By Megan Guerin
I recently had the opportunity to interview Dr. Bushra Raj, a newly minted assistant professor in the Cell and Developmental Biology Department. In a short time period, she has quickly established a lab that ambitiously aims to map vertebrate brain development through single-cell lineage tracing technology in zebrafish. This interview serves to highlight Dr. Raj’s influential work, as well as extend a warm welcome from the Penn community.
Could you tell us a bit about your doctoral and post-doctoral training?
I did my Ph.D. at the University of Toronto in Professor Ben Blencowe's lab. My thesis focused on investigating the mechanistic regulation and functional impacts of alternative splicing during neural development. For my post-doc, I worked with Alex Schier at Harvard University. My research was focused on characterizing cell diversity in the zebrafish and developing new technology to track the lineage histories of thousands of cells during development.
Congratulations on establishing your laboratory! Can you briefly describe your future area of research?
I'm very excited to be at Penn! Our big vision is to paint a molecular picture of vertebrate brain development. The main questions we plan to ask are: what cell types are generated at various stages of brain development? What are the fates and or the origins of these cells? What are the molecular cascades that underlie their specification? We plan to answer these questions using genomics and genetic tools, as well as zebrafish as our model system.
What initially sparked your interest in vertebrate brain development? What influenced your decision to tackle it from a computational genomics perspective?
Honestly, I think I was initially drawn to the innately complex nature of the brain. The complexity is simultaneously frustrating, as it's challenging to study, but exciting because it's unlikely that one would run out of ideas or areas to explore. The genomics aspect comes from my doctoral training, so I was very interested in answering these questions through large data sets. Those data sets allow you to observe changes over long periods and help establish simultaneous measurements, different inputs, or paradigms. However, it can also be quite challenging to make sense of those large data sets. But once you crack it, the code is very gratifying.
Based on your experience, what are some essential characteristics of a successful graduate student?
Success looks different for different people, and I believe there are many ways to achieve your vision of success. What worked for me was to be self-motivated, and that's definitely a hard one. Don't be afraid to ask questions, and always be open to feedback from others. Be able to adapt and pivot when needed.
Do you have any advice for students progressing through their Ph.D. or MD/Ph.D. training?
You know, there comes a time in your training where things are just not working and, in those moments, it's good to be proactive. Ask your colleagues about what you can do to change and read up on old papers because sometimes, the old school methods are better than the new-age ones. You can also work on a side project for a little bit, and if all else fails, be open to asking a different set of questions.
Looking back, what is one thing you wish you knew about graduate school ahead of time?
I wish I had known that a graduate degree does not limit you to academia. Personally, I love academia, and I've always wanted to be a professor. Still, sometimes I wonder if I had known that there were so many other options, would I have considered pursuing them? Perhaps. Right now, the climate is much better, and people are more aware of their options. As a new PI, it's my responsibility to ensure that graduate students get the experience and support for whatever they wish to do in the future.
What do you think has been the most important lesson that you've learned as a scientist? This can range anywhere from personal to moral, or technical to theoretical?
The most important thing that I've learned is that, often, there are many explanations for the data. Sometimes we are so focused on proving our theories correct that confirmation bias has become an issue. I'd say that it would be wise to pause for a moment and consider other alternatives as well.
As an assistant professor in the Cell and Developmental Biology department, do you have a favorite gene? If so, which one would you choose and why?
I love this question. My favorite gene is DSCAM, which stands for Down Syndrome Cell Adhesion Molecule, and it refers explicitly to the Drosophila melanogaster homolog. The human version is not nearly as interesting, but the fly gene can generate over 38,000 alternatively spliced isoforms that are important for neuronal circuit development. It's incredibly fascinating that the fly has figured a means to compact so much regulatory information into one gene.
How are you enjoying your time in Philadelphia? Have you found any hidden gems that you would like to share?
You know, being in Philly reminds me of living in the big city again after spending some time in the Boston and Cambridge area. It reminds me of all the things that I loved about living in Toronto. There's a diverse and expansive dining scene, people of many different backgrounds, and a thriving arts and culture scene. Also, I love outdoor activities and Philly, plus the surrounding areas, has several options to satisfy my biking, climbing, and skiing urges. One hidden gem is QU Japan Bistro & Bar. It was one of the first restaurants I tried after moving to Philly, and it really was just so good.
And finally, are you currently accepting rotation students? If so, do you have any exciting projects in mind?
I am accepting rotation students! I officially started my lab in the summer, and we're excited to establish a fun and supportive lab culture for new students. One of the projects we're working on is developing some new sensors to detect signaling pathways during development. We're planning to use CRISPR technology to record the signaling histories of cells during brain development. These histories are recorded in the animal's genome as barcodes that we can later recover and analyze through sequencing.
