Fellows Feature: Janet Song

Janet is a graduate student in David Kingsley’s lab,song7468_forweb where she is investigating genetic regions that might be involved in the evolution of the human brain. She received her B.A. in Chemical and Physical Biology from Harvard University in 2009.

Can you tell us a bit about yourself, personally and professionally? 

I grew up in the suburbs outside of Philadelphia where I had a pretty normal childhood – attending our local Chinese church and cheering rabidly for the Philadelphia Eagles. As a high school student, I was fortunate to do summer internships at Drexel University, where I worked with Dr. Timothy Block on the early detection of cancer, and later with Dr. Gordon Harris and Dr. Marlene Oscar-Berman at Massachusetts General Hospital on brain volumetric differences in alcoholics. These early exposures to research drove my interest in genetics and molecular biology.

In college at Harvard, I worked with Dr. Jeffrey Macklis. His lab studies the development of the cerebral cortex. I focused on genes that control axon extension in corticospinal motor neurons, which reside in the brain and extend long processes into the spinal cord. These neurons control voluntary movement and are often damaged during spinal cord injury.

After college, I came to Stanford to pursue my PhD with David Kingsley. My early experiences with research had made me very interested in gene regulation: How do the same set of instructions encode all the cells in the body? How do mutations in the genetic code affect these instructions? As I entered graduate school, I was particularly interested in asking these types of questions in relation to evolution. I wanted to understand how a relatively small amount of change to the genome – most of which is not in the genes themselves, but rather in non-coding regions – can distinguish one species from another.

How did you end up here? How did you first become interested in genetics and science?

My parents, who both got PhDs in biology in the early 1990s, talked about PCR so much that one of my first words was actually “PCR”. Because of this, I like to say that I was destined to be a biologist from birth. However, the truth is that I was not that enamored with science as a kid. That all changed in sixth grade, when my science teacher announced that students could do science fair projects for extra credit. I promptly informed my mom that I would be participating in this endeavor and needed to buy some plants. She was horrified at the thought of our house besieged by sunflower plants grown under different conditions for months (the de facto sixth grade project) and suggested instead that I come to her lab for a few days. To sixth grade me, a few days of work sounded way better than growing plants for months, and I agreed.

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Images courtesy of Janet Song

There, I UV irradiated DNA at different wavelengths and for different amounts of time to see how much DNA damage it would cause. That was my first exposure to “real” science and I was hooked. I went on to do more science fair projects (Question: Which brand of sunscreen is the best at protecting against UV irradiation? Answer: Rite Aid) and later, participated in multiple summer research internship programs in high school. I went to college certain that I wanted to run my own research group one day and have not wavered from that path since.

Can you tell us about your current research and what you want to achieve with it? What kind of responses have you gotten to your research/findings?

I study a human-specific element in the third intron of the calcium channel gene, CACNA1C. We discovered that this genomic region is misannotated in the human reference genome and is composed of hundreds to thousands of 30 bp repeats, expanded from a single 30 bp sequence found in chimpanzees and other primates. Intriguingly, this human-specific tandem repeat is also variable within humans. We found that different sequence variants on the 30-mer motif are linked to nearby SNPs that have been repeatedly associated with bipolar disorder and schizophrenia.

Using enhancer reporter assays, we showed that the expanded human tandem repeat arrays drive significantly higher enhancer activity than the single 30-mer found in chimpanzees, and that human repeat arrays associated with psychiatric disease risk have decreased enhancer activity compared to other human repeat arrays. These results suggest that changes in the structure and sequence of these repeat arrays may have contributed to changes in CACNA1C function during human evolution and may modulate neuropsychiatric disease risk in modern human populations. (See our recently published manuscript for more details: https://www.cell.com/ajhg/pdf/S0002-9297(18)30238-6.pdf)

This tandem repeat may provide a key example of how genetic regions are involved in both evolution and in disease. Previously, hallmarks of human evolution, such as bipedalism or smaller jaws, have been linked to lower back problems and impacted wisdom teeth present in adult humans.

Our research provides a genetic example of how the rapid evolution of larger brains with increased complexity could have led to susceptibility to psychiatric disease.

We are now studying the effects of adding or removing this tandem repeat from CACNA1C on neural development, calcium signaling, and gene expression in mouse models and in human cultured cells. We hope that further study of this tandem repeat can clarify treatment options for individuals with bipolar disorder or schizophrenia and further characterize how novel DNA insertions can alter neural function both in evolution and in human disease.

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Briefly, what’s the coolest thing about your work?

My research has provided an example of how the same genetic regions involved in human evolution may also play a role in human disease. From my anthropocentric perspective, I often think of the regions in the genome that are unique to humans as “better” than other regions of the genome because they are responsible in aggregate for improved cognition in modern humans. However, it also makes evolutionary sense that regions under selection during human evolution may have inadvertently contributed to human disease. Compared to ancient genetic regions, regions diverged between humans and chimps have had less time to be refined in response to negative selective pressure and would be selected for if they have beneficial effects that outweigh the negative effects.

Were there people (or one person) in particular to whom you would attribute your professional success?

There are so many people who have helped me along this path. My parents have been instrumental to my development as an individual. From them, I gained a moral compass and learned the importance of hard work and determination. I have also had a variety of scientific mentors throughout the years, including my mother, Dr. Timothy Block, Dr. Jeff Macklis, Dr. Vibhu Sahni, and Dr. David Kingsley. They imparted and nurtured my passion for genetics and provided me with different examples of creative and rigorous scientists.

What advice would you offer to other grad students or postdocs who are considering pursuing a similar educational and career path as you?

I still have a long way to go in my scientific journey, but here are some things I have learned so far:

  1. The most important attribute in research is perseverance, especially as an experimentalist. Many experiments will fail technically or give uninteresting results, but it is important to never lose that desire to try and try again.
  2. Science should be communal. Working with others can help you to avoid reinventing the wheel and allow you to iterate through scientific questions more quickly.
  3. Don’t be afraid to try new things! The best way to answer a question is not always with tools with which you are already familiar.

