GSA President Hugo Bellen announces a new seminar series on tools and resources for exploring gene function across organisms. 

Some of us are worried about the future of the research enterprise, especially funding support for science in our favorite model organism. Why worry? One of the main drivers of this concern is that some believe our work is not directly relevant to human biology. This is often based on the idea it is difficult to quickly translate basic discoveries into directly applicable medical paradigms. Yet, the model organisms that many of us study have been the driving force for most biomedical discoveries. More than 90% of the Nobel prizes in Medicine or Physiology in the past 40 years have been awarded for research carried out in model organisms such as mice, rats, Xenopus, worms, and flies. These include the discovery of monoclonal antibodies (mouse), RNAi technology (worms), CRISPR technology (bacteria), cell cycle and cancer (yeast), signaling pathways, and development (flies), and so many others. Such discoveries in fundamental biology have propelled advances in medicine, and I believe they will remain at the forefront.  

Genetics offers numerous important features for such advances, because genetic manipulations are the most elegant type of manipulations for answering biological questions. Is there a less intrusive experiment than changing a single nucleotide among millions or billions of bases and asking: what are the in vivo consequences? The answer is a flat no in my opinion! 

Despite the obvious relevance of our work to human biology, some are averse to a human-centric vision of research for good reasons, as nicely illustrated by the examples above. Diseases should not per se dictate our research because we don’t yet know where the next breakthrough will come from. Serendipity and curiosity are major players in discovery. 

Yet, I see no reason not to search for a middle ground. This is especially the case in the area of genetics, as the evolutionary conservation of genes and their function has been critical to understanding most biological processes across organisms. Forward genetic screens and evolution-based studies in model organisms have led, and will continue to lead, to discovery of many basic aspects of biology as they are unbiased and probe a very diverse set of biological functions.  

Doing biological research is not always a forced choice between creating fundamental knowledge or developing targeted medical applications. Both outcomes can result from the same efforts. Indeed, human genetics has advanced basic biology, from Archibald Garrod helping renew the understanding of Mendel’s laws by studying a rare disease, to prion biology revealed by Creutzfeldt-Jakob disease. The last ten years have seen remarkable changes as another set of scientists—human geneticists—have joined the cohort of screeners. They, like many of us, observe phenotypes (of patients) and attempt to identify the causative genes.  This approach has gained tremendous strength with the ability to sequence all exomes (WES) and genomes (WGS). WES or WGS of an affected individual and a few direct family members allows the identification of variants in one or a few genes that may be causative, especially for very rare diseases. 

Surprisingly, more than 50% of the orthologues of these genes have been poorly characterized in vivo in any organism, leaving a wide knowledge gap. Because an estimated 6,000–13,000 rare disease associated genes remain to be discovered, we have a full plate of genes and variants to tackle. Note that more than 80% of new human disease genes that have been discovered in the past few years are conserved in worm, flies and, more obviously, in vertebrates.

How can a scientist study the function of these genes, especially when the phenotypes associated with the loss of these genes in model organisms may be more subtle than many of the genes that have been characterized already? One productive approach is to generate clean loss-of-function tools using state-of-the-art genetic technologies and then to perform systematic phenotyping at many different levels, including transcriptomics, metabolomics, histological screens, as well as behavioral screens of the many collections of mutants available in yeast, worms, flies, fish, and more recently, mouse. 

Another approach is to team up with other model organism researchers who are performing similar screens and share data to identify genes and pathways to help define their function. 

A third approach is to identify researchers who are attempting to define the function of certain genes based on their scientific interest but are not even aware that others are interested in orthologues in other species.  The latter challenge can now be solved if open communication and collaborative ventures are explored at the onset. For example, a human geneticist may identify an evolutionarily conserved gene that has been poorly characterized in model organisms and may be interested in collaborating with a model organism researcher. Alternatively, a model organism researcher may have identified a conserved gene and wonder if a human geneticist has identified patients that carry variants in the orthologous human gene. Recent databases and online platforms now allow scientists to explore these unpublished data, connect, and explore or initiate collaborations.  These include GeneMatcher, ModelMatcher, and numerous international ventures designed to match researchers and clinicians with common interests. 

