This article is part of the supplement: Genetic Analysis Workshop 17: Unraveling Human Exome Data
Successful identification of rare variants using oligogenic segregation analysis as a prioritizing tool for whole-exome sequencing studies
1 Dalla Lana School of Public Health, University of Toronto, 155 College Street, Toronto, ON M5T 3M7, Canada
2 Hospital for Sick Children Research Institute, 555 University Avenue, Toronto, ON M5G 1X8, Canada
3 Ontario Institute for Cancer Research, 101 College Street, Suite 800, Toronto, ON M5G 0A3, Canada
BMC Proceedings 2011, 5(Suppl 9):S11 doi:10.1186/1753-6561-5-S9-S11Published: 29 November 2011
We aim to identify rare variants that have large effects on trait variance using a cost-efficient strategy. We use an oligogenic segregation analysis as a prioritizing tool for whole-exome sequencing studies to identify families more likely to harbor rare variants, by estimating the mean number of quantitative trait loci (QTLs) in each family. We hypothesize that families with additional QTLs, relative to the other families, are more likely to segregate functional rare variants. We test the association of rare variants with the traits only in regions where at least modest evidence of linkage with the trait is observed, thereby reducing the number of tests performed. We found that family 7 harbored an estimated two, one, and zero additional QTLs for traits Q1, Q2, and Q4, respectively. Two rare variants (C4S4935 and C6S2981) segregating in family 7 were associated with Q1 and explained a substantial proportion of the observed linkage signal. These rare variants have 31 and 22 carriers, respectively, in the 128-member family and entered through a single but different founder. For Q2, we found one rare variant unique to family 7 that showed small effect and weak evidence of association; this was a false positive. These results are a proof of principle that prioritizing the sequencing of carefully selected extended families is a simple and cost-efficient design strategy for sequencing studies aiming at identifying functional rare variants.