Monte Carlo methods for linkage analysis of two-locus disease models

MCMC-based linkage analysis for complex traits on general pedigrees: multipoint analysis with a two-locus model and a polygenic component

We describe a new program lm_twoqtl, part of the MORGAN package, for parametric linkage analysis with a quantitative trait locus (QTL) model having one or two QTLs and a polygenic component, which models additional familial correlation from other unlinked QTLs. The program has no restriction on number of markers or complexity of pedigrees, facilitating use of more complex models with general pedigrees. This is the first available program that can handle a model with both two QTLs and a polygenic component. Competing programs use only simpler models: one QTL, one QTL plus a polygenic component, or variance components (VC). Use of simple models when they are incorrect, as for complex traits that are influenced by multiple genes, can bias estimates of QTL location or reduce power to detect linkage. We compute the likelihood with Markov Chain Monte Carlo (MCMC) realization of segregation indicators at the hypothesized QTL locations conditional on marker data, summation over phased multilocus genotypes of founders, and peeling of the polygenic component. Simulated examples, with various sized pedigrees, show that two-QTL analysis correctly identifies the location of both QTLs, even when they are closely linked, whereas other analyses, including the VC approach, fail to identify the location of QTLs with modest contribution. Our examples illustrate the advantage of parametric linkage analysis with two QTLs, which provides higher power for linkage detection and better localization than use of simpler models.

TLINKAGE-IMPRINT: A Model-Based Approach to Performing Two-Locus Genetic Imprinting Analysis

OBJECTIVES

Imprinting refers to the expression of only one copy of a gene pair, which is determined by the parental origin of the copy. Imprinted genes play a role in the development of several complex diseases, including cancers and mental disorders. In certain situations, two-trait-loci models are shown to be more powerful than one-trait-locus models. However, no current methods use pedigree structure efficiently and perform two-locus imprinting analyses. In this paper, we apply the Elston-Stewart algorithm to the parametric two-trait-loci imprinting model used by Strauch et al. [2000] to obtain a method for qualitative trait linkage analyses that explicitly models imprinting and can be applied to large pedigrees.

METHODS

We considered a parametric approach based on 4 x 4 penetrance matrix to account for imprinting and modified TLINKAGE software to implement this approach. We performed simulation studies using a small and a large pedigree under dominant and imprinted and dominant or imprinted scenarios. Furthermore, we developed a likelihood ratio-based test for imprinting that compares the logarithm of odds (LOD) score obtained using the two-locus imprinting model with that obtained using the standard two-locus model that does not allow for imprinting.

RESULTS

In simulation studies of three scenarios where the true mode of inheritance included imprinting, accurate modeling through the proposed approach yielded higher LOD scores and better recombination fraction estimates than the traditional two-locus model that does not allow for imprinting.

CONCLUSIONS

This imprinting model will be useful in identifying the genes responsible for several complex disorders that are potentially caused by a combination of imprinted and non-imprinted genes.