PUBLICATION
Gene expression cartography
- Authors
- Nitzan, M., Karaiskos, N., Friedman, N., Rajewsky, N.
- ID
- ZDB-PUB-191122-5
- Date
- 2019
- Source
- Nature 576(7785): 132-137 (Journal)
- Registered Authors
- Keywords
- none
- MeSH Terms
-
- Animals
- Drosophila melanogaster
- Gene Expression*
- Gene Expression Profiling
- Gene Expression Regulation, Developmental
- Sequence Analysis, RNA
- Single-Cell Analysis
- Software
- PubMed
- 31748748 Full text @ Nature
Citation
Nitzan, M., Karaiskos, N., Friedman, N., Rajewsky, N. (2019) Gene expression cartography. Nature. 576(7785):132-137.
Abstract
Multiplexed RNA sequencing in individual cells is transforming basic and clinical life sciences1-4. Often, however, tissues must first be dissociated, and crucial information about spatial relationships and communication between cells is thus lost. Existing approaches to reconstruct tissues assign spatial positions to each cell, independently of other cells, by using spatial patterns of expression of marker genes5,6-which often do not exist. Here we reconstruct spatial positions with little or no prior knowledge, by searching for spatial arrangements of sequenced cells in which nearby cells have transcriptional profiles that are often (but not always) more similar than cells that are farther apart. We formulate this task as a generalized optimal-transport problem for probabilistic embedding and derive an efficient iterative algorithm to solve it. We reconstruct the spatial expression of genes in mammalian liver and intestinal epithelium, fly and zebrafish embryos, sections from the mammalian cerebellum and whole kidney, and use the reconstructed tissues to identify genes that are spatially informative. Thus, we identify an organization principle for the spatial expression of genes in animal tissues, which can be exploited to infer meaningful probabilities of spatial position for individual cells. Our framework ('novoSpaRc') can incorporate prior spatial information and is compatible with any single-cell technology. Additional principles that underlie the cartography of gene expression can be tested using our approach.
Genes / Markers
Expression
Phenotype
Mutations / Transgenics
Human Disease / Model
Sequence Targeting Reagents
Fish
Orthology
Engineered Foreign Genes
Mapping