Course Identification

Single Cell Genomics: practical topics in functional genomics and cellular profiling
20243262

Lecturers and Teaching Assistants

Dr. Diego Jaitin, Dr. Hadas Keren-Shaul, Dr. Avital Sarusi- Portuguez, Dr. Gili Friedlander
Merav Kedmi

Course Schedule and Location

2024
Second Semester
February 25-29, 2024,
25/02/2024
29/02/2024

Field of Study, Course Type and Credit Points

Life Sciences: Laboratory; Elective; 1.00 points
Life Sciences (ExCLS Track): Elective; 0.00 points

Comments

The course will be held between 25-29/2/24, 9:00-17:00 (Sunday-Thursday)

Prerequisites

No

Restrictions

24

Language of Instruction

English

Attendance and participation

Obligatory

Grade Type

Numerical (out of 100)

Grade Breakdown (in %)

30%
30%
40%

Evaluation Type

Other

Scheduled date 1

N/A
N/A
-
N/A

Estimated Weekly Independent Workload (in hours)

4

Syllabus

Biological systems are made of mixtures of heterogeneous cell populations that are difficult to characterize using conventional bulk methods. Today, a deeper understanding of biological systems requires applying state-of-the-art genomics methods with single-cell resolution. Indeed, single-cell genomics technologies provide a high-resolution and comprehensive view of the transcriptome of the different cellular constituents of tissues, organs, and even whole organisms under different states or conditions, pushing the frontiers in our understanding of normal physiology and disease. In recent years, several platforms for unbiased single-cell analysis have been developed. Amongst them 10x Genomics, the current leading commercial solution for high throughput single-cell RNA-seq analysis, makes this technology available to researchers in the academy, hospitals and industry. Yet, single cell analysis requires proper understanding of its capabilities and limitations.

The course will be composed of a comprehensive introduction to the field, a hands-on session, single cell data analysis, and a single cell genomics interpretation. You will be introduced to single-cell genomics technologies and learn conceptual tools for understanding and designing single-cell based experiments, with an emphasis on single cell gene expression profiling. This will include hands-on practice of the 10x Genomics technology and interpretation of the data generated. In addition, other single-cell genomics tools will also be covered, such as multiomics solutions, including analysis of surface protein expression and gene expression in the same single cell, chromatin accessibility at the single-cell level (single cell ATAC-seq), CRISPR-based gene perturbation with single-cell resolution and spatial transcriptomics analysis. Examples of applications of these technologies will be discussed in a seminar format.

Learning Outcomes

Upon successful completion of this course students should:

  1. Understand the concept of single-cell expression profiling
  2. Understand the unique features in single cell data analysis
  3. Get acquainted with the different single cell genomics platforms
  4. Understand the molecular processes and barcoding usage involved in single cell genomics experiments
  5. Get acquainted with analytical approaches for single cell analysis
  6. Design a single cell genomics based experiment relevant for his/her own project
  7. Interpret single cell data results in current publications

Reading List

  1. Jaitin DA, et al. Massively parallel single-cell RNA-seq for marker-free decomposition of tissues into cell types. Science 2014.PMID: 24531970 
  2. Keren-Shaul H, et al. MARS-seq2.0: an experimental and analytical pipeline for indexed sorting combined with single-cell RNA sequencing. Nature protocols 2019. PMID: 31101904
  3. Giladi et al. Single-Cell Genomics: A Stepping Stone for Future Immunology Discoveries. Cell 2018. PMID: 29328909
  4. Ziegenhain C. et al., Comparative Analysis of Single-Cell RNA Sequencing Methods. Molecular Cell 2017. PMID: 28212749
  5. Linnarsson  and Teichmann. Single-cell genomics: coming of age. Genome Biol. 2016. PMID: 27160975
  6. Luecken and Theis. Current best practices in single-cell RNA-seq analysis: a tutorial. Mol Syst Biol. 2019. PMID: 31217225
  7. https://www.10xgenomics.com/

 

Website

N/A