Yaniv Brandvain
Associate Editor, Empirical Population Genetics section

Yaniv Brandvain is an Associate Professor of Plant and Microbial Biology at the University of Minnesota working in theoretical and empirical population genomics. He received a BA in Human Ecology from the College of the Atlantic and a PhD in Biology from Indiana University, working on the robe of conflict, cooperation, and co-adaptation in plant evolution and speciation. During his postdoc at the University of California, Davis, he developed evolutionary theory concerning meiotic drive, and he developed population genomic approaches to study the evolutionary origins of self-fertilizing plant species. He is interested in understanding how new plant species arise with a particular interest in how mating systems and genomic conflicts shape plant diversity. His lab combines empirical and theoretical population genomic analyses with collaborative work in empirical systems to study the evolutionary forces shaping flowering plant diversity. He was also named McKnight Land-Grant Professor from the University of Minnesota (2017-2019) for his research efforts and received the Stanley Dagley-Samuel Kirkwood Undergraduate Education Award for his efforts in undergraduate instruction in biostatistics. 

After 60 years of mystery, researchers have identified the pathogen responsible for White Fat Cell Disease.

Water fleas of the genus Daphnia have long been critical tools for studying the ecology and evolution of host-pathogen interactions, but one of their natural pathogens has remained mysterious for more than six decades. In the 1950s, Daphnia magna isolated from rock pools in southwestern Finland were reported to suffer from a disease that obscured the normally semi-transparent animals with extremely large, white fat cells, giving them a greenish, iridescent shine. This highly infectious disease, called White Fat Cell Disease (WFCD), was also reported in water flea populations across Europe and Asia. Although bacteria were assumed to be the cause, no specific bacteria was ever linked to the disease.

In a report published in G3: Genes|Genomes|Genetics, Toenshoff et al. have finally unmasked the culprit behind WFCD: an iridovirus that they named Daphnia iridescent virus 1 (DIV-1). Iridoviruses are common invertebrate pathogens, and interestingly, another Daphnia-infecting iridovirus was previously reported to cause symptoms similar to WFCD—but until now, the two had never been linked.

D. magna infected with DIV-1 (left) and uninfected (right).

After confirming DIV-1 as the causative agent of WFCD, Toenshoff et al. sequenced its genome to gain a better understanding of its evolutionary origin. DIV-1 has some genes in common with other iridoviruses, including a set of core genes related to infection and replication in the host. Although these similarities remain, a number of differences suggest that DIV-1 diverged from other invertebrate iridoviruses so long ago that it has no close relatives that are known. Interestingly, DIV-1 also has a number of genes likely obtained through horizontal gene transfer with its water flea hosts—including genes that might inhibit apoptosis in its host’s cells.

DIV-1 is the first viral Daphnia pathogen to be characterized. The virus is both widespread in the wild and easily cultured, so its identification reveals it as a useful new tool for exploring the ecology of viral infections in these classic model hosts.

CITATION:

The End of a 60-year Riddle: Identification and Genomic Characterization of an Iridovirus, the Causative Agent of White Fat Cell Disease in Zooplankton

When a noni fruit ripens, it stinks like old cheese—or even vomit. Familiar to many in the form of expensive juices sold as health supplements, this pungent fruit is engaged in a slow-motion arms race with would-be insect pests. Fruit flies are unable to feast on noni—scientific name Morinda citrifolia—because the fruit is dosed with large quantities of octanoic acid (OA), making it highly toxic to them. But one species has sidestepped this defense system: in tropical Seychelles, a specialized type of fruit fly called Drosophila sechellia has evolved to feed exclusively on the unappetizing fruit.

To learn how D. sechellia thrives on a diet that should kill it, Lanno et al. looked for D. sechellia genes that were differentially expressed when the flies were given OA-containing food. Their analysis revealed 104 differentially regulated genes that have known orthologs in the OA-susceptible fly D. melanogaster. Many of the downregulated genes are involved in the immune system—an interesting result given the recent finding that D. sechellia can’t mount an immune response to an attack by the parasitoid wasp Asobara tabida. The downregulated immune genes include some that are involved in responses to a variety of threats, including bacteria, so OA exposure may deal a major blow to the immune system.  

