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Deconstructing Spinal Interneurons, One Cell Type at a Time Mariano Ignacio Gabitto

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Deconstructing Spinal Interneurons, One Cell Type at a Time Mariano Ignacio Gabitto Deconstructing spinal interneurons, one cell type at a time Mariano Ignacio Gabitto Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy under the Executive Committee of the Graduate School of Arts and Sciences COLUMBIA UNIVERSITY 2016 © 2016 Mariano Ignacio Gabitto All rights reserved ABSTRACT Deconstructing spinal interneurons, one cell type at a time Mariano Ignacio Gabitto Abstract Documenting the extent of cellular diversity is a critical step in defining the functional organization of the nervous system. In this context, we sought to develop statistical methods capable of revealing underlying cellular diversity given incomplete data sampling - a common problem in biological systems, where complete descriptions of cellular characteristics are rarely available. We devised a sparse Bayesian framework that infers cell type diversity from partial or incomplete transcription factor expression data. This framework appropriately handles estimation uncertainty, can incorporate multiple cellular characteristics, and can be used to optimize experimental design. We applied this framework to characterize a cardinal inhibitory population in the spinal cord. Animals generate movement by engaging spinal circuits that direct precise sequences of muscle contraction, but the identity and organizational logic of local interneurons that lie at the core of these circuits remain unresolved. By using our Sparse Bayesian approach, we showed that V1 interneurons, a major inhibitory population that controls motor output, fractionate into diverse subsets on the basis of the expression of nineteen transcription factors. Transcriptionally defined subsets exhibit highly structured spatial distributions with mediolateral and dorsoventral positional biases. These distinctions in settling position are largely predictive of patterns of input from sensory and motor neurons, arguing that settling position is a determinant of inhibitory microcircuit organization. Finally, we extensively validated inferred cell types by direct experimental measurement and then, extend our Bayesian framework to full transcriptome technologies. Together, these findings provide insight into the diversity and organizational logic through which inhibitory microcircuits shape motor output. Contents List of Figures ........................................................................................................................................... iii List of Tables ............................................................................................................................................ iv Acknowledgments ...................................................................................................................................... v Chapter 1 Introduction ............................................................................................................................... 1 1.1 General Overview ................................................................................................................... 1 1.2 Cellular Diversity .................................................................................................................... 3 1.3 The Organization of Spinal Circuits ..................................................................................... 7 1.4 Molecular Diversification of Spinal Neurons ................................................................... 10 1.5 Computational Assessment of Cellular Diversity ............................................................ 17 Chapter 2 Molecular Characterization of Spinal Interneurons ........................................................... 20 2.1 Introduction ........................................................................................................................... 20 2.2 Results .................................................................................................................................... 21 2.2.1 Transcriptional diversity of V1 inhibitory interneurons.................................. 21 2.2.2 A sparse Bayesian approach for uncovering neuronal diversity .................... 26 2.2.3 V1 diversity extracted from transcriptional data .............................................. 44 2.2.4 Clustering Cell types into Groups ...................................................................... 47 2.3 Discussion .............................................................................................................................. 52 Chapter 3 Analysis of the Settling Position of Spinal Interneurons .................................................. 55 3.1 Introduction ........................................................................................................................... 55 3.2 Results .................................................................................................................................... 56 i 3.2.1 Settling position of subsets of V1 interneurons ................................................ 56 3.2.2 Incorporating spatial information into our computational analysis ............... 65 3.2.3 Spatial information reveals further V1 interneuron diversity ......................... 71 3.2.4 A cladistic analysis of transcription factor expression .................................... 77 3.3 Discussion .............................................................................................................................. 83 Chapter 4 Corroborating V1 diversity and cell type physiological properties ................................. 85 4.1 Introduction ........................................................................................................................... 85 4.2 Results .................................................................................................................................... 86 4.2.1 Validation of Bayesian Model Prediction ......................................................... 86 4.2.2 Physiological Distinctions among V1 clades.................................................... 97 4.3 Discussion ............................................................................................................................ 101 Chapter 5 Spinal Inhibitory Interneuronal Micro-Circuitry ............................................................. 104 5.1 Introduction ......................................................................................................................... 104 5.2 Results .................................................................................................................................. 105 5.2.1 Mapping the relative position of V1 subpopulations and motor pools ....... 105 5.2.2 Positional constraints on interconnectivity between V1 interneurons and motor neurons ............................................................................................................... 109 5.3 Discussion ............................................................................................................................ 113 Chapter 6 Conclusion............................................................................................................................. 115 Bibliography ........................................................................................................................................... 120 Appendix A ............................................................................................................................................. 167 ii List of Figures 1.1 Cortical inhibitory interneurons are heterogeneous, with various subtypes distinguished by different morphological, physiological and molecular characteristics ............................................6 1.2 The organization of spinal circuits .............................................................................................9 1.3 The development of spinal progenitor domains and the specialization of motor pools ..........14 1.4 Spinal interneuron diversity .....................................................................................................15 2.1 Transcription Factors Enriched in V1 Interneurons and Characterization of Antibody Specificity ......................................................................................................................................24 2.2 Prevalence of Identified Transcription Factors within V1 Interneurons. ................................25 2.3 Bounds on the fractional values achieved by the NNCLS solution computed using transcriptional information.............................................................................................................31 2.4 Simulated tempering facilitates exploration of the diversity landscape. .................................41 2.5 Cross-Validation experiments ..................................................................................................44 2.6 Cell Type Discovery using Transcription Factor Expression Information ..............................46 2.7 Definition of clustering algorithm that creates groups of correlated cell types. ......................49 2.8 Clustering Algorithm Arranging Cell Types into Correlated Groups .....................................51 3.1 Spatial Distributions of Transcriptionally Defined V1 Subpopulations ..................................59 3.2 Spatial Segregation of V1 Interneuron Subpopulations...........................................................60 3.3 Constancy of V1Sp8 and V1Pou6f2 Interneuron
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