The Human Cell Atlas

The recent advent of methods for high-throughput single-cell molecular profiling has catalyzed a growing sense in the scientific community that the time is ripe to complete the 150-year-old effort to identify all cell types in the human body. The Human Cell Atlas Project is an international collaborative effort that aims to define all human cell types in terms of distinctive molecular profiles (such as gene expression profiles) and to connect this information with classical cellular descriptions (such as location and morphology). An open comprehensive reference map of the molecular state of cells in healthy human tissues would propel the systematic study of physiological states, developmental trajectories, regulatory circuitry and interactions of cells, and also provide a framework for understanding cellular dysregulation in human disease. Here we describe the idea, its potential utility, early proofs-of-concept, and some design considerations for the Human Cell Atlas, including a commitment to open data, code, and community.

Citing Articles

Human BioMolecular Atlas Program (HuBMAP): 3D Human Reference Atlas construction and usage.

Borner K, Blood P, Silverstein J, Ruffalo M, Satija R, Teichmann S Nat Methods. 2025; .

PMID: 40082611 DOI: 10.1038/s41592-024-02563-5.

Foundation models in bioinformatics.

Guo F, Guan R, Li Y, Liu Q, Wang X, Yang C Natl Sci Rev. 2025; 12(4):nwaf028.

PMID: 40078374 PMC: 11900445. DOI: 10.1093/nsr/nwaf028.

Quantifying and interpreting biologically meaningful spatial signatures within tumor microenvironments.

Jing S, Wang H, Lin P, Yuan J, Tang Z, Li H NPJ Precis Oncol. 2025; 9(1):68.

PMID: 40069556 PMC: 11897387. DOI: 10.1038/s41698-025-00857-1.

Augmenting the human interactome for disease prediction through gene networks inferred from human cell atlas.

Sung E, Cha J, Baek S, Lee I Anim Cells Syst (Seoul). 2025; 29(1):11-20.

PMID: 40066175 PMC: 11892045. DOI: 10.1080/19768354.2025.2472002.

Adapting systems biology to address the complexity of human disease in the single-cell era.

Fischer D, Villanueva M, Winter P, Shalek A Nat Rev Genet. 2025; .

PMID: 40065155 DOI: 10.1038/s41576-025-00821-6.

References

Moffitt J, Hao J, Wang G, Chen K, Babcock H, Zhuang X . High-throughput single-cell gene-expression profiling with multiplexed error-robust fluorescence in situ hybridization. Proc Natl Acad Sci U S A. 2016; 113(39):11046-51. PMC: 5047202. DOI: 10.1073/pnas.1612826113. View

Adamson B, Norman T, Jost M, Cho M, Nunez J, Chen Y . A Multiplexed Single-Cell CRISPR Screening Platform Enables Systematic Dissection of the Unfolded Protein Response. Cell. 2016; 167(7):1867-1882.e21. PMC: 5315571. DOI: 10.1016/j.cell.2016.11.048. View

May R . Simple mathematical models with very complicated dynamics. Nature. 1976; 261(5560):459-67. DOI: 10.1038/261459a0. View

Martincorena I, Roshan A, Gerstung M, Ellis P, Van Loo P, McLaren S . Tumor evolution. High burden and pervasive positive selection of somatic mutations in normal human skin. Science. 2015; 348(6237):880-6. PMC: 4471149. DOI: 10.1126/science.aaa6806. View

Angelo M, Bendall S, Finck R, Hale M, Hitzman C, Borowsky A . Multiplexed ion beam imaging of human breast tumors. Nat Med. 2014; 20(4):436-42. PMC: 4110905. DOI: 10.1038/nm.3488. View

Rosvall M, Bergstrom C . Maps of random walks on complex networks reveal community structure. Proc Natl Acad Sci U S A. 2008; 105(4):1118-23. PMC: 2234100. DOI: 10.1073/pnas.0706851105. View

Grun D, van Oudenaarden A . Design and Analysis of Single-Cell Sequencing Experiments. Cell. 2015; 163(4):799-810. DOI: 10.1016/j.cell.2015.10.039. View

Zhou J, Aliyu M, Aurell E, Huang S . Quasi-potential landscape in complex multi-stable systems. J R Soc Interface. 2012; 9(77):3539-53. PMC: 3481575. DOI: 10.1098/rsif.2012.0434. View

Stegle O, Teichmann S, Marioni J . Computational and analytical challenges in single-cell transcriptomics. Nat Rev Genet. 2015; 16(3):133-45. DOI: 10.1038/nrg3833. View

10.

Ramilowski J, Goldberg T, Harshbarger J, Kloppmann E, Kloppman E, Lizio M . A draft network of ligand-receptor-mediated multicellular signalling in human. Nat Commun. 2015; 6:7866. PMC: 4525178. DOI: 10.1038/ncomms8866. View

11.

Yosef N, Regev A . Impulse control: temporal dynamics in gene transcription. Cell. 2011; 144(6):886-96. PMC: 3148525. DOI: 10.1016/j.cell.2011.02.015. View

12.

Heimberg G, Bhatnagar R, El-Samad H, Thomson M . Low Dimensionality in Gene Expression Data Enables the Accurate Extraction of Transcriptional Programs from Shallow Sequencing. Cell Syst. 2016; 2(4):239-250. PMC: 4856162. DOI: 10.1016/j.cels.2016.04.001. View

13.

Crino P, Trojanowski J, Dichter M, Eberwine J . Embryonic neuronal markers in tuberous sclerosis: single-cell molecular pathology. Proc Natl Acad Sci U S A. 1996; 93(24):14152-7. PMC: 19509. DOI: 10.1073/pnas.93.24.14152. View

14.

Brenner S . Sequences and consequences. Philos Trans R Soc Lond B Biol Sci. 2009; 365(1537):207-12. PMC: 2842711. DOI: 10.1098/rstb.2009.0221. View

15.

Kim J, Eberwine J . RNA: state memory and mediator of cellular phenotype. Trends Cell Biol. 2010; 20(6):311-8. PMC: 2892202. DOI: 10.1016/j.tcb.2010.03.003. View

16.

Stewart-Ornstein J, Weissman J, El-Samad H . Cellular noise regulons underlie fluctuations in Saccharomyces cerevisiae. Mol Cell. 2012; 45(4):483-93. PMC: 3327736. DOI: 10.1016/j.molcel.2011.11.035. View

17.

Bendall S, Davis K, Amir E, Tadmor M, Simonds E, Chen T . Single-cell trajectory detection uncovers progression and regulatory coordination in human B cell development. Cell. 2014; 157(3):714-25. PMC: 4045247. DOI: 10.1016/j.cell.2014.04.005. View

18.

Angerer P, Haghverdi L, Buttner M, Theis F, Marr C, Buettner F . destiny: diffusion maps for large-scale single-cell data in R. Bioinformatics. 2015; 32(8):1241-3. DOI: 10.1093/bioinformatics/btv715. View

19.

Thul P, Akesson L, Wiking M, Mahdessian D, Geladaki A, Blal H . A subcellular map of the human proteome. Science. 2017; 356(6340). DOI: 10.1126/science.aal3321. View

20.

Habib N, Li Y, Heidenreich M, Swiech L, Avraham-Davidi I, Trombetta J . Div-Seq: Single-nucleus RNA-Seq reveals dynamics of rare adult newborn neurons. Science. 2016; 353(6302):925-8. PMC: 5480621. DOI: 10.1126/science.aad7038. View