mmg2040 lecture 24 - rna sequencing

Explain the purpose of RNA-seq

RNA-sequencing: A method to sequence and quantify RNA molecules

• Provides a snapshot of the transcriptome (all RNA molecules in a cell at a given time including: m/r/tRNA and noncoding RNA)

• Dynamic —> changes conditions, cell types, diseases

• RNA shows active gene expression vs. DNA showing potential gene expression

• reveals functional output of genome, regulatory changes

Answers:

• Which genes are expressed?

• How much are they expressed?

• Are there alternative transcripts?

Outline the workflow for RNA-seq

1. RNA isolation - High-quality RNA is critical

• Avoid degradation (RNases!)

• Quality check: Integrity + Purity

2. mRNA enrichment - 2 methods

• Poly-A selection - Captures mRNA via poly-A tail

• rRNA depletion - Removes abundant rRNA

3. cDNA synthesis - fragment, reverse transcribe

• add adapters + bar codes

4. Library preparation - PCR amplification, Size selection

• Add sequencing adapters

5. Sequencing - typically short-read sequencing (e.g., Illumina)

• Generates millions of reads

• Each read corresponds to a fragment of RNA

6. Data analysis - Reads mapped to reference genome OR transcriptome

• Software determines where reads came from

Outline the workflow for scRNA-seq

Key Idea - Measures gene expression in individual cells, not bulk populations

• Bulk RNA-seq = average signal

• scRNA-seq reveals: Cell-to-cell variation, rare cell types, cell states (e.g., differentiation)

1. Isolate individual cells - capture RNA from each cell

• Microfluidic chip - traps one cell per capture site

• Cell lysis, reverse transcription, and amplification within its own chamber

1. Convert to cDNA - add cell-specific barcodes

2. Pool and sequence

3. Assign reads back to original cells

Critical Concept —> Each read includes:

• Gene information

• Cell barcode → tells you which cell it came from

Outline the workflow for Drop-seq

A version of single-cell RNA seq (scRNA-seq)

Core Idea - Encapsulate: 1 cell + 1 bead + reagents inside tiny oil droplets

• Inside Each Droplet, a bead carries: Unique barcode + Oligo-dT primers (bind mRNA)

Key Advantage: Thousands of cells processed simultaneously —> High-throughput scRNA-seq

Process:

• Cell lyses → mRNA binds bead

• cDNA made with barcode attached

• All droplets pooled → sequenced together

Distinguish RNA-seq from older methods (e.g., microarrays

RT-PCR: low througput

Microarrays: Requires known sequences

RNA-seq: Unbiased, genome-wide

Interpret basic RNA-seq outputs

basic RNA seq: Raw reads are converted into standardized units to compare gene expression across samples

• Quantifying Gene Expression - Count number of reads per gene

  • More reads = higher expression

  • Normalization needed: Gene length + sequencing depth

Drop seq: After obtaining sequencing reads consisting of cell barcode, UMI and cDNA

• First group reads by cell barcode before aligning cDNA reads

• counting unique molecules per cell per gene using the UMIs

• estimate the transcript abundances

Describe key applications in research and medicine

Strengths of RNA-seq: Unbiased, Genome-wide, Detects novel transcripts, High sensitivity

Strengths of scRNA-seq: Measures gene expression in individual cells, not bulk
populations —> Bulk RNA-seq = average signal

• reveals: Cell-to-cell variation, rare cell types, cell states (e.g., differentiation)

Strengths of drop-seq: Identifies rare cell types, Maps cell differentiation pathways, Reveals heterogeneity in tumors

sc/RNA seq limitations

limitations to rna seq:

• Expensive

• Requires bioinformatics

• Sensitive to RNA quality

• Snapshot in time

Limitations to scRNA seq:

• Lower RNA capture per cell

• More technical noise

• Complex data analysis