Strategies for haplotype-based association mapping in a complex pedigreed population

Abstract

AbStrAct:In association mapping, haplotype-based methods are generally regarded to provide higher power and increased precision than methods based on single markers. For haplotype-based association mapping most studies use a fixed haplotype effect in the model. However, an increase in haplotype length raises the number of parameters in the model, resulting in low accuracy of the estimates especially for the low-frequency haplotypes. Modeling of haplotype effects can be improved if they are assumed to be random effects, as only one parameter, i.e. haplotype variance, needs to be estimated compared to estimating the effects of all different haplotypes in a fixed haplotype model. Using simulated data, we investigated statistical models where haplotypes were fitted either as a fixed or random effect and we compared them for the power, precision, and type I error. We investigated five haplotype lengths of 2, 4, 6, 10 and 20. The simulated data resembled the Danish Holstein cattle pedigree representing a complex relationship structure and QTL effects of different sizes were simulated. We observed that the random haplotype models had high power and very low type I error rates (after the Bonferroni correction), while the fixed haplotype models had lower power and excessively high type I errors. Haplotype length of 4 to 6 gave the best results for random model in the present study. Though the present study was conducted on data structure more frequent in livestock, our findings on random vs. fixed haplotype effects in association mapping models are applicable to data from other species with a similar pedigree structure.

A 0.5-Mbp deletion on bovine chromosome 23 is a strong candidate for stillbirth in Nordic Red cattle

“…We used a LMM that included random polygenic effects and random effects of the haplotype, i.e. random haplotype model (RHM) following [ 28 ]. The RHM model was: where q h 1 j and q h 2 j are random effects of the two haplotypes (one each from the sire and dam) carried by the j th individual, assumed to be normally distributed as , where σ h 2 is the variance of haplotype effects.…”

Loci associated with adult stature also affect calf birth survival in cattle

“…Haplotypes were constructed for markers selected from LMM analyses using BEAGLE software [ 31 ]. We used a linear mixed effect model with random polygenic and haplotype effects following Boleckova et al [ 37 ] as follows: where, q h1j and q h2j are random effects of the two haplotypes carried by the j-th individual. Each haplotype effect is assumed independent and identically distributed (i.i.d), with a normal prior distribution , where is variance explained by the haplotype.…”

High-frequency marker haplotypes in the genomic selection of dairy cattle

“…They reported that a higher accuracy of prediction was achieved for the validation dataset using models with random haplotype effects. Boleckova et al ( 2012 ) drew a similar conclusion after having tested linear models with haplotypes as explanatory variables. A like tendency was described by Mucha and Wierzbicki ( 2012 ), who used simulated data in a haplotype-based breeding value prediction study.…”

“…A similar approach was used by Huang et al ( 2007 ), who used the limiting value of this criterion computed as 1/ n and 2/ n , where n is the population size. Also, Kolbehdari et al ( 2007 ) and Boleckova et al ( 2012 ) showed that predictions of breeding values using haplotypes with higher frequencies were more accurate than using haplotypes with lower frequencies. In the study by Hayes et al ( 2006 ), haplotypes with a frequency of less than 1% were eliminated.…”