An exploration of heterogeneity in genetic analysis of complex pedigrees: linkage and association using whole genome sequencing data in the MAP4 region.

Shelley B Bull,Kuan-Rui Tan,Julia Poirier,Zhijian Chen

doi:10.1186/1753-6561-8-s1-s107

Abstract

We conduct pedigree-based linkage and association analyses of simulated systolic blood pressure data in the nonascertained large Mexican American pedigrees provided by Genetic Analysis Workshop 18, focusing on observed sequence variants in MAP4 on chromosome 3. Because pedigrees are large and sequence data have been completed by imputation, it is feasible to conduct analysis for each pedigree separately as well as for all pedigrees combined. We are interested in quantifying and explaining between-pedigree heterogeneity in linkage and association signals. To this end, we first examine minor allele frequency differences between pedigrees. In some of the pedigrees, rare and low-frequency variants occur at a higher prevalence than in all pedigrees combined. In simulation replicate 1, we conduct variance-components linkage and association analysis of all 894 MAP4 variants to compare analytic approaches in single pedigree and combined analysis. In all 200 replicates, we similarly examine the 15 causal variants in MAP4 known under the generating model. We illustrate how random allele frequency variation among pedigrees leads to heterogeneity in pedigree-specific linkage and association signals.

Highlights

Whole genome sequencing holds out the promise of being able to more effectively map the effects of genetic variants on complex traits, and thereby identify the causal variants involved in disease expression [1]
Overall minor allele frequency (MAF) values for the 15 “causal” loci in MAP4 ranged from 0.5% to 37.8%: 3 common variants (>5% MAF) were observed in all 20 pedigrees, 3 low-frequency variants (1% to 5% MAF) appeared in 7 or more pedigrees, with 9 rare variants (
The combined pedigree maxLOD of 2.26 and minimum measured genotype (MG) asymptotic p value of 1.3 × 10−14 occurred at causal locus 10 corresponding to a low-frequency variant (3.2%) with a large effect size and the highest systolic blood pressure (SBP) %variance explained within MAP4

Summary

Introduction

Whole genome sequencing holds out the promise of being able to more effectively map the effects of genetic variants on complex traits, and thereby identify the causal variants involved in disease expression [1]. Pedigree heterogeneity could arise from variation in genetic effect size, in minor allele frequency, or from allelic or locus heterogeneity. Heterogeneity is largely caused by variation in minor allele frequencies between pedigrees, because the causal variants and their effect sizes were fixed under the generating model and applied to all individuals. We anticipated that analysis of the observed sequence data and the simulated systolic blood pressure (SBP) would allow us to describe natural genetic variation among the San Antonio Family Study (SAFS) pedigrees, as well as assess whether selection of pedigrees with linkage can enrich for rare variants and improve detection of variants in association analysis

Methods

Results

Conclusion