EPID 7310 Lecture 8

Lecture Overview

  • Exam Reminder: First exam next Tuesday covering the material up to today's lecture.
    • Format: Online, available for 24 hours from midnight to midnight.
    • Once started, the exam cannot be paused or resumed later.
    • Instructions will include cell phone number for technical issues during the exam.
  • Exam Review: An overview of what to expect in the exam will be provided in the next class.

Next Generation Sequencing (NGS) Basics

  • Last Topic Recap: Strategies in Next-Generation Sequencing (NGS).
    • Recently discussed Illumina sequencing method.

Illumina Sequencing Strategy

  • Principle: Uses a chip to take simultaneous snapshots of reactions.
    • Dideoxy chain terminator strategy employed to stop DNA incorporation at specific points.
    • Process:
    • Different colored terminators are incorporated into the DNA strand.
    • The chain is terminated upon insertion of these labeled nucleotides.
    • Signal capture is done using laser excitation to identify the incorporated nucleotides.
  • Key Objective: Removal of the chain terminator is necessary for continued sequencing.
  • Challenges:
    • Multiple reactions lead to shorter sequence reads due to harsh conditions.
    • Defacing can occur, resulting in inconsistent signal reads from different reactions.
  • PCR Amplification: Important in NGS to amplify the number of sequences being analyzed.

Limitations and Considerations

  • Defacing: Occurs when reactions become unsynchronized.
    • Example: If one molecule gets a T signal and another an A signal due to defacing, it causes variability in data.
  • Error Rates:
    • Fundamental errors such as defacing and polymerase amplification can occur.
    • Important Point: No enzyme is perfect; mutations during early PCR impact all subsequent copies.

Next-Generation Sequencing Summary

  • Cost:
    • Approximately $3,000 to sequence a human genome, but costs can be divided among multiple samples pulled together.
    • More flexibility in handling samples (e.g., pooling 10 samples costs about $300 each).
  • De Novo Sequencing: Difficult due to small read lengths and repetitions.
  • RNA-seq vs. Microarrays: Next-generation sequencing outperforms microarray techniques for gene expression studies.

Third Generation Sequencing

  • Key Differences from Second Generation:
    • No PCR amplification step, reducing associated errors.
  • Common Technologies:
    • Pacific Biosciences (PacBio) and Oxford Nanopore.

Detailed Methodologies

Pacific Biosciences (PacBio)
  • Technology Overview: Utilizes a smart chip with a polymerase enzyme that incorporates nucleotides.
  • Duplex Sequencing: Sequences both strands to reduce error rates owing to repeated sequencing from both strands.
    • High error rate near 20%, but redundancy reduces false positives.
Oxford Nanopore Sequencing
  • Mechanism:
    • Incorporates DNA through a nanopore in a lipid bilayer, sensing individual nucleotides, including methylation detection.
    • Key advantage: Long read lengths without amplification, useful for complex genomic landscapes.

Application of Long Reads

  • Beneficial for:
    • De novo assembly.
    • Chromosome scaffolding (understanding DNA interactions and structure).
    • Structural variation analysis (e.g., cancer mosaicism).
    • Haplotype phasing for distinguishing sequences in homologous chromosomes.

Challenges and Innovations

  • Second vs. Third Generation: Chart comparing read lengths, error rates, and depth of coverage.
  • Applications:
    • Whole genome analysis, population evaluations, and more precise understanding of biological processes.

Exon Sequencing and RNA-seq

  • Exon Sequencing: Focuses on expressed regions of genes, minimizing irrelevant genomic elements.
  • RNA-seq: Comprehensive analysis of transcriptomics, superior to microarrays due to its depth of sequencing and discovery capabilities.

Metagenomics

  • Definition: Study of genetic material recovered directly from environmental samples.
  • Application: Allows analysis of mixed DNA samples without prior culture purification, useful for evaluating microbial community structures.

Data Interpretation Challenges

  • Big Data Issues:
    • Challenges in data storage and analysis, including the trend for raw sequencing data to be delivered on physical drives due to their sizes.
  • Software Tools: Importance of bioinformatics in fine-tuning sequencing data interpretation.

Sequence Analysis Pipeline

  • Description: Using image processing, data captured during sequencing is analyzed and aligned to reference genomes.
  • Significance of Coverage:
    • Importance of depth and coverage statistics for identifying true variants.
  • Software Challenges: Potential for discrepancies due to different alignment settings.

Quality Control in NGS Analysis

  • Coverage and Depth: Understanding average coverage across the genome is critical for interpreting sequencing reliability.
  • PCR Artifacts and Duplicates: Identifying and correcting these biases is essential in ensuring data integrity.

Conclusion on NGS and Future Directions

  • Emerging Challenges:
  • Validation of findings through alternative sequencing methods, continued development of software tools, and research in evolving sequencing strategies.
  • Next Steps: Encouragement to attend further lectures and apply learned concepts to upcoming exam preparation.