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De novo Sequencing and Resequencing

Jun 14, 2024

De novo Sequencing and Resequencing

Introduction

  • De novo sequencing and assembly: Applied to organisms without a reference genome or with a poor-quality reference genome.
  • Resequencing: Performed when a reference genome is available. Sequencing reads are aligned back to the reference genome to determine their location.

Applications

  • De novo sequencing: Used for initial genome assembly for future resequencing projects.
  • Resequencing: Explores genetic variation in individuals, families, and populations, especially concerning human genetic diseases.

Sequencing Depth

  • Requirements: Determined by the variant type, disease model, and size of regions of interest.
  • Reveals: Single nucleotide polymorphisms (SNPs), small insertions/deletions (indels), structural variants, and copy number variations (CNVs).

Study Design

  • Varies: Depending on the biological hypothesis and sequencing strategy.
  • Whole-genome sequencing (WGS): High-depth WGS is the 'gold standard' for DNA resequencing, covers both coding and non-coding regions.
  • Whole-exome sequencing (WES): Focuses on SNVs and indels in protein-coding regions, less expensive but omits regulatory regions like promoters and enhancers.

Sequencing Strategies

  • High-depth WGS: Interrogates all variant types, considered the gold standard.
  • WES: More cost-effective, increases potential sample numbers but has limitations, such as missing regulatory regions.

Challenges in Sequencing

  • Historical focus: Early sequencing studies focused on SNVs and small indels.
  • Depth requirement: Higher depth (30x or more) often required for heterozygous SNV detection.
  • Sample preparation: Uniformity of depth affected by GC bias introduced during DNA amplification by PCR.

Technical Considerations

  • WES Coverage: Efficiency of capture probes can vary, influenced by GC content, can result in regions with little/no coverage.
  • PCR Amplification: Still used in WES, needs optimization to reduce GC bias.
  • Uniformity of Coverage: Can be influenced by repetitive/low-complexity sequences.

Detection of Variants

  • CNV Detection: Methods analyze depth of coverage to infer copy number changes.
  • WGS Specificity: Obtained with low average depth (0.1x), sensitivity improved with higher read depth.
  • False Positives: Depth-of-coverage methods prone to local variations.

Population Genomics

  • Trade-off: Sample numbers vs. sequencing depth. Low depth across many genomes enables joint variant calling.
  • Common Variants: Low-depth sequencing captures common variation effectively.
  • Tumor Studies: Require higher depth of coverage due to heterogeneity of cell populations.

Genetic Disease Studies

  • Parent-Child Trios: Best for identifying de novo or recessive variants, requires balanced sequencing depth across family members to minimize false calls.