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Genome-Wide Analysis of Differential Gene Expression and Splicing in Excitatory Neurons and Interneuron Subtypes

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Genome-Wide Analysis of Differential Gene Expression and Splicing in Excitatory Neurons and Interneuron Subtypes Research Articles: Cellular/Molecular Genome-wide analysis of differential gene expression and splicing in excitatory neurons and interneuron subtypes https://doi.org/10.1523/JNEUROSCI.1615-19.2019 Cite as: J. Neurosci 2019; 10.1523/JNEUROSCI.1615-19.2019 Received: 8 July 2019 Revised: 17 October 2019 Accepted: 3 December 2019 This Early Release article has been peer-reviewed and accepted, but has not been through the composition and copyediting processes. The final version may differ slightly in style or formatting and will contain links to any extended data. Alerts: Sign up at www.jneurosci.org/alerts to receive customized email alerts when the fully formatted version of this article is published. Copyright © 2019 Huntley et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license, which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properly attributed. 1 Genome-wide analysis of differential gene expression and splicing in excitatory 2 neurons and interneuron subtypes 3 4 Abbreviated Title: Excitatory and inhibitory neuron transcriptomics 5 6 Melanie A. Huntley1,2*, Karpagam Srinivasan2, Brad A. Friedman1,2, Tzu-Ming Wang2, 7 Ada X. Yee2, Yuanyuan Wang2, Josh S. Kaminker1,2, Morgan Sheng2, David V. Hansen2, 8 Jesse E. Hanson2* 9 10 1 Department of Bioinformatics and Computational Biology, 2 Department of 11 Neuroscience, Genentech, Inc., South San Francisco, CA. 12 *Correspondence to [email protected] or [email protected] 13 14 Conflict of interest: All authors are current or former employees of Genentech, Inc. 15 16 Abstract 17 Cortical circuit activity is shaped by the parvalbumin (PV) and somatostatin (SST) 18 interneurons that inhibit principal excitatory (EXC) neurons and the vasoactive intestinal 19 peptide (VIP) interneurons that suppress activation of other interneurons. To understand 20 the molecular-genetic basis of functional specialization and identify potential drug targets 21 specific to each neuron subtype, we performed a genome wide assessment of both gene 22 expression and splicing across EXC, PV, SST and VIP neurons from male and female 23 mouse brains. These results reveal numerous examples where neuron subtype-specific 24 gene expression, as well as splice-isoform usage, can explain functional differences 25 between neuron subtypes, including in presynaptic plasticity, postsynaptic receptor 26 function, and synaptic connectivity specification. We provide a searchable web resource 27 for exploring differential mRNA expression and splice form usage between excitatory, 28 PV, SST, and VIP neurons (http://research- 29 pub.gene.com/NeuronSubtypeTranscriptomes). This resource, combining a unique new 30 data set and novel application of analysis methods to multiple relevant data sets, 31 identifies numerous potential drug targets for manipulating circuit function, reveals 1 32 neuron subtype-specific roles for disease-linked genes, and is useful for understanding 33 gene expression changes observed in human patient brains. 34 35 Significance statement 36 Understanding the basis of functional specialization of neuron subtypes and identifying 37 drug targets for manipulating circuit function requires comprehensive information on 38 cell-type specific transcriptional profiles. We sorted excitatory neurons and key 39 inhibitory neuron subtypes from mouse brains and assessed differential mRNA 40 expression. We used a genome-wide analysis which not only examined differential gene 41 expression levels but could also detect differences in splice isoform usage. This analysis 42 reveals numerous examples of neuron subtype-specific isoform usage with functional 43 importance, identifies potential drug targets, and provides insight into the neuron 44 subtypes involved in psychiatric disease. We also apply our analysis to two other 45 relevant data sets for comparison, and provide a searchable website for convenient access 46 to the resource. 47 48 Introduction 49 Circuit activity in the cortex and hippocampus is shaped by distinct contributions from 50 specific interneuron subpopulations 1. Recently, cell-type specific manipulation using 51 optogenetic approaches has provided insight into the circuit roles of three classes of 52 interneurons—those that express parvalbumin (PV), somatostatin (SST), or vasointestinal 53 peptide (VIP) 2. While PV, SST and VIP neurons can be further subdivided, and other 54 interneuron subtypes also exist, the majority of interneurons fall into these three broad, 55 non-overlapping classes 3-5. PV interneurons provide feed-forward inhibition to 56 pyramidal neurons and control the temporal fidelity and synaptic integration of excitatory 57 inputs 6,7, and are critical for the generation of gamma oscillations 8-10. SST interneurons 58 are spontaneously active and provide powerful regulation of local neuronal activity 59 through dense connections to nearby pyramidal neurons 11. VIP interneurons exert their 60 influence on network function via a dis-inhibitory circuit such that when driven by local, 61 long-range, or neuromodulatory inputs, VIP neurons inhibit SST interneurons (and to a 62 lesser extent PV interneurons), resulting in reduced inhibition of pyramidal neurons 12-14. 