Among the upregulated genes are several in the insect-specific Osiris family. One of these, Osi6, is the only gene in the set of 104 that is found in a region of the genome known to have a major impact on OA resistance. This aligns with the research group’s previous discoveries that Osi6 expression is 72 times greater in D. sechellia than it is in D. simulans, an OA-susceptible fly, and that knocking down Osi6 in D. melanogaster makes it even more vulnerable to OA.

A different research group recently found that the Osiris gene cluster is under strong selection in an isolated population of the fly D. yakuba that has just begun adapting to a diet of poison-laden noni, another clue that learning more about these genes may be crucial for understanding OA resistance and this compelling model of ecological adaptation.

CITATION:

Lanno, S.; Gregory, S.; Shimshak, S.; Alverson, M.; Chiu, K.; Feil, A.; Findley, M.; Forman, T.; Gordon, J.; Ho, J.; Krupp, J.; Lam, I.; Lane, J.; Linde, S.; Morse, A.; Rusk, S.; Ryan, R.; Saniee, A.; Sheth, R.; Siranosian, J.; Sirichantaropart, L.; Sternlieb, S.; Zaccardi, C.; Coolon, J. Transcriptomic Analysis of Octanoic Acid Response in Drosophila sechellia Using RNA-Sequencing.
G3, 7(12), 3867-3873.
DOI: 10.1534/g3.117.300297
http://www.g3journal.org/content/7/12/3867

Illuminating the cover of the May issue of G3 is a lake-dwelling filter feeder no more than a couple millimeters long. This microcrustacean—Daphnia pulex, also known as the water flea—is an important model organism, especially in ecological genetics. But despite Daphnia’s status as a model organism, no one had examined its population genomics until now.

Four papers in GENETICS and G3 by Michael Lynch’s group delve into Daphnia’s population genomics. Although the Daphnia genome had been sequenced, Ye et al. provide a new reference genome assembly that bolsters the field and enhances the group’s three other papers. The new assembly also corrects the prior version; when the researchers compared the two assemblies, they found that the old version contained 7,000 false-positive genes.

Lynch et al. report the first population genomic study of Daphnia and compare one population’s genomic structure to that of the better-known Drosophila melanogaster, the only other arthropod for which extensive population genomic information is available. They found some similarities: the two species have similar mutation rates, and based on long-term averages, both appear to have similar effective population sizes. This is surprising because Daphnia switches between clonal reproduction and sexual reproduction depending on environmental conditions, and Daphnia lives in lakes with little exchange between a population in one lake and a population in another, in contrast to Drosophila populations, which have no hard boundaries separating them.

There were also differences between Drosophila and Daphnia—most strikingly, the efficiency of natural selection seems to be higher in Drosophila because, as their analysis shows, mutations in Daphnia are often less strongly opposed by purifying selection. There may be an ecological explanation for this: Daphnia and Drosophila develop differently and live in different environments, and notably, Daphnia, unlike Drosophila, is capable of resting as an egg for hundreds of years. But to find the mechanistic link between ecology and the evolution of genomes, more research on more species will have to be done.

Lynch et al. also found that Daphnia exhibits high nucleotide diversity and that its genome is very close to being in Hardy-Weinberg equilibrium and that the Daphnia genome has apparently neutral sites, including in introns, that could be used as benchmarks in selection studies. Similar sites in Drosophila appear to be under selection and thus are more difficult to apply in the same way. Together, these investigations set the stage for new lines of research on evolutionary genomics in natural populations.

