FunRes: resolving tissue-specific functional cell states based on a cell–cell communication network model
Open accessAbstract
The functional specialization of cell types arises during development and is shaped by cell–cell communication networks determining a distribution of functional cell states that are collectively important for tissue functioning. However, the identification of these tissue-specific functional cell states remains challenging. Although a plethora of computational approaches have been successful in detecting cell types and subtypes, they fail in resolving tissue-specific functional cell states. To address this issue, we present FunRes, a computational method designed for the identification of functional cell states. FunRes relies on scRNA-seq data of a tissue to initially reconstruct the functional cell–cell communication network, which is leveraged for partitioning each cell type into functional cell states. We applied FunRes to 177 cell types in 10 different tissues and demonstrated that the detected states correspond to known functional cell states of various cell types, which cannot be recapitulated by existing computational tools. Finally, we characterize emerging and vanishing functional cell states in aging and disease, and demonstrate their involvement in key tissue functions. Thus, we believe that FunRes will be of great utility in the characterization of the functional landscape of cell types and the identification of dysfunctional cell states in aging and disease.
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Ligand-receptor interactions between Sen cells and NSen SCs are predominantly inflammatory.
“we reconstructed ligand–receptor interactions between Sen cells (producing SASP ligands) and NSen SCs (with cognate receptors) using a modified FunRes algorithm39; this revealed predominantly inflammatory interactions (Extended Data Fig. 11e).”
From Senescence atlas reveals an aged-like inflamed niche that blunts muscle regeneration (2023) · cites this paper as [39]
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- Authors
- Jung, S., Singh, K., & del Sol, A.
- Affiliations
- CIC bioGUNE (ES)
- Luxembourg Centre for Systems Biomedicine (LU)
- Computational Biology Group, Luxembourg Centre for Systems Biomedicine (LCSB), Esch-sur-Alzette, L-4362, Luxembourg
- Venue
- Briefings in Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2020-11-12
- Volume
- 22
- Issue
- 4
- ISSN
- 1467-5463 (ISSN-L)
- 1477-4054
- PMC
- PMC8293827
- OpenAlex
- W3100436234
- Cited by
- 9
- References
- 69
- Citations by year
- 2024: 2 · 2023: 3 · 2022: 3 · 2021: 1
- FWCI
- 0.57
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Briefings in Bioinformatics (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Open Repository and Bibliography (University of Luxembourg) (submittedVersion, cc-by-nc-sa)
- Funders
- Luxembourg National Research Fund (11012546)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Keywords
- cell-cell communication networks, single-cell RNA sequencing, network partitioning, aging, disease, tissue function
- MeSH terms
- RNA-Seq, Animals, Cell Communication, Humans, Models, Biological, Organ Specificity, Mice, Single-Cell Analysis
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