GSA is exploring ways to introduce the model organism community to these approaches.  In addition, there are now many databases that attempt to centralize knowledge from many model organisms to help geneticists explore gene function across evolution, such as the Monarch Initiative and the Alliance of Genome Research, as well as databases to integrate clinical and scientific databases such as MARRVEL. GSA will organize a series of seminars this year to introduce these opportunities and provide tips and tutorials to help explore the available websites and databases. We believe that these seminars will be useful to investigators at all career stages and across different model organisms, as well as for human biologists. We hope this will add a new dimension to research, reveal unanticipated phenotypes, speed up discovery, allow new funding opportunities, and lead to the discovery of new fundamental aspects of biology. 

Sign up for the Seminars Now!

The recipient of the 2018 Crow Award reveals details of flu evolution at the smallest —and largest—scales.

For many viral diseases, a vaccine can provide lifelong protection. But for flu, you need a new shot every year. The influenza virus evolves so fast it presents a constantly moving target for both our immune systems and public health authorities, fueling epidemics like the particularly bad season we just endured. With over 30,000 people hospitalized in the United States alone this season, the flu provides a dramatic reminder of the importance of understanding evolutionary dynamics.

Katherine Xue, a graduate student at the University of Washington, is revealing the mechanics of influenza evolution on scales ranging from an individual person up to the entire planet. Xue was awarded the 2018 James F. Crow Award for Early Career Researchers for her doctoral work on the subject after a presentation at the Population, Evolutionary, and Quantitative Genetics Conference in May.

In a special session of talks by Crow Award finalists, Xue spoke about using deep sequencing to examine diversity in flu virus populations.

“Up until recently, we were only able to look at the average genetic identity across the millions or billions of flu viruses in a single infection,” says Xue. “We’ve used deep sequencing to show that within a single infection there are fast evolutionary dynamics that have been invisible to previous technologies.”

Xue approaches clinical topics with the conceptual tools developed by evolutionary and population geneticists. Linking ideas across fields is characteristic of Xue, says her mentor Jesse Bloom (Fred Hutchinson Cancer Research Center / University of Washington), whether it’s between medicine and evolutionary theory or between science and the humanities.

“What makes Katherine stand out is her ability to think about big scientific concepts and connect ideas,” says Bloom. “She’ll see and connect ideas in ways that I can’t.”

Viral cooperation

When Xue first rotated in Bloom’s lab, she was working on a molecular virology project about how a particular viral protein binds to a cell. In the course of examining sequence databases, she noticed the mutation she was studying was often ambiguously annotated.

Inspired by this hint of population diversity, she wondered whether the two viral variants might interact with each other. She was able to establish that the mutation tended to occur alongside the wild type version within a population; the mutation was deleterious to virus reproduction on its own but beneficial when mixed with wild-type. This example of cooperation suggests that interactions between different variants within flu populations can be important factors in virus evolution.

A glimpse of evolution in action

But can evolution be detected within the virus population of a single individual? Xue was drawn to the question of how global flu evolution traces back to the founding infections in which each mutation must first arise.

“I was intrigued because it was hard to imagine how this works,” says Xue. “Flu infections are very short; there’s not a lot of time for a new mutation to reach frequencies large enough to ensure it makes it over to the next infected person.” In the language of population geneticists, flu populations are repeatedly subjected to extreme bottlenecks. But observing such rapid evolution in action is extremely challenging.

Xue and her colleagues in the Bloom lab used a unique approach to get around this problem. They partnered with clinicians Michael Boeckh and Steve Pergam at the Fred Hutchinson Cancer Research Center, who had collected samples from four immunocompromised patients over the course of their months-long flu infections. Deep sequencing these samples gave them an in-depth view of a process that would normally be finished within days in a person with healthy immune defenses.

“I initially had doubts that this project would show us anything interesting or be worth doing,” says Bloom. “But Katherine is very independent and persistent, and she kept going despite my occasional words of discouragement.”

The results were dramatic. Over the span of about two months, there was a substantial amount of flu evolution within each patient. Mutations arose regularly, fluctuated in frequency, and even became fixed in the population in a few cases. They also saw evidence that some of these changes are due to selection. The same mutations would often arise independently and then rise to substantial frequencies in multiple patients, suggesting these particular changes were adaptive.

