The Carolyn Slayman Prize is awarded yearly in the Department of Genetics to recognize graduate students who have excelled both in their research as well as in fostering collaboration and growth in the larger community. This year, that prize has been awarded to Dr. Xiao Liu of the Hammarlund Lab and Dr. Daniel Burkhardt of the Krishnaswamy Lab.
Liu developed an interest in neurobiology and development during her undergraduate years working on fear memory. Her graduate studies focused on an RNA ligase called RTCB, and how its targets affect axon regeneration. It was previously thought in the lab that a novel target was mediating regeneration, but Liu discovered that it was one of the endogenous substrates of the ligase - a fragment of mRNA - that mediated it via a novel mechanism. This work “has implications in three fields of biology,” Liu said. This is the first noncoding RNA directly generated from cleavage of mature RNA - an unexpected finding. The work also reveals a novel mechanism for how cells can cope with stress and how they mediate axon regeneration.
Throughout her training, Liu has been heavily involved in mentoring, having worked with high school students, undergraduates, and other graduate students from all levels of experience. She believes that “mentoring helps promote further discovery in science,” and strives to include these efforts in her career in academia. Motivated by her own experiences, she helped promote United States graduate programs to other international students while at Yale. Alongside another graduate student, she was able to advertise information relevant to international students on Yale’s website for Biological and Biomedical Sciences, to “encourage more international students to apply and come to graduate school in the United States.”
Currently, Liu is in her postdoctoral fellowship at UC Berkeley studying frog biology and hopes to remain in academia. She is drawn to the idea of spending her future collaborating with other scientists, and focusing on “clear scientific communication.” In her spare time, she enjoys hiking - something she does more often now that she’s in California - and baking.
The joint recipient of the prize, Burkhardt developed his passion for genomics as an undergraduate student. He was drawn to the Genetics department at Yale as a place to seek answers to biologically and clinically relevant questions using single-cell analysis. “There has been a revolution over the past few years in single-cell sequencing,” said Burkhardt. This revolution has enabled researchers to profile gene expression in thousands of single cells in a way that has “become routine in many genomics labs,” he said. Making sense of this massive amount of data, however, is a different matter. In his graduate studies, Burkhardt worked on unsupervised machine learning as a way to investigate the effect of experimental perturbation on single cell readouts. Previous methods used at “bulk” data analyses, which grouped cells together, whereas the work done by Burkhardt was able to look at this type of data in a granular sense, to “get a much better picture of the underlying biology,” he said.
Burkhardt, like Liu, is passionate about community outreach and education. Recognizing the gap between the cutting-edge work being done by machine learning researchers and the tools that biological researchers need, he spearheaded a workshop entitled Machine Learning for Single Cell Analysis together with another graduate student. The workshop sought to educate other graduate and postdoctoral students regarding topics in computational biology for biologists. The course received funding from the Center for Teaching and Learning to expand and in each iteration has grown in scope and size. Burkhardt feels that this workshop has helped “foster the computation-curious community of researchers at Yale.” More recently, Burkhardt began work with a group of other researchers in partnership with the Chan Zuckerberg Initiative to formalize biological problems into quantified problems. Eight tasks across single cell analysis are organized, accompanied by scoreboards and benchmarking, on the website Open Problems in Single Cell Biology (OPSCB). Looking forward, he hopes to expand these challenges to look at multimodal single cell sequencing.
Currently, Burkhardt works for Cellarity, a biotechnology company in Boston, which is also supporting the OPSCB challenge alongside the Chan-Zuckerberg Initiative. He found the work he completed during his graduate studies made his “transition to industry a very smooth one,” and is grateful to the Genetics Department for supporting student-run initiatives that helped him realize his desire to foster collaboration between computer science and biology.