A Spatiotemporal Organ-Wide Gene Expression and Cell Atlas of the Developing Human Heart

Abstract

Highlights d Profiled spatiotemporal gene expression patterns in human cardiogenesis d Mapped cell-type distribution and spatial organization in the human embryonic heart d Thoroughly analyzed roles of diverse cell types in cardiac development d A publicly available web resource of the human embryonic heart

Spatial mapping of cell types by integration of transcriptomics data

“…[19] Epicardial cells form a thin outer layer of the heart known as the epicardium, and this type is mainly assigned high proportion values in spots covering the edges of the heart. [20] Epicardium-derived cells arrange themselves adjacent to the epicardial cells on the inner side of the heart in a somewhat thicker layer than the epicardium, and they are also known to be present in the outflow tract during its formation, a pattern recapitulated by our results. [21] Finally we generated synthetic ST data from single cell data (Methods), providing us with a "ground truth" for the proportion values.…”

“…The complete single cell data set provided in the paper "A spatiotemporal organ-wide gene expression and cell atlas of the developing human heart", was used to estimate the type parameters hence resulting in a usage of 3717 cells distributed over 15 clusters. [20] Only the top 5000 highest expressed genes were used in the analysis. For the exact composition of the single cell data set, see Supplementary section 1.1.1.…”

Hybridization-based In Situ Sequencing (HybISS): spatial transcriptomic detection in human and mouse brain tissue

“…SBL ISS has been demonstrated to assign cell types in mouse hippocampus 21 and neural crest development 18 . ISS has also been applied and analyzed together with scRNA-seq data and data from untargeted transcriptome-wide Spatial Transcriptomics 31 to develop a spatiotemporal atlas of the developing human heart 32 . As demonstrated here on human tissue, the capacity is in place to start creating a comprehensive spatial reference map for the Human Cell Atlas 10 .…”

Discovery of molecular features underlying morphological landscape by integrating spatial transcriptomic data with deep features of tissue image

“…In particular, recent progress in spatial gene expression technologies which applies nextgeneration sequencing with spatial barcode, fluorescence in situ hybridization (FISH), or in situ sequencing (ISS) have innovated experimental approaches to decipher the spatial heterogeneity of biological process [2][3][4][5] . A spatial context at single-cell level resolution has allowed the analysis of the location of heterogeneous cells and their spatial interactions in tumor tissues as well as brain, the human heart, and inflammatory tissues 4,[6][7][8][9][10][11] .…”

“…Even though spatial gene expression analyses have been actively developed and applied to various tissues and diseases, analytic methods that integrate transcriptome and imaging data are lacking. In spite of the feasibility of analysis that combines gene expression, spatial interaction between different spots of spatial barcodes and image patterns, most methods have regarded gene expression from spots as independent samples and interpreted like singlecell RNA-sequencing (scRNA-seq) data 4,[6][7][8][9] . Especially, one of the advantages of spatial gene expression data is additional information of co-registered images which contains morphological as well as functional patterns.…”