What are your future plans? Where do you see yourself professionally in the next 5 or 10 years?

In a decade, I hope to be an assistant professor running my own research program centered on gene regulation. I have remained endlessly fascinated by how almost every living thing is encoded by the same molecule, DNA. Like many other geneticists, I am driven by the desire to understand how this deceivingly simple code can produce such a wide variety of complex organisms and how the same exact code can be interpreted differently within a single organism to produce neurons, T cells, bone, and all the other kinds of cells in the body.

CEHG’s core values include “interdisciplinary research” and “collaboration.” Can you speak to the ways your work has embodied these values or to their importance to your future work or past experience?

Collaborations combine the expertise of different individuals to best address a scientific question. I have been fortunate to collaborate both within the Kingsley lab and with other labs. The main project I am working on (see earlier answers) started as a collaboration with Craig Lowe in the Kingsley lab. Craig performed a screen for regions of the human genome that are unique to humans and overlap chromatin marks indicative of regulatory activity. One of the regions he identified was the human-specific repeat element that we then went on to study further. As this project evolved toward approaches outside of our areas of expertise, we began collaborations with a number of other labs at Stanford – including Sergiu Pasca’s lab to differentiate stem cells into 3D brain organoids, Paul Khavari’s lab to identify the transcription factors that bind to different repeat variants, and Alistair Boettiger’s lab to probe the chromosome structure at our region of interest. These collaborations have allowed us to use a variety of approaches to more efficiently answer questions about the function of this repeat element.

Tell us what you do when you aren’t working on research and why. Do you have hobbies? Special talents? Other passions besides science?

When I’m not working on research, I enjoy cheering for my hometown Philadelphia Eagles, playing cards and board games, and attending musicals. I recently bought a pair of rollerblades and have been slowly learning to rollerblade around Stanford. I’m still very much a beginner, but I hope to be able to rollerblade to and from lab one day!

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Fellows Feature: Daniel Hornburg

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Daniel is a postdoctoral scholar in Mike Snyder’s Lab on Stanford campus, working to discover personalized molecular fingerprints across omes, opening up new avenues to define health and disease phenotypes and predict personalized disease trajectories. He received his Ph.D. from Max Planck Institute of Biochemistry/ LMU in 2015, and earned his M.S. at Technical University of Munich in 2010.  

Can you tell us a bit about yourself, personally and professionally? 

Science makes me a great chef, but not because I follow the recipes… more to that later. I am Dan, a postdoc in Mike Snyder’s Lab. I received my Bachelor and Master’s degree in Molecular Biotechnology from the Technical University of Munich (TUM) in Germany. While I was conducting my master studies, I also worked on a startup in which we developed multi-enzyme complexes from extremophile bacteria to degrade biomass efficiently for use in biotech.

After my studies at the TUM, I joined Matthias Mann at the Max Planck Institute of Biochemistry for my PhD. In the Mann lab, I developed proteomics strategies to investigate neurodegenerative diseases. Since I am a biochemist by training, I started my PhD with some wet lab work but after the first year, I began to operate various mass spectrometers and ended up with complex proteomics datasets. This was a great opportunity to learn and establish data analysis strategies in the field of neuroproteomics. Since then, I love to do both and the best percentage for me is 20% experimentalist, 80% data scientist.

How did you end up here? What first got you interested in genetics and science?

As long as I can think back, I have been curious. There is hardly anything more mind-blowing than thinking about the scale of the universe, or the complexity of life. If you talk to my grandparents, they will tell you about a 5-year old boy who tells everyone that he is going to be an astronaut or scientist (I am not implying that an astronaut cannot be a scientist, but I did not have such a nuanced view on job opportunities back then).

Science provides us with a unique perk that allows seeing so much more of the world. If you look at the night sky, you see hundreds of stars. Isn’t it fascinating that the photons hitting your retina started their journey millions of years ago, which means you look back into the past on the very same scale? These photons excite molecules in your Rod cells, starting a signal transduction cascade giving you the feeling of wonder and excitement in the first place. On top of that, some other molecular processes make you think about that or type these words… For me, that experience is addictive and I am glad that we live in a time and socioeconomic context where we have access to the tools to explore the beautiful complexity of nature.

Beyond that, I quickly realized that reason and science are the best tools to fix problems and will be key to making the world a better place. There is a nice quote from Neil deGrasse Tyson that brings it to the point:

Any time scientists disagree, it’s because we have insufficient data. Then we can agree on what kind of data to get; we get the data; and the data solves the problem. Either I’m right, or you’re right, or we’re both wrong. And we move on. That kind of conflict resolution does not exist in politics or religion.

Can you tell us about your current research and what you hope to achieve with it?

An asteroid is about to hit Earth. Why is it useful to know that 10 years ahead, instead of one day before it happens? First, knowing it 10 years in advance gives us more time to do something about it. Second, while we would need to massively interfere with its trajectory a day before it impacts, it only takes a gentle poke 10 years earlier to change its path by an iota of a degree to prevent a disaster.

I am convinced the same holds true in biomedicine. Think about devastating chronic diseases, such as diabetes or Alzheimer’s: When a patient shows symptoms, the damage is done. We cannot cure it. What if we could identify and understand molecular deteriorations 10 years earlier and a minor, personalized intervention is sufficient to prevent the diseases from happening?

This is my research mission. I develop biochemical, mass spectrometry, and computational strategies to characterize thousands of molecules from small amounts of biological samples (e.g. blood) to discover and characterize molecular alterations to predict disease trajectories at an early stage. I have been working for 7 years in proteomics and when I joined Stanford, I wanted to expand my omics expertise with another molecular layer. That is why I am now responsible for the lipidomics in the lab and I explore the function of lipids in human physiology and their role in diseases.

Lipids are a complex, yet largely unexplored, molecular family with thousands of individual species. A growing body of evidence suggests that lipids are involved in a variety of physiological processes beyond energy metabolism. This includes key roles as molecular precursors for hormones, structural elements, transporters, or signaling molecules. Alarmingly, more than 70 % of adults show abnormal lipid metabolism (dyslipidemia), which results in an altered lipid concentration in the blood and is associated with chronic metabolic conditions, including diabetes and cardiovascular diseases.