CITATIONS:

Ye, Z.; Xu, S.; Spitze, K.; Asselman, J.; Jiang, X.; Ackerman, M.; Lopez, J.; Harker, B.; Raborn, R.; Thomas, W.; Ramsdell, J.; Pfrender, M.; Lynch, M. A New Reference Genome Assembly for the Microcrustacean Daphnia pulex.
G3, 7(5), 1405-1416.
DOI: 10.1534/g3.116.038638
http://www.g3journal.org/content/7/5/1405

Lynch, M.; Gutenkunst, R.; Ackerman, M.; Spitze, K; Ye, Z.; Maruki, T.; Jia, Z. Population Genomics of Daphnia pulex.
GENETICS, 206(1), 315–332.
DOI: 10.1534/genetics.116.190611
http://www.genetics.org/content/206/1/315

Ackerman, M.; Johri, P.; Spitze, K.; Xu, S.; Doak, T.; Young, K.; Lynch, M.
Estimating Seven Coefficients of Pairwise Relatedness Using Population-Genomic Data.
GENETICS, 206(1), 1 105-118.
DOI: 10.1534/genetics.116.190660
http://www.genetics.org/content/206/1/105

Maruki, T.; Lynch, M.
Genotype Calling from Population-Genomic Sequencing Data.
G3, 7(5), 1393-1404.
DOI: 10.1534/g3.117.039008
http://www.g3journal.org/content/7/5/1393

In the fast-paced life of a bacterium, the ability to manufacture proteins quickly and efficiently is crucial. In these organisms, mRNAs—the templates for building proteins—have a string of bases near the start called the Shine-Dalgarno (SD) sequence. This motif increases the rate at which translation is initiated. Some results suggest that the presence of SD sequences further into an mRNA, in the coding region, actually slow the elongation rate—but work by a few other groups does not support this claim.

In the November issue of G3, Yang et al. reason that if SD sequences do slow elongation, there should be fewer of the sequences than would be expected (given codon use biases) in the coding regions of bacterial mRNAs. Using data from many species of bacteria, they found that not only are SD sequences rarer in coding regions, but they are also even more depleted in the genes that are most expressed—and the effect was greatest in the bacteria with the shortest generation times.

In addition to slowing elongation, there are a few other possible explanations for the dearth of SD sequences in coding regions. The sequences may be mistaken by ribosomes for translation start sites, resulting in truncated proteins, or they may cause ribosomes to slip up and result in a frameshift. It’s also possible that the ribosomes get stuck on the SD sequences, leading to a reduced pool of ribosomes available to start translation.

If SD sequences are so detrimental in this context, it might seem strange that the coding regions of bacterial mRNAs would have any SD sequences at all. But natural selection typically keeps bacterial genomes small—a trim genome allows bacteria to replicate quickly and potentially beat out its competitors—so it’s possible that the initiation sites for a gene might need to overlap with the end of the prior gene in the operon. And despite being potentially harmful, random mutations ensure that some of these misplaced sequences will arise by chance.

An important implication of this work is that the presence or absence of SD sequences within coding regions is a significant modulator of translation efficiency. So far, much research has been dedicated to codon usage as the primary contributor to translation speed, since codons calling for rarer tRNAs might take longer to be translated. But according to these researchers’ results, SD sequences in coding regions also have a significant effect. This implies that when designing artificial genes to insert into bacteria, researchers might want to avoid including SD sequences if they hope to get the highest protein yield. Thinking like a bacterium may not sound like a good strategy for a scientist, but after being molded by billions of years of competition with their fellow microbes, these organisms do seem to have learned a trick or two.

CITATION:

Yang, C.; Hockenberry, A.; Jewett, M.; Amaral, L. Depletion of Shine-Dalgarno Sequences within Bacterial Coding Regions Is Expression Dependent.
G3, 6(11), 3467–3474.
DOI:10.1534/g3.116.032227
http://www.g3journal.org/content/6/11/3467

Geography and ecology are key factors that have influenced the genetic makeup of human groups in southern Africa, according to new research discussed in the journal GENETICS, a publication of the Genetics Society of America. By investigating the ancestries of twenty-two KhoeSan groups, including new samples from the Nama and the ≠Khomani, researchers conclude that the genetic clustering of southern African populations is closely tied to the ecogeography of the Kalahari Desert region.

