Our lab is interested in uncovering the genetic basis of human-specific traits such as sweating. While humans use sweat glands all over their bodies to cool off, nearly every other mammal employs them exclusively in their feet to aid in traction during climbing. In order to understand this massive transformation in function, it is first necessary to understand the genetic factors controlling sweat gland development, about which there is very little known. In order to gain insight on this, we employed single-nucleus RNA sequencing (sn-Seq) on the sweat-gland rich foot skin of mice during a developmental stage where the sweat glands are being formed (P1.5). Our aim was to identify the genetic signature of the sweat gland progenitors, patches of basal keratinocyte cells called placodes.
My task was to analyze the data from this experiment in silico. I used dimensionality reduction methods to group the sequenced cells into cell types which I classified using well-known gene markers. I then identified subpopulations of cell types and uncovered differentially expressed genes in these distinct cell populations. Within basal keratinocytes, which give rise to skin appendages such as sweat glands and hair follicles, I uncovered 3 distinct subpopulations expressing different genes. In the Fall, I will use in situ hybridization to try to uncover the spatial distribution of the cell populations and if they can be marked by the differentially expressed genes I pulled out. If any of these populations pertain to sweat gland progenitors, the other genes expressed by these cells will give us invaluable information about what is needed to build sweat glands and therefore what might’ve been acted on throughout evolutionary history to adjust their function.
Being my first time using computational biology, this research experience has complemented my wet-lab genetics experience such that I can now propose stronger hypotheses before doing experiments at the bench.