Remarkably, the mutations that arose repeatedly in different patients were sometimes the same mutations that spread through the global flu population within the next decade. The immunocompromised patients seemed to be microcosms of global evolutionary patterns. “We were astonished,” said Xue.

Most of these recurring mutations affect the part of the flu haemagglutinin protein that is most recognized by the host immune system, so the team hypothesizes that the changes help the flu escape host defenses.

These results raise many questions about how evolutionary dynamics interact across scales. How far do the conclusions generalize? Where and when do natural selection and genetic drift act? How do normal week-long infections generate enough diversity to fuel rapid global evolution? Could understanding these processes translate to better flu season predictions? Xue’s graduate research continues to explore flu evolution with these questions in mind.

Connecting ideas

The scientific big picture is never far from Xue’s mind, it seems. Alongside her thesis research, Xue is pursuing a certificate in science and technology studies, with a capstone project on the history of flu research. “I have really loved being part of the history, philosophy, and sociology of science community here,” she says. “It’s given me a lot of perspective that has been really enriching.”

A few years ago Xue helped start the UW Genomics Salon, which is a group of students and postdocs who take part in freeform discussions about the intersections of science and society. These discussions touch on policy, advocacy, communication, education, representation, law, art, and a host of other topics.

Bloom thinks Xue’s broad interests are yet another reflection of her creativity and ability to link ideas across fields. Before graduate school, she spent a few years working as a science writer for the Harvard Magazine. “She’s an exceptionally good science communicator and very dedicated to creating connections between science and other fields. It’s pretty awesome to have someone like that around!”

[youtube https://youtu.be/fTdaAwqdt0k&w=500&rel=0]

Watch #PEQG18 presentations from all the other  outstanding finalists for the Crow Award here.

Identifying signatures of polygenic adaptation is getting easier—but a commentary calls for caution in drawing conclusions.

If you’ve ever wished for a stepstool so you could see the stage at a crowded concert, or, conversely, if you’re tired of being asked “How’s the weather up there?”, you’ve likely pondered what makes some of us tall and others short. You’re in good company; geneticists have been thinking hard about height since the dawn of the field.

Height is a classic example of a polygenic trait, meaning that its genetic component is dictated by the combined action of many genes and genetic loci acting together in a complex way. With the advent of new techniques, analyzing the evolution of these complex traits is becoming easier. But a new Commentary in GENETICS by editors John Novembre and Nick Barton cautions that such studies are ripe for misinterpretation by the public and policymakers—particularly when it comes to human traits more controversial than our height.

The Commentary was prompted by a useful new method reported in the same issue of GENETICS. This technique, developed by Racimo, Berg, and Pickrell, helps geneticists analyze how polygenic traits like height have adapted and changed over the course of evolution.

Through heritability studies, linkage analyses, and genome-wide association studies (GWAS), we now have a reasonable view of which genetic loci contribute to determining a person’s height. But piecing together how selection shapes such traits is much more complicated than studying how a single-gene trait evolves. In some cases, a trait responds to selection by a big change in the frequency of a single variant that strongly affects that trait. Other times, however, the trait adapts via the added effects of many tiny adjustments—small changes in frequency of many variants that subtly affect the trait in question. This phenomenon is known as polygenic adaptation.

While these subtle changes are too weak to have been picked up by more classical methodology, GWAS has made it possible to identify SNPs associated with polygenic traits, and it provides the power to detect small-effect variants. Comparing SNPs across populations can identify the signature of selection, and the new method does just that.

The authors use admixture graphs—a simplified representation of how populations have mixed and diverged over time—to explore the adaptation of over 40 traits measured in previous GWAS, finding preliminary evidence for selection on variants associated with height, self-reported unibrow, and educational attainment (years of schooling). By combining GWAS data with the known history of the populations in question, the authors were able to identify when in evolutionary history the selective pressures were most likely applied—they can pinpoint which branch of the graph shows signs of selection. That they found a signal for the polygenic adaptation of height is consistent with previous studies; however, the signals for self-reported unibrow in European populations and educational attainment in East Asian populations were more surprising.

