SCOG Virtual Lecture Series

1 March 2023: Matthias Heinig (Helmholtz Munich): "Designing multi-sample single cell experiments to infer personalized regulatory networks"

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1 February 2023: Hedda Wardemann (DKFZ, Heidelberg): "Single-cell based antigen-receptor gene and function analyses of the human immune response to a complex pathogen"

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16 December 2022: Fabian Theis (Helmholtz Munich): "*ingle *ells, *ingle *ells: my letter to Santa on what single cell can bring next year"

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21 October 2022: Simone Picelli (IOB, Basel): "Fast and highly sensitive full-length single-cell RNA-sequencing using FLASH-seq"

Single-cell RNA-sequencing (scRNA-seq) has undergone exponential growth in the past 10 years. Emulsion droplets methods, such as those commercialized by 10x Genomics, have enabled robust, reproducible analysis of thousands of cells in parallel. However, in contrast to full-length sequencing protocols like Smart-seq 2/3, 10x Genomics technology captures only the 3´-end or the 5´-end of each transcript, thus lacking the coverage and the sensitivity for a comprehensive analysis of the entire transcriptome. Moreover, 3´/5´-sequencing can´t discriminate between splicing isoforms, identify internal SNPs or establish allele usage in different cells. Building upon the existing SMART-seq 2/3 protocols we developed FLASH-seq (FS), a new full-length scRNA-seq method with increased sensitivity, limited hands-on time and the potential for customization to meet demands of specific biological questions. Every step in FLASH-seq has been carefully optimized by testing hundreds of conditions to find the best-performing combination of buffers, additives and enzymes. FLASH-seq combines Reverse Transcription (RT) and pre-amplification in a single reaction, decreases RT time by using a more processive enzyme and boosts template switching reaction efficiency by adding an unbalanced mixture of deoxyribonucleotides. FLASH-seq is an automation-friendly, modular protocol that can be efficiently miniaturized to reduce library preparation costs. By reducing the number of PCR cycles required for cDNA synthesis and eliminating the need for sample cleanup, QC and normalization, we have developed an iteration of the protocol, FLASH-seq Low-Amplification (FS-LA), which enables generation of sequencing-ready libraries in just 4.5 hours. To address the need for molecule counting and isoform reconstruction, we have introduced a Template Switching Oligonucleotide containing Unique Molecular Identifiers (TSO-UMI) into the FLASH-seq system. Our novel TSO-UMI was designed to minimize the well-known (but largely neglected) phenomenon of strand-invasion during RT along with resulting sequencing artifacts. We introduced a 5-bp spacer between the 3 terminal ribonucleotides and the UMI sequence of the TSO, obtaining a significant reduction in the number of strand invasion artifacts compared to Smart-seq3. Such a modification also dramatically increased cDNA yield and, more importantly, resulted in a higher number of detected genes (15% more compared to the standard FS protocol).

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23 September 2022: Ozgun Gokce (ISD/LMU, Munich): "Spatial transcriptomics-correlated electron microscopy to study brain aging"

Current spatial transcriptomics methods identify cell states in a spatial context but lack morphological information. Scanning electron microscopy, in contrast, provides structural details at nanometer resolution but lacks molecular decoding of the diverse cellular states. To address this, we correlated MERFISH spatial transcriptomics with large area volume electron microscopy using adjacent tissue sections. We applied our technology to characterize the damage-associated microglial identities in mouse brain, allowing us, for the first time, to link the morphology of foamy microglia and interferon-response microglia with their transcriptional signatures.

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SCOG Workshop "Single Cell Genomics meets Data Science",
Munich, 12-13 September 2022

Session 1 "Technology"

Christoph Bock (CeMM, Vienna): “Single-cell analysis of epigenetic cell states in immunology and cancer”

0:00 Predicting developmental states using transfer learning (Gaurav Jumde, BIMSB/MDC Berlin)

15:39 Cross-species comparison of gene regulatory networks (Anita Térmeg, LMU Munich)

31:40 Swarm Learning for single-cell data in human immunology (Maren Büttner, DZNE Bonn)

More info: Twitter: @singlecellomics

Session 2 "Spatial"

0:00 Mapping human tissue architecture and pathology using spatial transcriptomics (Omer Bayraktar, Wellcome Sanger Institute, Hinxton)

30:20 Combining single-cell and spatial transcriptomics to study metastatic microenvironments (Johanna Klughammer, LMU Munich)

01:00:35 Using biological knowledge to extract disease mechanisms from single-cell and spatial data (Julio Saez-Rodriguez, Heidelberg University)

01:16:32 Using temporal flow models for dissecting epigenetic function and intercellular signaling in gastrulation (Markus Mittnenzweig, Weizmann Institute of Science)

More info: Twitter: @singlecellomics

Session 3 "Regulation"

0:00 Measuring somatic mutations and their consequences to identity and target cancer subclones (Ashley Sanders, BIMSB/MDC, BIH/Charité, Berlin)

31:16 Decoding gene regulation using single-cell multi-omics, deep learning, and synthetic biology (Stein Aerts, KU Leuven)

01:04:14 Identification of genetic variants that impact gene co-expression relationships using large-scale single-cell data (Maryna Korshevniuk, UMCG, Groningen)

01:18:28 CanSig: Discovering de novo shared transcriptional programs in single cancer cells (Florian Barkmann, ETH Zurich)

More info: Twitter: @singlecellomics

Session 4 "Machine Learning"

0:00 Gaussian process methods for modeling temporal and spatial gene expression changes (Magnus Rattray, The University of Manchester)

32:48 Interpretable and reliable machine learning for large heterogeneous data (Florian Büttner, DKFZ, Heidelberg)

01:03:46 Predicting transcriptional outcomes of novel multi-gene perturbations (Yusuf Roohani, Stanford University)

01:20:02 Unifying t-SNE and UMAP (Sebastian Damrich, Heidelberg University)

More info: Twitter: @singlecellomics

Session 5 "Dynamics"

Laleh Haghverdi (BIMSB/MDC, Berlin): “The dynamics of cell differentiation”

More info: Twitter: @singlecellomics

SCOG Virtual Lecture Series

1 July 2022: Kikuë Tachibana (MPI Biochemistry, Munich): "Insights into the emergence of 3D genome architecture at the start of life by single-nucleus Hi-C"

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17 June 2022: Gabriela Salinas (University Medical Center, Göttingen): "Technical Improvements in Single-Cell RNA-Sequencing delivering the promise of RNA therapeutics"

Single-cell multi-omics analysis has the potential to yield a comprehensive understanding of the cellular events that underlie the basis of human diseases. The cardinal feature to access this information is the technology used for single-cell isolation, barcoding, and sequencing. Most currently used single-cell RNA-sequencing platforms have limitations in several areas including cell selection, documentation and library chemistry. In this study, we describe a novel high-throughput, full-length, single-cell RNA-sequencing approach that combines the CellenONE isolation and sorting system with the ICELL8 processing instrument. This method offers substantial improvements in single cell selection, documentation and capturing rate. Moreover, it allows the use of flexible chemistry for library preparations and the analysis of living or fixed cells, whole cells independent of sizing and morphology, as well as of nuclei. We applied this method to dermal fibroblasts derived from six patients with different segmental progeria syndromes and defined phenotype associated pathway signatures with variant associated expression modifiers. These results validate the applicability of our method to highlight genotype-expression relationships for molecular phenotyping of individual cells derived from human patients.

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03 June 2022: Florian Mair (ETH, Zurich): "Disentangling human tumor-unique immune alterations from non-malignant tissue inflammation using multi-omic single cell analysis"

Immunotherapies to treat cancer have achieved remarkable successes, but major challenges persist. An inherent weakness of current treatment approaches is that therapeutically targeted pathways are not only found in tumors, but also in tissue microenvironments, particularly inflamed tissues. This confounding overlap complicates treatment as well as predictions of treatment outcome. In an effort to identify potential tumor-unique immunotherapeutic targets that are distinct from general tissue inflammation, we used complementary single-cell analysis approaches to interrogate immune cell alterations and interactions in human head and neck squamous cell carcinomas (HNSCC) and site matched non-malignant, inflamed oral tissues. Using a combination of scRNA-sequencing and high-dimensional flow cytometry we found that a distinct population of intratumoral regulatory T cells (Tregs) is receiving T cell receptor (TCR) signals from antigen-presenting cells (APCs). This Treg population can be uniquely identified among all hematopoietic cells in the tumor by co-expression of ICOS and IL-1 receptor type 1 (IL-1R1), allowing therapeutic targeting and depletion by bispecific antibodies or logic-gated CAR T cells. In addition, we used targeted transcriptomics and protein profiling (AbSeq) to assess the functional response of these human intratumoral IL-1R1+ Tregs after stimulation via the T cell receptor or cytokines. Overall, our work provides a blueprint for identifying tumor-unique therapeutic targets distinct from general inflammatory patterns in other tumors and reveals a possible strategy for specific depletion of intratumoral Tregs.

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SCOG Workshop "Spatial transcriptomics data analysis in Python",
23-24 May 2022

The workshop was held by Giovanni Palla (Helmholtz Munich, Germany), David Fischer (Helmholtz Munich, Germany), Anna Schaar (TUM, Germany), Alma Andersson (KTH, Sweden), Vitalii Kleshchevnikov (Wellcome Sanger Institute, UK), Johanna Klughammer (LMU, Germany) and Fabian Theis (Helmholtz Munich, Germany). It covered the analysis of spatial transcriptomics data in Python, with tools like squidpy, node-centric expression models (ncem) as well as deconvolution (cell2location) and registration methods (eggplant). The workshop introduced the participants to both theoretical concepts as well as hands-on tutorials for the analysis of spatial transcriptomics data. Publicly available data was available for this purpose, but users were welcome to analyze their own data in the context of the workshop. Basic python and scanpy knowledge required.

SCOG Virtual Lecture Series

20 May 2022: Heiko Lickert (Helmholtz Munich): "Deciphering mechanisms of beta cell development and regeneration"

The lack or dysfunction of insulin-producing ß-cells is the cause of type I or type II diabetes, respectively. The primary objective of the Institute of Diabetes and Regeneration Research (IDR) at the Helmholtz Zentrum München is to develop regenerative therapeutic approaches to treat diabetes mellitus – complementary and alternative to the classical immunological and metabolic therapy strategies. In vitro generation of ß-cells from pluripotent stem cells for cell-replacement therapy or triggering endogenous mechanisms of ß-cell repair have great potential in the field of regenerative medicine. Both approaches rely on a thorough understanding of ß-cell development and homeostasis in pre-clinical models. Therefore, the aim is to improve current strategies for functional ß-cell production in vitro with the ultimate goal to provide alternative sources of ß-cells for therapy. Additionally, we analyze and characterize the embryonic and adult pancreatic progenitor cells to understand ß-cell development, homeostasis and function for in vivo regeneration.

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06 May 2022: Christian Schmidl (Leibniz Institute for Immunotherapy, Regensburg): "Integrated single-cell profiling dissects cell-state-specific enhancer landscapes of human tumor-infiltrating T cells"

Despite extensive studies on the chromatin landscape of exhausted T cells, the transcriptional wiring underlying the heterogeneous functional and dysfunctional states of human tumor-infiltrating lymphocytes (TILs) is incompletely understood. Here, we identify tissue-specific and general gene-regulatory landscapes in the wide breadth of CD8+ TIL functional states covering four cancer entities using single-cell chromatin profiling. We map enhancer-promoter interactions in human TILs by integrating single-cell chromatin accessibility with single-cell RNA-seq data from tumor entity-matching samples, and prioritize key elements by super-enhancer analysis. Besides revealing entity-specific chromatin remodeling in exhausted TILs, our analyses identify a human core chromatin trajectory to TIL dysfunction and determine involved key enhancers, transcriptional regulators, and deregulated target genes in this process. Finally, we validate enhancer regulation at immunotherapeutically relevant loci by targeting non-coding regulatory elements with potent CRISPR activators and repressors. In summary, our study provides a framework for understanding and manipulating cell-state-specific gene-regulatory cues from human tumor infiltrating lymphocytes.

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22 April 2022: Laleh Haghverdi (BIMSB/MDC, Berlin): "Towards reliable quantification of cell state velocities"

The talk mainly focuses on new kappa-velo (detailed) and eco-velo (cost efficient and minimal) methods for more reliable quantification of cell state velocities from simultaneous measurement of unspliced and spliced messenger RNA (mRNA) in high-throughput snapshots of single cell RNA sequencing data. Current methods for inferring cell state velocities from such data (known as RNA velocities) are afflicted by several theoretical and computational problems, hindering realistic and reliable velocity estimation. Kappa-velo and eco-velo address some of the current challenges in consistency of data processing, inference and visualisation of single cells’ velocities.

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08 April 2022: Christoph Bock (CeMM, Vienna, AT): "Looking into the past and future of cells: Single-cell analysis of epigenetic cell states in cancer and immunology"

Most diseases develop through the complex interplay of genetic and environmental influences, involving signaling pathways, metabolic changes, immune deregulation, and diverse cellular phenotypes. Our research is based on the hypothesis that the “epigenetic landscape” constitutes a highly informative intermediate layer of information processing that allows cells to maintain their regulatory state and cellular identity over time, while retaining the flexibility to respond swiftly to a broad range of perturbations. In our definition, the “epigenetic landscape” is not restricted to epigenetic marks such as DNA methylation and histone modifications. Rather, it reflects the full spectrum of transcription regulation by which cells translate various inputs into sustainable changes in their cell state. Notably, the epigenetic landscape not only reflects a cell’s current state, but also its developmental history (e.g., cell-of-origin in cancer) and its potential for future adaptation (e.g., plasticity in response to an immunological challenge). I will present our work within and beyond the Human Cell Atlas, dissecting epigenetic cell states in immunology and cancer; and I will present methods for causal, mechanistic analysis at scale (CROP-seq and KPNNs) and for ultra-high throughput transcriptome profiling in millions of single cells (scifi-RNA-seq). Funding: C.B. is supported by an ERC Consolidator Grant (n° 101001971) of the European Union.

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25 March 2022: Bart Deplancke (EPFL, Lausanne): "Engineering next-generation single cell phenomics technologies"

Single cell transcriptomics (scRNA-seq) is transforming biomedical research by providing unique insights into a cell’s identity and characteristics. However, several key single cell-related technological challenges remain, including the need for methods that i) are tailored toward low-input cell samples to process small, individual tissues; ii) enable linking the transcriptome of a cell to a high-resolution image of that same cell; and 3) allow retrieving the transcriptome of a cell without lysing it to support downstream phenotyping or direct trajectory inference. In this technology-centric talk, I will present my lab’s efforts to address each of these challenges. Specifically, I will introduce DisCo, a deterministic, mRNA-capture bead and cell co-encapsulation dropleting system. DisCo enables precise particle and cell positioning and droplet sorting control through combined machine-vision and multilayer microfluidics, enabling continuous processing of low-input single cell suspensions at high capture efficiency. I thereby will discuss how further integration of high-resolution imaging into DisCo is paving the way for an interconnecting robotic image and scRNA-seq (IRIS) platform uniquely enabling the selection, sorting, and molecular as well as phenotypic characterization of individual cells. Finally, I will introduce Live-seq, a novel cell lysis-devoid, single cell transcriptomics approach that can act as a transcriptomic recorder to predict cell response heterogeneity and that can be used to perform sequential transcriptome profiling on cells to directly map cell trajectories.

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SCOG Workshop "Sfaira"

Hosts: David Fischer, Leander Dony, Felix Fischer, Fabian Theis (Helmholtz Munich)

The workshop covers the use of pre-curated data for re-analysis or model fitting (consumption) and curation of new data (contribution). Both sessions introduce the overall context of the respective step along the data life cycle and a hands-on example session with room for translating this into your own projects.

14 February 2022: Day 1 - Introduction, API walk-through, Tutorials

0:00 Session 1: Introduction to Sfaira

38:20 Session 2: Universe and Dataset API

01:32:15 Session 3: cellxgene API

01:46:35 Session 4: Store API

02:20:45 Session 5: Managing Private Data with Sfaira

02:25:53 Session 6: Preparation for Day 2, Q&A

15 February 2022: Day 2 - Introduction CLI

SCOG Virtual Lecture Series

05 November 2021: Adrián Granada (Charité, Berlin): "How proliferation cell cycle dynamics affect the responses of single cells to chemotherapy"

DNA damaging chemotherapeutics are widely used in cancer treatments, but they suffer from incomplete eradication of tumor cells and development of drug resistance. Recent studies have revealed how non-genetic cell-to-cell variability can drive significant phenotypic differences in response to identical drug treatment, leading to the hypothesis that the heterogeneity of cellular states might underlie the heterogeneous response within a tumor. In this talk I will present our recent study investigating how the dynamics of cellular states affect the response of individual cells to the chemotherapeutic drug Cisplatin. Our results show how two intertwined cellular states present in every cell have distinct control of cell fate choices in response to the chemotherapeutic drug Cisplatin. Contrary to tumor observations, we find that in dividing cells higher proliferation activity increases resistance and that cell cycle state determines the arrest likelihood of the surviving population. These findings show how the dynamics of cellular states shape the individual cell choices that collectively determine the overall response to therapy.

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SCOG Virtual Workshop: "Recent Advances in single cell Epigenomics"

20-21 October 2021

Catherine Blish (Stanford University, USA): "Innate immune dysfunction during COVID-19"
Fabian Mueller (USAAR, Saarbruecken): "Chromatin and gene-regulatory dynamics of the developing human cerebral cortex at single-cell resolution"
Elana Fertig (Johns Hopkins University, Baltimore, USA): "Transfer learning for transcriptional regulation"
Goncalo Castelo-Branco (Karolinska Institutet, Stockholm): "Single-cell transcriptomics and epigenomics of oligodendroglia in neural development and in multiple sclerosis"
Andrew Adey (OHSU, Portland, USA): "High-content single-cell epigenomics"
Michael Robson (MPI-MolGen, Berlin): "Multi-omic single-cell profiling reveals nuclear envelope release precedes gene activation during mouse embryogenesis"
Steffen Rulands (MPI-PKS, Dresden) : "From sequence to space and time in single-cell genomics"

SCOG Virtual Lecture Series

22 October 2021: Malte Luecken (ICB/HMGU, Munich): "Building the integrated human lung cell atlas"

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8 October 2021: Ashley Sanders (BIH@Charité, BIMSB/MDC, Berlin): "Characterizing somatic mutations by single-strand sequencing"

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16 July 2021: Carsten Marr (HMGU, Munich): "Artificial Intelligence for Computational Hematopathology"

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04 June 2021: Herbert Schiller (HMGU, Munich): "Integrative analysis of cell state changes in lung fibrosis with peripheral protein biomarkers"

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21 May 2021: Emanuel Wyler (BIMSB/MDC, Berlin): "Investigating COVID-19 pathogenesis in hamster animal models"

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23 April 2021: Roi Avraham (Weizmann Institute of Science, Israel): "scRNA-seq Reveals A Macrophage Subset That Provides A Splenic Replication Niche For Intracellular Salmonella"

Interactions between intracellular bacteria and mononuclear phagocytes give rise to diverse cellular phenotypes that may determine the outcome of infection. Recent advances in single-cell RNA-seq (scRNA-seq) have identified multiple subsets within the mononuclear population, but the implications to their function during infection is unknown. Here, we applied microscopy, flow cytometry and scRNA-seq to survey the mononuclear niche of intracellular Salmonella Typhimurium (S.Tm) during early systemic infection in mice. We describe an eclipse like growth kinetics in the spleen, with a first phase of bacterial control mediated by tissue-resident red-pulp macrophages. A second phase involved bacterial growth mediated by intracellular replication within a macrophage population we termed CD9 macrophages that originate from non-classical monocytes Nr4a1e2-/- mice, specifically depleted of non-classical monocytes, are more resistant to S.Tm infection. Our study underscores a cell-type specific host-pathogen interaction that determines early infection growth dynamics and has implications to the infection outcome of the entire organism.

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9 April 2021: Samantha Morris (WUSTL, St. Louis, USA): "New single-cell technologies to dissect reprogramming and development"

Direct lineage reprogramming involves the remarkable conversion of cellular identity. Single-cell technologies aid in deconstructing the considerable heterogeneity in transcriptional states that typically arise during lineage conversion. However, lineage relationships are lost during cell processing, limiting accurate trajectory reconstruction. We previously developed ‘CellTagging’, a combinatorial cell indexing methodology, permitting the parallel capture of clonal history and cell identity, where sequential rounds of cell labeling enable the construction of multi-level lineage trees. CellTagging and longitudinal tracking of fibroblast to induced endoderm progenitor (iEP) reprogramming reveals two distinct trajectories: one leading to successfully reprogrammed cells, and one leading to a dead-end state. Here, I present two new methods to enable the molecular mechanisms underlying reprogramming outcome to be dissected. The first is an experimental method, ‘Calling Cards’, enabling transcription factor binding to be recorded, in individual cells, in the earliest stages of reprogramming. The second method is a new computational platform, called ‘CellOracle’, that uses single-cell transcriptome and chromatin accessibly data to reconstruct changes in GRN configurations across the reprogramming process. Together, these tools provide new mechanistic insights into how transcription factors can drive changes in cell identity, and help reveal new factors to enhance the efficiency and fidelity of reprogramming.

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26 February 2021: Maria Colomé-Tatché (ICB/HMGU, Munich): "Single cell computational epigenomics"

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SCOG Virtual Workshop: "Spatial Single Cell Analysis" - February 2021

This one-day workshop took place on February 10, 2021. It was hosted by SCOG founders Nikolaus Rajewsky (BIMSB/MDC, Berlin) and Fabian Theis (ICB/HMGU, Munich) and provided an overview of the latest findings and developments in the field of spatial single cell analysis.

Agenda of Session 1:

0:00 Welcome (Fabian Theis, ICB/HMGU, Germany)

7:12 Leeat Keren (Weizmann Institute, Israel)

25:02 Omer Bayraktar (Wellcome Sanger Institute, UK)

42:01 Evan Macosko (Broad Institute, USA)

59:15 Joint Discussion (Keren, Bayraktar, Macosko, Theis, Rajewsky)

Agenda of Session 2:

0:00 John Marioni (EMBL-EBI/Sanger Institute, UK)

16:20 Long Cai (California Institute of Technology, USA)

30:24 Felix Hartmann (Stanford University, USA)

46:00 Joint Discussion (Marioni, Cai, Hartmann, Rajewsky, Theis)

SCOG Virtual Course - "Sfaira" (Theis lab - ICB/HMGU, Munich) / Feb 08, 2021

Sfaira is a data loader and model repository for single-cell data. The tutorial will focus on the data loader zoo, a new software capable of scaling up data streamlining efforts in a community-driven fashion. In particular, it will be shown 1) how sfaira makes your life a lot easier when using other people’s data and 2) how you can increase re-usage of your public data sets with sfaira. The tutorial will start with a brief introductory presentation of the sfaira data zoo, followed by a tutorial for using the data zoo (1) and a tutorial for contributing to the data zoo (2). After the tutorial, participants will be able to write their own data loaders and maintain their own data collections.

SCOG Virtual Lecture Series

04 December 2020: Wolf Reik (Babraham Institute, Cambridge/UK): "Single cell multi-omics and spatial transcriptomics of mammalian development"

Wolf Reik and the Wellcome gastrulation consortium

Epigenetics Programme, Babraham Institute, Cambridge CB22 3AT

Centre for Trophoblast Research, University of Cambridge, CB2 3EG

Wellcome Trust Sanger Institute, Cambridge CB10 1SA

With our collaborators we are interested in the regulation of cell fate decisions in early mammalian development. We are charting mouse and human development using single cell multi-omics approaches. We are interested in epigenetic regulators of early development including factors that control lineage priming. We have recently developed single cell transcriptomics, epigenome triple-omics, and spatial transcriptome atlases of gastrulation and early organogenesis.

Pijuan-Sala et al 2019, Argelaguet et al 2019, Eckersley-Maslin et al 2020, Lohoff et al 2020

Please find the pre-print to this lecture here:

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07 November 2020: Boyan Bonev (HPC/HMGU, Munich): "Single-cell multiomics analysis reveals extensive epigenome remodeling during cortical development"

Despite huge advances in stem-cell, single-cell and epigenetic technologies, the precise molecular mechanisms that determine lineage specification remain largely unknown. Applying an integrative multiomics approach, e.g. combining single-cell RNA-seq, single-cell ATAC-seq together with cell-type-specific DNA methylation and 3D genome measurements, we systematically map the regulatory landscape in the mouse neocortex in vivo. Our analysis identifies thousands of novel enhancer-gene pairs associated with dynamic changes in chromatin accessibility and gene expression. We provide evidence that although epigenetic remodeling generally precedes transcriptional activation, true priming appears limited to a subset of lineage-determining enhancers. Notably, we reveal that enhancer-promoter contact frequency varies considerably despite overall cell-type specificity. Finally, our work suggests a so far unrecognized function of several key transcription factors as putative “molecular bridges”, facilitating the reorganization of chromatin landscape accompanying lineage specification in the brain.

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09 October 2020: Prisca Liberali (FMI, Basel): "Lineage tracing of stem cell dynamics using single cell technologies"

Multicellular organisms are composed of cells and tissues with identical genomes but different properties and functions. They all develop from one cell to form multicellular structures of astounding complexity. During development, in a series of spatio-temporal coordinated steps, cells differentiate into different cell types and establish tissue-scale architectures and functions. Throughout life, continuous tissue renewal and regeneration is required for tissue homeostasis, which also requires fine-tuned spatio-temporal coordination of cells. How cellular interactions generate the specific contexts and spatio-temporal coordination underlying development and regeneration is a key question in biology and we specifically investigate what are the molecular and physical mechanisms that allow a cell, in a tissue, to sense its complex environment, to take individual coordinated decisions. And what are the design principles governing coordinated cellular behavior during tissue organization? We take three main approaches using single cell technologies to tackle these questions: (i) We investigate the molecular mechanisms of intestinal organoid self-organization with a special focus on the role of cell-to-cell variability in populations of differentiating cells. (II) We use human organoids from patients to understand regeneration of the intestine. (III) We use different in vitro self-organizing systems, such as gastruloids to reveal general design principles of self-organization and how tissues use distinctive strategies to maintain homeostasis and repair lost cells.

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SCOG Virtual Workshop: "Temporal Single Cell Analysis" - September 2020

The one-day workshop is hosted by Fabian Theis (Institute of Computational Biology, Helmholtz Munich) and Emmanuel Saliba (Helmholtz Institute for RNA-based infection research, Würzburg) and will cover the new exciting fields of RNA metabolic labeling and velocity. Motivation: A major obstacle to understanding dynamical processes in biology is that they happen in the scale of a few hours and are highly heterogeneous and asynchronous across cells. We are currently lacking a clear molecular, temporal and spatial picture of transition processes. Recent advances in single-cell and computational technologies are making addressing these challenges possible. Thus, this workshop will bring together experts in temporal single-cell technologies from the experimental and computational sides that are developing novel methods to uncover cellular transitions.

Alexander van Oudenaarden (Hubrecht Institute, Utrecht): "Integration of multiple lineage measurements from the same single cell reconstructs parallel tumor evolution"
Caroline Uhler (ETH, Zurich): "Multi-Domain Data Integration: From Observations to Mechanistic Insights"
Dana Pe'er (MSKCC, New York City): "Trajectories and Gene Regulation"
Volker Bergen (Helmholtz Munich): "RNA velocity state-of-the-art and future directions"
Florian Erhard (University of Würzburg): "infect me if you can: Studying virus infection in single cells"

SCOG Virtual Lecture Series

11 September 2020: Dominic Grün (MPI-IE, Freiburg): "Revealing Dynamics of Gene Expression Variability in Cell State Space "

The availability of high-throughput single-cell RNA-sequencing methods has facilitated the identification of cell types in organs and tissues, allowing the creation of tissue cell type atlases. In these efforts typically tens of thousands of cell are sequenced, frequently at low sequencing depth, and cell type identification relies on computational methods sensitive to highly expressed genes. To understand cell differentiation and cell state transitions in general it is crucial to quantify weak expression of lineage determining factors, requiring computational methods sensitive to variability of lowly expressed genes. We here introduce VarID, a computational method that identifies locally homogenous neighborhoods in cell state space, permitting the quantification of local gene expression variability. By controlling for the variance-mean dependence of transcript counts VarID delineates neighborhoods with differential variability and reveals pseudo-temporal dynamics of gene expression variability during differentiation. VarID recovers the stochastic activity of lineage-associated transcription factor networks in murine hematopoietic multipotent progenitors, and reveals increased variability of transcription factors associated with secretory lineages in mouse intestinal epithelial stem cells. In conclusion, our approach enables the investigation of stochastic gene activity, a previously understudied aspect, with the help of single-cell RNA-seq data and can provide novel insights in the regulation of cell fate decision.

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28 August 2020: Uwe Ohler (BIMSB/MDC, Berlin): "Single-cell decoding of gene regulatory programs"

In the 7th SCOG Virtual Lecture, Uwe Ohler from the BIMSB/MDC presented ongoing research and recently published data. The title of the talk is “Single-cell decoding of gene regulatory programs” and you can find references to the published papers on the slides.

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03 July 2020: Julio Saez-Rodriguez (Heidelberg University): "Extracting mechanistic insight from single-cell and spatial transcriptomics"

Single-cell technologies generate large datasets that allow us to study biomedical processes with unprecedented detail. These data could, in principle, shed light on the cellular communication mechanisms that control homeostasis in multi-cellular systems, and how these mechanisms go wrong in diseases ranging from cancer to heart failure. We have developed a set of tools for the analysis transcriptomic data, ranging from a meta-resource of biological knowledge (Omnipath) to methods to infer pathway and transcription factor activities (PROGENy and DoRothEA, respectively) from gene expression and subsequently infer causal paths among them (CARNIVAL). We have recently adopted these tools to single-cell data, supported by a comprehensive benchmark with in silico and real data. We have also developed approaches to analyze transcriptomic data with spatial resolution. In particular, our method MISTy is a flexible, scalable, and explainable machine learning framework for extracting interactions from spatial omics data. MISTy builds multiple views focusing on different spatial or functional contexts to dissect different effects. We have also integrated the aforementioned to estimate the activities of pathways and transcription factors in MISTy, enabling us the analysis of intercellular signaling in a spatial context. All our methods are freely available as R-packages. I will illustrate these strategies in ongoing studies of with unpublished data in various disease contexts that we are performing with clinical collaborators.

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19 June 2020: Joachim L. Schultze (DZNE, Bonn): "Single Cell Omics on COVID-19 in DeCOI"

The current pandemic crisis triggered by SARS-CoV-2 leads to very different disease courses of COVID-19 ranging from very mild to very severe  with multi-organ failure. A significant number of patients with severe symptoms even succumb the infection. The host’s cellular reaction seems to be of utmost importance and responsible for this heterogenous response to the virus. Clearly, single cell omics can significantly contribute to our understanding of cellular reactions of infected cells and the response of the immune cells towards the infected cells. Over the last weeks, the German COVID-19 OMICS Initiative was established to coordinate NGS-based research efforts in COVID-19 research in Germany and together with colleagues world-wide. I will present initial results from single cell omics studies that are conducted on patient samples derived from COVID-19 patients within DeCOI.

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SCOG Workshop Computational Single Cell Genomics, March 2019, Munich

Watch the workshop sessions following the links. Thanks to the Chan Zuckerberg Initiative for sponsoring the recordings.

Christoph BockCeMM Research Center, ViennaCRISPR single-cell sequencing: Toward functional biology in high throughput
Joachim SchultzeDZNE, BonnFrom single cells to patients: A LifeTime journey
Sam RiesenfeldBroad Institute of MIT and Harvard, BostonUsing topic models to analyze the transcriptional spectrum of innate lymphoid cells
Clément CochainComprehensive Heart Failure Center, WürzburgTime series single-cell analysis of cardiac myeloid cells after acute myocardial infarction in mice
Heiko LickertHelmholtz MunichDeciphering mechanisms of β-cell failure and regeneration by single cell RNA Sequencing
Peter KharchenkoHarvard Medical School, BostonWiring together large single-cell RNA-seq collections
Vahid ShahrezaeiImperial College LondonBayesian gene expression recovery, imputation and normalisation for single cell RNA-sequencing data
Amit FrishbergTel Aviv UniversityCell composition analysis of bulk genomics using single-cell data
David FischerHelmholtz Munichdiffxpy: Scalable differential expression analysis for single-cell RNA-seq data
Angela GoncalvesDKFZ HeidelbergDetermining KIR repertoires using single cell transcriptomics
Maria Colomé-TatchéHelmholtz MunichEpiscanpy: epigenomic single cell analysis
Sara AibarVIB-KU LeuvenExploiting single-cell transcriptomics and epigenomics to reconstruct gene-regulatory networks

Helmholtz Horizons 2018

The Helmholtz Horizons Symposium 2018, hosted by the President of the Association, highlights scientific breakthroughs of Helmholtz’s established researchers, showcases talented early career researchers, and gives a platform to the entrepreneurs and innovators, who ensure that Helmholtz research has societal impact.

Visit the Helmholtz Horizons Website.

Video production: BIOCOM

Fabian Theis: ‘The Digital (R)Evolution in Science’ – Berlin, 2018 talking about ‘Learning cell lineages using artificial intelligence’.

Christin Sünkel @ Helmholtz Horizons 2018: ‘The Digital (R)Evolution in Science’ – Berlin, 2018

“Single Cells in Time and Space”

Single cell RNA sequencing allows us to study all genes that are being used in a single cell. However powerful this method is, it leaves us with thousands of data points for each cell and we study thousands of cells per experiment. Hence, there is a big need to develop computational methods that can deal with this kind of “big data”.

In her presentation Christin also introduces the LifeTime initiative for a new FET-Flagship which is coordinated  by Nikolaus Rajewsky, Head of the Berlin Institute for Medical Systems Biology at the  Max-Delbrück Center for Molecular Medicine.

Christin Sünkel studied biochemistry and molecular biology at the University of Bayreuth. As a student intern at the Rockefeller University in New York City, in the laboratory of Thomas Tuschl she worked on the role of certain RNA-binding proteins. Her studies were supported by the Studienstiftung des deutschen Volkes. For her master thesis she moved to the laboratory of Nikolaus Rajewsky at Max-Delbrück Center for Molecular Medicine / Berlin Institute for Medical Systems Biology in Berlin to develop in vitro methods for the study of circular RNAs. Now she is pursuing her PhD in Nikolaus Rajewsky’s lab focusing on the function of circular RNAs and on the development of a method to study single cell gene expression in a spatial context. Her PhD work is supported by the Boehringer Ingelheim Fonds, Signgene and MDC BOOST.

Single Cell Data Analysis - Overview

This video has been made for bioinformatics students in Cairo University, Egypt; to discuss the main Single Cell Data Analysis challenges.

Hemberg lab course:

Abdelrahman Mahmoud @ DKFZ – Heidelberg, 2018.