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. 2017 Dec 5:6:e27041.
doi: 10.7554/eLife.27041.

The Human Cell Atlas (V体育官网入口)

Aviv Regev  1   2   3 , Sarah A Teichmann  4   5   6 , Eric S Lander  1   2   7 , Ido Amit  8 , Christophe Benoist  9 , Ewan Birney  5 , Bernd Bodenmiller  5   10 , Peter Campbell  4   11 , Piero Carninci  6   12 , Menna Clatworthy  13 , Hans Clevers  14 , Bart Deplancke  15 , Ian Dunham  5 , James Eberwine  16 , Roland Eils  17   18 , Wolfgang Enard  19 , Andrew Farmer  20 , Lars Fugger  21 , Berthold Göttgens  11   22 , Nir Hacohen  1   23 , Muzlifah Haniffa  24 , Martin Hemberg  4 , Seung Kim  25 , Paul Klenerman  26   27 , Arnold Kriegstein  28 , Ed Lein  29 , Sten Linnarsson  30 , Emma Lundberg  31   32 , Joakim Lundeberg  33 , Partha Majumder  34 , John C Marioni  4   5   35 , Miriam Merad  36 , Musa Mhlanga  37 , Martijn Nawijn  38 , Mihai Netea  39 , Garry Nolan  40 , Dana Pe'er  41 , Anthony Phillipakis  1 , Chris P Ponting  42 , Stephen Quake  43   44 , Wolf Reik  4   45   46 , Orit Rozenblatt-Rosen  1 , Joshua Sanes  47 , Rahul Satija  48   49 , Ton N Schumacher  50 , Alex Shalek  1   51   52 , Ehud Shapiro  53 , Padmanee Sharma  54 , Jay W Shin  12 , Oliver Stegle  5 , Michael Stratton  4 , Michael J T Stubbington  4 , Fabian J Theis  55   56 , Matthias Uhlen  57   58 , Alexander van Oudenaarden  59 , Allon Wagner  60 , Fiona Watt  61 , Jonathan Weissman  3   62   63   64 , Barbara Wold  65 , Ramnik Xavier  1   66   67   68 , Nir Yosef  52   60 ; Human Cell Atlas Meeting Participants
Affiliations

The Human Cell Atlas

Aviv Regev (VSports注册入口) et al. Elife. .

Abstract

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) VSports手机版. 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. .

Keywords: cell atlas; cell biology; computational biology; human; lineage; mouse; science forum; single-cell genomics; systems biology V体育安卓版. .

PubMed Disclaimer

Conflict of interest statement

Reviewing Editor, eLife.

Senior Editor, eLife.

Deputy Editor, eLife.

No competing interests declared.

VSports在线直播 - Figures

Figure 1.
Figure 1.. A hierarchical view of human anatomy.
A graphical depiction of the anatomical hierarchy from organs (such as the gut), to tissues (such as the epithelium in the crypt in the small intestine), to their constituent cells (such as epithelial, immune, stromal and neural cells).
Figure 2.
Figure 2.. Anatomy: cell types and tissue structure.
The first three plots show single cells (dots) embedded in low-dimensional space based on similarities between their RNA-expression profiles (A, C) or protein-expression profiles (B), using either t-stochastic neighborhood embedding (A,B) or circular projection (C) for dimensionality reduction and embedding. (A) Bi-polar neurons from the mouse retina. (B) Human bone marrow immune cells. (C) Immune cells from the mouse spleen. (D) Histology. Projection of single-cell data onto tissue structures: image shows the mapping of individual cells onto locations in the marine annelid brain, based on the correspondence (color bar) between their single-cell expression profiles and independent FISH assays for a set of landmark transcripts.
Figure 3.
Figure 3.. Developmental trajectories.
Each plot shows single cells (dots; colored by trajectory assignment, sampled time point, or developmental stage) embedded in low-dimensional space based on their RNA (A-C) or protein (D) profiles, using different methods for dimensionality reduction and embedding: Gaussian process patent variable model (A); t-stochastic neighborhood embedding (B, D); diffusion maps (C). Computational methods then identify trajectories of pseudo-temporal progression in each case. (A) Myoblast differentiation in vitro. (B) Neurogenesis in the mouse brain dentate gyrus. (C) Embryonic stem cell differentiation in vitro. (D) Early hematopoiesis.
Figure 4.
Figure 4.. Physiology.
Each plot shows single cells (dots) embedded in low-dimensional space on the basis of their RNA profile, based on predefined gene signatures (A) or PCA (B, C), highlighting distinct dynamic processes. (A) The cell cycle in mouse hematopoietic stem and progenitor cells; adapted under terms of CC BY 4.0 from Scialdone et al. (2015). (B) Response to lipopolysaccharide (LPS) in mouse immune dendritic cells. (C) Variation in the extent of pathogenicity in mouse Th17 cells.
See this image and copyright information in PMC

"V体育2025版" References

    1. Achim K, Pettit JB, Saraiva LR, Gavriouchkina D, Larsson T, Arendt D, Marioni JC. High-throughput spatial mapping of single-cell RNA-seq data to tissue of origin. Nature Biotechnology. 2015;33:503–509. doi: 10.1038/nbt.3209. - DOI - PubMed
    1. Adamson B, Norman TM, Jost M, Cho MY, Nuñez JK, Chen Y, Villalta JE, Gilbert LA, Horlbeck MA, Hein MY, Pak RA, Gray AN, Gross CA, Dixit A, Parnas O, Regev A, Weissman JS. A multiplexed single-cell CRISPR screening platform enables systematic dissection of the unfolded protein response. Cell. 2016;167:e1821. doi: 10.1016/j.cell.2016.11.048. - DOI (VSports最新版本) - PMC - PubMed
    1. Albayrak C, Jordi CA, Zechner C, Lin J, Bichsel CA, Khammash M, Tay S. Digital quantification of proteins and mRNA in single mammalian cells. Molecular Cell. 2016;61:914–924. doi: 10.1016/j.molcel.2016.02.030. - DOI - PubMed
    1. Angelo M, Bendall SC, Finck R, Hale MB, Hitzman C, Borowsky AD, Levenson RM, Lowe JB, Liu SD, Zhao S, Natkunam Y, Nolan GP. Multiplexed ion beam imaging of human breast tumors. Nature Medicine. 2014;20:436–442. doi: 10.1038/nm.3488. - DOI - PMC - PubMed
    1. Angerer P, Haghverdi L, Büttner M, Theis FJ, Marr C, Buettner F. Destiny: diffusion maps for large-scale single-cell data in R. Bioinformatics. 2016;32:1241–1243. doi: 10.1093/bioinformatics/btv715. - DOI - PubMed