2 63 Consistent with important roles in circuit regulation, dysfunction of cortical 64 interneurons has been implicated in various psychiatric and cognitive disorders. For 65 example, data from mouse models and human postmortem tissue point to PV neuron 66 dysfunction in schizophrenia (SCZ) 15,16, and PV and SST interneuron dysfunction are 67 seen in Alzheimer’s disease (AD) mouse models 17-20. Interneuron dysfunction is also 68 implicated in autism spectrum disorder (ASD) and bipolar disorder (BD) 21,22. 69 Consistent with the roles of PV and SST interneurons in inhibition of pyramidal neurons, 70 reduced function of these interneurons occurs in animal models of epilepsy 23,24. 71 Conversely, reducing activation of VIP interneurons (which normally disinhibit 72 excitatory neurons) can oppose seizure induction in animal models 25. Given the roles in 73 diverse nervous system diseases, it is of great interest to identify therapeutic targets that 74 could selectively modulate these interneuron subtypes widely across the cortex. 75 Recent studies profiling neurons from specific brain regions using single-cell 76 RNA-seq and sorted population sequencing strategies have improved our understanding 77 of neuron subtype-specific gene expression 4,5,26-28. However, despite the importance of 78 alternative splicing in the nervous system 29, the current understanding of interneuron 79 subtype-specific spliceform usage is superficial. Large-scale, genome-wide analysis of 80 splicing across neuron subtypes has been limited by 1) the low throughput of long-read 81 technologies, 2) few data sets containing both excitatory neurons and inhibitory neuron 82 subtypes with sufficient coverage at splice junctions, and 3) a lack of methods that can 83 utilize biological replicates and harness splice junction data, rather than relying upon 84 inference from exonic coverage. 85 In order to identify druggable targets with interneuron subtype-specific expression 86 across the cortex, and to comprehensively assess alternative splicing across neuron 87 subtypes, we used FACS to isolate cortical neurons (neocortex + archicortex) from 88 transgenic mice expressing fluorescent proteins in excitatory neurons (EXC), or PV, SST, 89 or VIP interneurons, and obtained RNA-seq data for each cell type. In these 90 experiments, we used a robust number of biological replicates for each neuron subtype, 91 and used Thy1-GFP mice to sort a population of excitatory neurons that avoids the glial 92 contamination inherent in Emx-cre sorting strategies. We analyzed this data to identify 93 differential gene expression and used graph analysis of splice junction reads to assess 3 94 differential splicing with more power and specificity than can be obtained by inference 95 from exonic reads. We provide this genome-wide analysis of neuron subtype 96 transcriptomes in a searchable database as an online resource for the community, and 97 include new analysis of relevant published datasets for comparison. This resource and our 98 analysis provide extensive insight into transcriptomic differences correlating with the 99 unique functional properties of interneurons, highlight numerous genes that might 100 represent targets for selective modulation of interneuron and circuit function, and 101 implicate specific neuron subtypes in psychiatric diseases. 102 103 104 Materials and Methods 105 Mice 106 All protocols involving animals were approved by Genentech’s Institutional Animal Care 107 and Use Committee, in accordance with guidelines that adhere to and exceed state and 108 national ethical regulations for animal care and use in research. Excitatory neurons were 109 sorted from four male and two female Thy1-GFP-M mice, which exhibit sparse 110 expression of EGFP in excitatory neurons (RRID:IMSR_JAX:007788) 30. Interneurons 111 were sorted using tdTomato Cre reporter mice (RRID:IMSR_JAX:007914) 31 crossed to 112 PV-Cre (RRID:IMSR_JAX:008069) 32 (three males and three females), or Sst-IRES-Cre 113 (RRID:IMSR_JAX:013044) (four males and two females), or Vip-IRES-Cre knock-in 114 mice (RRID:IMSR_JAX:01908) 33 (two males and four females). For optogenetic 115 experiments, PV-Cre mice were crossed to R26-CAG-LSL-2XChETA-tdTomato mice 116 (RRID:IMSR_JAX:017455).
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