A Nama man holding whip outside his tent while herding sheep and goats in the Richtersveld, South Africa. Photo courtesy of Justin Myrick.

The name KhoeSan refers to several indigenous populations in southern Africa; KhoeSan people speak “click” languages and include both hunter-gatherer groups and pastoralists. They are genetically distinct and strikingly isolated from all other African populations, suggesting they were among the first groups to diverge from the ancestors of all humans. Much scientific interest has focused on the KhoeSan as researchers try to reconstruct this early divergence; however, little genetic material was collected until the past decade.

Brenna Henn, of Stony Brook University in New York, has been studying southern African population genetics for over a decade. She notes that there is a tendency to lump all indigenous southern Africans into a single group – often called “Bushmen” – but in fact, the KhoeSan includes many distinct populations. She and her team set out to explore genetic diversity in the area and to better understand the differences between these KhoeSan groups.

“For the last twenty years or so, there has been a lot of interest in understanding how genetic patterns are determined by geography in addition to language,” says Henn. The genetic differences between human populations are strongly correlated with their linguistic histories, and both of these factors are also linked with geography. Henn argues that ecology and geography together are likely a better explanation for the genetic differentiation between groups than either linguistic differences or method of subsistence (i.e. hunting/gathering or farming). However, much of the research on southern African populations had previously focused on linguistics and subsistence, with little attention paid to ecogeography.

Henn and her colleagues analyzed genetic information from the KhoeSan. They collected genome-wide data from three south African populations: the Nama, the ≠Khomani San, and the South African Coloured (SAC) group. Their analysis also included samples from 19 other southern African populations. It quickly became apparent that the geography of the Kalahari Desert was closely tied to the population structure that they uncovered. The outer rim of the Kalahari Desert presented a barrier to genetic mixing, while populations that live within the Kalahari basin mixed more freely.

Their findings suggest a more complex history for the KhoeSan populations than originally predicted. Previous work argued for a northern vs. southern divergence pattern among the human groups, but this new work identifies five primary ancestries in the region, which points to a geographically complex set of migration events responsible for the heterogeneity observed in the region.

Henn points out that there are more KhoeSan populations who were not sampled. Sampling in the area is a significant challenge for a number of reasons, including the complex politics of the region in the post-Apartheid era. Most populations in South Africa and Zimbabwe no longer identify as KhoeSan and have been absorbed into other populations over the past 500 years. Still, their findings add to the body of knowledge surrounding the history of southern African populations – while also complicating them.

“There are a lot of threads of information to bring together – linguistics, subsistence, geography, genetics, archaeology. They don’t always reconcile easily,” says Henn.

View of arid mountains at dusk in the Richtersveld Community Conservancy, South Africa.

The challenge continues to fascinate Henn and her colleagues. She established a field site in 2005 and has maintained and expanded it over the years as she continues to research ancestry in the KhoeSan. She emphasizes that it is extremely important for investigators doing research in developing countries to work closely with local collaborators as they try to understand the genetic diversity of the region.

“The first author on this paper, Caitlin Uren, is a South African student. I’m very proud of our collaboration and her excellent work,” says Henn.

Much work remains to be done in understanding and uncovering the factors that contributed to the formation of southern African population structure.

“There is a huge amount of diversity in southern Africa populations. These groups speak differently, look distinct, and have divergent genetic histories. They are not homogenous people, and the historic and prehistoric factors that led to their divergence are still being explored. It’s amazing how much work there is to do.”

CITATION

Uren, C., Kim, M., Martin, A.R., Bobo, D., Gignoux, C.R., van Helden, P.D., Möller, M., Hoal, E.G., Henn, B.M. 2016. Fine-Scale Human Population Structure in Southern Africa Reflects Ecogeographic Boundaries. GENETICS, 204(1): 303-314. doi: 10.1534/genetics.116.187369 http://www.genetics.org/content/204/1/303

Guest post by Julia Kreiner. #TAGC16 Shorts are brief summaries of presentations at The Allied Genetics Conference, a combined meeting of seven genetics research communities held July 13-17, 2016 in Orlando, Florida.

