Whole Exome Sequencing

Whole Exome Sequencing (WES) analyses protein-coding regions, including exons and adjacent sequences required for correct transcript splicing.

Exons account for approximately 1-2% of the human genome but contain a substantial proportion of variants that directly affect protein structure and function. By targeting coding regions, WES achieves high coverage of the regions of interest with less sequencing data than Whole Genome Sequencing (WGS).

The method is used primarily to identify germline and somatic variants associated with inherited disorders, rare diseases, and cancer.

WES workflow

Applications of WES

Available WES service options

Available exome capture strategies:

• Agilent SureSelectXT Human All Exon V6 + UTR + mtDNA
• Agilent SureSelectXT Human All Exon V6 + UTR + mtDNA (with UMI)
• IDT xGen Exome Hyb Panel V2

- Standard workflow is primarily intended for identifying germline variants such as:

• SNVs, or single-nucleotide variants,
• small insertions and deletions (indels),
• variants affecting coding sequences or RNA splice sites.

- WES using UMIs. Unique Molecular Identifiers (UMIs) are short, unique sequences attached to DNA molecules during library preparation. They distinguish independent DNA molecules from copies generated by PCR amplification.

The use of UMIs enables:

• more accurate removal of PCR duplicates,
• reduction of technical artefacts,
• generation of consensus sequences,
• increased confidence in detecting variants with a low variant allele frequency,
• more accurate analysis of low-input DNA samples or samples requiring high sequencing depth.

Technical specifications of WES

Recommended capture-area coverage (output)

The required data yield depends on the project objective, sample quality, capture panel, and expected sensitivity of variant detection.

• approximately 5 Gb of data per sample: approximately 50× mean coverage,
• approximately 10 Gb of data per sample: approximately 100× mean coverage,
• minimum 12 Gb of data per sample: germline variant analysis requiring increased sequencing depth,
• minimum 15 Gb of data per sample: somatic variant analysis.

Exome coverage is not completely uniform. Some regions may be underrepresented because of high or low GC content, repetitive sequences, similarity to other genomic regions, or limited probe-hybridisation efficiency.

Data quality assessment therefore considers not only mean sequencing depth but also:

• the percentage of reads mapped to target regions (on-target reads),
• the proportion of regions covered at 10×, 20×, or higher,
• coverage uniformity,
• sequencing-depth distribution,
• duplicate rate,
• the number of regions with insufficient coverage.

Sample Requirements

WES bioinformatics analysis

Basic analysis

• post-sequencing data quality control,
• removal of adapters and reads that do not meet quality criteria,
• alignment of reads to the reference genome,
• assessment of target-region enrichment performance,
• analysis of mean coverage depth and coverage uniformity,
• assessment of coverage across individual exons and genes,
• SNV identification,
• identification of small insertions and deletions,
• variant filtering and annotation,
• prediction of variant effects on genes and encoded proteins,
• tabular summary of variants.

Germline Variant Analysis

In addition to the basic analysis, the workflow includes:

• filtering variants by allele frequency in population databases,
• analysis of the predicted effect of each variant on gene or protein function,
• summary of variants reported in clinical and scientific databases,
• analysis of genes associated with a defined phenotype,
• analysis of the inheritance model,
• comparison of variants among family members,
• identification of de novo variants,
• prioritisation of candidate variants.

Including phenotype, family history, and the predicted mode of inheritance can substantially improve the effectiveness of result interpretation.

Tumour Sample Analysis

For paired tumour-normal analysis, the workflow can include:

• identification and annotation of somatic variants,
• identification of germline variants,
• variant allele frequency (VAF) analysis,
• mutational spectrum analysis,
• mutational signature analysis,
• analysis of potential cancer driver genes,
• analysis of frequently mutated genes,
• biological pathway enrichment analysis,
• preparation of summaries and visualisations showing variant distribution.

To obtain pricing for the available services, we recommend completing the project specification form and/or reading the article on service pricing.