What are we to conclude from these data? It’s tempting to make assumptions about the type of selective pressure acting on these traits and what the data say about fitness—especially when a trait like “educational attainment” is under discussion. But Novembre and Barton—together with the authors of the study—urge extreme caution in leaping to conclusions.

The editors provide context for interpreting any tests for polygenic adaptation, including those of Racimo, Berg, and Pickrell, critically urging care and attention when drawing conclusions from such data and communicating the implications. First, they discuss technical concerns like population stratification, transferring effect sizes, ascertainment bias, and accurate population modeling. Second, they remind us that it’s a difficult task to untangle the relationship between a trait that we can measure and a fitness advantage; it is misleading to assume that height itself, which we can measure, is directly conferring a fitness advantage such as increased survival or finding a mate. As in many areas of science, precision in language is key here: the Commentary points out that Racimo, Berg, and Pickrell also stress the many caveats of this type of analysis and choose their words carefully, discussing the signs of selection on loci associated with the studied traits—not on the traits themselves. Indeed, the target of selection may not be the actual trait measured in GWAS, but something genetically correlated with it.

While geneticists are getting a better view of the genetics behind complex human traits, it’s easy to sow confusion outside the field. Getting clear about what new data do and don’t say is the crucial first step in preventing our insights being misused.

CITATIONS

Detecting Polygenic Adaptation in Admixture Graphs
Fernando Racimo, Jeremy J. Berg and Joseph K. Pickrell
GENETICS April 2018. 8(4): 1565–1584.
DOI: 10.1534/genetics.117.300489
http://www.genetics.org/content/208/4/1565.full

Tread Lightly Interpreting Polygenic Tests of Selection
John Novembre and Nicholas H. Barton
GENETICS April 2018. 8(4): 1351–1355.
DOI: 10.1534/genetics.117.300786
http://www.genetics.org/content/208/4/1351.full

The mitochondria powering your cells are not all genetically identical. Genetic variation across the mitochondria of a single individual is common. This diversity is called mitochondrial heteroplasmy, and it plays an important role in the severity of mitochondrial disease. Problematically, the complexities of mitochondrial inheritance makes it extremely difficult to predict how this diversity is transmitted between generations or cells.

In a report in GENETICS, Wilton et al. developed a mathematical model of mitochondrial heteroplasmy. Using previously published data, as well as a statistical framework based on population genetic principles, their model was able to account for observed diversity in mitochondria.

This model highlights how heteroplasmy is regulated by developmental bottlenecks: For example, because mitochondria are passed on mother-to-child, the random sample of mitochondria present in the mother’s egg cells determine the genetic makeup of mitochondria in her offspring—just like founder’s effect in classical population genetics. The authors also find evidence of less severe bottlenecks during the formation of distinct germ layers and organs; any time a cell or a small subset of cells gives rise to a larger structure during development, the mitochondria present in those first few cells set the mitochondrial heteroplasmy of the resulting organs.

The authors acknowledge that their model is preliminary. It doesn’t take into account any kind of quality control during the formation of egg cells that would change which mitochondrial mutations are passed on. Still, this model is an important starting point. It could be used to examine how natural selection plays out at the level of mitochondria, which in turn could help us better understand mitochondria-associated diseases and aging. It could even prove useful beyond heteroplasmy: cancer is another kind of genetic heterogeneity within a single person, and a similar approach could be used to investigate the bottlenecks and other factors that shape the evolution of a tumor.

CITATION

A Population Phylogenetic View of Mitochondrial Heteroplasmy 

When a mutation arises in an egg or sperm cell, it could be evolutionarily important. But if a mutation occurs in somatic tissue instead, the result could be cancer. Mutations in the germline and soma not only have contrasting consequences, they also arise at different rates that may reflect the balance of DNA damage and repair pathways in different tissue types. In the September issue of GENETICS, Chen et al. predict gene mutation rates in different tissues and find that high expression increases mutation rates in the germline, but not in somatic tissue.  

The first step was to obtain a reliable estimate of the mutation rate in both germ cells and somatic tissues. The researchers relied on a set of germline mutations, previously identified using exome data from thousands of sets of parents and children. Any variation that was unique to the children must be caused by germline mutation in either the father or mother. To identify somatic mutations, the researchers analyzed three different cancer samples that included whole exome sequence of both normal and malignant cells. Variation unique to either tissue type predates the tumor and should be due to somatic mutations.

