1st Presenter: Aaron Wong, Ph.D, Data Scientist & Project Leader, Genomics
Topic: Large-scale genomic data exploration with HumanBase
Biologists using modern experimental methods are generating massive amounts of genome-scale data, capturing molecular-level changes in diverse cellular conditions. The accumulation of public gene expression data offers numerous opportunities for researchers to utilize these data to characterize gene function, understand pathway action, and formulate hypotheses about the molecular basis of disease. However, extracting unbiased signals from these large collections of transcriptomic data remains challenging. I will discuss our work developing a cross-platform multi-organism co-expression search system and building a data processing pipeline architecture for HumanBase.
2nd Presenter: Hayden Nunley, Ph.D., Research Scientist, DevDy
Topic: Making Salt-and-Pepper on a Small Dynamic Graph
Proper development of an embryo requires that stem cells — able to generate embryonic and extraembryonic tissues — choose a specific fate, allowing them to perform different functions. In a model organism like Drosophila, asymmetries already present in the fertilized egg guide highly reproducible spatial patterns of fate; however, in pre-implantation mammalian embryos, no such maternally provided asymmetries exist. Thus, cells in mammalian embryos must self-organize and determine their fates based on interactions with each other. Via the segmentation and tracking of live-imaged embryos with fate reporters, we probe a crucial fate decision in the mouse embryo: the formation of a salt-and-pepper spatial pattern of epiblast and primitive endoderm cells, which go on to form the embryo proper and extra-embryonic tissue, respectively. Our findings challenge existing mathematical models, largely based on fixed-and-stained embryos, of this process — redefining our understanding of the initial conditions for patterning as well as the trajectories of cells in gene expression space.