Dr. Bushra Raj
PhD
Harvard University
Friday, June 8, 2018 - 11:00am
CCBR Red Room
Abstract:
A central goal in the field of developmental biology is to understand how the brain is specified and
organized regionally, cellularly and molecularly. A fundamental component of realizing this vision is
characterizing the origins and fates of cells during development. Critical insights into these processes have
been gained using genetic markers, perturbations and fate mapping. However, analyses have been largely
restricted to small gene sets or particular cell types resulting in ‘local’ views of neural development. To
advance the field further, efforts need to be directed towards obtaining a global view of the genealogy of the
brain.
We developed a technology, scGESTALT, which combines cell type identification by single-cell RNA
sequencing with lineage recording by CRISPR-Cas9 cumulative barcode editing to simultaneously
determine cell identity and lineage relationships. We sequenced ~60,000 transcriptomes from the juvenile
zebrafish brain and identified more than 100 cell types and marker genes, generating a global catalogue of
cell types in a vertebrate brain. In addition, we implemented a strategy for in vivo barcode editing across
two time windows that encompass early and late embryogenesis, and obtained >10,000 distinct barcodes.
We isolated thousands of single-cell transcriptomes and their associated lineage barcodes from the brain
with droplet microfluidics. Using the patterns of shared edits between barcodes, we generated lineage trees
with hundreds of branches and tips representing the associated cell types. Inspection of the trees identified
restrictions at the level of cell types and brain regions.
Using a time series of single-cell transcriptomics data of >140,000 cells spanning 10 developmental stages
from embryo to larva, and a trajectory reconstruction algorithm (URD), we are now now generating largescale
cell specification trees during zebrafish brain development to interrogate molecular regulation of
neuronal cell diversity at a global scale. Combining this with scGESTALT will enable one to query the
relationship between lineage and cell identity for thousands of cells during development.
Donnelly Centre Postdoc/Research Associate Seminar series
Poster: