ABSTRACT
Spatial transcriptomic and proteomic technologies have provided new opportunities to investigate cells in their native microenvironment. Here we present Giotto, a comprehensive and open-source toolbox for spatial data analysis and visualization. The analysis module provides end-to-end analysis by implementing a wide range of algorithms for characterizing tissue composition, spatial expression patterns, and cellular interactions. Furthermore, single-cell RNAseq data can be integrated for spatial cell-type enrichment analysis. The visualization module allows users to interactively visualize analysis outputs and imaging features. To demonstrate its general applicability, we apply Giotto to a wide range of datasets encompassing diverse technologies and platforms.
Subject(s)
Computational Biology/methods , Gene Expression Profiling/methods , In Situ Hybridization , Software , Data Analysis , Image Processing, Computer-Assisted , Immunohistochemistry/methods , In Situ Hybridization/methods , Organ Specificity/genetics , Spatial Analysis , TranscriptomeABSTRACT
Identifying the relationships between chromosome structures, nuclear bodies, chromatin states and gene expression is an overarching goal of nuclear-organization studies1-4. Because individual cells appear to be highly variable at all these levels5, it is essential to map different modalities in the same cells. Here we report the imaging of 3,660 chromosomal loci in single mouse embryonic stem (ES) cells using DNA seqFISH+, along with 17 chromatin marks and subnuclear structures by sequential immunofluorescence and the expression profile of 70 RNAs. Many loci were invariably associated with immunofluorescence marks in single mouse ES cells. These loci form 'fixed points' in the nuclear organizations of single cells and often appear on the surfaces of nuclear bodies and zones defined by combinatorial chromatin marks. Furthermore, highly expressed genes appear to be pre-positioned to active nuclear zones, independent of bursting dynamics in single cells. Our analysis also uncovered several distinct mouse ES cell subpopulations with characteristic combinatorial chromatin states. Using clonal analysis, we show that the global levels of some chromatin marks, such as H3 trimethylation at lysine 27 (H3K27me3) and macroH2A1 (mH2A1), are heritable over at least 3-4 generations, whereas other marks fluctuate on a faster time scale. This seqFISH+-based spatial multimodal approach can be used to explore nuclear organization and cell states in diverse biological systems.
Subject(s)
Cell Compartmentation/genetics , Cell Nucleus/genetics , Genomics/methods , Mouse Embryonic Stem Cells/cytology , Single-Cell Analysis/methods , Transcriptome/genetics , Animals , Cell Line , Chromatin/genetics , Chromatin/metabolism , Chromosomes, Mammalian/genetics , Clone Cells/cytology , Fluorescent Antibody Technique , Genetic Markers , Histones/metabolism , Lysine/metabolism , Male , Mice , Time FactorsABSTRACT
Imaging the transcriptome in situ with high accuracy has been a major challenge in single-cell biology, which is particularly hindered by the limits of optical resolution and the density of transcripts in single cells1-5. Here we demonstrate an evolution of sequential fluorescence in situ hybridization (seqFISH+). We show that seqFISH+ can image mRNAs for 10,000 genes in single cells-with high accuracy and sub-diffraction-limit resolution-in the cortex, subventricular zone and olfactory bulb of mouse brain, using a standard confocal microscope. The transcriptome-level profiling of seqFISH+ allows unbiased identification of cell classes and their spatial organization in tissues. In addition, seqFISH+ reveals subcellular mRNA localization patterns in cells and ligand-receptor pairs across neighbouring cells. This technology demonstrates the ability to generate spatial cell atlases and to perform discovery-driven studies of biological processes in situ.
Subject(s)
Brain/anatomy & histology , Brain/metabolism , In Situ Hybridization, Fluorescence/methods , RNA, Messenger/analysis , RNA, Messenger/genetics , Single-Cell Analysis/methods , Transcriptome/genetics , 3T3 Cells , Animals , Brain/cytology , Dopaminergic Neurons/metabolism , Endothelial Cells/metabolism , Female , Gene Expression Profiling , Ligands , Male , Mice , Microglia/metabolism , Organ SpecificityABSTRACT
Visualization of the transcriptome and the nuclear organization in situ has been challenging for single-cell analysis. Here, we demonstrate a multiplexed single-molecule in situ method, intron seqFISH, that allows imaging of 10,421 genes at their nascent transcription active sites in single cells, followed by mRNA and lncRNA seqFISH and immunofluorescence. This nascent transcriptome-profiling method can identify different cell types and states with mouse embryonic stem cells and fibroblasts. The nascent sites of RNA synthesis tend to be localized on the surfaces of chromosome territories, and their organization in individual cells is highly variable. Surprisingly, the global nascent transcription oscillated asynchronously in individual cells with a period of 2 hr in mouse embryonic stem cells, as well as in fibroblasts. Together, spatial genomics of the nascent transcriptome by intron seqFISH reveals nuclear organizational principles and fast dynamics in single cells that are otherwise obscured.
Subject(s)
In Situ Hybridization, Fluorescence/methods , Transcriptome , Animals , Catalytic Domain , Cell Line , Chromosomes/metabolism , Fibroblasts/cytology , Fibroblasts/metabolism , Introns , Mice , Microscopy, Fluorescence , Microscopy, Video , Mouse Embryonic Stem Cells/cytology , Mouse Embryonic Stem Cells/metabolism , RNA Polymerase II/genetics , RNA Polymerase II/metabolism , RNA, Long Noncoding/genetics , RNA, Messenger/genetics , Single-Cell AnalysisABSTRACT
Single-molecule FISH (smFISH) has been the gold standard for quantifying individual transcript abundances. Here, we scale up multiplexed smFISH to the transcriptome level and profile 10,212 different mRNAs from mouse fibroblast and embryonic stem cells. This method, called RNA sequential probing of targets (SPOTs), provides an accurate, flexible, and low-cost alternative to sequencing for profiling transcriptomes.
