Course Identification

Gene expression profiling: a practical course for RNA library preparation ready for sequencing
20253081

Lecturers and Teaching Assistants

Dr. Diego Jaitin, Dr. Hadas Keren-Shaul, Dr. Bareket Dassa, Dr. David Pilzer, Dr. Ronnie Blecher
N/A

Course Schedule and Location

2025
First Semester
17-21/11/24 (9:00-16:30) + 3/12 (10:00-12:00), FGS, Lab
17/11/2024
03/12/2024
26

Field of Study, Course Type and Credit Points

Life Sciences: Laboratory; Elective; 1.00 points

Comments

This course will be held in person only
17-21/11/24 (9:00-16:30)-FGS Lab + 3/12 Analysis (10:00-12:00)-FGS room B

Prerequisites

No

Restrictions

16

Language of Instruction

English

Registration by

04/11/2024

Attendance and participation

Obligatory

Grade Type

Numerical (out of 100)

Grade Breakdown (in %)

70%
30%

Evaluation Type

Examination

Scheduled date 1

09/12/2024
WSoS, Rm C
0915-1100
N/A

Scheduled date 2

N/A
N/A
-
N/A

Estimated Weekly Independent Workload (in hours)

3

Syllabus

Understanding biological systems using state-of-the-art genomics methods require, among other approaches, the gene expression profiling of different tissues, states, or conditions. RNA-seq is the method of choice to study gene expression with little background noise and a large dynamic range for detection of differentially expressed genes. This laboratory course will provide hands-on training on bulk MARS-seq, a method for digital gene expression analysis developed in Ido Amit lab at the Weizmann Institute. This protocol is designed for preparation of 3’ RNA sequencing libraries from low input RNA material in a simple, cost-effective fashion, due to early multiplexing of the samples. Libraries prepared in the course will be sequenced and analyzed. In order to enable fast and user-friendly data analysis, the LSCF Bioinformatics unit developed an intuitive and scalable transcriptome pipeline (UTAP) that executes the full process on Weizmann computer cluster (WEXAC), starting from sequences and ending with a comprehensive report. The sequenced data analysis part will be included in a session (2 hours) that will cover the theoretical basis for the analysis steps UTAP performs and a hands-on session to run the pipeline and understand the outputs it produces.

During the course, we will also present and discuss key aspects of genomics research, the power of unbiased gene expression profiling and Next Generation Sequencing (NGS), as well as quality control evaluation of input material, libraries and sequenced samples.

Learning Outcomes

Upon successful completion of this course students should be able to:

  1. Demonstrate an understanding of the notion of NGS technologies
  2. Demonstrate knowledge of RNA-seq technologies in general, including input requirements 
  3. Demonstrate an understanding of molecular biology processes in the process of RNA-seq library preparation
  4. Generate RNA-seq libraries from limiting amounts of RNA, ready to be sequenced in any available Illumina sequencer.
  5. Demonstrate familiarity with data resulting from Illumina platforms

 

Reading List

Recommended 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. PMID: 31101904

3. Wang Z. et al. RNA-Seq: a revolutionary tool for transcriptomics. Nat Rev Genet. 2009. PMID: 19015660

4. Geraci F. Editorial: RNA-Seq Analysis: Methods, Applications and Challenges. Front Genet. 2020 PMID: 32256522 

5. Stark R. RNA sequencing: the teenage years. Nat Rev Genet. 2019. PMID: 31341269

 

Website

N/A