Cellular-Resolution Gene Expression Profiling in the Neonatal Marmoset Brain Reveals Dynamic Species- and Region-Specific Differences

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Cellular-Resolution Gene Expression Profiling in the Neonatal Marmoset Brain Reveals Dynamic Species- and Region-Specific Differences Cellular-resolution gene expression profiling in the neonatal marmoset brain reveals dynamic species- and region-specific differences Yoshiaki Kitaa, Hirozumi Nishibea, Yan Wanga, Tsutomu Hashikawaa, Satomi S. Kikuchia, Mami Ua, Aya C. Yoshidaa, Chihiro Yoshidaa, Takashi Kawaseb, Shin Ishiib, Henrik Skibbec, and Tomomi Shimogoria,1 aLaboratory for Molecular Mechanisms of Brain Development, Center for Brain Science, RIKEN, Saitama 351-0198, Japan; bIntegrated Systems Biology Laboratory, Department of Systems Science, Graduate School of Informatics, Kyoto University, Kyoto 606-8501, Japan; and cBrain Image Analysis Unit, Center for Brain Science, RIKEN, Saitama 351-0198, Japan Edited by Edward M. Callaway, Salk Institute for Biological Studies, La Jolla, CA, and approved March 12, 2021 (received for review September 25, 2020) Precise spatiotemporal control of gene expression in the develop- (12). However, these studies are highly resource intensive, re- ing brain is critical for neural circuit formation, and comprehensive quiring substantial time and cost. Consequently, such efforts expression mapping in the developing primate brain is crucial to have been limited, focusing on a few brain regions in limited species understand brain function in health and disease. Here, we devel- (13). Thus, interspecific comparison of brain-cell heterogeneity has oped an unbiased, automated, large-scale, cellular-resolution in situ not been possible. hybridization (ISH)–based gene expression profiling system (GePS) Here, we describe the development and implementation of an and companion analysis to reveal gene expression patterns in the unbiased gene expression profiling system (GePS) for use with neonatal New World marmoset cortex, thalamus, and striatum the Marmoset Gene Atlas (MGA) (https://gene-atlas.brainminds. that are distinct from those in mice. Gene-ontology analysis of riken.jp/) (14), which is adaptable for use with other atlases. The marmoset-specific genes revealed associations with catalytic activ- system, developed as a part of “Brain Mapping by Integrated ity in the visual cortex and neuropsychiatric disorders in the thal- Neurotechnologies for Disease Studies (Brain/MINDS),” a brain amus. Cortically expressed genes with clear area boundaries were mapping program in Japan (15, 16), enables systematic and au- used in a three-dimensional cortical surface mapping algorithm to de- tomatic analysis of gene expression across brain regions. Brain/ NEUROSCIENCE lineate higher-order cortical areas not evident in two-dimensional ISH MINDS aims to develop knowledge-based tools to explore primate- data. GePS provides a powerful platform to elucidate the molecular specific brain structure, function, and connectivity in health and mechanisms underlying primate neurobiology and developmental disease. Specifically, we analyzed the expression patterns of identi- psychiatric and neurological disorders. fied risk genes for psychiatric disorders in the neonatal marmoset brain. There are >2,000 gene expression profiles for the neonatal gene expression | database | nonhuman primate | evolution | common-marmoset brain in the MGA. Although each ISH section developmental disorder is complemented by an adjacent neuroanatomically stained section (visualizing the Nissl substance), enabling users to compare gene he mammalian brain contains many functionally distinct re- expression against a brain atlas, mapping gene expression patterns Tgions that are extensively interconnected, enabling rapid and accurate information processing. Each region contains diverse Significance cell types that differ in their molecular, morphological, electrophys- iological, and functional characteristics (1, 2). Advanced neurosci- The MGA contains a large gene expression dataset from the ence technologies, which are generally optimized and extensively developing brain of the common marmoset. However, the data applied in mice, provide complicated approaches to analyze represent the gene expression patterns across the entire brain, these characteristics and model the genetic basis of this regional- and methods to isolate region-specific gene expression pat- and cell-type diversity. However, clear cognitive differences arise terns will provide important information regarding primate from interspecies differences in these key characteristics, and most brain structure, function, and cellular and molecular organiza- contemporary technologies are difficult to apply in species whose tion. We have developed a system, GePS, that systematically study involves extensive ethical, practical, and experimental im- identifies genes expressed in