Neighbor-specific gene expression revealed from physically interacting cells during mouse embryonic development

Author:

Kim Junil12ORCID,Rothová Michaela Mrugala3,Madan Esha4,Rhee Siyeon5,Weng Guangzheng1,Palma António M.4ORCID,Liao Linbu1ORCID,David Eyal6,Amit Ido6,Hajkarim Morteza Chalabi1,Vudatha Vignesh7ORCID,Gutiérrez-García Andrés4,Moreno Eduardo4,Winn Robert8,Trevino Jose7,Fisher Paul B.8910ORCID,Brickman Joshua M.3ORCID,Gogna Rajan8910,Won Kyoung Jae111

Affiliation:

1. Biotech Research and Innovation Centre, University of Copenhagen, Copenhagen N 2200, Denmark

2. School of Systems Biomedical Science, Soongsil University, Dongjak-Gu, Seoul 06978, Republic of Korea

3. Novo Nordisk Foundation Center for Stem Cell Medicine (reNEW), University of Copenhagen, Copenhagen 2200, Denmark

4. Champalimaud Centre for the Unknown, Lisbon 1400-038, Portugal

5. Department of Biology, Stanford University, Stanford, CA 94305

6. Department of Immunology, Weizmann Institute of Science, Rehovot 7610001, Israel

7. Department of Surgery, Virginia Commonwealth University, Richmond, VA 23298-0033

8. School of Medicine, Virginia Commonwealth University Massey Cancer Center, Virginia Commonwealth University, Richmond, VA 23298-0033

9. Department of Human and Molecular Genetics, School of Medicine, Virginia Commonwealth University, Richmond, VA 23298-0033

10. School of Medicine, VCU Institute of Molecular Medicine, Virginia Commonwealth University, Richmond, VA 23298-0033

11. Department of Computational Biomedicine, Cedars-Sinai Medical Center, Los Angeles, CA 90069

Abstract

Development of multicellular organisms is orchestrated by persistent cell–cell communication between neighboring partners. Direct interaction between different cell types can induce molecular signals that dictate lineage specification and cell fate decisions. Current single-cell RNA-seq technology cannot adequately analyze cell–cell contact-dependent gene expression, mainly due to the loss of spatial information. To overcome this obstacle and resolve cell–cell contact-specific gene expression during embryogenesis, we performed RNA sequencing of physically interacting cells (PIC-seq) and assessed them alongside similar single-cell transcriptomes derived from developing mouse embryos between embryonic day (E) 7.5 and E9.5. Analysis of the PIC-seq data identified gene expression signatures that were dependent on the presence of specific neighboring cell types. Our computational predictions, validated experimentally, demonstrated that neural progenitor (NP) cells upregulate Lhx5 and Nkx2-1 genes, when exclusively interacting with definitive endoderm (DE) cells. Moreover, there was a reciprocal impact on the transcriptome of DE cells, as they tend to upregulate Rax and Gsc when in contact with NP cells. Using individual cell transcriptome data, we formulated a means of computationally predicting the impact of one cell type on the transcriptome of its neighboring cell types. We have further developed a distinctive spatial-t-distributed stochastic neighboring embedding to display the pseudospatial distribution of cells in a 2-dimensional space. In summary, we describe an innovative approach to study contact-specific gene regulation during embryogenesis.

Funder

Novo Nordisk Fonden

Lundbeckfonden

National Research Foundation of Korea

"la Caixa" Foundation

Fundação para a Ciência e a Tecnologia Grant

HHS | NIH | National Cancer Institute

Publisher

Proceedings of the National Academy of Sciences

Subject

Multidisciplinary

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