Course Identification

Gene expression profiling: a practical course for RNA library preparation ready for sequencing
20203192

Lecturers and Teaching Assistants

Dr. Diego Jaitin, Dr. Hadas Keren-Shaul, Dr. David Pilzer
Dr. Adam Yalin

Course Schedule and Location

2020
Second Semester
3-7/5/20: 9:00-16:30, FGS Lab, 24/5 - 14:00-16:00 & 27/5 - 11:00-13:00, rm B, FGS, Lab
03/05/2020
07/05/2020

Field of Study, Course Type and Credit Points

Life Sciences: Laboratory; Elective; Regular; 0.50 points
Life Sciences (Molecular and Cellular Neuroscience Track): Laboratory; Elective; Regular; 0.50 points
Life Sciences (Brain Sciences: Systems, Computational and Cognitive Neuroscience Track): Laboratory; Elective; Regular; 0.50 points
Life Sciences (Computational and Systems Biology Track): Laboratory; Elective; Regular; 0.50 points

Comments

Additional lectures, at FGS room B:
24/5 - 14:00-16:00
27/5 - 11:00-13:00

Prerequisites

No

Restrictions

16

Language of Instruction

English

Attendance and participation

Obligatory

Grade Type

Pass / Fail

Grade Breakdown (in %)

100%

Evaluation Type

Laboratory

Scheduled date 1

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.

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

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

Kukurba, KR and Montgomery, SB. RNA Sequencing and Analysis. Cold Spring Harb Protoc 2015. PMID: 25870306

Hrdlickova, R, Toloue M and Tian, B. RNA-seq methods for transcriptome analysis. Wiley Periodicals 2017. PMID: 27198714

Jaitin, DA, Kenigsberg, E, Keren-Shaul, H. et al. Massively parallel single-cell RNA-seq for marker-free decomposition of tissues into cell types. Science 2014. PMID: 24531970

 

 

Website

N/A