selected regions of the common pediments. The ability to compare gene expression patterns be- marmoset brain. Comprehensive, comparative gene expression tween primates and model species such as mice is crucial for analysis with mice revealed many genes with species- and understanding the human brain (3, 4). region-specific expression. Moreover, by combining GePS with Recent developments in technologies, such as microarray, single- the gene expression comparison and cortical area projection cell RNA-sequencing (RNA-seq), and Drop-seq, have allowed for mapping systems, we were able to provide further insight into high-resolution genome-wide expression analysis in specific regions the molecular organization of these species- and region- of the brain or in thousands of individual cells simultaneously specific gene expression patterns. (5–10). However, these methods provide limited anatomical in- formation and no morphological observations. Slide-seq solves Author contributions: S.I., H.S., and T.S. designed research; Y.K., H.N., Y.W., T.H., S.S.K., these problems by transferring RNA from tissue sections onto a M.U., A.C.Y., C.Y., T.K., and H.S. performed research; T.S. analyzed data; and T.S. wrote surface covered in DNA-barcoded beads, allowing the preserva- the paper. tion of positional information (11). However, the unbiased nature The authors declare no competing interest. of next-generation sequencing technologies may hinder the mo- This article is a PNAS Direct Submission. lecular identification of specific cell types or their direct analysis. This open access article is distributed under Creative Commons Attribution-NonCommercial- In situ hybridization (ISH) databases of humans and nonhuman NoDerivatives License 4.0 (CC BY-NC-ND). primates (NHPs) have revealed brain gene expression profiles at 1To whom correspondence may be addressed. Email: [email protected]. cellular resolution, while preserving key morphological and ana- This article contains supporting information online at https://www.pnas.org/lookup/suppl/ tomical characteristics, ultimately providing important informa- doi:10.1073/pnas.2020125118/-/DCSupplemental. tion about the genetic conservation of analogous brain regions Published April 26, 2021. PNAS 2021 Vol. 118 No. 18 e2020125118 https://doi.org/10.1073/pnas.2020125118 | 1of11 Downloaded by guest on September 23, 2021 over the entire brain is both time and labor intensive. A large mouse comparisons of signal-to-noise ratios in a given grid area were ISH database, the Allen Brain Atlas (ABA; http://developingmouse. performed to determine whether the nitro blue tetrazolium/ brain-map.org/), demonstrated that an anatomic gene expression 5-bromo-4-chloro-3-indolyl-phosphate reaction provided a posi- atlas (AGEA) can characterize local gene expression in the tive signal. Fig. 1A shows a Nissl substance-stained section from mouse brain without prior knowledge of classical anatomy (17). the reference atlas, with a position indicator to search for genes To enhance the MGA in this manner, we developed GePS to expressed within the selected area. All ISH sections were over- systematically and automatically identify gene expression pat- laid with a grid (Fig. 1 A and B), and the gene expression de- terns in specific regions of the neonatal marmoset brain. tection software was used to sum the number and intensities of GePS, including the gene expression comparison system and expressing pixels (Fig. 1C). Different grids were tested (from cortical surface projection mapping function, is publicly available 20 × 20 pixel grids to 200 × 200 pixel grids), and we concluded as an open resource on our website (https://gene-atlas.brainminds. that 200 × 200 pixel grids provide the most accurate result. When riken.jp/). It provides primate-specific whole brain–gene expres- grid size becomes smaller, a chance to pick dust, scratch, and sion patterns and will be a valuable platform in the field of primate background becomes higher and provides false-positive results neuroscience, helping reveal primate-specific brain functions and more often. Therefore, we decided to use 200 × 200 pixel grids connections and providing insights into brain evolution and for the automated signal identification system. Fig. 1C depicts the pathology. grid system for detecting the positivesignalineachgrid(redsquares indicate 200 × 200 pixel grids). The anatomical location of the Results position indicator on the reference atlas was then transferred to a The MGA contains coronally sectioned ISH data from marmoset grid position on a selected plane of ISH data. When the sections brains at different ages, including 2,000 gene expression profiles had rostral–caudal misalignment, the software also searched for from neonatal common-marmoset brains. To enable automatic, gene expression in one rostral section and one caudal section ∼200 systematic, and unbiased comparisons of gene
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