Prediction of haplotypes for ungenotyped animals and its effect on marker-assisted breeding value estimation

Abstract

Background: In livestock populations, missing genotypes on a large proportion of animals are a major problem to implement the estimation of marker-assisted breeding values using haplotypes. The objective of this article is to develop a method to predict haplotypes of animals that are not genotyped using mixed model equations and to investigate the effect of using these predicted haplotypes on the accuracy of marker-assisted breeding value estimation.

Methods: For genotyped animals, haplotypes were determined and for each animal the number of haplotype copies (nhc) was counted, i.e. 0, 1 or 2 copies. In a mixed model framework, nhc for each haplotype were predicted for ungenotyped animals as well as for genotyped animals using the additive genetic relationship matrix. The heritability of nhc was assumed to be 0.99, allowing for minor genotyping and haplotyping errors. The predicted nhc were subsequently used in marker-assisted breeding value estimation by applying random regression on these covariables. To evaluate the method, a population was simulated with one additive QTL and an additive polygenic genetic effect. The QTL was located in the middle of a haplotype based on SNP-markers.

Results: The accuracy of predicted haplotype copies for ungenotyped animals ranged between 0.59 and 0.64 depending on haplotype length. Because powerful BLUP-software was used, the method was computationally very efficient. The accuracy of total EBV increased for genotyped animals when marker-assisted breeding value estimation was compared with conventional breeding value estimation, but for ungenotyped animals the increase was marginal unless the heritability was smaller than 0.1. Haplotypes based on four markers yielded the highest accuracies and when only the nearest left marker was used, it yielded the lowest accuracy. The accuracy increased with increasing marker density. Accuracy of the total EBV approached that of gene-assisted BLUP when 4-marker haplotypes were used with a distance of 0.1 cM between the markers.

Conclusions: The proposed method is computationally very efficient and suitable for marker-assisted breeding value estimation in large livestock populations including effects of a number of known QTL. Marker-assisted breeding value estimation using predicted haplotypes increases accuracy especially for traits with low heritability.

Figure 1

Mean proportion of QTL-variance explained by haplotypes as a function of distance between SNP-markers. Mean proportion of QTL-variance explained by neighboring marker (NM), 2-marker haplotype (HAP2) and 4-marker haplotype (HAP4); average of 200 replicates.

Figure 2

Frequency distribution of QTL-variance explained by haplotypes. Proportion of replicates per 0.1-bin class of proportion of QTL variance (r²) explained by neighboring marker (NM), 2-marker haplotype (HAP2) and 4-marker haplotype (HAP4); average of 200 replicates; sires and males in last generation are genotyped; distance between markers is 0.1 cM.

Figure 3

Accuracy of QTL-EBV and total EBV as a function of marker distance for genotyped males and ungenotyped females. Accuracy of QTL-EBV and total EBV for marker-assisted BLUP with neighboring marker (NM), 2-marker haplotype (HAP2) and 4-marker haplotype (HAP4), gene-assisted BLUP (GABLUP) when all animals are genotyped and conventional BLUP (CONBLUP); panels A and B: accuracy of QTL-EBV; panels C and D accuracy of total EBV; for MABLUP, sires and males in the last generation were genotyped, the rest was not genotyped, heritability is 0.30, the QTL explains 15% of the genetic variance, results are averages of 200 replicates.

Figure 4

Frequency distribution of accuracy of QTL-EBV of genotyped animals. Proportion of replicates per 0.1-bin-class for accuracy of QTL-EBV of genotyped animals for neighboring marker (NM), 2-marker haplotype (HAP2) and 4-marker haplotype (HAP4); sires and males in last generation are genotyped, distance between markers is 0.1 cM, heritability is 0.3, the QTL explains 15% of the genetic variance, average of 200 replicates.