When I started in the Snyder lab a year ago, I established a targeted lipidomics pipeline. I spent the first months optimizing biochemical protocols and the mass spectrometer to extract, identify, and reliably quantify lipids from bio specimens. Now, we can measure close to 1000 lipids across 100 samples in less than 2 days.

Since then, my focus has been to develop and employ computational strategies to interpret alterations I observe in the lipidome; for instance, comparing healthy and pre-diabetic people performing an exhaustive cardiopulmonary exercise. To this end, I integrate: i) known biological functions of individual lipid molecules; ii) specific biochemical properties (including the degree of saturation, fatty acid chain length etc.); and iii) information on how these lipids connect to other molecules, such as processing enzymes.

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All post images and figures provided by Daniel Hornburg.

Ultimately, we aim to identify not only early biomarkers but also to further our molecular understanding of disease mechanisms by being able to follow disease trajectories over time, on a personalized level.

Briefly, what’s the coolest thing about your work?

I think it is pretty cool to monitor thousands of molecules from a small drop of blood. In particular, I like our inverted research approach. Instead of starting with a narrow hypothesis, I observe complex molecular changes through mass spectrometry and interpret these alterations, using tailored computational strategies. Based on that data, I formulate a falsifiable hypothesis that I can test in close collaboration with a great team of scientists from various disciplines. Another cool thing is the coding itself. I can code from anywhere. I recommend the combination of laptop, hot coffee, and ocean view. 🙂

Were there people (or one person) in particular to whom you would attribute your professional success?

That starts with my family that never got tired of supporting curiosity and exploration. Beyond that, I have been blessed to work with great scientists like Matthias Mann, Felix Meissner, Jurgen Cox, Dieter Langosch, Harald Luksch and, of course, Mike Snyder. Moreover, throughout my career, I worked with friends at the same career stage. All these interactions contributed, and are still contributing, to my personal and professional development and I wouldn’t be where I am without them.

Can you speak a bit to the role you see CEHG playing on Stanford campus?

I am a passionate advocate of interdisciplinary and collaborative research for two reasons. First, it is undoubtedly more fun and helps you get through all the ups and downs. Second, having many brains working on a problem makes it more likely to come up with a solution.

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I think research will increasingly depend on collaborative efforts. For instance, if you want to establish a molecular landscape of health this cannot be done without a collaborative interdisciplinary team. Thus, fostering a collaborative scientific network is one key ingredient for success. That said, I think we have to rethink some of the core policies in academia in order to provide the optimal environment to motivate flourishing collaborations across large teams. This is one of the major challenges academia faces, which is why I have expressed my opinion on authorship policies in a blog and correspondence.

What advice would you offer to other grad students or postdocs who are considering pursuing a similar educational and career path as you? 

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If it is applicable to your field of research, I recommend becoming proficient at both, biochemistry/biology and data analysis. An in-depth biochemical understanding is key to devising and interpreting lab experiments. In turn, knowing how to deal with the data helps you in designing the right experiment in the first place and efficiently analyzing and disseminating your results. Moreover, more often than not, experiments fail and we don’t even know why since the underlying variables of the biological system are underdetermined. This will be frustrating from time to time. It can be very refreshing to work on bioinformatics. Coding is more deterministic and each hour you invest, you learn and/or progress.

Finally, always remember what you like and what you don’t like in science (and life). You might not be able to make a change right now, but the time can come when it is your responsibility to remember and be that great mentor or the devoted voice to advocate for improving our (scientific) community.

What are your future plans? Where do you see yourself professionally in the next 5 or 10 years?

In the long run, I woud like to lead an interdisciplinary and collaborative team that expands our understanding of the biomolecular world and makes a difference. Whether this is in academia, a start-up or industry depends on how things are developing. I keep an open mind and explore opportunities across these three fields. Conceptually, I love academic science and teaching, but success in academia involves many random variables such as: Are you lucky with getting positive results in a timely manner that will result in papers with the “right” author position? I‘ll reflect on my opportunities and select for inspiring environments, cool people and exciting topics. For me, that is the best way to be happy and successful and there are usually more opportunities than there is time.

Tell us what you do when you aren’t working on research and why. Do you have hobbies? Special talents? Other passions besides science?

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I love doing sports like jujitsu and biking. This is a great way to free my mind. I also like cooking. The “special talent” in that context is that I can endure hunger for hours. This is important: It motivates me to get started and gives enough time to craft a delicious meal. Perhaps delayed gratification is something you acquire during a scientific career.

Besides that, I am a passionate advocate for science and reason. I am convinced that science provides the best toolset to learn from the past, understand the present and shape the future and, thus, is useful beyond academic research. 

Fellows Feature: Atish Agarwala

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Atish is a PhD student in Daniel Fisher’s group in Stanford’s Applied Physics department. His primary interest is in studying models of epistasis, and understanding how the statistics of “fitness landscapes” affect the speed and predictability of evolution. He also works at the intersection of evolution and ecology, trying to understand how co-evolutionary processes generate and maintain diversity in complex ecosystems.

Can you tell us a bit about yourself, personally and professionally?

I grew up in San Jose, a diverse city still near and dear to my heart. I’ve always been interested in math and science. I was influenced by my father’s job as an engineer, and my mother always pushed me to succeed academically. When I was 10 years old, I decided I wanted to be a theoretical physicist. For better or for worse, it stuck. I studied math and physics as an undergrad at Swarthmore College, outside of Philadelphia. I love that both fields begin with basic assumptions, and, with those alone, you can discover fundamental truths about the universe.

Near the end of undergrad, I became interested in quantitative biology. It seemed like a more open and underdeveloped field compared to modern physics, which would give me a chance to make a big scientific impact. I applied to Stanford because it had strong research groups in theoretical biology (and because I was tired of being cold in Pennsylvania!). I eventually joined Daniel Fisher’s group, where I now study various aspects of evolution.