A statistical model that evaluated how well various factors predict the mutation rate revealed a key difference. In germ cells, a high gene expression level was linked to a higher mutation rate, but the opposite was observed in somatic tissues. Though the magnitude of the effect varied in the three different cancer types, there was always a negative correlation with expression. Other factors also contributed differently to mutation in the germline and somatic tissues, including GC content for the germline and replication timing in the soma.

Gene expression level probably affects mutation rate because the DNA double helix unzips to accommodate transcription machinery, making the individual strands more vulnerable to mutagens, and because there is a dedicated repair mechanism to fix DNA damage that occurs in transcribed regions. The opposite effects of expression level on mutation rates suggests germline and somatic tissues have marked differences in the balance between damage and repair. For example, expression may be more mutagenic in the germline, or repair mechanisms may be more efficient in the soma. There could even be unidentified DNA damage repair processes that are unique to certain tissues. Though somatic mutations can’t be passed down to the next generation like germline mutations, they are the root cause of most cancers. Quickly and correctly repairing this DNA damage is vital for an organism’s survival.

CITATION:

Contrasting Determinants of Mutation Rates in Germline and Soma

Chen Chen, Hongjian Qi, Yufeng Shen, Joseph Pickrell, and Molly Przeworski

GENETICS September 1, 2017. 207 (1): 255-267

https://doi.org/10.1534/genetics.117.1114

http://www.genetics.org/content/207/1/255

Despite being covered by a massive, permanent ice sheet, Greenland has been continuously inhabited by humans for over a thousand years. Most modern Greenlanders are Inuit whose ancestors migrated eastward from Canada around 1000 AD, bringing technology like kayaks and dogsleds. They eventually settled on the coasts of the world’s largest island, hunting whales and seals. As well as their cultural and historical contributions, the people of Greenland carry important information in their genes. A study by Pedersen and colleagues published in the February issue of GENETICS examines variation in whole exome sequences of 18 Greenlandic Inuit individuals, showing the power this unique population could have for identifying rare genetic variants linked to diseases.

The patterns of genetic variation in any group of organisms, including humans, are closely tied to its size and history. The larger a population, the more genetically diverse it should be, and a migrant population will be less diverse than its source since its genetic diversity is a subset of the larger source population. Human populations from Africa are the most genetically diverse of all because their ancestors were the source for all other groups that migrated out of Africa to populate the rest of the world.

The ancestors of the Greenlandic Inuit journeyed most of the way around the world to get from equatorial Africa to the fringes of the Arctic Circle in Greenland: through Asia and across the Bering Strait to North America, and then across vast northern Canada to Greenland. This epic migration and settlement history is reflected in their genomes. Pedersen and colleagues show that the Greenlandic Inuit population has recently undergone a prolonged bottleneck of around 20,000 years, making it one of the historically smallest and most isolated human populations. When compared to much larger populations, the patterns of variation differ in specific ways.

The study found that Greenlandic Inuit have fewer genetic variants overall than other human populations tested so far, but the variants they do carry occur at higher frequencies. This might reflect the prediction that very small populations see increases in deleterious variation since natural selection is less effective in small groups. To explore this idea, the authors estimated how much of the genetic variation in the Greenlandic population is likely to alter protein function, including potential loss-of-function alleles and variants that alter the amino acid sequence of a protein. However, the evidence was conflicting, and the results depended strongly on the type of model used.

Nevertheless, the increased frequency of certain rare variants compared to other groups could prove a boon for disease association mapping by increasing the statistical power to detect links between gene variants and human diseases. One example is a single nucleotide change in the gene TBC1D4, which has been previously linked to type 2 diabetes. This particular allele is found at a much higher frequency in the Greenlandic Inuit population than other surveyed populations, even though type 2 diabetes is not reported to be more common in Greenland. The authors speculate this difference may be due to compensatory variation elsewhere in the genome since type 2 diabetes is a multigenic trait with many underlying contributing factors. In contrast, sucrase-isomaltase deficiency, a metabolic disease that prevents infants from digesting a certain sugar, is very rare in most populations but affects about 5–10% of people in Greenland. The exome data suggests this is due to the relatively high frequency of a particular frameshift mutation in the SI gene.

