Using linkage analysis of large pedigrees to guide association analyses

Seung-Hoan Choi,Gyungah Jun,Chunyu Liu,Josée Dupuis,Mark W Logue

doi:10.1186/1753-6561-5-s9-s79

Seung-Hoan Choi, Gyungah Jun + Show 3 more

Open Access

https://doi.org/10.1186/1753-6561-5-s9-s79

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Abstract

To date, genome-wide association studies have yielded discoveries of common variants that partly explain familial aggregation of diseases and traits. Researchers are now turning their attention to less common variants because the price of sequencing has dropped drastically. However, because sequencing of the whole genome in large samples is costly, great care must be taken to prioritize which samples and which genomic regions are selected for sequencing. We are interested in identifying genomic regions for deep sequencing using large multiplex families collected as part of earlier linkage studies. We incorporate linkage analysis into our search for Q1-associated alleles. Overall, we found that power was low for both whole-exome and linkage-guided sequencing analysis. By restricting sequencing to regions with high LOD peaks, we found fewer associated single-nucleotide polymorphisms than by using whole-exome sequencing. However, incorporating linkage analysis enabled us to detect more than half of the associated susceptibility loci (52%) that would have been identified by whole-exome sequencing while examining only 2.5% of the exome. This result suggests that incorporating linkage results from large multiplex families might greatly increase the efficiency of sequencing to detect trait-associated alleles in complex disease.

Highlights

Linkage studies have fallen out of favor in recent years as genome-wide association has become the new paradigm for gene discovery
We explore the utility of linkage analysis of large pedigrees to prioritize certain genomic areas for sequencing
After correcting for the number of single-nucleotide polymorphism (SNP) tested in the genome-wide approach, we found that the power to detect both of these SNPs was greater than 99%

Summary

Introduction

Linkage studies have fallen out of favor in recent years as genome-wide association has become the new paradigm for gene discovery. Genome-wide association itself is perhaps reaching its limit, because the price of sequencing has decreased and is likely to drop much further. At this point, the cost of whole-genome sequencing is still high enough that great care must be taken to select which samples or genomic regions to sequence. We are interested in the potential of large multiplex families (with multiple affected individuals), obtained as part of linkage studies, to guide subsequent sequencing efforts. This analysis could be done either by identifying highly informative individuals to sequence, by directing the analysis to gain

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