Can you tell us about your current research and what you hope to achieve with it?

I use a combination of modeling, simulation, and data analysis to understand what determines the tempo and character of evolution in different scenarios. One of my main projects has been to analyze how epistasis (interaction between mutations) affects evolution. For example, a pair of mutations might do nothing individually, but give benefits to an organism if both are present. Or, they could be beneficial individually, but harmful together. I used a combination of mathematical and computational approaches to show that the linked effects of mutations cause the statistics of future evolution to depend on the statistics of past evolution. My modeling suggests that picking up lots of weakly-beneficial mutations might be better in the long run than picking up a few big, advantageous ones.

Insights like these have practical importance. A quantitative understanding of evolution is critical to solve the most urgent issues in global health today. For example, choosing strategies to curtail antibiotic resistance requires knowledge of how resistances arise in the first place. Cancers require cells to pick up multiple mutations, the probability and timing of which depends on the interactions between them. The flu vaccine needs to be designed to stop next year’s strain of the virus, which requires prediction of which rare strains will be common in the future. Characterizing these complex systems requires theoretical understanding of how different evolutionary processes play off each other.

More recently, I’ve become interested in the intersection of evolution and ecology: what happens when different types of organisms are living together, interacting, and evolving all at once? These co-evolutionary scenarios are important in nature, and can have a very different flavor from evolution within a single population only. I’m currently working on understanding how diversity is stabilized within models of ecosystems, and I hope to branch out and study data from real ecosystems (either in the lab or the wild).

What’s the coolest thing about your work?

It’s exciting that many basic things about evolution are not known. Although there is a lot of great experimental work (enabled by amazing technological development), theory is far behind the data we can collect. It feels akin to what doing physics in the 1700s must have felt like: there is clearly structure in the world, but the overarching understanding still eludes us!

Were there people (or one person) in particular to whom you would attribute your professional success?

I owe a lot to the first physicist who I ever met: Dave Dorfan. Dave was then a professor at UC Santa Cruz who taught at a summer camp for high school students. At that camp, Dave taught me what being a physicist was all about: asking lots of questions, carefully refining them, and, even more carefully, testing them. I also learned two important facts about science: it was, in fact, fun, and also something I could make a career out of.

Dave continued to help me throughout my scientific journey. He was always available with advice about coursework and finding research internships. Dave was also the first person to suggest quantitative biology as an area that I should look into. Without him, I’d likely be in a more traditional subfield of physics.

What are your future plans? Where do you see yourself professionally in the next 5 or 10 years?

I’ve always loved science. From an early age, I was fascinated by space. I wanted to be an astronaut, and I can still remember the glow-in-the-dark map of the solar system I had on my bedroom wall as a kid. In 5th grade, my teacher gave me a copy of A Brief History of Time. I tore through it. At the time, I didn’t understand most of the book, but, nevertheless, I was spellbound by the mysteries of the very microscopic and very macroscopic. I asked my teacher what job Stephen Hawking had, and he told me, “Well, I think he’s referred to as a theoretical physicist.” That day, I made up my mind to become one. Surprisingly, I stuck with it, and even more surprisingly, it panned out!

I hope to continue to do theory. I enjoy my work, in part because it aligns nicely with my skills and temperament. I’d love to run a research group in a few years’ time, with the freedom to set my own research directions as well as the ability to mentor students through the process of becoming a scientist.

What advice would you offer to other grad students or postdocs who are considering pursuing a similar educational and career path as you? 

In my mind, one of the biggest determiners of success in grad school is the people you work with. It’s important to find people who you find inspiring, who are fun to work with, and who have a vested interest in your success. Research is difficult enough without having to deal with people who you don’t mesh with.

My other piece of advice for those in the throes of a PhD is: academia is not the only path forward.. I strongly encourage PhD students to learn about and explore other options while they’re still in grad school. The non-academic path is often stigmatized, but it shouldn’t be. Of my friends who started grad school when I did, some of the happiest are those who left academia, either before or after finishing their PhD. Both paths are valid.

Can you speak a bit to the role you see CEHG playing on Stanford campus?

I’ve been fortunate enough to collaborate with the Petrov and Sherlock labs, both of which are heavily involved with the Center. I worked with scientists in both labs (especially CEHG Fellow-mate Yuping Li) to study the character of fitness gains in microbial experimental evolution. Combining their experimental expertise and my theory expertise, we designed experiments and analysis methods to tease apart the tradeoffs made by organisms evolving on short timescales. The type of work we did wouldn’t have been possible without both sides of the equation, and that collaboration has been one of the highlights of my PhD.

Tell us what you do when you aren’t working on research and why. Do you have hobbies? Special talents? Other passions besides science?

I’m into gaming, both board games and video games. I also play jazz flute with a group on campus.

My biggest non-scientific passion, however, is hockey. I play on the Stanford Club Ice Hockey team with both undergrad and grad students, and I’m involved in organizing team activities. My favorite moment on the team was when we played a game at the San Jose Sharks NHL arena. I’ve dreamed about what it would be like to play in my hometown team’s arena, but I never thought I’d actually get the chance!

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Fellows Feature: Monica Sanchez

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Monica Sanchez is a Postdoctoral Fellow in the Petrov lab (2017-now). She received her Ph.D in Molecular and Cellular Biology at the University of Washington. She is interested in studying the effect of genetic background differences on general mechanisms of evolvability and aims to understand how genetic and environmental interactions affect adaptation and complex traits.

Can you tell us a bit about yourself, personally and professionally? 

I am originally from Albuquerque, New Mexico, where I attended the University of New Mexico. I studied biology and chemistry, and initially performed research in a biomedical engineering lab, where I designed low-cost diagnostic devices. As I took more advanced biology courses, I quickly became interested in genetics and joined a research program that allowed me to work in a yeast lab where I discovered the power of genomics. I became very interested in functional genomics, and I eventually joined a molecular and cellular biology PhD program at the University of Washington in the Department of Genome Sciences.

