Academic journal article Genetics

Identity-by-Descent Estimation and Mapping of Qualitative Traits in Large, Complex Pedigrees

Academic journal article Genetics

Identity-by-Descent Estimation and Mapping of Qualitative Traits in Large, Complex Pedigrees

Article excerpt

ABSTRACT

Computing identity-by-descent sharing between individuals connected through a large, complex pedigree is a computationally demanding task that often cannot be done using exact methods. What I present here is a rapid computational method for estimating, in large complex pedigrees, the probability that pairs of alleles are IBD given the single-point genotype data at that marker for all individuals. The method can be used on pedigrees of essentially arbitrary size and complexity without the need to divide the individuals into separate subpedigrees. I apply the method to do qualitative trait linkage mapping using the nonparametric sharing statistic S^sub pairs^. The validity of the method is demonstrated via simulation studies on a 13-generation 3028-person pedigree with 700 genotyped individuals. An analysis of an asthma data set of individuals in this pedigree finds four loci with P-values <10^sup -3^ that were not detected in prior analyses. The mapping method is fast and can complete analyses of ~150 affected individuals within this pedigree for thousands of markers in a matter of hours.

(ProQuest: ... denotes formulae omitted.)

COMPUTATION of identical-by-descent (IBD) allele sharing between related individuals is a necessary ingredient in many methods for linkage mapping of complex traits. Typically, IBD allele sharing is used either directly to assess whether affected individuals are sharing more at a locus than expected under the null hypothesis or as a component in the covariance matrix in a variance component model. A number of algorithms for computing IBD exactly exist (e.g., Elston and Stewart 1971; Lander and Green 1987; Kruglyak et al. 1996; Fishelson and Geiger 2002); however, these methods become computationally infeasible when pedigrees are very large and complex. Under such circumstances approximate methods become necessary, whether Markov chain Monte Carlo (Thompson et al. 1993; Sobel and Lange 1996; Heath 1997) or regression based (Fulker et al. 1995; Almasy and Blangero 1998). Even these methods, however, have difficulty when the pedigree is very deep with many generations of individuals with no data.

In humans, very deep, and possibly complex, pedigrees often arise in conjunction with genetic studies of isolated populations. Isolated populations are commonly thought to have characteristics that may prove advantageous formapping(Wright et al. 1999; Peltonen et al. 2000; Escamilla 2001; Shifman and Darvasi 2001; Service et al. 2006), yet may require specialized statistical methods to both properly leverage these advantages and provide a valid test for the presence of a traitinfluencing gene (Bourgain and Genin 2005). Large pedigrees also arise in other animal systems where breeding is carefully controlled. For example, there is interest in methods that are applicable to complex pedigrees for both livestock (Thallmanet al. 2001) and dogs (Sutter and Ostrander 2004).

What I present here is a rapid computational method for estimating, in large complex pedigrees, the probability that pairs of alleles are IBD given the single-point genotype data at that marker for all individuals. Because the method is very fast, it can easily be used on genomewide data with many thousands of markers on hundreds of related individuals. It can be used directly to do linkage mapping with affected individuals using the S^sub pairs^ statistic or to compute approximate multipoint probabilities both for alleles being IBD, using regression-based approaches (e.g., Almasy and Blangero 1998), and for alleles being homozygous by descent (HBD) using a hidden Markov model (HMM) (Abney et al. 2002). Here, I describe this computational method and its application to qualitative trait linkage analysis. Although computing S^sub pairs^ is straightforward, in principle, a number of challenges must be overcome in creating a practical and valid mapping method for very large, and possibly complex, pedigrees. …

Search by... Author
Show... All Results Primary Sources Peer-reviewed

Oops!

An unknown error has occurred. Please click the button below to reload the page. If the problem persists, please try again in a little while.