Transcriptomics_Flashcards

Introduction to Transcriptomics

• Presenter: Dr Manuela Platé (Email: m.plate@ucl.ac.uk, UCL)

Objectives of the Lecture

• Understand what transcriptomics is and its applications.

• Learn the methodology behind bulk RNA-Seq.

• Review the main steps involved in bulk RNA-Seq analysis.

• Differentiate between bulk RNA-Seq, scRNA-Seq, and spatial transcriptomics.

• Explore the methodology of scRNA-Seq.

• Review the main steps in scRNA-Seq analysis.

• Understand the methodology of spatial transcriptomics.

• Review the main steps in spatial transcriptomics analysis.

• Learn about new transcriptomics techniques and their functions.

Understanding Transcriptomics

• Definition: The study of the transcriptome, which represents the complete set of RNA transcripts produced by a genome under specific conditions or in particular cells.

• Significance: Provides insights into gene expression patterns, regulatory mechanisms, and cellular responses to stimuli.

• Gene Expression:

  • Only 40-50% of all ~25,000 genes are expressed in a cell at one time.

  • Housekeeping genes: Approximately 8,000-10,000 are consistently expressed to maintain basic functions (e.g., metabolism).

  • Cell Type-Specific Expression: Different cell types express different subsets of genes based on their functions (e.g., neurons vs. muscle cells).

  • Tissue-Specific & Condition-Specific Genes: Certain genes are activated in specific tissues or under specific conditions, like stress or immune responses.

  • The same gene can have varying expression levels in different cell types or conditions.

When to Use Transcriptomic Techniques

• Requirements for transcriptomic studies:

  • Unbiased, genome-wide view of gene expression.

  • Simultaneous study of thousands of genes.

  • Exploration of novel transcripts, isoforms, or alternative splicing.

  • Investigation of unknown or poorly characterized genes.

  • Need for single-cell resolution.

Bulk RNA-Seq Overview

• Definition: A high-throughput sequencing technique measuring gene expression levels across populations of cells.

• Process: Captures mRNA from a mixture of cells to provide an average transcriptomic profile.

Bulk RNA-Seq - Library Preparation

1. Poly-A Selection

   • Purpose: Enrich for mRNA and remove non-relevant RNA types.

   • Method: Uses magnetic beads with oligo-dT to bind poly-A mRNAs while washing away rRNA and other types.

   • Limitations: Does not capture non-polyadenylated RNAs and may introduce bias toward highly polyadenylated transcripts.

   • Alternative: rRNA depletion.

2. Fragmentation

   • Purpose: Create short RNA fragments suitable for sequencing (100-300 bp).

   • Methods: Heat & magnesium ions, ultrasonication, nebulization or enzymatic fragmentation.

   • Note: Long-read sequencing typically avoids fragmentation.

3. Random Priming

   • Purpose: Generate complementary DNA (cDNA) from RNA.

   • Process: Reverse transcription using random hexamer primers to ensure unbiased representation of the transcriptome.

4. First and Second Strand cDNA Synthesis

   • Creation of RNA-DNA hybrid: Reverse transcriptase synthesizes first-strand cDNA from RNA template.

   • Optional RNA Removal: RNA strand may be removed before second-strand synthesis using RNase H.

   • Second Strand Creation: DNA Polymerase I extends second strand, completing cDNA synthesis.

5. End Repair and Phosphorylation

   • Purpose: Converts cDNA into blunt-ended molecules.

   • Processes: Fixes overhangs and nicks with T4 DNA polymerase and adds phosphate to 5′ end (T4 Polynucleotide Kinase).

6. A-Tailing

   • Purpose: Adds adenine nucleotide to the 3′ end of cDNA fragments for efficient adapter ligation.

   • Process: Taq DNA Polymerase or Klenow Fragment adds an adenine overhang.

7. Adapter Design & Preparation

   • Types of Adapters: Include single-end, paired-end, and Y-adapters.

   • Features: Sticky ends, index sequences for multiplexing, and platform-specific sequences.

8. Ligation of Adapters

   • Process: T4 DNA Ligase attaches adapters to cDNA fragments, forming phosphodiester bonds between cDNA and adapters.

Bulk RNA-Seq - Sequencing and Analysis

1. Sequencing Steps:

   • Input library into flow cell for in situ PCR and sequencing.

2. Analysis Workflow:

   • Quality control of raw Fastq files.

   • Trimming and quality screening using tools like FastQC and Trimmomatic.

   • Mapping to genome/transcriptome using splice-aware aligners (STAR, HISAT2).

   • Annotation of genes and functional analysis through databases (GO, KEGG).

   • Quantification of expression levels using tools like htseq-count and featureCounts.

   • Differential expression analysis using tools such as DESeq2 and edgeR.

3. Visual Representation:

   • Volcano Plots: Show differential expression between conditions.

   • Heatmaps: Visualize expression levels across samples.

   • Enrichment Analysis: Identifies biological pathways influenced by DEGs.

Comparison: Bulk RNA-Seq vs. scRNA-Seq vs. Spatial Transcriptomics

• Timeline of Development:

  • Bulk RNA-Seq (2006), scRNA-Seq (2012), Spatial Transcriptomics (2019).

• Methodologies:

  • Bulk RNA-Seq captures average expression from cell populations.

  • scRNA-Seq analyzes individual cell gene expression, revealing heterogeneity and subpopulations.

  • Spatial transcriptomics provides spatial context to gene expression by mapping transcripts to their original locations in tissues.

Conclusion

• Future Directions: Continuous advancements in transcriptomic technologies will enhance our understanding of cellular functionality and gene regulation in health and disease.

Advanced Transcriptomic Techniques

• RIP-Seq: Identifies RNA associated with RNA-binding proteins.

• PRO-Seq: Maps RNA polymerase location to understand transcription activity.

• ATAC-Seq: Identifies open chromatin regions to inform gene expression potential.

• Ribo-Seq: Determines mRNA translation activity by mapping ribosome-protected fragments.

• CAGE-Seq: Identifies transcription start sites to aid promoter annotation.

• CLIP-Seq: Maps RNA-protein interactions via crosslinking.

• SMART-Seq: Enhances scRNA-Seq sensitivity for full-length transcript sequencing.