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Gene Expression Atlas of a Developing Tissue by Single Cell Expression Correlation Analysis

Overview
Journal Nat Methods
Date 2019 Aug 1
PMID 31363221
Citations 34
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Abstract

The Drosophila wing disc has been a fundamental model system for the discovery of key signaling pathways and for our understanding of developmental processes. However, a complete map of gene expression in this tissue is lacking. To obtain a gene expression atlas in the wing disc, we employed single cell RNA sequencing (scRNA-seq) and developed a method for analyzing scRNA-seq data based on gene expression correlations rather than cell mapping. This enables us to compute expression maps for all detected genes in the wing disc and to discover 824 genes with spatially restricted expression patterns. This approach identifies clusters of genes with similar expression patterns and functional relevance. As proof of concept, we characterize the previously unstudied gene CG5151 and show that it regulates Wnt signaling. Our method will enable the leveraging of scRNA-seq data for generating expression atlases of undifferentiated tissues during development.

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References
1.
Calleja M, Moreno E, Pelaz S, Morata G . Visualization of gene expression in living adult Drosophila. Science. 1996; 274(5285):252-5. DOI: 10.1126/science.274.5285.252. View

2.
Bellen H, Kooyer S, DEvelyn D, PEARLMAN J . The Drosophila couch potato protein is expressed in nuclei of peripheral neuronal precursors and shows homology to RNA-binding proteins. Genes Dev. 1992; 6(11):2125-36. DOI: 10.1101/gad.6.11.2125. View

3.
Karaiskos N, Wahle P, Alles J, Boltengagen A, Ayoub S, Kipar C . The embryo at single-cell transcriptome resolution. Science. 2017; 358(6360):194-199. DOI: 10.1126/science.aan3235. View

4.
Andrews T, Hemberg M . M3Drop: dropout-based feature selection for scRNASeq. Bioinformatics. 2018; 35(16):2865-2867. PMC: 6691329. DOI: 10.1093/bioinformatics/bty1044. View

5.
Zhu Q, Shah S, Dries R, Cai L, Yuan G . Identification of spatially associated subpopulations by combining scRNAseq and sequential fluorescence in situ hybridization data. Nat Biotechnol. 2018; . PMC: 6488461. DOI: 10.1038/nbt.4260. View