Jenny Chen, PhD

Research

The existence of innate animal behaviors that are heritable and don't require learning suggests that behavior can be controlled, in part, by genes. However, only a handful of behavior-modifying genes are known, and even less is known about the mechanisms by which they act. My research leverages natural variation in innate animal behavior and uses comparative genomics, single-cell transcriptomics, and computational and statistical methodologies to identify the molecular products responsible for governing behavior. My interdisciplinary research program combines my PhD training in computational genomics with my postdoctoral training in behavioral genetics.

My lab will have to major arms of research: (1) identifying the genetic mechanisms that specify mating and parental care behavior across monogamous and promiscuous rodents, and (2) using computational methods to identify novel, conserved neuropeptides and experimentally probing their biological functions.

Genetic Basis of Reproductive Behaviors

I seek to identify the genetic pathways involved in controlling mating and parental care behaviors. To do so, I take advantage of two sister species of deer mice (P. maniculatus and P. polionotus) with divergent reproductive behaviors. P. maniculatus mate promiscuously and only mothers exhibit parental care while P. polionotus produce offspring with the same mate across their lifetime and both fathers and mathers provide parental care. Using single-nucleus RNA-sequencing and immunostaining, I have identified two hypothalamic cell types -- arginine vasopression neurons and galanin-expressing neurons -- whose abundance appears to govern the extent of parental care innately performed by a species. We are currently performing a large-scale genetic cross to test the association between cell type abundances and parental care behaviors. My independent research lab will continue to investigate the mechanism by which these cell types control behavior, and the genetic determinants of their abundances.

Neuropeptide Discovery

Neuropeptides are potent signaling molecules that play vital roles ranging from regulating sleep to feeding behavior to social behavior. My postdoctoral work also suggests neuropeptides are important evolutionary dials for tuning behavior. While over 100 neuropeptides are known, more likely await discovery: their small size and rapid evolution hinder bioinformatics identification, and those that are expressed in very specific cell types are challenging to detect by bulk RNA-seq or mass spectrometry. I developed a computational screen to uncover new neuropeptides conserved across vertebrates by using advancements in machine learning and large language models to identify small, secreted peptides and single-cell sequencing data to identify genes expressed in specific neuronal cell populations. I have discovered one putative neuropeptide that appears to impact fertility when knocked out of rodent animal models. This work is ongoing and will be continued in my independent lab.

Mentoring/Teaching

Mentoring Philosophy

I have mentored many undergraduate students and research technicians in both experimental and computational work, a few of whom are listed below. My mentoring goal is to ensure my mentees not only gain scientific skills like performing experiments or writing bioinformatics code, but also develop creative and critical thinking skills to design informative experiments, as well as resiliency skills to cope with setbacks. My mentorship style typically begins with hands-on guidance for troubleshooting and experimental design but allows students to increasingly take the lead in decision-making as students grow in expertise. However, I appreciate that students come from diverse backgrounds and may need different levels of guidance depending on their prior exposure to research. My ultimate aim is to empower students with the confidence to question the world around them and equip them with the scientific skills to independently answer those questions.

Ann Gao is currently a sophomore at Harvard College majoring in Bioengineering. She has been instrumental in carrying out our genetic cross the test the association between specifical neuronal cell types and parental care behavior. Ann hopes to enter an MD/PhD program after graduation.

Phoebe Richardson was a key research technician in our investigation of the cellular evolution underlying parental care behavior differences across Peromyscus species. She performed mouse behavior assays and bench work including immunostaining for specific neuronal cell types. She is a co-author on our latest manuscript under review at eLife. Phoebe is now pursuing a PhD in Molecular Biology at Princeton University.

Vicki Wong is a junior at Northeastern University majoring in Data Science and Behavioral Neuroscience. Vicki analyzed terabytes of publicly available RNA-sequencing data to infer the functions of putative neuropeptides. She presented her work as a poster at The Allied Genetics Conference (TAGC) 2024 where she was honored with the NSF Rising Scientist Award for Minoritized Scientists.

Meiling Thompson graduated from Harvard College in 2022 with a joint degree in Neuroscience and Computer Science. For her senior thesis, she developed a deep learning-based software to automatically segment brain regions from scientific images of coronal brain sections. Her software uncovered major anatomical differences between two species of Peromyscus deer mice that may be responsible for their behavioral differences.

Abigail Joseph graduated from Harvard College in 2021 with a degree in Molecular and Cellular Biology. As a sophomore, Abby spearheaded the effort to develop an automated pipeline for segmenting scientific images of the brain. She is currently pursuing an MD/PhD at Harvard Medical School.

Shylee Ezroni participated in the Broad Summer Research Program in 2018 where she analyzed whether conservation of a gene's expression level is predictive of whether that gene is involved in human disease. Her work won the poster award at the National Biomedical Research Conference for Minority Students in 2015.

Teaching Philosophy

My teaching goal is to generate excitement about the topic at hand and, through an intentionally designed syllabus, lead students toward mastery of the topic as painlessly as possible. I believe effective courses include 1) well-designed learning objectives, 2) appropriately-paced communication of new information and skills, and 3) skill-building assignments that give students opportunities to build mastery. My courses encourage active learning through activities that involve student participation, such as small-group paper discussions, or hands-on learning, such as exercises that involve analyzing real-world data. Additionally, the most impactful courses I've taken have showcased how the subject has profoundly influenced humanity or reshaped our perception of our world. In my own genetics course, I paired the science of genetics with patient presentations that challenged student's notions about the distinction between human variation and disease and provoked discussion on the ethical implications of CRISPR editing and gene therapy. Ultimately, my goal is to cultivate curiosity and empower my students with the technical and critical thinking skills to better understand the world around them.

Courses Taught
Molecular Biology and Genetics in Modern Medicine, MIT/Harvard Medical School [Instructor 2016; Teaching Assistant 2013-2015]

Selected Publications

Full publication list available at Google Scholar

Chen J, Richardson PR, Kirby C, Eddy SR, and HE Hoekstra. Cellular evolution of the hypothalamic preoptic area of behaviorally divergent deer mice. Under review at eLife.

Kautt A*, Chen J*, Lewarch CL, Hu C, Turner K, Lassance JM, Baier F, Bedford NL, Bendesky A, and HE Hoekstra. Evolution of gene expression across brain regions in behaviorally divergent deer mice and their hybrids. Molecular Ecology. 2024; e17270. *Contributed equally.

Chen J, Swofford R, Johnson J, Cummings BB, Rogel N, Lindblad-Toh K, Haerty W, di Palma F, and A Regev. A quantitative model for characterizing the evolutionary history of mammalian gene expression. Genome research. 2019; 29: 53-63.

Dixit A*, Parnas O*, Li B, Chen J, Fulco CP, Jerby-Arnon L, Marjanovic ND, Dionne D, Burks T, Raychowdhury R, Adamson B, Norman TM, Lander ES, Weissman JS, Friedman N, and A Regev. Perturb-seq: dissecting molecular circuits with scalable single-cell RNA profiling of pooled genetic screens. Cell. 2016; 167: 1853-1866.

Engreitz JM, Haines JE, Perez EM, Munson G, Chen J, Kane M, McDonel PE, Guttman M, and ES Lander. Local regulation of gene expression by lncRNA promoters, transcription and splicing. Nature. 2016; 539: 452.

Chen J, Shishkin A, Zhu X, Kadri S, Hanna J, Regev A, and M Garber. Evolutionary analysis across mammals reveals distinct classes of long noncoding RNAs. Genome biology. 2016; 17: 19.