By any measure, Greenland is an isolated place. The people who first settled there used their creativity and ingenuity to flourish in a difficult environment, the same way humans have all over the Earth. Though genetic patterns differ subtly between groups, the deeper similarities show how closely humanity is connected. Thanks to this shared heritage, small differences between populations can serve as powerful tools for unearthing discoveries that will help us all.    

Pedersen, C. E. T., Lohmueller, K. E., Grarup, N., Bjerregaard, P., Hansen, T., Siegismund, H. R., Moltke, I., & Albrechtsen, A. (2016). The Effect of an Extreme and Prolonged Population Bottleneck on Patterns of Deleterious Variation: Insights from the Greenlandic Inuit. GENETICS, 205 (2): 787-801. DOI:10.1534/genetics.116.193821

http://www.genetics.org/content/205/2/787

A genomic analysis of 28 dog breeds has traced the genetic history of the remarkable Fonni’s Dog, a herd guardian endemic to the Mediterranean island of Sardinia. The results, published in this month’s issue of GENETICS, reveal that the regional variety has developed into a true breed through unregulated selection for its distinctive behavior, and that its ancestors came from the very same geographic areas as Sardinia’s human migrants. Just as Sardinian people have long provided a wealth of genetic insights to scientists, the canine natives are an example of an isolated population that could prove a powerful resource for finding genes that influence health and behavior.

Fonni’s Dogs (Cane Fonnese in Italian) are large, rugged dogs known for their wariness towards strangers and their intense facial expression. Although there are descriptions of these shephard’s companions dating to at least the mid-nineteenth century, it is not officially recognized as a breed by most international registries, including the largest federation of kennel clubs, the Federation Cynologique Internationale.

“If you were to look at ten Fonni’s Dogs, you would see there’s a lot of variation in coat color and fur length. But they are all good protectors of their flocks. That’s because nobody cares what they look like; they’ve been bred to do a job and to do it right,” says study leader Elaine Ostrander of the National Human Genome Research Institute (NHGRI).

The Fonni’s Dog (Cane Fonnese or Sardinian Sheepdog) is endemic to Sardinia and is known for its fiercely protective guarding behaviors. Photo credit: Stefano Marelli

That job is guarding the possessions of their owner, to whom they are fiercely loyal. “Fonni’s are also outstanding thieves,” says Ostrander. “They can be trained to sneak over to the neighbors’ and bring items home.” While this particular duty isn’t required by today’s Fonni Dogs, written records from the mid-1800’s indicate that thievery was part of their historical repertoire.

The island home of the Fonni’s Dog has long held the interest of geneticists. Because Sardinia is geographically isolated, its human inhabitants share a unique ancestry and relatively low genetic diversity. Those characteristics make it easier to study genetic influences on disease and aging in Sardinians than in other human groups. Ostrander and other canine geneticists argue that each of the hundreds of different dog breeds also represents an isolated population that could be harnessed for genetic studies.

“Dogs get all the same diseases as humans, and there are lots of dog breeds with genetic predispositions, for example to particular types of cancer,” Ostrander says. “Once we understand the genetic history of a breed we can search for disease genes in a much more powerful way than is possible in humans, enabling us to hone in on medically-relevant genes.”

To better understand how the Fonni’s Dog developed, scientists from the NHGRI, the University of Milan, and G. d’Annunzio University analyzed blood samples from Fonni’s Dogs living in different parts of Sardinia and sequenced the whole genome of one of these dogs. To trace the Fonni’s relationship to dogs from around the Mediterranean, the team compared the data to DNA from 27 other European, Middle Eastern, and North African breeds.

