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: