Rapid haplotype reconstruction in pedigrees with dense marker maps

Abstract

Summary Reconstruction of marker phases is not straightforward when parents are untyped. In these cases information from other relatives has to be used. In dense marker maps, however, the space of possible haplotype configurations tends to be too large for procedures such as Monte Carlo Markov chains (MCMC) to be finished within a reasonable time. We developed an algorithm that is fast and generally finds the most probable haplotype. The basic idea is to use, the smallest informative marker brackets in offspring, for each marker interval. By using only information from the offspring and analysing each marker interval separately, the lengthy analysis of large numbers of different haplotype configurations is avoided. Nevertheless the most probable haplotype can be found quickly provided the marker map is dense and enough offspring are available. Simulations are provided to indicate how well the algorithm works at different combinations of marker density, number of offspring and number of alleles per marker. In situations where the algorithm reconstruction of the most probable haplotype is not guaranteed, the algorithm may still provide a haplotype close to the optimum, i.e. a suitable starting point for numeric optimization algorithms.

Fine Mapping and Physical Characterization of Two Linked Quantitative Trait Loci Affecting Milk Fat Yield in Dairy Cattle on BTA26

“…Construction of maternally and paternally inherited marker haplotypes for each recorded individual (Windig and Meuwissen 2004). Computation of the matrix H p of identity-by-descent (IBD) probabilities among pairs of base haplotypes at each putative QTL position p (typically the midpoint of each marker bracket), as previously described (Meuwissen and Goddard 2001).…”

A Hidden Markov Model Combining Linkage and Linkage Disequilibrium Information for Haplotype Reconstruction and Quantitative Trait Locus Fine Mapping

“…In these studies, phasing has so far relied on familial information provided by the extended pedigrees typical of livestock (e.g., Windig and Meuwissen 2004). This approach, however, leaves a nonnegligible proportion of genotypes unphased, especially for the less connected individuals.…”

“…Present-day genotyping platforms do not directly provide information about linkage phase; i.e., co-inherited alleles at adjacent heterozygous markers (haplotypes) are not identified as such. As haplotype information may considerably empower genetic analyses, indirect phasing strategies have been devised: haplotypes can be reconstructed from unphased genotypes using either familial information (Mendelian segregation and linkage) and/ or population information (linkage disequilibrium, LD, and surrogate parents) (e.g., Windig and Meuwissen 2004;Scheet and Stephens 2006;Kong et al 2008).Haplotype-based approaches are routinely applied in animal genetics for combined linkage and LD mapping of QTL (e.g., Meuwissen and Goddard 2000;Blott et al 2003). In these studies, phasing has so far relied on familial information provided by the extended pedigrees typical of livestock (e.g., Windig and Meuwissen 2004).…”

“…Present-day genotyping platforms do not directly provide information about linkage phase; i.e., co-inherited alleles at adjacent heterozygous markers (haplotypes) are not identified as such. As haplotype information may considerably empower genetic analyses, indirect phasing strategies have been devised: haplotypes can be reconstructed from unphased genotypes using either familial information (Mendelian segregation and linkage) and/ or population information (linkage disequilibrium, LD, and surrogate parents) (e.g., Windig and Meuwissen 2004;Scheet and Stephens 2006;Kong et al 2008).…”

A Two-Stage Approximation for Analysis of Mixture Genetic Models in Large Pedigrees

“…Note that numerous other methods have been presented to estimate segregation probabilities in the literature (Wang et al 1995;Pong-Wong et al 2001;Totir et al 2003;Windig and Meuwissen 2004;Kong et al 2008) and these can be used in the first step of the two-step approach. These methods are approximations to the joint sampling of ordered genotypes and segregation indicators of all markers, but may be computationally more efficient than our Gibbs approach.…”