A common perception of evolution sees only slow and consistent genetic change over thousands of generations. But geneticists are increasingly shedding light on examples of evolution over ecological timescales — genes tracking changes in the environment. At The Allied Genetics Conference, Emily Behrman (University of Pennsylvania) revealed that adaptation can occur even faster than we may have expected. Her findings show changes in the frequency of Drosophila life history phenotypes and the underlying genes are associated with changes in selection pressures between seasons.

In Behrman’s long-term data set, allele frequencies and the fitness of phenotypes change seasonally, on a scale comparable to the differences caused by living in distant geographic regions. During the summer, phenotypes that can exploit the undemanding conditions are favored, but winter selects for those that can best withstand harsher conditions. This is seen as stabilizing selection over years. Traditional examinations that use such longer time scales would detect only stabilizing selection, masking the finer scale fluctuating dynamics. Behrman interprets these dynamics of selection as playing an important role in maintaining variation in natural populations. This principle is likely true not only in fruit flies but across a wide variety of taxa.

Allele frequency change at ∼1750 seasonal SNPs. From Bergland et al.

TAGC Program number P332

Dynamics of seasonal adaptation in Drosophila melanogaster.

Emily L. Behrman¹, Alan O. Bergland^2,3, Dmitri A. Petrov², Paul S. Schmidt¹.

1) University of Pennsylvania, Philadelphia, PA; 2) Stanford University, Stanford, CA; 3) University of Virginia, Charlottesville, VA.

Further reading:  http://onlinelibrary.wiley.com/doi/10.1111/jeb.12690/abstract

About the author: Julia Kreiner is a graduate student at University of Toronto studying the rapid adaptation of herbicide resistance, a burnt out athlete, and a nature lover.

When it comes to genotyping technology, poop genetics is stuck in the 1990s. While most geneticists are now awash in genome-scale data from thousands of individuals, those who depend on  fecal and other non-invasively collected samples still rely on old-school, boutique panels of a dozen or so genetic markers.

But feces — along with fur, feathers, and urine — is critically important stuff for understanding the population genetics, ecology, evolution, behavior, and conservation of wild animals. Many are too elusive or endangered to allow collection of blood samples, and even for common species it is a logistical nightmare to immobilize and draw blood from large numbers of animals in the field. In the latest issue of GENETICS, Snyder-Mackler et al. describe tools that promise to advance studies of such samples into the genomic era.

Patrick Chiyo collecting noninvasive samples from elephants in Amboseli National Park. Photo courtesy Jenny Tung.

Noninvasively collected samples have the obvious advantage of easy access. “We have freezers and freezers full of baboon poop,” says study co-leader Jenny Tung (Duke University). Tung’s group works on behavior and  genetics in a wild baboon population in Kenya. But though abundant, poop also presents serious challenges for standard genetic analysis. The DNA present in noninvasive samples is typically a fragmented mixture of host and contaminant sequence. For example, only around 1% of the DNA in a fecal sample comes from the animal that produced the poop. Most of the rest is microbial.

These limitations were first overcome in the 1980s and 1990s, and the ability to analyze DNA from noninvasive samples revolutionized the field. Using such samples not only allowed geneticists to understand the genetic diversity and viability of endangered animals, it allowed them to empirically test important theories about animal behavior and evolution.

“There are many examples. Noninvasive sampling of chimps, baboons, rhesus macaques and other primates revealed that animals really do bias their behavior towards relatives, even paternal relatives that are likely more difficult for an individual to identify as kin,” says Tung. “And in baboons, it also showed that males provide some paternal care to their offspring, which wasn’t expected for a polygamous primate.”

But the genotyping methods used in such studies have changed surprisingly little over the last twenty years. For the most part, researchers still use small groups of carefully validated markers, usually based on stretches of short tandem repeat sequences (microsatellites). This means the field has mostly missed out on the benefits of genomics that have become routine for medical researchers and those who work with laboratory organisms.

“Microsatellite approaches still work. But over the last 5 or 10 years it has become impossible to ignore the way genome-scale datasets allow you to answer entirely different questions,” says Tung.

For example, data on how a genome varies across a population can provide crucial evidence of the evolutionary and demographic forces that have shaped it. Genomic data can also trace in detail the mergers and separations of mixing populations.

Vet, a female yellow baboon, and her children in Amboseli National Park. Photo courtesy Susan Alberts.

The good news for poop genomics is that short-read next-generation sequencing methods are well suited to the fragmented DNA found in noninvasive samples. These methods have been famously adapted for analyzing a sample type that also suffers from vanishingly small amounts of target sequence: ancient DNA. The bad news is that the expensive, intensive approaches that work well for a precious sample of Neanderthal bone are not practical for a geneticist facing a freezer full of poop.

About six years ago, Tung’s friend and colleague George (PJ) Perry published a major advance that allowed large-scale resequencing from noninvasive samples. It was based on a method known as sequence capture, which enriches for host sequence using synthetic RNA “baits” to capture the target DNA. Tung was excited by the possibilities of the methods, but realized it was still too expensive for most applications. This was partly because the baits had to be custom-designed and synthesized for the species of interest. The method also had the drawback of only capturing a tiny fraction of the genome, while consuming large amounts of sample.

“Even fecal samples are exhaustible,” says Tung. “We have a lot of irreplaceable samples from dead animals, for instance. If we’re going to use them up, we want to cover all our bases and gather data on a truly genome-wide scale.”

So Tung’s group and their collaborators worked to modify and scale up Perry’s protocol. They also constructed the baits in a considerably cheaper way, using in vitro transcription of RNA from baboon DNA templates, sidestepping the need for custom synthesis. The new protocol had more modest input DNA requirements and could enrich the target DNA by 40-fold.

But getting enough sequence per sample was just the beginning. Xiang Zhou (University of Michigan) led the group’s efforts to develop tools to analyze data from the new method. Zhou says one of the reasons microsatellites became so popular was the availability of standard and easy-to-use software for assigning paternity from the data. “If people are going to transition to a new method, we thought it would be incredibly important that we package our models into software that will make it as easy as possible,” says Zhou.

But to develop something comparable for low-coverage sequence, the team faced two major challenges: the data is simultaneously much richer (more sequence) and much lower quality (more uncertainty). To deal with the large quantity of data they needed much more computationally efficient algorithms. They also had to factor in the lower data quality, which makes it  impossible to use the simpler approaches that work when the genotype at each site is known with certainty. Instead, they incorporated the error rate across all the sites in the genome, generating a sophisticated statistical model.

One of (several) freezers in the Tung lab containing boxes of fecal samples. Photo courtesy Jenny Tung.

Using the new capture method and the paternity assignment software (called WHODAD), the team were able to construct pedigrees from baboon fecal samples that almost perfectly  matched those created using traditional analysis of high-quality DNA from blood. In short, despite the low coverage of the genome (typically less than 1x), and the resulting very high uncertainty of the genotype at any one site, the trends in the data were more than enough to reconstruct family relationships.

But what about cost? Lead author Noah Snyder-Mackler gave the project the pet name “fecal alchemy” because it aims to transform poop into a data goldmine. But not every researcher can afford gold — most labs must use the cheapest tool that will get the job done. Tung says they included a cost analysis in the paper because they are regularly asked about the price of making the switch.

“Right now it costs about twice as much to produce 1x coverage of the entire baboon genome as it does to type 14 microsatellites. But the amount of information you get is much greater! So if you’re thinking in terms of cost per genotype, our method is way more cost effective. But in terms of absolute amounts it’s more expensive. In the end the cost-benefit decision depends on what questions you’re trying to answer,” says Tung. “Of course we’d like to get it even cheaper and more efficient and more robust. We’re working on it!”

FUNDING

This work was partly funded by the National Science Foundation DEB through an EAGER grant, with co-funding from NSF Biological Anthropology.

