Cross-species analysis of single-cell transcriptomic data
- 1Biozentrum, Universität Basel, Switzerland
- 2Department of Molecular and Cellular Biology, Faculty of Arts and Sciences, Harvard University, United States
The ability to profile hundreds of thousands to millions of single cells using scRNA-sequencing has revolutionised the fields of cell and developmental biology, providing incredible insights into the diversity of forms and functions of cell types across many species. These technologies hold the promise of developing detailed cell type phylogenies which can describe the evolutionary and developmental relationships between cell types across species. This will require sampling of many species and taxa using single-cell transcriptomics, and methods to classify cell type homologies and diversifications. Many tools currently exist for analyzing single cell data and identifying cell types. However, cross-species comparisons are complicated by many biological and technical factors. These factors include batch effects common to deep-sequencing approaches, well known evolutionary relationships between orthologous and paralogous genes, and less well-understood evolutionary forces shaping transcriptome variation between species. In this review, I discuss recent developments in computational methods for the comparison of single-cell-omic data across species. These approaches have the potential to provide invaluable insight into how evolutionary forces act at the level of the cell and will further our understanding of the evolutionary origins of animal and cellular diversity.
Keywords: Evolutionary Cell Biology, single-cell RNA sequencing, transcriptome evolution, species comparisons, cell types
Received: 31 Mar 2019;
Accepted: 12 Aug 2019.
Copyright: © 2019 Shafer. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Dr. Maxwell E. Shafer, Biozentrum, Universität Basel, Basel, Switzerland, email@example.com