While at UW, I joined a lab that combines experimental evolution with genomic analysis to study the structure and function of genetic networks in yeast. I was very interested in understanding how different species of yeast adapt to a variety of different conditions and I am pursuing similar questions in evolutionary biology in my current postdoc position. I hope to understand adaptation in the context of ecology in order to gain a deeper understanding of general evolutionary processes.

Why did you become a scientist? What first attracted you to genetics and science?

I grew up in New Mexico in the Rio Grande Valley, where I would spend a lot of my childhood exploring the Bosque trails with my father.  I cherished the escape from the city in the wooded areas and I loved identifying new creatures during our visits. It was obvious to me that I wanted to grow up to become a scientist in order to discover new species and learn how they interact with their environment. Although I wasn’t exactly sure how to obtain such a profession, I always knew that I loved learning new things about biology and I would try my hardest to make that dream a reality.

Can you tell us about your current research and what you hope to achieve with it? What kind of responses have you gotten to your research/findings?

As a postdoctoral fellow in the Petrov lab, I am focused on two questions that specifically focus on the importance of genetic background on adaptation, using yeast as a model. In the first, I focus on the difference in the nature of adaptive mutations in haploids and diploids in terms of their molecular basis, distribution of fitness effects, and the distribution of dominance. I am also specifically interested in whether, as predicted, adaptive mutations in diploids are often not just partially dominant but also overdominant.

In the second, I attempt to test whether genetic background has any predictive effect on the ability of lineages to evolve over the long-term in a way that cannot be fully predicted from the patterns of adaptation over the short term.  To accomplish this, I incorporated a diverse set of barcode sequences to track natural isolates of yeast to test mutational spectrums in each natural isolate as well as in mixed communities. This strategy will allow me test how different compositions of competitors influence adaptive trajectories. The overall goal of this project is to determine generalizable rules of adaptation, which is important for understanding adaptive events involved in many human diseases such as cancer and pathogenic diseases.

The next steps in the process of discovery for my project would be to incorporate different elements from natural environments. For example, we can test more complex mixture of microbial species, different carbon sources, or the effects of spatial distributions on their adaptive potential, providing insight into their evolutionary history.

What is the coolest thing about your work?

The coolest aspect about my work is that it incorporates an element of what is actually seen in nature. Most microbes don’t grow in isolation, and if we study them as single cultures, we may be missing important evolutionary forces that are shaped when complex microbial communities are formed.

Were there people (or one person) in particular to whom you would attribute your professional success?

As an undergraduate, I participated in a research program directed by Dr. Maggi Werner-Washburne, who has made a tremendous impact on my success as a scientist. The mentorship and support I received from her was essential for me to navigate through graduate school applications, and a key part of why I decided to apply to graduate school. Dr. Werner-Washburne is inspiring and her mentoring resonated with me, allowing me to realize my own potential.

Furthermore, she urged me to perform research through a summer program with Dr. Jay Shendure at the University of Washington, where I discovered my passion for genomics. This experience influenced my decision to attend UW for graduate school, where I applied genomic approaches to evolutionary questions with Dr. Maitreya Dunham, who is an extremely supportive role model for women in science as well.

What advice would you offer to other grad students or postdocs who are considering pursuing a similar educational and career path as you? 

I would advise grad students or postdocs to think hard and think early about where they see themselves in the future. It’s easy to get caught in the routine of everyday life and time goes by really fast. I think it is important to make sure to plan out the necessary steps needed to achieve your ultimate goal, regardless of what that end goal is.

What are your future plans? Where do you see yourself professionally in the next 5 or 10 years?

I see myself continuing to perform research in evolutionary biology with a team of researchers. I am open to the possibility of leading my own independent research group, hopefully in an academic institution. At this point I know that I love performing research in the basic sciences and I am open to the possibility of doing research regardless of the type of institution that I end up performing it in.

Can you speak a bit to the role you see CEHG playing on Stanford campus?

I think CEHG plays an integral role in fostering interactions with many influential faculty members in the CEHG fields across Stanford campus. It also provides the opportunity to expand my network of potential collaborators by meeting other CEHG fellows that span a variety of different disciplines. Specifically, the Evolgenome seminar series is an ideal opportunity to present and engage with other members of the program through meaningful discussions with speakers and faculty members about their research.

Tell us what you do when you aren’t working on research. Do you have hobbies? Special talents? Other passions besides science? 

My escape is music. I love seeing live shows, finding new artists and talking and sharing and experiencing music with friends. I tried to play music but I think I am much better at appreciating it!

I also like to hike and unplug from technology for a while, and I enjoy being in the moment, surrounded by nature. It’s a time for me to think and my mind resets in a way that I don’t get on a daily basis. I also enjoy snowboarding, running, and cooking.

Fellows Feature: Solomon Endlich

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Solomon Endlich is a CEHG postdoctoral fellow in the Gill Bejerano lab. He received his PhD in theoretical physics at Columbia University and has held postdoctoral positions at the École Polytechnique Fédérale de Lausanne and the Stanford Institute for Theoretical Physics. 

Can you tell us a bit about yourself, personally and professionally?

As a clear romantic, I am daily struck by the wonder of the natural world; I am overwhelmed with its majesty, its beauty, and its kaleidoscope of forms. These inspirational feelings have led me to focus my life on exploring it, intellectually and physically. From physics to biology, and from catching lizards in the backyard to performing technical scuba dives in the mighty Pacific, the narrative has pretty much stayed the same — there is always more to learn and always new things to explore.

This lifestyle has it drawbacks, of course. My garage looks like the used section of some kind of super outdoor shop; bags of ropes compete for space with drysuits and scuba tanks, while backcountry skis and outrageous winter camping gear try to stay relevant during the hot California summer months. Meanwhile, my strange (and large) book collection makes moving a huge pain. But what would I do without Lalli and Gilmer’s Pelagic Snails, or Munk and MacDonald’s The Rotation of the Earth – A Geophysical Discussion?

How did you end up here? What first got you interested in genetics and science?

It is amazing working everyday at Stanford. I was born just across the Bay and always dreamed of being a scientist in a university. So everyday, walking into the lab feels like a dream come true.

I was born in Berkeley and raised in nearby beautiful Sonoma County. I was always romping around the forests or catching insects or reading books about sharks. To me, it was clear that I had to be a scientist, but it was not so clear what that actually meant or how one does that. My family are creatives (artists, designers) and I always felt a little bit like the black sheep. Lucky for me, I somehow found the right books to read and had the right teachers who encouraged me. I was directed to Jacques Cousteau, Richard Feynman, Carl Sagan, and Charles Darwin, and found my people.

Intellectually, I was always drawn to fundamental principles as opposed to collections of facts. I wanted to know the key features that united disparate phenomena. I was interested in *why* things worked the way they do. This led me down the rabbit hole of mathematical physics, where I then spent a solid portion of my adult life. Quantum Mechanics and General Relativity. Statistical Mechanics and Fluid Dynamics. Cosmology and Astrophysics. That rigorous quantitative experience gave me a new set of eyes that saw the world so differently then when I was a boy.

After my PhD and a few years as a postdoc, I felt like some of the excitement was gone. I wanted to be where discoveries did not happen on a decade-long time scale. I rekindled my love of the life sciences and found a calling in genomics. It had the fundamental nature (they are the instructions — the rules — that ultimately govern organisms) that I so enjoyed, but also a pace of discovery that I could only dream about. At the risk of being too bold, I knew immediately: “This is where the action is!”

Can you tell us about your current research and what you hope to achieve with it?

My current research has shifted quite a bit since I began my fellowship. Frustrated with the quality of the various vertebrate genome assemblies, I became more and more interested in all the missing pieces (and there are many!). What is lurking in uncharted territory? Entranced, I pivoted towards an ambitious new goal: sequence the unsequencable and *fully* map out the most important genomes. I told myself: “Since I am giving this genomics thing a try, why not pick a really audacious goal?”

It turns out that to some people, it may be too audacious. In the initial stages, I discussed my intentions with some visiting senior researchers and they kindly suggested I lower my sights and work on something more practical and secure for my career. Needless to say, I didn’t listen and, in fact, felt even more motivated.

The plan involves a combination of molecular biology and computational techniques (which I will not get into the details here) that, *if* they work, could be absolutely transformative for the field. To this end, I have been toiling away in the lab for the last 8 months to optimize the protocols and demonstrate a solid proof of principle. So far, I have had very encouraging data! Computational results indicate that the idea in question will, as hoped, give us an advantage over standard sequencing experiments, and the lab work has demonstrated that the needed chemistry can operate as needed.

At this point, all that is needed is to put the pieces together and see how much of an improvement we can really make. Even a partial success will then allow us to see genomes in more detail then we have ever before.

Were there people (or one person) in particular to whom you would attribute your professional success?

There are so many. As I mentioned before, I received a lot of support from my early teachers. Looking back, it seems incredible that a few kind words said at the right time can have such a big impact. [Thank you Dr. Karen Frindell, Mr. G, and Mr. Lee. Don’t know where I would be without you.] Years later, my close colleagues in physics very much shaped my attitudes and intuition: Alberto Nicolis, Riccardo Penco, and Rachel Rosen. They are all incredible scientists and have been role models for years.

More currently, the environment at Stanford has let me explore far outside my initial lab space. In the early stages of this project, I found Dr. Ashby Morrison in Biology and she opened her door to me to work on some “crazy” ideas. Without her, I am not sure this project would ever have gotten off the ground. There is also a whole list of students and postdocs who have been of invaluable help; Stanford has such an incredible pool of talent and energy!

Can you speak a bit to the role you see CEHG playing on Stanford campus?

Institutions like CEHG are absolutely vital to science at Stanford. The most interesting things happening are usually at the intersection of disparate fields. Almost by definition, if something has not been discovered, there can be no “department” of it. And in the same vein, many of the groundbreaking experiments and analyses in a given field often require assistance from other fields for their execution. Take, for instance, the human genome project: it was clearly a biology project, but one that took an enormous amount of molecular biology, engineering, and computer science expertise to bring to fruition. And institutions like CEHG set just such a tone and encourage scientists to stretch their research programs beyond the comfortable boundaries of their own disciplines.

And for me personally, CEHG gave me the freedom to search out an interdisciplinary opportunity and to collaborate with scientists whose expertise could compliment my own. So far, it has worked incredibly well.

What are your future plans? Where do you see yourself professionally in the next 5 or 10 years?

If all goes well, I see myself doing research daily. Working with a team of people whose different areas of expertise illuminate the complex and many faceted problems of modern biology. But I also see myself interacting extensively with the public and the larger scientific community. As scientists, we can’t simply expect people to see the value in our work and support us in kind. I see myself engaged in this discussion, as well as working to inspire and support the next generation of inquisitive minds.

What advice would you offer to other grad students or postdocs who are considering pursuing a similar educational and career path as you? 

  • Keep your education general. You can spend a lifetime learning all the things that *could* be useful at sometime or another. Instead, focus on the problem that you want to solve and you can learn the appropriate tools as you need them.
  • Talk to people. They often know a lot more then you and can point you in the right direction. A couple conversations with the right minds can save you months of work.
  • Work with people you like and get along with, scientifically and emotionally. We all take our work very personally (I know I do). Having colleagues that you are on the same wavelength with, and whose company you enjoy, will greatly improve the experience and ultimately make your work easier and better.

Tell us what you do when you aren’t working on research. Do you have hobbies? Special talents? Other passions besides science?

Too many hobbies actually. I may have to start making some hard choices! I participate in lots of outdoor activities, the more “adventure-y” the better: rock climbing (personal goal: climb “The Nose”); backcountry skiing (it is like winter hiking, but with a cherry on top); scuba diving (most recently, I have been trained to use a rebreather); fly fishing; and cycling. These go a long way toward scratching the adventure/explorer itch, especially when you share the experience with friends.

On the creative side, I have recently picked up ceramics, which has been a wonderful way to slow down an otherwise overactive mind. Very meditative, with the side benefit of being great for gift giving.

