A high proportion of purebred Hampshire pigs carries the dominant RN- mutation, which causes high glycogen content in skeletal muscle. The mutation has beneficial effects on meat content but detrimental effects on processing yield. Here, it is shown that the mutation is a nonconservative substitution (R200Q) in the PRKAG3 gene, which encodes a muscle-specific isoform of the regulatory gamma subunit of adenosine monophosphate-activated protein kinase (AMPK). Loss-of-function mutations in the homologous gene in yeast (SNF4) cause defects in glucose metabolism, including glycogen storage. Further analysis of the PRKAG3 signaling pathway may provide insights into muscle physiology as well as the pathogenesis of noninsulin-dependent diabetes mellitus in humans, a metabolic disorder associated with impaired glycogen synthesis.

A whole-genome scan to detect quantitative trait loci (QTL) for functional traits was performed in the German Holstein cattle population. For this purpose, 263 genetic markers across all autosomes and the pseudoautosomal region of the sex chromosomes were genotyped in 16 granddaughter-design families with 872 sons. The traits investigated were deregressed breedingvalues for maternal and direct effects on dystocia (DYSm, DYSd) and stillbirth (STIm, STId) as well as maternal and paternal effects on nonreturn rates of 90 d (NR90m, NR90p). Furthermore, deregressed breeding values for functional herd life (FHL) and daughter yield deviation for somatic cell count (SCC) were investigated. Weighted multimarker regression analyses across families and permutation tests were applied for the detection of QTL and the calculation of statistical significance. A ten percent genomewise significant QTL was localized for DYSm on chromosome 8 and for SCC on chromosome 18. A further 24 putative QTL exceeding the 5% chromosomewise threshold were detected. On chromosomes 7, 8, 10, 18, and X/Yps, coincidence of QTL for several traits was observed. Our results suggest that loci with influence on udder health may also contribute to genetic variance of longevity. Prior to implementation of these QTL in marker assisted selection programs for functional traits, information about direct and correlated effects of these QTL as well as fine mapping of their chromosomal positions is required.

Risk factors and variance components of pre-weaning mortality were estimated using generalized linear mixed models. Data were from 12 727 piglets born alive from 1338 litters recorded at the pig breeding farm of the University of Kiel from 1989 to 1994. Deviances due to risk factors were estimated by generalized linear model and their odds-ratios by generalized linear mixed model both with binomial errors and a logistic link. Variance components of sire, dam and litter were estimated using a logit or probit link function as well as a linear model for which estimates were transformed to the underlying continuous scale. Highest increase in deviance, indicating the risk factor, which accounts for the greatest amount of unexplained variation of pre-weaning mortality was obtained after exclusion of individual birth weight (1206) from the model, followed by year-season (217), parity-farrowing age or interval (58), genotype of piglets (56), sex (39), total number of piglets born (18) and gestation length (16). Substitution of individual birth weight successively by average piglet birth weight per litter, litter birth weight and standard deviation of birth weight within litter resulted in models with substantially lower explained variation of pre-weaning mortality. Odds of pre-weaning mortality was 1·5 times higher for males than for females and 2·0 times higher in piglets from German Landrace dams than from Large White dams. Odds increased to the fifth parity by 2·2 times the odds of the first parity or increased for the age group of dams between 850 and 949 days by 2·3 times the odds of the age group with less than 350 days. When the continuous risk factors of individual birth weight, average piglet birth weight and litter birth weight decreased or standard deviation of birth weight within litter increased by one standard deviation from the mean, the odds ratios increased by 6·0, 1·6, 0·8 and 0·4, respectively. Piglets with individual birth weights of 1·8, 1·5, 1·2 and 1·0 kg showed a rapid increase in odds ratios of pre-weaning mortality of 1·4, 2·7, 7·0 and 16·1, respectively, relative to piglets with 2·1 kg. Estimates of direct heritability for pre-weaning mortality on the linear observed, transformed underlying, logit and probit scale were 0·02, 0·06, 0·07 and 0·07, respectively. Low estimates of heritability for pre-weaning mortality, even on the underlying continuous scale, suggested low potential for improvement by selection. Therefore, selection for individual birth weight phenotypically closely associated with pre-weaning mortality was recommended to improve survival of piglets during the nursing period.

At the dairy research farm Karkendamm, the individual roughage intake was measured since 1 September 2005 using a computerised scale system to estimate daily energy balances as the difference between energy intake and calculated energy requirements for lactation and maintenance. Data of 289 heifers with observations between the 11th and 180th day of lactation over a period of 487 days were analysed. Average energy-corrected milk yield, feed intake, live weight and energy balance were 31.8 kg, 20.6 kg, 584 kg and 13.6 MJ NEL (net energy lactation), respectively, per day. Fixed and random regression models were used to estimate repeatabilities, correlations between cow effects and genetic parameters. The resulting genetic correlations in different lactation stages demonstrate that feed intake and energy balance at the beginning and the middle of lactation are genetically different traits. Heritability of feed intake is low with h 2 50.06 during the first days after parturition and increases in the middle of lactation, whereas the energy balance shows the highest heritability with h 2 50.34 in the first 30 days of lactation. Genetic correlations between energy balance and feed intake and milk yield, respectively, illustrate that energy balance depends more on feed intake than on milk yield. Genetic correlation between body condition score and energy balance decreases rapidly within the first 100 days of lactation. Hence, to avoid negative effects on health and reproduction as consequences of strong energy deficits at the beginning of lactation, the energy balance itself should be measured and used as a selection criterion in this lactation stage. Since the number of animals is rather small for a genetic analysis, the genetic parameters have to be evaluated on a more comprehensive dataset.

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