Can whole-exome sequencing data be used for linkage analysis?

Area of Science:

• Genetics
• Genomic Medicine

Background:

• Whole-exome sequencing (WES) is crucial for identifying causal variants in monogenic disorders.
• WES data often yields extensive candidate variants, including sequencing errors (false positives).
• Reducing candidate variant lists is essential for efficient genetic diagnosis.

Purpose of the Study:

• To evaluate the efficacy of linkage analysis using common polymorphisms from WES data.
• To compare WES-derived linkage analysis with SNP chip data for variant filtering.
• To assess the cost-effectiveness of using WES data for linkage analysis in genetic studies.

Main Methods:

• Simulations were performed on two pedigrees with dominant and recessive traits.
• Linkage analysis was conducted using common single nucleotide polymorphisms (SNPs) extracted from WES data.
• Performance was compared between WES-derived SNPs and SNP chip data for excluding genomic regions.

Main Results:

• WES-derived SNPs and SNP chip data demonstrated similar performance in excluding genomic regions.
• No significant advantage was observed when using SNP chip data over WES-derived common SNPs.
• Linkage information from WES common polymorphisms halved the candidate variant list in real WES data analysis.

Conclusions:

• Linkage analysis using common polymorphisms from WES data is a powerful strategy.
• This approach effectively reduces the number of false-positive candidate variants.
• Integrating WES linkage analysis offers a cost-effective method for improving genetic diagnoses.