Gene expression atlas of a developing tissue by single cell expression correlation analysis.
Josephine BageritzPhilipp WillnowErica ValentiniSvenja LeibleMichael BoutrosAurelio A TelemanPublished in: Nature methods (2019)
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.
Keyphrases
- machine learning
- single cell
- gene expression
- genome wide
- rna seq
- poor prognosis
- dna methylation
- high throughput
- deep learning
- binding protein
- oxidative stress
- copy number
- electronic health record
- long non coding rna
- bone marrow
- cell proliferation
- genome wide identification
- high resolution
- epithelial mesenchymal transition
- mesenchymal stem cells
- transcription factor
- data analysis
- endoplasmic reticulum stress
- high density