Description

Mapping splicing bias of the single hematopoietic stem cell by meta-analysis

Tal Shay^1,2*, 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