Description
Mapping splicing bias
of the single hematopoietic stem cell by meta-analysis
Tal Shay1,2*, Amit Magen2, Hadas Ner-Gaon1, Guy
Shani2, Roi Gazit3
1Department of Life
Sciences; 2Department of Software and Information
Systems Engineering; 3The Shraga Segal Department for Microbiology,
Immunology and Genetics, Ben-Gurion University of the Negev, Be'er Sheva 84105,
Israel
*Corresponding author
Hematopoietic
stem cells (HSCs) differentiate into all blood and immune cell types. As a
population, HSCs express many genes, and for the vast majority of those genes,
many isoforms. Single cell RNA sequencing (scRNA-seq) has revolutionized the
understanding of cell population heterogeneity in many biological systems. In
particular, for hematopoietic stem cells (HSCs), scRNA-seq revealed lineage priming,
clonality, and differentiation trajectories. However, the isoform usage at the
single HSC level is still unknown, and while the number of publically available
scRNA-seq datasets of HSCs increases fast, each such dataset explores a
specific question and meta-analysis to leverage multiple scRNA-seq datasets is
practically non-existent.
Here we collected
ten publicly available murine HSCs scRNA-seq datasets to demonstrate the
feasibility of meta-analysis of scRNA-seq from different experiment. We
identified genes for which HSCs display splicing bias, where the single cell
isoform usage is significantly different from the population level usage. As
splicing bias is consistent between scRNA-seq protocols, it seems to reflect a
real biological preference of the cells, whose regulation and functional
consequence remains to be studied.
Funding:
ISF Grant 500/15; Broad-ISF
Grant 1644/15