This diagram indicates the geographic origin of the 28 dog breeds studied. Abbreviations: Anatolian Shepherd, ANAT; Azwahk Hound, AZWK; Berger Picard, BPIC; Bouvier des Flandres, BOUV; Cane Corso, CANE; Cane Paratore, CPAT; Cirneco dell’Etna, CIRN; Fonni’s Dog, FONN; Great Pyrenees, GPYR; Ibizan Hound, IBIZ; Istrian Shorthaired Hound, ISHH; Italian Greyhound, ITGY; Komondor, KOMO; Lagotto Romagnolo, LAGO; Levriero Meridionale, LVMD; Maltese, MALT; Mastino Abruzzese, MAAB; Neapolitan Mastiff, NEAP; Pharaoh Hound, PHAR; Portuguese Water Dog, PTWD; Saluki, SALU; Sloughi, SLOU; Spanish Galgo, GALG; Spanish Water Dog, SPWD; Spinone Italiano, SPIN; Standard Schnauzer, SSNZ; St Bernard, STBD; Volpino Italiano, VPIN.

The data revealed that the Fonni’s dog shows all the genetic hallmarks of being a breed, even though it developed in the absence of a regulated pedigree program and only arose through the tendency of Sardinian shepherds to choose their best guard dogs for breeding. The researchers compared individual dogs from within the same breed and across different breeds, quantifying many aspects of genome variation and genetic distinctiveness. All these measures confirmed that the Fonni’s Dog, in genetic terms, is a breed.

The study also revealed the ancestors of the Fonni’s Dog were related to the Saluki, a swift and graceful “sight” hound from the Near and Middle East, and a large mastiff like the Komondor, a powerfully-built sheep guardian from Hungary that looks a bit like a mop.

Strikingly, the origins of the Fonni’s Dog mirror human migration to Sardinia. Studies of the island’s human inhabitants have shown they share greatest genetic similarity with people from Hungary, Egypt, Israel, and Jordan. “The map we can draw of the dog’s origins is the same as the map of human migration to Sardinia,” says Ostrander. “Clearly ancient people traveled with their dogs, just as they do now.”

The close parallels between the history of the dog and human inhabitants of the island has a practical implication, says Ostrander. “Our study shows how closely dog migration parallels human migration. It could be that if you have missing pieces in a study of a human population’s history, samples collected from dogs in the right place could fill in those gaps.”

Smooth-coated (left) and rough-coated (right) varieties of Fonni’s Dog. Genetic analysis confirms the varied appearance of the Fonni’s Dog masks the underlying unity of the breed. Photo credit: Luca Spennacchio

The team plans next to study in greater detail eleven regions of the genome that likely make the Fonni’s Dog distinct — these may be responsible for their characteristically loyal and protective behavior.

Ostrander points out the study was a collaborative effort with scientists from Italy, including Sardinia, and says she is gratified to find so many researchers across the world interested in similar questions. Her group is hoping to work with colleagues in a range of countries to explore other so-called “niche” dog populations, regional varieties that often have a history of being bred for a particular job. Their goals are to better understand how dogs have evolved and to demonstrate yet another important job for these faithful human companions: tracking down disease genes.

CITATION

Commonalities in Development of Pure Breeds and Population Isolates Revealed in the Genome of the Sardinian Fonni’s Dog

Dayna L. Dreger, Brian W. Davis, Raffaella Cocco, Sara Sechi, Alessandro Di Cerbo, Heidi G. Parker, Michele Polli, Stefano P. Marelli, Paola Crepaldi, Elaine A. Ostrander

GENETICS October 1, 2016 vol. 204 no. 2 737-755;

http://www.genetics.org/content/204/2/737

DOI: 10.1534/genetics.116.192427

New Faculty Profiles showcase GSA members who are establishing their first independent labs. If you’d like to be considered for a profile, please complete this form on the GSA website.

Clement Chow (credit: Bryan William Jones)

Clement Chow

Assistant Professor
Department of Human Genetics
University of Utah School of Medicine
Lab website
Personal Twitter:  @ClementYChow
Lab Twitter:  @ChowLab

Research program:

Our lab is focused on understanding the role of genetic variation on disease outcomes. We employ quantitative and functional tools in a variety of model organisms to study how genetic variation impacts basic cellular traits important to human health. Our work in model organisms will help to model and to inform studies of genetic variation observed in the human population. We hope to identify variation in the human population that can lead to more precise, personalized therapies.

We have two main projects in our lab: 1) The role genetic variation plays in basic cellular traits like the endoplasmic reticulum (ER) stress response and 2) Identifying modifiers of Mendelian disease through the use of natural genetic variation.