CITATION

Noah Snyder-Mackler, William H. Majoros, Michael L. Yuan, Amanda O. Shaver, Jacob B. Gordon, Gisela H. Kopp, Stephen A. Schlebusch, Jeffrey D. Wall,Susan C. Alberts, Sayan Mukherjee, Xiang Zhou, Jenny Tung (2016). Efficient Genome-Wide Sequencing and Low-Coverage Pedigree Analysis from Noninvasively Collected Samples. Genetics, 203(2), 699-714.

http://www.genetics.org/content/203/2/699

DOI: 10.1534/genetics.116.187492

Amphibians around the world have been devastated by the spread of the deadly fungus Batrachochytrium dendrobatidis (Bd). But although many populations have been decimated, others have survived the same threat. One reason for such different outcomes is variation in virulence between Bd isolates. In the latest issue of G3, Refsnider and Poorten et al. investigate Bd virulence changes by taking advantage of the rapid evolution that can take place in the lab.

The authors studied a strain isolated in 2005 from an infected frog found in the El Yunque rainforest, Puerto Rico; one isolate was frozen soon after, while a second isolate was maintained in laboratory culture for six years. Today, the isolate that has grown used to lab life is significantly less lethal to frogs. Studying the genetic basis of this shift may shed light on how virulence is attenuated in the wild, particularly because many of the confounding factors inherent in natural systems can be controlled for by comparing two isolates from a single lineage.

The authors resequenced the pair of isolates to look for genomic changes underlying the phenotype difference. They found that the two strains had diverged at a rate of 1.6 x 10^-5 mutations per site per year, which is faster than most fungi but similar to other fungal pathogens. The less virulent isolate had lower chromosomal copy numbers than its wilder cousin, suggesting one way that virulence can be rapidly lost. The extra chromosome copies needed for virulence may become costly to the pathogen once normal selection pressures have been relaxed.

The speed of Bd’s change in the lab suggests this pathogen is capable of rapid adaptation to new conditions, consistent with its alarming spread across habitats and continents.

CITATION

Refsnider, J. M., Poorten, T. J., Langhammer, P. F., Burrowes, P. A., & Rosenblum, E. B. (2015). Genomic Correlates of Virulence Attenuation in the Deadly Amphibian Chytrid Fungus, Batrachochytrium dendrobatidis. G3: Genes| Genomes| Genetics, 5(11), 2291-2298 doi:10.1534/g3.115.021808

http://www.g3journal.org/content/5/11/2291.full

Directly observing evolution in nature is often impossible. But biologists who use experimental systems to study these processes have the luxury of observing the fine details directly, controlling the conditions, and even replicating the results. In the age of genomics, experimental approaches to ecology and evolution have become particularly powerful for genetic model systems, including yeast, bacteria, and fruit flies.

In the latest issue of G3, Gasch and Yvert report on the third EMBO-sponsored conference on Experimental Approaches to Evolution and Ecology Using Yeast and Other Model Systems, hosted at the European Molecular Biology Laboratory (EMBL) in Heidelberg, Germany, October 12–15, 2014. The meeting covered a wide array of evolutionary and ecological systems, from experimental evolution in yeast to Drosophila genetics, phytoplankton phylogenomics, and microbial interactions in a mammalian host. Themes that emerged from the meeting included the prevalence of aneuploidy in evolution, the role of epistasis in shaping evolutionary trajectories, selection on protein translation, and the importance of ecological interactions.

This article is the first G3: Genes|Genomes|Genetics Meeting Report. Meeting Reports provide an overview of recent scientific meetings related to genetics and genomics and are typically authored by meeting organizers and/or select participants. G3 Meeting Reports are published by invitation only. If you have a presubmission inquiry for a particular meeting, please contact g3-gsa@thegsajournals.org.

Gasch, A. P., & Yvert, G. (2015). MEETING REPORT on Experimental Approaches to Evolution and Ecology Using Yeast & Other Model Systems. G3: Genes|Genomes|Genetics June 2015 5:1021-1023; doi:10.1534/g3.115.018614 http://www.g3journal.org/content/5/6/1021.full