EPID 7310 Lecture 9

Developmental Milestones of a 3-Year-Old

  • Common Activities
    • Tend to get into trouble
    • Exhibit high energy and curiosity

Next-Generation Sequencing (NGS) Strategies

  • Applications

    • Used for quantitation and detection of small changes and variants
    • Excellent at identifying variants that traditional methods may miss

  • Limitations of NGS

    • No assay is perfect, all NGS methods can have errors and biases
    • The type of software used can skew data interpretation
    • Importance of acknowledging limitations in data handling

Experimental Design Considerations

  • Significance of Controls

    • Internal controls must demonstrate expected RNA presence/absence in specific cell types
    • Wet bench experiments needed for data validation

  • Formulation of Hypotheses

    • Focus on important problems with a clear hypothesis

  • Appropriate Model Systems

    • Ensure the model has relevant receptors (e.g., TNF receptors)

  • Replicates Required

    • Minimum of 3 biological replicates necessary for statistical analysis

Validation and Analysis of NGS Data

  • Bioinformatics Tools

    • Helpful websites and tools for troubleshooting and analysis
    • Important to ensure accurate data treatment and interpretation

  • Experimental Pipeline Overview

    • Primary data collection by sequencing centers leading to FASTQ files
    • Quality analysis, trimming, alignment, and mapping to genomes

Sequencing Techniques and Terminology

  • Types of Reads

    • Single-End Reads:
    • Sequence from one end of the DNA fragment
    • Paired-End Reads:
    • Sequence from both ends, allowing confirmation that reads are from the same DNA piece
    • Mate-Pair Reads:
    • Similar to paired-end, but with larger DNA fragments

  • Key Concepts

    • Depth Coverage:
    • Indicating the number of times a sequence is read (e.g., 5X, 10X)
    • Library Complexity:
    • Refers to the variety of sequences in a library, affecting sequencing outcomes

Structural Variants Detection via NGS

  • Detecting Variants

    • Deletion Example:

    • Mapped reads farther apart than the expected distance

    • Example, if reads 600 bp apart appear as 800 bp, indicates a deletion of 200 bp

    • Insertion Example:

    • Reads appearing closer than the expected distance, indicating additional material

  • Inversions and Translocations

    • Detect inversions by inappropriate read orientation
    • Translocations demonstrated by mapping different chromosomes in a single read

File Formats in NGS

  • FASTQ Files

    • Store raw sequence data with 4 lines per read:
    • Line 1: Sequence identifier
    • Line 2: Raw sequence of bases (A, C, T, G)
    • Line 3: + sign, may repeat identifier
    • Line 4: Quality score for bases

  • BAM and SAM Files

    • SAM files are text versions; BAM are binary (compressed) versions

Quality Control in NGS Data

  • Importance of Quality Control
    • Tools like FastQC assist in monitoring the quality of reads
    • High-quality data essential for reliable analysis
    • Potential filtering of low-quality reads to retain data integrity

Genome Sequencing and Annotation

  • Historical Overview

    • Human genome sequencing involved extensive international collaboration
    • Generated significant advancements in sequencing technologies

  • Concept of Contigs

    • Contigs represent continuous sequences constructed from overlapping DNA fragments

  • Marker Identification

    • Markers are genetic variations useful in distinguishing individuals
    • Used microsatellites for applications in forensics and genetic studies

  • Annotation Process

    • Requires identification of gene locations, exon boundaries, etc.

Limitations and Variability of Gene Identification

  • Challenges in Counting Genes

    • Estimating the number of genes remains complex due to difficulties in identifying non-coding regions and pseudogenes

  • Techniques for Gene Discovery

    • Approaches such as open reading frames and evolutionary conservation assessments to identify potential genes

Summary of DNA Variant Detection Methodologies

  • PCR, Sequencing, and Hybridization Techniques

    • Common methods for detecting genetic variations

  • Experimental Techniques Overview

    • Utilizes high-throughput methods for extensive gene expression analysis

Future Directions and Data Opportunities

  • Data Mining Potential
    • Opportunity for reanalysis of previously gathered data for new discoveries
  • Utilization of Homology Searches for Gene Function Prediction

Course Announcements

  • Exam Details

    • Online availability, format includes multiple choice and short answer questions

  • Next Class Preparation

    • Expect to dive deeper into the analysis of expression and genetic data

Study Recommendations

  • Be Familiar with Key Concepts
    • Especially NGS terminology, file formats, methods of gene detection, and sequencing principles.