シンポジウム
52 神経科学とシングルセル解析技術
52 Neuroscience and single-cell transcriptomics
座長：山形 方人（Harvard University） |
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| 2022年6月30日 14:00～14:15 沖縄コンベンションセンター 会議場A1 第2会場
1S02a-01
シングルセル技術と神経科学
A Primer of Single Cell Technologies and Neuroscience
*山形 方人(1)
1. ハーバード大学
*Masahito Yamagata(1)
1. Harvard University
Keyword: single-cell transcriptomics, cell atlas, chick, retina
Recent advances in single-cell RNA sequencing technologies are changing our view on neuronal and glial type classification, as well as cellular state and biomarker identification underlying development, aging, and diseases of the nervous system. Accordingly, single-cell technologies are becoming widely adopted in many research laboratories. The advancements have coincided with cutting edge methods in genetic, epigenetic, spatial, temporal, proteomic, and taxonomic information profiling in individual cells. With the increasing availability of both commercial and in-house single-cell technology platforms and reagents, as well as the rapid development of computational tools, we have reached a point where neuroscientists can use single-cell technologies and multimodal approaches to achieve exciting discoveries. Furthermore, biomedical researchers are beginning to use the same technologies to understand various clinical problems in the nervous system, such as malignant tumors, developmental disorders, and dementia. In this symposium, introductory information will be provided to help researchers design single-cell transcriptomic studies, including experimental hardware, protocol selection, quality control, data analysis, biological interpretation, and novel applications. One straightforward goal of single cell technologies is to create cell atlases based on single-cell transcriptomics. As an example, the first chick retinal atlas will be presented, revealing the diversity of neurons and glia in the retina and providing new insights to the extent that neuronal types are evolutionarily conserved between aves and mammals.
Ref. Yamagata M, Yan W, Sanes JR. (2021) A cell atlas of the chick retina based on single-cell transcriptomics. eLife. 10:e63907. | | 2022年6月30日 14:15～14:45 沖縄コンベンションセンター 会議場A1 第2会場
1S02a-02
Single-cell analysis of neural development in the visual system
*Karthik Shekhar(1)
1. University of California, Berkeley
Keyword: Visual system, single-cell transcriptmomics , neuronal types, machine learning
A central question in neurobiology is how the brain’s diverse neuronal types arise through a combination of genetically hardwired mechanisms ("nature") and experience ("nurture"). We are studying this question through the lens of single-cell transcriptomics, focusing on the visual system (retina and visual cortex). I will begin by describing our efforts to build and validate comprehensive taxonomies of neuronal types, and harmonize molecular definitions of neurons with morphology and physiology. Next, we will discuss ways to use these taxonomies as a foundation to understand how cell types are specified during early development, both in the retina and more recently, in the primary visual cortex. Inference of molecular trajectories of cell types will be discussed together with the role of vision-mediated activity. Our findings suggest that visual activity does not affect the diversification of retinal ganglion cells (RGCs), the output neurons of the retina, but does affect their molecular maturation. In the visual cortex, vision plays a profound but selective role in the specification of a subpopulation of glutamatergic cell types. Connecting genomic findings with in vivo experiments will be discussed. | | 2022年6月30日 14:45～15:15 沖縄コンベンションセンター 会議場A1 第2会場
1S02a-03
脊椎動物の網膜における種間に共通した遺伝子制御コードとその種間分岐
Conservation and divergence of cis-regulatory codes during vertebrate retinal evolution
*小川 洋平(1)、Yu Liu(1)、Joseph C. Corbo(1)
1. ワシントン大学医学部
*Yohei Ogawa(1), Yu Liu(1), Joseph C. Corbo(1)
1. Washington University School of Medicine, St. Louis, MO
Keyword: single-cell RNA-seq/ATAC-seq, retina, photoreceptor, transcriptional regulation
The fundamental architecture of the vertebrate retina, consisting of six major cell classes, has remained largely invariant over half a billion years of evolution. In contrast, individual vertebrate species have expanded or contracted cell type repertoires within each retinal cell class to adapt to specific light environments. Here, we performed comparative epigenomic analysis using single-cell RNA-seq and single-nucleus ATAC-seq in three diverse vertebrate species (zebrafish, chicken, and mouse) and evaluated the evolution of cell-type-specific transcriptional regulatory networks. We defined cis-regulatory codes of four major retinal cell classes (photoreceptors, bipolar cells, horizontal cells, and Müller glia) and all cell types within a single class (photoreceptors). Each retinal cell class showed remarkable evolutionary conservation of transcription factor binding site enrichment in the cis-regulatory regions, mirroring the architectural invariance of the vertebrate retina. In contrast, we found divergence of cis-regulatory codes within individual photoreceptor cell types, which correlated with patterns of transcription factor (TF) expression and the phenotypes of specific TF mutants. On top of a highly conserved retinal Bauplan, vertebrates have modified cis-regulatory codes to generate within-class cell type diversity that permitted the exploitation of divergent photic niches. | | 2022年6月30日 15:15～15:45 沖縄コンベンションセンター 会議場A1 第2会場
1S02a-04
Integrative Analysis of Single-cell Transcriptomics with Multiplexed RNA Imaging for Mapping Autism Pathophysiology
*Jinyue Liu(1)
1. Genome Institute of Singapore
Keyword: Single-cell transcriptomics, spatial transcriptomics, neurodevelopmental disorder
Autism spectrum disorder is a chronic psychiatric condition of developmental origins. Genetic influences and gene expression changes associated with autism have been widely documented. However, emergent cellular phenotypes – the link between genes and behavior – remain elusive. Here, by integrating single-cell transcriptomics (scRNAseq) and multiplexed RNA imaging (mFISH), we report altered cell type proportions and spatial re-positioning of cellular subtypes within cortical layers of organoids derived from autism subjects relative to controls. Using a next-generation histopathology platform that enables spatially-resolved RNA imaging at subcellular scale, we generated spatial gene expression maps for as many as 557 genes over 50 brain organoid tissue sections. These maps span more than 600,000 cells, segmented using enhanced deep-learning techniques to overcome dense packing. Our spatial omics data precisely recapitulated known gene expression patterns in brain organoid models of the developing human brain, such as NESTIN and CTIP2. These transcriptomic patterns are not only consistent with scRNAseq analysis, but also correspond to neuroanatomically distinct cell lineages known to populate the developing human brain. We also developed a scalable, broadly applicable spatial co-regulation based algorithm that unbiasedly delineated tissue domains within the brain organoid architecture. Through transcriptome-wide imputation of spatial gene expression patterns, we mapped patient-specific spatial distributions of refined cellular subtypes and signaling components related to diagnosis. Our integrative approach has revealed previously inaccessible cellular phenotypes in a psychiatric disease model, opening up new directions for characterizing autism pathophysiology in a model of human fetal brain, and for developing and validating therapeutic strategies. | |
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