Journal Article

In silico lineage tracing through single cell transcriptomics identifies a neural stem cell population in planarians

Molinaro, Alyssa M., Pearson, Bret J.

2016

Overview

Background The planarian Schmidtea mediterranea is a master regenerator with a large adult stem cell compartment. The lack of transgenic labeling techniques in this animal has hindered the study of lineage progression and has made understanding the mechanisms of tissue regeneration a challenge. However, recent advances in single-cell transcriptomics and analysis methods allow for the discovery of novel cell lineages as differentiation progresses from stem cell to terminally differentiated cell. Results Here we apply pseudotime analysis and single-cell transcriptomics to identify adult stem cells belonging to specific cellular lineages and identify novel candidate genes for future in vivo lineage studies. We purify 168 single stem and progeny cells from the planarian head, which were subjected to single-cell RNA sequencing (scRNAseq). Pseudotime analysis with Waterfall and gene set enrichment analysis predicts a molecularly distinct neoblast sub-population with neural character (νNeoblasts) as well as a novel alternative lineage. Using the predicted νNeoblast markers, we demonstrate that a novel proliferative stem cell population exists adjacent to the brain. Conclusions scRNAseq coupled with in silico lineage analysis offers a new approach for studying lineage progression in planarians. The lineages identified here are extracted from a highly heterogeneous dataset with minimal prior knowledge of planarian lineages, demonstrating that lineage purification by transgenic labeling is not a prerequisite for this approach. The identification of the νNeoblast lineage demonstrates the usefulness of the planarian system for computationally predicting cellular lineages in an adult context coupled with in vivo verification.

• Publisher: BioMed Central,Springer Nature B.V
• Subject: adult stem cells / adults / Animal Genetics and Genomics / Animals / Bioinformatics / Biomedical and Life Sciences / brain / Cell cycle / Cell Lineage / Computer Simulation / data collection / Evolutionary Biology / Gene expression / Gene set enrichment analysis / genes / genetically modified organisms / head / Homeostasis / Human Genetics / labeling techniques / Life Sciences / Microbial Genetics and Genomics / Nervous system / Neural stem cells / Neural Stem Cells - cytology / Neural Stem Cells - metabolism / Neurogenesis / Planarians - cytology / Planarians - metabolism / Plant Genetics and Genomics / prediction / progeny / Purification / Regeneration / Ribonucleic acid / RNA / Schmidtea mediterranea / sequence analysis / Sequence Analysis, RNA - methods / Single-Cell Analysis - methods / Single-Cell Omics / Stem cell transplantation / Stem cells / tissue repair / Transcriptome / transcriptomics / Turbellaria