The Single Cell Genomics Team at the CNAG is dedicated to advancing genome research of single cells.

The mission of the group is the implementation of the latest single-cell and spatial sequencing technologies and their application in a research and translational/clinical context. The group focuses on the systematic integration of genomic data from individual cells to elucidate causalities underlying cell identities in health and disease.

The group joins computational, genomics, immunology, and biotechnology expertise to establish and apply best practices in single-cell and spatial research. The group combines technology development activities with research lines that center on cell atlas projects, immuno-oncology, and immune-mediated diseases. The group is a member of the Human Cell Atlas (HCA) project and LifeTime initiative, with projects to generate atlases of human immune cells, the pancreas and kidney. Dr. Heyn is also co-chairing the Standards and Technology working group to scout, benchmark and scale emerging technologies for the HCA and wider Genomics community.

The Single Cell Genomics Team successfully established protocols to quantify gene expression, immune repertoires, and open chromatin sites of hundred-thousands of isolated single cells (10x Chromium X, 10x Chromium Connect, Singleron, FluentBio, MissioBio Tapetri, etc) or in tissues (Nanostring CosMx, BGI Stereo-seq, 10x Visium). Their computational pipelines together with their long-standing experience allow sophisticated analysis of single-cell and spatial data and a meaningful interpretation of results.

Publications:

Detection of early seeding of Richter transformation in chronic lymphocytic leukemia, Nat Med. 2022 Aug; 28(8):1662-1671. doi: 10.1038/s41591-022-01927-8

The emerging landscape of spatial profiling technologies, Nat Rev Genet. 2022 Dec;23(12):741-759. doi: 10.1038/s41576-022-00515-3

A single-cell tumor immune atlas for precision oncology, Genome Res. 2021 Oct;31(10):1913-1926.doi: 10.1101/gr.273300.120

Immune cell profiling of the cerebrospinal fluid enables the characterization of the brain metastasis microenvironment, Nat Commun. 2021 Mar 8;12(1):1503. doi: 10.1038/s41467-021-21789-x

SPOTlight: seeded NMF regression to deconvolute spatial transcriptomics spots with single-cell transcriptomes, Nucleic Acids Res. 2021 Feb 5;gkab043. doi: 10.1093/nar/gkab043. Online ahead of print

Building a high-quality Human Cell Atlas, Nat Biotechnol. 2021 Feb;39(2):149-153. doi: 10.1038/s41587-020-00812-4

Modeling Human TBX5 Haploinsufficiency Predicts Regulatory Networks for Congenital Heart Disease, Dev Cell. 2020 Dec 8;S1534-5807(20)30929-1.doi: 10.1016/j.devcel.2020.11.020.

The order and logic of CD4 versus CD8 lineage choice and differentiation in mouse thymus, Nat Commun. 2021 Jan 4;12(1):99.doi: 10.1038/s41467-020-20306-w

Zonation of Ribosomal DNA Transcription Defines a Stem Cell Hierarchy in Colorectal Cancer, Cell Stem Cell. 2020 Jun 4;26(6):845-861.e12.https://doi.org/10.1016/j.stem.2020.04.012

Sampling time-dependent artifacts in single-cell genomics studies, Genome Biol. 2020 May 11;21(1):112.https://doi.org/10.1186/s13059-020-02032-0

Benchmarking Single-Cell RNA Sequencing Protocols for Cell Atlas Projects, Nat Biotechnol. 2020 Jun;38(6):747-755.doi: 10.1038/s41587-020-0469-4

Single-cell transcriptomics unveils gene regulatory network plasticity, Genome Biol. 2019 Jun 4;20(1):110. doi: 10.1186/s13059-019-1713-4.

Single cell RNA-seq identifies the origins of heterogeneity in efficient cell transdifferentiation and reprogramming, Elife. 2019 Mar 12;8. pii: e41627. doi: 10.7554/eLife.41627.

Tutorial: guidelines for the experimental design of single-cell RNA sequencing studies, Nat Protoc. 2018 Dec;13(12):2742-2757. doi: 10.1038/s41596-018-0073-y. Review.

Identity Noise and Adipogenic Traits Characterize Dermal Fibroblast Aging, Cell. 2018 Nov 29;175(6):1575-1590.e22. doi: 10.1016/j.cell.2018.10.012. Epub 2018 Nov 8.

matchSCore: Matching Single-Cell Phenotypes Across Tools and Experiments, BioRxiv 2018, May 7. doi.org/10.1101/314831

bigSCale: An Analytical Framework for Big-Scale Single-Cell Data, Genome Res. 2018 Jun;28(6):878-890. doi: 10.1101/gr.230771.117. Epub 2018 May 3.

PM20D1 methylation quantitative trait locus is associated with Alzheimer’s disease, Nature Medicine 2018, May 7. doi: 10.1038/s41591-018-0013-y. [Epub ahead of print]

Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation, Cell. 2018 Apr 5;173(2):338-354.e15. doi: 10.1016/j.cell.2018.03.034.

Single-cell transcriptome conservation in cryopreserved cells and tissues, Genome Biol. 2017 Mar 1;18(1):45. doi: 10.1186/s13059-017-1171-9.

Targeting lymphoid-derived IL-17 signaling to delay skin aging, Nat Aging. 2023 Jun;3(6):688-704. doi: 10.1038/s43587-023-00431-z. Epub 2023 Jun 8.PMID: 37291218 Free PMC article.

Systematic benchmarking of single-cell ATAC-sequencing protocols, Nat Biotechnol. 2023 Aug 3. doi: 10.1038/s41587-023-01881-x. Online ahead of print.PMID: 37537502.

Detection of early seeding of Richter transformation in chronic lymphocytic leukemia, Nat Med. 2022 Aug;28(8):1662-1671. doi: 10.1038/s41591-022-01927-8. Epub 2022 Aug 11.PMID: 35953718 Free PMC article.

The emerging landscape of spatial profiling technologies, Nat Rev Genet. 2022 Dec;23(12):741-759. doi: 10.1038/s41576-022-00515-3. Epub 2022 Jul 20.PMID: 35859028 Review.