We are now looking for talented and motivated graduate students and postdocs to join the lab. Our lab uniquely combines cell biology, functional genetics, genomics, and natural variation to address important questions relevant to human disease. We are interested in individuals with a variety of interests and skills. If you are interested in working with a new vibrant, expanding lab, please contact me. If you are interested in joining as a postdoc, please see our ad.

Role of GSA in your career:

The GSA has played an incredibly important role in my training by providing valuable trainee resources. The GSA’s role in organizing the fly meeting has always made it one of my favorite venues for sharing our science. Finally, as a DeLill Nasser Award recipient, I was able to attend the American Society of Human Genetics annual meeting.

“One of the most exciting aspects of science is the prospect of finding or observing something that no one has ever seen.” – Clement Chow’s favorite part of his work

Previous training experiences:

• Postdoc in the Department of Molecular Biology and Genetics at Cornell University with Andy Clark and Mariana Wolfner
• Graduate school in the Department of Human Genetics at the University of Michigan
• Undergrad at Cornell University with a BA in Biology

Teaching:

My teaching will be mostly focused on graduate and medical education.

Interests Outside of Work:

When not working, I enjoy exploring the beautiful mountains surrounding Salt Lake City. I also love to cook. And…taking care of my two crazy kids.

The Conversations in Genetics project, led by former GSA President Rochelle Easton Esposito, has a new in-depth interview of Mary-Claire King by Evan Eichler.

As described in the video “Talking with Mary-Claire King,”

Dr. King is American Cancer Society Professor of Genome Sciences and Medicine at the University of Washington in Seattle. Her innovative studies of human genetics have had enormous scientific and social impact. As a graduate student with Allan Wilson at UC Berkeley, she demonstrated that human and chimpanzees are 99% identical at the level of protein coding genes, suggesting that the profound differences between these organisms result from a small number of regulatory or structural changes. These findings are consistent with a divergent time of 5-6 million years ago, rather than 15-20 million years, as previously thought.

Next, in a novel pioneering and painstaking approach combining genetics and epidemiology, King discovered and mapped BRCA1, the first gene shown to harbor inherited mutations leading to breast cancer. She later exploited her knowledge of genetics to develop mitochondiral DNA sequencing as a forensic tool to identify children kidnapped by Argentina’s former military dictatorship. She is presently involved in international partnerships to identify genes for severe congenital disorders and individually rare, but collectively common, mutations leading to schizophrenia.

The interview was conducted by King’s friend and colleague, Evan Eichler, Professor of Genome Sciences and Howard Hughes Medical Institute Investigator at the University of Washington, Seattle. The interview was recorded at the Health Sciences Center on the UW campus in Seattle, Washington, on August 28, 2015.

Conversations in Genetics now contains 20 interviews with prominent scientists who have made seminal contributions to the conceptual development of modern genetics.

To help support continued development of Conversations in Genetics, you can make a tax-deductible contribution to the project through the GSA or the Swiss National Grid Association.

Additional Information:

• Conversations in Genetics

John Novembre, photographed at University of Chicago, in Chicago. Image Credit: John D. & Catherine MacArthur Foundation

GSA is proud to congratulate GENETICS author John Novembre, who was recently named a 2015 MacArthur Fellow or “MacArthur Genius.”  Novembre is a computational biologist whose research focuses on understanding human evolutionary history. His research findings have improved the field’s knowledge of human migratory patterns and demonstrated a correlation between shared ancestral geography and genetic similarity among Europeans. These findings make it possible for a person’s ancestry to be pinpointed within several hundred miles based on his or her genetic markers. In this brief video, Dr. Novembre describes his current scientific interests, which investigate ways to analyze complex genetic data to learn more about evolution, genetics, and disease.

The MacArthur Fellows Program awards unrestricted fellowships to talented individuals who have shown extraordinary originality and dedication in their creative pursuits and a marked capacity for self-direction. There are three criteria for selection of fellows: exceptional creativity, promise for important future advances based on a track record of significant accomplishment, and potential for the fellowship to facilitate subsequent creative work. Fellows receive a $625,000 stipend over 5 years, with no strings attached to encourage creativity during the term of the grant.