to find discrepancies between Wade’s description of basic population genetic results and the actual, um, results.

First and foremost, Wade claims that when population geneticists apply a class of statistical methods called clustering algorithms to datasets containing hundreds or thousands of genetic markers, they objectively identify five geographic groups that he calls “continental races”—differentiating African, European/Middle Eastern/South Asian, East Asian, Oceanian, and American people. What he does not make particularly clear is that while clustering methods do group genetic samples without direct instructions, the algorithms do not decide how many clusters there are. The geneticists using them do.

To make me feel somewhat better for having paid actual money to read this book, go read my whole review.◼

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The Molecular Ecologist: More functions, stronger selection?

Victorinox Swiss Army Knife Photo by James Case.

Over at The Molecular Ecologist I’m discussing a new paper in the journal Genetics, which demonstrates that selection acts more strongly on genes that affect multiple traits:

Genes that have roles in multiple traits—pleiotropic genes—have long been thought to be under stronger selection as a result of those multiple functions. The basic logic is that, when a gene produces a protein that has a lot of different functional roles, there are more functions that will be disrupted by changes to that protein. Which would be more inconvenient: if your smartphone suddenly needed a new type of power connector, or if every electrical outlet in your house suddenly accepted only plugs with four prongs?

A team at the University of Queensland tested this idea using a lot of fruit flies and some cleverly applied gene expression resources. To find out how it all worked, go read the whole post, and check out the original paper.◼

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The Molecular Ecologist: Tracing soft selective sweeps in your gut microbiota

ποντίκι / μυς, mouse (Mus musculus) by George Shuklin Why is my poop glowing blue? Photo by George Shuklin.

Over at The Molecular Ecologist, I’m discussing a new study that traces the adaptation of bacteria moving into a mammalian gut:

João Barroso-Batista and colleagues at the Instituto Gulbenkian de Ciência and Instituto de Tecnologia Química e Biológica in Portugal first treated mice with streptomycin to clear their guts of bacteria, then fed them cultures of Escherichia coli that were genetically uniform—except that half the E. coli cells in the culture had been engineered to produce a blue fluorescent protein, and half had been engineered to produce a yellow fluorescent protein. … If a single mutation made that one cell so successful that its descendants entirely dominated the gut, the authors would be able to tell—by checking the color of the host mouse’s poop.

To find out what the study’s authors learned by sequencing the bacterial genomes in that colored mouse poop, go read the whole thing.◼

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The Molecular Ecologist: The 2014 Next-Generation Sequencing Field Guide

Alineando secuencias (1) Photo by Shaury.

One of the most popular items at The Molecular Ecologist isn’t a blog post—it’s Travis Glenn’s “Field Guide” to the capabilities and costs of the many next-generation sequencing technologies currently available. Today we’re pleased to release the 2014 update to the Guide, this time with some new personal insight from Travis in the form of both an introductory blog post and a new table rating the overall quality of each technology:

Overall, if you are in the market for a next generation DNA sequencer in early 2014, the data indicate one clear inexorable trend – think Illumina. For fans of the Brady Bunch – Illumina, Illumina, Illumina! For fans of Star Trek – Prepare to be assimilated by one of Illumina’s Borg-like cubes. For fans of Henry Ford – You can have any NSG instrument you want, so long as it’s an Illumina.

Travis’s post is well worth reading in full, and you’ll want to update your bookmarks to the new comparison tables.◼

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The Molecular Ecologist: Is Homo sapiens a model organism?

New York City Photo by Bikoy.

Over at The Molecular Ecologist, guest contributor Jacob Tennessan suggests that for those of us who study the genetics of natural populations, the ultimate “model organism” may be … us.

Thus, the field of human population genetics has always been a step or two ahead of the molecular ecology of wildlife. Common techniques like mitochondrial- or microsatellite-based phylogeography analyses were pioneered with data from humans. Research into human molecular ecology has yielded countless fascinating stories that provide a baseline for what to expect when examining other taxa. Some are well-known textbook examples, like the sickle-cell hemoglobin balanced polymorphism that conveys resistance to malaria, or the human global diaspora reflected in sequence diversity that traces back to “mitochondrial Eve” and “Y-chromosome Adam.”

Does that make Homo sapiens a “model organism” in the same sense as fruitflies and Caenorhabditis elegans, or more of a proving ground for new molecular methods? Go read the whole thing, and tell us what you think in the comments.◼

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