Fellows Feature: Gili Greenbaum

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Gili Greenbaum (giligreenbaum.wordpress.com) is a CEHG postdoctoral fellow in the lab of Noah Rosenberg. Gili completed his B.Sc. in mathematics and philosophy at the Hebrew University of Jerusalem and his M.Sc. and Ph.D (Physics and Ecology departments) at Ben-Gurion University, Israel. He is interested in population-level evolutionary dynamics and complex-systems theory, and is working to understand how complex spatial structuring impacts evolutionary processes. 

Can you tell us a bit about yourself, personally and professionally? 

I grew up in the Galilee in Northern Israel. There, I spent a lot of my time turning over rocks to see what was under them and following ants to see where they were going. I was also very much interested in math. Eventually, I started my academic route at the Hebrew University of Jerusalem, where I studied both Mathematics and Philosophy. During my studies, I also worked for the Society for Protection of Nature in Israel, so as to remain connected to the natural world. I worked with nature-education and hiking activities for kids and teenagers. After finishing my B.Sc., I joined the Israel Trails Committee, where I was working on developing hiking trails, particularly new long-distance trails.

In order to bring together the various disciplines that interest me – mathematics, evolutionary biology, and conservation biology – I decided to focus on mathematical population genetics, joining the Physics and Ecology Departments at the Sede Boker campus of Ben-Gurion University on an inter-disciplinary fellowship. Although I worked mainly on theoretical and methodological problems, I kept grounded by collaborating on conservation projects.

How did you end up here? How did you first become interested in genetics and science?

Ever since I heard about it (don’t quite remember when that was), I thought evolution was the coolest idea ever. I still get dizzy when I think too deeply about it, biologically, mathematically or philosophically. For a long time, I wasn’t sure what would be my research focus, and I explored different topics (from math and physics all the way to philosophy and history), but when I had to settle on a field for my graduate studies, it was clear to me that I would study evolutionary theory. I always liked reading popular science books, with perhaps Richard Dawkins and Douglas Hofstadter having the most impact, and I believe that these early readings played a significant role in steering me towards a career in science.

Can you tell us about your current research and what you hope to achieve with it? 

During my Ph.D. I was lucky to observe and think about several different biological systems in different parts of the world, such as Asiatic wild ass, Przewalski’s horses, Nubian Ibex, collared lizards, bats, and even Acacia trees and other plant systems. These experiences have helped me appreciate the complexity of many natural systems, and be aware of the difficulties of understanding and modeling evolutionary processes in real-world systems.

My work is focused on developing approaches for inference and prediction of population genetics that incorporate the structural complexities, at the population level, that are more often the rule rather than the exception in natural systems. In my work, I try to draw ideas from complex systems theory, particularly network theory.

One of the projects that I have been working on is to develop a data-driven network-based methodology for inference of population structure that minimizes the a priori biological assumptions needed, that is applicable to whole-genome datasets and that can describe simultaneously many hierarchical levels of population structure. For example, analyzing a world-wide Arabidopsis thaliana, we were able to describe very fine-scale population structures, sometimes restricted to single rivers or adjacent to specific cities, but also retain the context of the coarser world-wide structure.

Besides inference of population structure, I am interested in the evolutionary consequences of structured populations when the structure is complex and does not conform to simple topologies, such as in the Island Model or the Stepping-Stone Model. For example, under a given complex population structure, I am interested in understanding which types of evolutionary processes are more likely to occur (e.g. global selection, local adaptation, erosion of genetic diversity, etc.). I am looking into connecting theory on generative network models to theory of population structure, by analyzing population genetic properties of such models under a coalescent-theory framework. This line of work can be particularly useful in the context of conservation, since our goal in conservation is not only to maintain endangered populations, but also to consider their evolutionary trajectories.

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Were there people (or one person) in particular to whom you would attribute your professional success?

I have really been fortunate to be mentored by fantastic people. In my Ph.D. studies, I was mentored by Alan Templeton, a Professor at Washington University. We spent many days in the Ozarks, catching collared lizards and talking about (almost) all of science. These chats made me appreciate the fact that being a specialist in a scientific field and having a broad scientific interest are not necessarily in contradiction. Now, at Noah Rosenberg’s lab, I am again lucky to find myself mentored by a researcher who is both an expert and retains an immensely large scientific scope (check out our lab’s library!). I am hoping that some of the abilities of these great people–to be experts and, at the same time, be involved and interested in many topics–will rub a bit onto me.

What are the differences between the US and your home country (or the country of your previous study)? Have you enjoyed your time at Stanford so far?

Stanford is a fantastic place to do science. So much cutting-edge stuff is going on all around you. Hopefully, you’ll get infected by some of it.

What advice would you offer to other grad students or postdocs who are considering pursuing a similar educational and career path as you? 

Keep doing what you are most interested in. That’s as much as anyone can ask, I guess, and in academia, that is really your mission. Sometimes it seems complicated, and there are struggles, but in the end it actually is pretty simple.

Can you speak a bit to the role you see CEHG playing on Stanford campus?

CEHG is all about combining different perspectives to better understand evolution and genetics, an approach I truly believe in. The scientific community today is huge, and continuously expanding, and CEHG helps tie together different points in this expanding scientific space so we can make some sense of the bigger picture.

What are your future plans? Where do you see yourself professionally in the next 5 or 10 years?

My goal is to start my own lab, and continue exploring and expanding evolutionary theory. In particular, I would like to address the current issues that are on the minds of conservationists, and develop ideas that can help us address some of the evolutionary consequences of the Anthropocene.

Tell us what you do when you aren’t working on research and why. Do you have hobbies? Special talents? Other passions besides science?

I like being outside, hiking long-distance trails. I hiked long trails in in Greenland and Iceland, across Europe, Central and Eastern Asia, and the Israel National Trail is, of course, a favorite. Haven’t gotten to the US long trails yet. Nowadays, with my two boys, I prefer less long and less harsh trails, but I am learning to enjoy other things on shorter hikes, such as the way spider webs stick to your fingers and how funny some acorns are.

