title: Spatial transcriptomic analysis of cryosectioned tissue samples with Geo-seq.
abstract: Conventional gene expression studies analyze multiple cells simultaneously or single cells, for which the exact in vivo or in situ position is unknown. Although cellular heterogeneity can be discerned when analyzing single cells, any spatially defined attributes that underpin the heterogeneous nature of the cells cannot be identified. Here, we describe how to use Geo-seq, a method that combines laser capture microdissection (LCM) and single-cell RNA-seq technology. The combination of these two methods enables the elucidation of cellular heterogeneity and spatial variance simultaneously. The Geo-seq protocol allows the profiling of transcriptome information from only a small number cells and retains their native spatial information. This protocol has wide potential applications to address biological and pathological questions of cellular properties such as prospective cell fates, biological function and the gene regulatory network. Geo-seq has been applied to investigate the spatial transcriptome of mouse early embryo, mouse brain, and pathological liver and sperm tissues. The entire protocol from tissue collection and microdissection to sequencing requires ∼5 d, Data analysis takes another 1 or 2 weeks, depending on the amount of data and the speed of the processor.
authors.affiliation: State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, Shanghai, China.|Department of Genetics and Cell Biology, College of Life Sciences, Nankai University, Tianjin, China.
authors.forename: Jun
authors.initials: J
authors.lastname: Chen
authors.affiliation: Key Laboratory of Computational Biology, CAS Center for Excellence in Molecular Cell Science, Collaborative Innovation Center for Genetics and Developmental Biology, Chinese Academy of Sciences-Max Planck Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China.|University of Chinese Academy of Sciences, Beijing, China.
authors.forename: Shengbao
authors.initials: S
authors.lastname: Suo
authors.affiliation: Embryology Unit, Children's Medical Research Institute and School of MedicalSciences, Sydney Medical School, University of Sydney, Sydney, Australia.
authors.forename: Patrick Pl
authors.initials: PP
authors.lastname: Tam
authors.affiliation: Key Laboratory of Computational Biology, CAS Center for Excellence in Molecular Cell Science, Collaborative Innovation Center for Genetics and Developmental Biology, Chinese Academy of Sciences-Max Planck Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China.
authors.forename: Jing-Dong J
authors.initials: JJ
authors.lastname: Han
authors.affiliation: State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, Shanghai, China.
authors.forename: Guangdun
authors.identifier: 0000-0002-8586-0637
authors.initials: G
authors.lastname: Peng
authors.affiliation: State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, Shanghai, China.
authors.forename: Naihe
authors.initials: N
authors.lastname: Jing
mesh_terms: D000818:Animals; D016616:Cryoultramicrotomy / Q000379:methods*; D005260:Female; D020869:Gene Expression Profiling / Q000379:methods*; D061346:Laser Capture Microdissection; D051379:Mice; D008810:Mice, Inbred C57BL; D016133:Polymerase Chain Reaction; D011247:Pregnancy; D017423:Sequence Analysis, RNA / Q000379:methods*; D059010:Single-Cell Analysis