H. Bovenhuis

Behavior, type traits, and muscular development are of interest for beef cattle breeding. Genome-wide association studies (GWAS) enable the identification of candidate genes, which enables gene-based selection and provides insight in the genetic architecture of these traits. The objective of the current study was to perform a GWAS for 3 behavior traits, 12 type traits, and muscular development in Charolais cattle. Behavior traits, including aggressiveness at parturition, aggressiveness during gestation period, and maternal care, were scored by farmers. Type traits, including udder conformation, teat, feet and legs, and locomotion, were scored by trained classifiers. Data used in the GWAS consisted of 3,274 cows with phenotypic records and genotyping information for 44,930 SNP. When SNP had a false discovery rate (FDR) smaller than 0.05, they were referred to as significant. When SNP had a FDR between 0.05 and 0.20, they were referred to as suggestive. Four significant and 12 suggestive regions were detected for aggressiveness during gestation, maternal care, udder balance, teat thinness, teat length, foot angle, foot depth, and locomotion. These 4 significant and 12 suggestive regions were not supported by other significant SNP in close proximity. No SNP with major effects were detected for behavior and type traits, and SNP associations for these traits were spread across the genome, suggesting that behavior and type traits were influenced by many genes, each explaining a small part of genetic variance. The GWAS identified 1 region on chromosome 2 significantly associated with muscular development, which included the myostatin gene (GDF8), which is known to affect muscularity. No other regions associated with muscular development were found. Results showed that the myostatin region associated with muscular development had pleiotropic effects on udder volume, teat thinness, rear leg, and leg angle.

In a previous study, QTL for carcass composition and meat quality were identified in a commercial finisher cross. The main objective of the current study was to confirm and fine map the QTL on SSC4 and SSC11 by genotyping an increased number of individuals and markers and to analyze the data using a combined linkage and linkage disequilibrium analysis method. A modified version of the method excludes linkage disequilibrium information from the analysis, enabling the comparison of results based on linkage information only or results based on combined linkage and linkage disequilibrium information. Nine additional paternal half-sib families were genotyped for 18 markers, resulting in a total of 1,855 animals genotyped for 15 and 13 markers on SSC4 and SSC11, respectively. The QTL affecting meat color on SSC4 was confirmed, whereas the QTL affecting LM weight could not be confirmed. The combined linkage and linkage disequilibrium analysis resulted in the identification of new significant effects for 14 traits on the 2 chromosomes. Heritabilities of the QTL effects ranged from 1.8 to 13.2%. The analysis contributed to a more accurate positioning of QTL and further characterized their phenotypic effect. However, results showed that even greater marker densities are required to take full advantage of linkage disequilibrium information and to identify haplotypes associated with favorable QTL alleles. Copyright © 2007. . Copyright 2007 Journal of Animal Science

In the present study, a selection experiment for antibody (Ab) titer against SRBC in chickens was analyzed. Two lines were divergently selected for increased and decreased Ab titer. Further, a randombred control line, originating from the same base population, was included in the experiment. The heritability for immune response against SRBC was estimated after 18 generations of selection. In total, Ab titers obtained from 16,459 chickens were included in the analysis. Data was analyzed using an animal model. Posterior distributions for variance components and heritability were obtained using Markov Chain Monte Carlo methods. Response to selection was evaluated by constructing the posterior distribution for the genetic trend. In addition, a bivariate animal model was used in which male and female antibody titers were treated as different traits to estimate correlations between male and female immune response against SRBC. The heritability of Ab titer response, when using information from all three lines, was 0.18. The 90% highest posterior density region for the estimated heritability ranged from 0.16 to 0.19. In Generation 18, the genetic difference between the high and the low line was 5.1 phenotypic standard deviations. Analyses of each line separately revealed large differences in heritabilities between the lines, which could be mainly attributed to differences in error variances between the lines. The results suggest that selection for high Ab titers cause an increased environmental sensitivity. The estimated genetic correlation between male and female Ab titer was 0.92 and was not significantly different from 1.

The porcine genome was scanned to identify loci affecting coat color in an experimental cross between the Meishan breed and Dutch commercial lines. Linkage was studied in 1181 F₂ animals for 132 microsatellite markers and seven binary coat color scores: White, Black spotting, Speckle, Gray, Black, and specific color phenotypes for head and legs. The analyses were performed using interval mapping under various models. The study confirmed the existence of coat color loci on chromosome 8 and chromosome 6. One additional locus affecting White was detected on chromosome 5, possibly representing the porcine equivalent of the steel factor. Two new loci affecting Black were detected on chromosome 2. One of these showed exclusive maternal expression and mapped to a region where imprinted genes have been reported. The effect of the binary coding was tested by additional analyses excluding the white animals (>50% of F₂ animals). This showed that Black spotting was strongly influenced by the locus on chromosome 6 and the other color phenotypes were mainly influenced by the locus on chromosome 8. Epistatic effects were found between the loci on chromosomes 6 and 8 for Black spotting. For Black color, all combinations among chromosomes 2, 6, and 8 showed epistatic effects.

Detection of genes located on the Z-chromosome differs from the detection of genes located on autosomal chromosomes. In the present study, the chicken Z-chromosome is scanned for genes affecting growth traits and feathering. For this purpose, data from a three-generation full-sib-half-sib design was available: parents, full-sib offspring, and half-sib grandoffspring. The parents and full-sib offspring were genotyped for 17 markers on the Z-chromosome. Phenotypic data were only available for grandoffspring. Only the segregation of male chromosomes provides information on the presence of genes, and therefore, a half-sib interval mapping approach was used. The feathering gene was detected significantly and was located between markers ADL0022 and MCW0331. No significant indications were found for the presence of quantitative trait loci affecting growth traits on the Z-chromosome.

A whole-genome scan was conducted using 132 microsatellite markers to identify chromosomal regions that have an effect on teat number. For this purpose, an experimental cross between Chinese Meishan pigs and five commercial Dutch pig lines was used. Linkage analyses were performed using interval mapping by regression under line cross models including a test for imprinting effects. The whole-genome scan revealed highly significant evidence for three quantitative trait loci (QTL) affecting teat number, of which two were imprinted. Paternally expressed (i.e., maternally imprinted) QTL were found on chromosomes 2 and 12. A Mendelian expressed QTL was found on chromosome 10. The estimated additive effects showed that, for the QTL on chromosomes 10 and 12, the Meishan allele had a positive effect on teat number, but, for the QTL on chromosome 2, the Meishan allele had a negative effect on teat number. This study shows that imprinting may play an important role in the expression of teat number.

Selective genotyping (i.e., genotyping of individuals that are extreme for a quantitative trait) has been undertaken in many studies but has usually been limited to one trait of interest. This paper outlines the implications of selective genotyping when applied to a daughter design. Formulas are presented that enable unbiased estimation of QTL effects for the selectively genotyped and correlated traits. Formulas were verified using simulation. Further, formulas are presented to enable power calculations to be undertaken for the selectively genotyped trait and correlated traits. These algorithms are demonstrated with a numerical example.