 

Fellows Feature: Alison Feder

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Alison Feder is a CEHG graduate fellow in Dmitri Petrov’s lab. Before coming to Stanford, she received her BA in mathematics at the University of Pennsylvania and her MSc (res) in statistics at the University of Oxford. Her current research is focused on using the dynamics of HIV drug resistance evolution as a model for understanding how rapid adaptation proceeds across space and time.

Can you tell us a bit about yourself, personally and professionally? 

I grew up in Chicago. I went to college at the University of Pennsylvania, where I earned a BA in math and developed an enthusiasm for quantitative evolutionary biology. After graduation, I pursued an MSc by research in statistics at Oxford before moving to Stanford for my PhD.

How did you end up here? Tell us a bit about how you first became interested in genetics and science. 

I took a world-expanding statistics course with Rosa McCullagh in high school and knew I wanted to do something that involved understanding data quantitatively. Someone told me (probably incorrectly) that one could do either econometrics or biostatistics. I liked high school biology much better than high school economics, so I figured I’d better just be a biostatistician.

When I arrived at college, I sought out a research experience combining biology and statistics. My initial inquiries led me to Warren Ewens, a Big Deal population geneticist, who I definitely would have been too intimidated to email had I understood how Big a Deal he was. Warren handed me a stack of population genetics books, suggested that I read what I wanted and then come back to talk about whatever I found interesting. I came back every week that semester. These conversations ultimately led to a small project investigating inference from nucleotide substitution models.

However, I did the bulk of my undergraduate research in Josh Plotkin’s lab, upon the recommendation of a then-stranger in a computer lab who saw me designing a course schedule featuring both math and biology.

Can you tell us about your current research and what you hope to achieve with it? 

I’m interested in how natural populations adapt when strong population genetic forces are at play. In my PhD, I’ve studied this adaptation in the context of HIV drug resistance evolution. In the late 1980s/early 1990s, we treated HIV with single drugs that led to fast and predictable acquisition of drug resistance. Now we treat patients with efficacious combinations of drugs that rarely lead to resistance. What makes these drugs work so well, and why do they sometimes still fail? In answering these questions, I think we can learn a lot about evolution in huge populations under strong natural selection.

One mystery that fascinates me is HIV’s ability to evolve when it’s treated with three drugs simultaneously. We think that this should be very difficult because HIV should need not just one or two but three different mutations to be able to replicate at all in the presence of three drugs. Further, we might expect that any single mutation shouldn’t help the virus, because it will still be suppressed by two other drugs. Yet somehow, drug resistance does sometimes still emerge, and the mutations that confer resistance to single drugs can spread within patients one at a time.

Our mental model of HIV intra-patient evolution is missing some important factor that accounts for this behavior. I’m trying to understand what this intra-patient evolutionary process looks like using a combination of clinical and experimental HIV sequences, genomic analysis and mathematical modeling. If we can resolve how HIV can win against three simultaneous drugs, maybe this can help us understand more generally how populations solve seemingly impossible evolutionary tasks.

Were there people (or one person) in particular to whom you would attribute your professional success?

So many people have been so important towards my scientific development:

Warren Ewens first introduced me to the field of population genetics, and spent an inordinate amount of time fielding absurdly naive questions with admirable enthusiasm.

Josh Plotkin welcomed me into his lab as a first-year undergrad even though I basically had no skills whatsoever. Despite this, he trusted me with a project and provided direct mentorship and unceasing support for years. He cultivated a lab environment and research program that made me want to go to graduate school and become a scientist. To this day, I can trace the bulk of my scientific interests to discussions in Josh’s lab as an undergraduate.

Pleuni Pennings has been a mentor, a colleague, a friend and an ever-flowing source of inspiration, both scientific and otherwise. Every time we talk, I walk away with three new projects ideas and renewed excitement for my scientific endeavors. Below I’m asked to give some advice. Here it is: find your Pleuni Pennings.

I don’t know how I got so lucky as to stumble into Dmitri Petrov’s lab. Dmitri is an incisive thinker, gifted communicator and fantastic mentor. I frequently feel like I come up with ideas only to realize that he had actually suggested something similar three weeks ago that I just hadn’t fully understood. He’s also just a kind and compassionate person, and one of the things that has made my graduate school experience so fantastic has been his commitment to maintaining a lab full of people who like each other.

I also want to highlight in particular the postdoctoral mentors I’ve worked with in the past who have taught me the vast majority of my practical skills: Kirk Lohmueller, Alan Bergland, Jeremy Draghi and Sergey Kryazhimskiy.

What advice would you offer to other grad students or postdocs who are considering pursuing a similar educational and career path as you? 

My best experiences in science have been in working with people I like. If you enjoy talking with someone, those conversations will naturally result in new ideas and directions. Science is hard, and being surrounded by a network of support makes a huge difference. Related to this, I think I’ve benefited tremendously from seeking out advice from lots of mentors. Everyone brings their own set of experiences to the table, and trying to see a problem from many perspectives has often kept me from getting too stuck.

Can you speak a bit to the role you see CEHG playing on Stanford campus?

Stanford is huge and dispersed. I am confident that there are fantastic scientists doing extremely relevant research here on campus that I’ve never even heard about, much less met. However, if it weren’t for CEHG, I am also confident that there would be many more. CEHG’s seminars, symposia and other events make the genomics community on campus accessible across departmental, school and university lines.

What are your future plans? Where do you see yourself professionally in the next 5 or 10 years?

I’ve actually just defended my dissertation. Next year, I’m moving on to Berkeley to do a postdoc with Oskar Hallatschek and Monty Slatkin. I’m excited about trying to understand how populations solve difficult evolutionary problems by separating them into simpler problems in space and time.

Tell us what you do when you aren’t working on research and why. Do you have hobbies? Special talents? Other passions besides science?

I play soccer and lots of board games. I also like messing around with drawing and animation when I have the time. Inspired by Pleuni Pennings, I’ve begun making animated video abstracts for my research that are hopefully accessible to a broad audience. Here’s one I made about how better HIV therapies have fundamentally changed the way that drug resistance evolves within people: