Single cell profiling and analysis in neuroscience #SCPAN

June 13 to July 1 (2022)

Understanding the cellular complexity of the nervous system is a key endeavor in the pursuit to reveal the biological underpinnings of brain function. The recent methodological development of high-throughput single-cell profiling techniques and analysis has emerged as an essential tool for characterizing cellular diversity in the brain offering data sets that hold the promise of being complete, accurate and permanent. This course will teach central ideas, methods, and practices of single cell profiling and hands-on computational analysis through a combination of lectures from prominent international faculty speakers, experimental projects and data analysis workshops.

The course will include practical training in small groups of students on single cell methodologies and computational and statistical data analysis needed to interpret large data sets. This integration of data analysis with hands-on experiments will allow the students to gain knowledge in technical performance as well as biological interpretation of single cell data sets.

This advanced course is aimed for graduate students from a variety of disciplines, including neuroscience, physics, computer science and applied mathematics. Students are expected to have a keen interest and basic background in neurobiology, and to fully benefit from the data analysis it is expected that the students have at least a basic knowledge in programming.

Course director & co-directors

  • Jens Hjerling-Leffler (Karolinska Institute, Sweden)
  • Peter Kharchenko (Harvard Medical School, USA)
  • Ana Munoz-Manchado (University of Cádiz/INiBICA, Spain)
  • Alexandre Favereaux (University of Bordeaux, France)

Marek Bartosovic (Karolinska Institute, Sweden)
Lisa Bast (Karolinska Institute, Sweden)
Song Chen (Wellcome Sanger Institute, USA)
Hattie Chung (Broad Institute/MIT, USA)
Lisbeth Harder (Karolinska Institute, Sweden)
Martin Häring (Muenster University Hospital, Germany)
Danny Kitseberg (Edmond & Lily Safra Center for Brain Sciences, Israel)
Gioele La Manno (Federal Institute of Technology Lausanne – EPFL, Switzerland)
Romain Lopez (University of California Berkeley, USA)
Malte Lucken (Institute of Computational Biology, Germany)
Christoffer Mattsson Langseth (Stockholm University, Sweden)
Christian Mayer (Max Planck Institute of Neurobiology, Germany)
Viktor Petukhov (University of Copenhagen, Denmark)
Milda Valiukonyte (Karolinska Institute, Sweden)

During this course, students will get hands-on experience with entire single-cell transcriptomic projects from tissue dissociation to publishable figures. We will teach the use of different kinds of starting material, three different sequencing techniques, how to treat the raw sequencing data and a multitude of analytical tools. After attending the course, our goal is that the students should be able to go back to their institute and have enough knowledge and understanding to initiate well-designed single-cell sequencing projects to tackle important questions in Neuroscience.

The course will cover following topics:

  • Cell classification in the nervous system and its implication on how we do neuroscience
  • Discrete versus continuous variability in gene expression
  • Single-cell transcriptomics and analysis of disease
  • advantages and disadvantages of different techniques; RNA amplification, SmrtSeq, SplitSeq, Dropseq, 10X genomics,
  • What type of biological insights can be gained from single cell transcriptomics
  • multimodal analysis of single cell biology where transcriptomics is coupled with other biological parameters such as a cell’s morphology, tissue localization, epigenome, proteome and/or function
  • Preparation and isolation of single cell, nuclei isolation, RNA isolation, single cell RNA amplification procedures, library construction for sequence analysis and RNA sequencing
  • experimental design considerations, data processing, data handling, quality control of the sequencing data, understanding the variances of the data, clustering of cell types
  • Nervous system development and other dynamical processes including lineage tracing including RNA-Velocity and pseudotime analysis
  • Project 1: Visualization and quantification of cellular complexity of the CA1 region of the mouse brain
  • Project 2: Understanding cellular maturation during the development of the embryonic nervous system by whole-cell RNA seq
  • Project 3: GABAergic neuronal diversity across different forebrain structures
  • Project 4: Single whole cells analysis of an Alzheimer’s disease mouse model
  • Project 5: Single nuclei analysis of an Alzheimer’s disease mouse model
  • Project 6: Single nuclei analysis of GABAergic cells in the dorsal horn in a chronic pain model
  • Project 7: Single whole cells analysis of GABAergic cells in the dorsal horn in a chronic pain model
  • Project 8: Large scale single-cell RNA-sequencing of brain tissue using SPLiT-Seq
  • Project 9: Single-cell profiling of histone modifications in the mouse cortex using scCUT&Tag
  • Project 10: InCiteSeq
  • Computational Projects: state-of-the-art approaches for computational analysis and interpretation of single-cell RNA-seq data

Keynote speakers

Kenneth Harris (University College London, UK)
Ed Lein (Allen Institute for Brain Science, USA)
John Marioni (European Bioinformatics Institute – EMBL-EBI, UK)
Ana Martin-Villalba (University of Heidelberg, Germany)
Rahul Satija (New York Genome Center – NYGC, USA)
Kun Zhang (University of California, USA)

In partnership with