Whole Exome Sequencing for Population Genetics

Unlock the mysteries of the genome and reveal the unique genetic differences within populations! CD Genomics offers Whole Exome Sequencing (WES) services, combined with precise bioinformatics analysis, providing in-depth genetic information to support breakthroughs in population genetics research.

Overview

CD Genomics provides advanced Whole Exome Sequencing (WES) to identify genetic variations linked to diseases. Our services focus on the exonic regions, crucial for protein encoding and disease-related mutations. Utilizing state-of-the-art sequencing platforms and expert bioinformatics analysis, we deliver high-quality, cost-effective results tailored to your research needs, whether in disease studies, population genetics, or evolutionary research.

What is Whole Exome Sequencing

WES focuses on sequencing the exonic regions of the genome, which are the parts of genes responsible for encoding proteins. Although exons only make up about 1-2% of the entire genome, they contain approximately 85% of known genetic mutations related to diseases. WES is a cost-effective and efficient alternative to Whole Genome Sequencing (WGS), particularly useful for studying common and rare genetic variations associated with diseases, population genetics, and evolutionary research. It uses high-throughput sequencing technology to capture and enrich the exonic regions, making it a powerful tool for identifying genetic mutations linked to protein function and disease mechanisms.

Diagram of a whole genome sequence pipeline. (Akoniyon, et al. 2022)

Sequencing Platforms

NextSeq 500

Illumina NovaSeq

PacBio Sequel II

Workflow of WGS in Population Genetics

Our WGS service workflow includes sample collection, library preparation, high-throughput sequencing, quality control, and detailed variant analysis to uncover genetic variations and population insights. Customers are encouraged to ensure proper sample handling and share specific research goals for tailored analysis. For any questions about sample requirements, sequencing, or data interpretation, our team is always ready to assist.

Workflow of WGS in Population Genetics

Bioinformatics content

Basic Analysis	Advanced analysis
Data Quality Control: Removes contaminants and low-quality sequences. Sequence Alignment: Maps reads, analyzes depth, coverage. Sex Validation: Confirms sample sex using genetic data. Priority Annotation: Labeling SNPs, InDels, and CNVs of interest	Dominant/Recessive Inheritance Pattern Analysis De Novo Mutation Screening De Novo SNP/InDel Screening SNPs/InDels Family Linkage Analysis

Demo Results

Shared SNP number between samples

SNP mutation type distribution.

Statistics pie of InDel annotations.

Why CD Genomics

Cutting-edge Sequencing Platforms: Utilize advanced high-throughput sequencing platforms and standardized laboratory workflows for consistent results.
High-throughput, High-quality Sequencing: Deliver reliable sequencing data with short turnaround times, high efficiency, cost-effectiveness, and exceptional quality.
Standardized Analysis Workflow: Leverage a professional bioinformatics team and comprehensive service framework for standard, advanced, and customized data analysis solutions.
Extensive Experience in Exome Sequencing: Skilled sequencing experts assist in experimental design, troubleshoot challenges, and provide in-depth result interpretation.
Customized Exome Sequencing Solutions: Tailor sequencing strategies to meet specific project requirements, ensuring personalized solutions for diverse research needs.

Case Study

Whole-exome sequencing of individuals from an isolated population implicates rare risk variants in bipolar disorder

Journal:Transl Psychiatry

Published:2017

Background
Results

Bipolar disorder affects approximately 1% of the population, with an estimated heritability of 75%. However, there have been few studies identifying rare coding variants, and none have robustly linked such variants to the disorder. This study aimed to identify rare risk variants by performing whole-exome sequencing on 28 bipolar disorder cases and 214 controls from the isolated population of the Faroe Islands, followed by replication in a British sample. The Faroe Islands, with its isolated population, offers a unique environment where rare variants may occur at higher frequencies due to genetic drift, making it ideal for identifying new risk variants. The study identified 17 significant variants in single-variant analysis, and further validation through protein–protein interaction network analysis and GWAS data confirmed the association of genes with bipolar disorder, providing new insights into its underlying biology.

Whole exome sequencing of 28 bipolar disorder cases and 214 controls identified 259,904 variants, including 47,800 novel variants. The study focused on rare risk variants with frequencies <0.05 in 1000 Genomes and found 86,563 variants suitable for analysis. After Bonferroni correction, 17 variants in 16 genes surpassed exome-wide significance, suggesting potential genetic associations with bipolar disorder.

The figures report the Manhattan plots of the single-variant analysis with q.emmax . (Lescai, et al. 2017)

Gene-wise analysis of rare variants identified 419 nominally significant genes (P < 0.01), with three genes showing exome-wide significance after Bonferroni correction. In replication, only the NCL gene was fully represented in the British sample, where it showed a significant association (P = 0.029). A DAPPLE analysis of the nominally significant genes supported 16 genes with protein–protein connectivity, with NCL being the most significant (P = 0.002). This further validates the association of NCL with bipolar disorder and suggests additional genes within its interaction network may also be involved in disease susceptibility.

The plot shows the connections resulting from a DAPPLE analysis The most significant connections resulting from a DAPPLE analysis. (Lescai, et al. 2017)

FAQs

What is exome capture efficiency?

Exome capture efficiency refers to the proportion of sequencing data that corresponds to exonic regions during whole exome sequencing. In this process, hybridization is used, but some non-exonic homologous regions on the human chromosomes may also be captured, leading to the inclusion of non-exonic sequences in the final data. The ratio of sequences that correspond to exonic regions to the total sequencing data is referred to as capture efficiency.

How efficient is exome capture sequencing?

With an average sequencing depth greater than 30X, exome sequencing typically covers at least 90% of the target regions captured by the hybridization chip, identifying 99% of the SNPs (single nucleotide polymorphisms) within these regions. For more accurate results, especially in tumor or clinical applications, we recommend sequencing at a depth greater than 100X.

What is the recommended sequencing depth for whole exome sequencing?

The sequencing depth depends on the research objectives and sample size. Generally, we recommend a minimum effective sequencing depth of 100X. Literature has shown that sequencing depth impacts variant detection rates, with detection rates increasing as depth rises. At a depth of 100X, variant detection reaches a stable and optimal level, with reliable SNP detection and 20X coverage, providing the most effective and significant results for variant discovery.

References

Akoniyon, O. P., Adewumi, T. S., et al. (2022). Whole Genome Sequencing Contributions and Challenges in Disease Reduction Focused on Malaria. Biology, 11(4), 587. https://doi.org/10.3390/biology11040587
Lescai, F., Als, T. D., et al. (2017). Whole-exome sequencing of individuals from an isolated population implicates rare risk variants in bipolar disorder. Translational psychiatry, 7(2), e1034. https://doi.org/10.1038/tp.2017.3

* Designed for biological research and industrial applications, not intended for individual clinical or medical purposes.