Whole Exome Sequencing

Whole exome sequencing (WES) is a next-generation sequencing (NGS) application which generates genomic information for all protein coding genes across the human genome. Although targeted sequencing of a preselected gene set is an important aspect of current testing strategy WES provides an unbiased view of the exome.1 This comprehensive genomic analysis is considered the consensus gold standard approach for the detection of somatic variants required for emerging applications such as tumor mutation burden and neo-antigen discovery.2-5

Whole Exome Sequencing Highlights

Efficient Genomic Screening – Targeted, deep sequencing of protein-coding regions and UTRs to uncover low frequency SNPs and structural variants.
Increased Sequencing Efficiency – Focus on the full throughput of NGS on the regions that contain ~85% of the known disease-causing mutations6
Multiple Capture Technologies – Customized assistance in helping you select the most efficient exome capture technology


Sample Type/Minimum Requirements:

  • FFPE ≥ 10 unstained slides
  • Cell culture, 106 cells
  • Frozen section, 5-10 mg
  • DNA, 200 ng – 1 µg
  • TAT: 2-4 weeks


Sample Prep and Exome Capture Technologies:

  • Agilent SureSelect® v5
  • Agilent Haloplex
  • Roche NimbleGen v3.0
  • Illumina TruSeq
  • Life Technology Ion AmpliSeq™


Deliverables:

  • Mapping and variant analysis
  • SNP report, annotated to include SNP statistics
  • Structural analysis, including large deletions and translocations
  • Comparisons between tumor and matched normal samples
  • Variant discovery, including SNPs found in major databases (COSMIC, dbSNP, etc.)


QC and Bioinformatics:

  • Basic statistics data - Read length, data output, GC content, read counts
  • Quality scores


Reference:

  1. Damodaran S, Berger M, Roychowdhury S: Clinical Tumor Sequencing: Opportunities and Challenges for Precision Cancer Medicine. Am Soc Clin Oncol Educ Book. 2015; e175–e182.

  2. Vilimas T: Measuring Tumor Mutational Burden Using Whole-Exome Sequencing. Methods Mol Bio 2020; 2055:63-91

  3. Wu HX, Wang ZX, Zhao Q, et al: Designing gene panels for tumor mutational burden estimation: the need to shift from ‘correlation’ to ‘accuracy’. Journal for ImmunoTherapy of Cancer. 2019; 7, Article number: 206

  4. Fancello L, Gandini S, Pelicci PG, et al: Tumor mutational burden quantification from targeted gene panels: major advancements and challenges. Journal for ImmunoTherapy for Cancer. 2019; 7, Article number: 183

  5. Kvistborg P, Clynes R, Song W, et al: Immune monitoring technology primer: whole exome sequencing for neoantigen discovery and precision oncology Journal for ImmunoTherapy for Cancer. 2016; 4, Article number: 22

  6. Choi et al. (2009) PNAS 106: 19096-1910

Exome Certified
Illumina
Agilent