Department of Chemical and Biomolecular Engineering; Helen Wills Neuroscience Institute; Center for Computational Biology; California Institute for Quantitative Biosciences, QB3, University of California, Berkeley, Berkeley, United States; Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, United States; Broad Institute of Harvard and MIT, Cambridge, United States; Center for Brain Science and Department of Molecular and Cellular Biology, Harvard University, Cambridge, United States
Irene E Whitney
Center for Brain Science and Department of Molecular and Cellular Biology, Harvard University, Cambridge, United States
Salwan Butrus
Department of Chemical and Biomolecular Engineering; Helen Wills Neuroscience Institute; Center for Computational Biology; California Institute for Quantitative Biosciences, QB3, University of California, Berkeley, Berkeley, United States
Yi-Rong Peng
Center for Brain Science and Department of Molecular and Cellular Biology, Harvard University, Cambridge, United States; Department of Ophthalmology, Stein Eye Institute, UCLA David Geffen School of Medicine, Los Angeles, United States
The genesis of broad neuronal classes from multipotential neural progenitor cells has been extensively studied, but less is known about the diversification of a single neuronal class into multiple types. We used single-cell RNA-seq to study how newly born (postmitotic) mouse retinal ganglion cell (RGC) precursors diversify into ~45 discrete types. Computational analysis provides evidence that RGC transcriptomic type identity is not specified at mitotic exit, but acquired by gradual, asynchronous restriction of postmitotic multipotential precursors. Some types are not identifiable until a week after they are generated. Immature RGCs may be specified to project ipsilaterally or contralaterally to the rest of the brain before their type identity emerges. Optimal transport inference identifies groups of RGC precursors with largely nonoverlapping fates, distinguished by selectively expressed transcription factors that could act as fate determinants. Our study provides a framework for investigating the molecular diversification of discrete types within a neuronal class.
