Lawrence is a CEHG postdoctoral fellow in the lab of Noah Rosenberg. He is a graduate of Carleton College (BA, Physics), the University of Chicago (MS, Biophysical Sciences & Computer Science) and UCSF (PhD, Bioinformatics). His research focuses on modeling and simulating evolutionary processes and using the results of simulations to make inferences about how evolution has shaped patterns of genetic and phenotypic variation in natural populations.
This content has been transcribed from an interview that took place on Stanford campus Wednesday, October 14, 2015 with CEHG’s Director of Programs, Cody Montana Sam and Communications Manager, Katie M. Kanagawa. Special thanks to Sharon Greenblum, a postdoc in the Petrov lab, for her help with editing this post.
Can you tell us a bit about your professional background and where you came from?
I’m just starting my postdoc in the Rosenberg lab. I’m a population geneticist. I’ve been doing genetics research for about five or six years now. I got my start as a scientific programmer in Carole Ober’s lab at the University of Chicago, thinking that I would eventually make the jump to software development at a tech company. I wound up becoming completely fascinated with genetics, so I applied instead to graduate school and did my Ph.D. at UCSF on human population genetics. I finished up there in December.
What drew you to population genetics?
I think there are a lot of really fun computational problems in genetics. It’s very challenging to reduce genetic data to summary statistics that provide complete information about evolutionary processes or the relationship between evolutionary processes and interesting traits like hereditary diseases. Because the field is so rich and exploding now with a lot of data, it seemed like a good time to become a geneticist.
Since you started in genetics, have you seen much change in the field?
Yes. When I started as a programmer, it was in the fairly early days of high-throughput sequencing studies. Genotyping had been around for a long time, as well as more traditional sequencing; scientists had gotten very used to those technologies and more or less knew what to do with them, but next-generation sequencing provided new challenges for both data interpretation and data storage. One of my first projects was an exome sequencing study of a small number of individuals. Now, there are sequences for thousands and thousands of people and lots of publically available data. I think the number of open research problems that can potentially be addressed using these datasets seems to have completely exploded. So it has changed quite a bit (laughs).
How would you summarize your research interests?
My interests are mostly on the theory side of population genetics, and trying to test theoretical predictions in novel ways with DNA sequence data. I’m interested in how to efficiently simulate model-based processes like natural selection and demography, and how we can use genetic and phenotypic variation to get some insight into how evolutionary processes work.
Have you had people you looked up to on the path to your postdoc?
When I was in Chicago, I worked with Carole Ober, a geneticist, and also with Dan Nicolae, a statistician;. they were both instrumental mentors for me early on. They reinvigorated my interest in science and introduced me to a new field that I didn’t really know a lot about. They’ve also been really supportive of my career since then—they’ve written a lot of letters for me over the years (laughs).
My Ph.D. mentor was Ryan Hernandez. Ryan’s been really instrumental for my career and training. I had this interest in simulations going way back; when I was an undergraduate, I was a Physics major and I did a lot of simple stochastic simulations. I had tabled that interest for a long time, and luckily,Ryan is one of the foremost experts in population genetics simulation, so getting to work in his lab and pick his brain on these things was really fun. He’s both intellectually stimulating and incredibly supportive, a really good mentor.
Noah Rosenberg is also a fantastic mentor. I started a few months ago and he’s already been really great. It’s really fun to see the different processes that scientists work by. Noah is an exceptionally rigorous thinker, which I really admire.
What lessons would you like to share with other trainees? Are there skills you would recommend they develop?
For Ph.D. students, it’s great for their first project to be something novel but also manageable. Noah seems to have a special talent for finding this balance.
Being able to get a quick first-author project completed early in the PhD allows students to build rigorous research skills and confidence, and gives them the freedom to dream big and take risks in their subsequent projects.
What are your plans for the future?
Ultimately, I want a career that strikes a balance between teaching and research. I went to Carlton College, which is a small liberal arts college. I would love to be somewhere like that, or maybe a teaching-focused state university, somewhere with a strong teaching emphasis and an undergraduate-focused research component too. Many of my most productive summers have been when I’m working with a high-school or college student. Just interacting with them teaches me a lot and gets me to think a little deeper about how to explain and extend my work. Teaching is also really fun-simply presenting ideas (they don’t have to be mine) and having students turn them over, dissect them, and ask questions about them is so rewarding.