6.1 Background: Single-cell RNA sequencing

6.1.1 Purpose

The purpose of this lab is to introduce single-cell RNA sequencing, how it works, and how it is different from bulk RNA sequencing.

6.1.2 Learning Objectives

  1. Compare and contrast single-cell and bulk RNA-seq
  2. Explain what a UMAP plot is and why it is useful for single-cell RNA-seq

6.1.3 Introduction

While bulk RNA sequencing allows us to examine gene expression in a tissue as a whole, newer technologies enable us to look at gene expression in individual cells, opening up new avenues for scientific research. This tutorial will explain the basics of single-cell RNA sequencing and discuss how it compares to bulk RNA-seq. It will also introduce you to UMAP plots - a common method for exploring single-cell sequencing data.

6.1.4 Activity 1 - Biotechnology: scRNA-seq

Estimated time: 15 min

6.1.4.1 Instructions

  1. Watch this video (video)(slides) introducing single-cell RNA-seq.

6.1.4.2 Questions

Which of the following steps are typically involved in bulk vs. single-cell RNA-sequencing?

  • A) Obtain/dissect sample
  • B) Separate cells
  • C) Select for mRNA
  • D) Convert to cDNA

List the steps involved in each technique.

Bulk RNA-seq
Single-cell RNA-seq


Which of the following scientific questions can be investigated using bulk vs. single-cell RNA-sequencing?

  • Compare gene expression between healthy and diseased samples
  • Investigate gene expression changes as an embryo develops
  • Compare gene expression between different cells within a tissue

For each scientific question, state whether it can be investigated with bulk, single-cell, or both, and briefly explain your answer.

Healthy vs. diseased
Embryo development
Compare cells

6.1.5 Activity 2 - Introduction to UMAP plots

Estimated time: 10 min

6.1.5.1 Instructions

  1. Watch this video (video)(slides), which explains what a UMAP plot is and why it’s useful for single-cell RNA-seq.

6.1.5.2 Questions

Explain why UMAP plots are useful for looking at single-cell RNA-seq data

6.1.6 Footnotes

6.1.6.1 Resources

6.1.6.2 Contributions and Affiliations

  • Katherine Cox, Ph.D., Johns Hopkins University
  • Javier Carpinteyro-Ponce Ph.D., Carnegie Institution for Science
  • Matthew McCoy, Ph.D., Stanford University
  • Frederick Tan, Ph.D., Carnegie Institution for Science

Last Revised: October 2023