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Most quantitative trait loci (QTL) studies have focussed on the identification of individual QTL effects (additive, dominance and imprinting) in the absence of interactions (epistasis). There are numerous reports in the literature for QTL associated with growth and body composition of pigs, however much less effort has focussed around the identification of epistatic QTL for these traits. Growth and body composition of pigs are probably influenced by numerous QTL located throughout the genome as well as interactions between QTL. Therefore the objective of this study was to investigate the contribution of epistasis to the genomic regulation of growth and body composition of pigs.
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 31.8kg, 20.6kg, 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 h2=0.06 during the first days after parturition and increases in the middle of lactation, whereas the energy balance shows the highest heritability with h2=0.34 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.
Identification of quantitative trait loci (QTL) provides insight into the genetic control of growth and body composition in pigs. The majority of QTL have been identified on autosomes with less QTL reported on the sex chromosomes. A reason may be that the genomic analysis of the X chromosome is more statistically challenging. Computer programmes accounting for the unique features of chromosome X have been unavailable until recently. Most studies have adopted a regression-based approach analysing males and females separately, which results in a decrease in power to detect QTL. In the present study, a QTL analysis of pig chromosome X (SSCX) was carried out using a method which accounts for the unique features associated with chromosome X, including the pseudoautosomal region of the Y chromosome.
Serial measurements of three milkability traits from two commercial dairy farms in Germany were used to estimate heritabilities and breeding values (BVs). Overall, 6352 cows in first, second and third lactations supplied 2 188 810 records based on daily values recorded from 1998 to 2003. Only the records between day 8 and day 305 after calving were considered. The estimated genetic correlations between different parities within the three milkability traits ranged from rg = 0.88 to 0.98, i.e. they were sufficiently high to warrant a repeatability model. The resulting estimated heritability coefficients were h2 = 0.42 for average milk flow, h2 = 0.56 for maximum milk flow and h2 = 0.38 for milking time. We analysed the genetic correlation between milkability and somatic cell score (SCS) and between milkability and the liability to mastitis, respectively, as the optimum milk flow for udder health is not well defined. There were 66 146 records with information on somatic cell count. Furthermore, 23 488 days of medical treatment for udder diseases were available, resulting in 2 600 302 days of observation in total. Heritabilities for the liability to mastitis, estimated with a test-day threshold model, were h2 = 0.19 and h2 = 0.13, depending on the data-recording period (first 50 days of lactation and first 305 days of lactation, respectively). With respect to the relationship between milkability and udder health, the results indicated a slight and linear correlation insofar as one can assume: the higher the milk flow, the worse the udder health. For this reason, bulls and cows with high BVs for milk flow should be excluded from breeding to avoid a deterioration of udder health. The establishment of a special data-recording scheme for functional traits such as milkability and mastitis on commercial dairy farms may be possible according to these results.
Quantitative trait loci (QTL) associated with physical and chemical body composition of the pig are of substantial economic interest. Previous studies have reported QTL for physical body composition such as lean and fat tissue traits (Roehe et al., 2003). In contrast, QTL associated with chemical body composition and for the change in deposition of such components during growth have only been reported in one previous study (Mohrmann et al., 2006). Knowledge of the genomic regulation of body composition during growth is important to accurately estimate nutritional requirements, optimise the entire production system, characterise the population of interest, and to optimise food intake capacity by breeding.
A serial slaughter trial was carried out to examine the developmental change of physical and chemical body composition in pigs highly selected for lean content. A total of 48 pigs (17 females and 31 castrated males) were serially slaughtered and chemically analysed. Eight pigs were slaughtered at 20, 30, 60, 90, 120 and 140 kg live weight, (LW) respectively. The carcass was chilled and the left carcass side was dissected into the primal carcass cuts ham, loin, shoulder, belly and neck. Each primal carcass cut was further dissected into lean tissue, bones and rind. Additionally, the physical and chemical body composition was obtained for the total empty body as well as for the three fractions soft tissue, bones and viscera. Viscera included the organs, blood, empty intestinal tract and leaf fat. The relationship between physical or chemical body composition and empty body weight (EBWT) at slaughter was assessed using allometric equations (log10y=log10a+b log10 EBWT). Dressing percentage increased from 69·4 to 85·2% at 20 to 120 kg and then decreased to 83·1% at 140 kg LW, whereas percentage of soft tissue, bones and viscera changed from 23·5 to 33·0%, 10·1 to 6·3% and 14·7 to 10·3%, respectively, during the entire growth period. Substantial changes in proportional weights of carcass cuts on the left carcass side were obtained for loin (10·5 to 17·5%) and belly (11·3 to 13·8%) during growth from 20 to 140 kg. Soft tissue fraction showed an allometric coefficient above 1 ( b=1·14) reflecting higher growth rate in relation to the total empty body. The coefficients for the fractions bones and viscera were substantially below 1 with b=0·77 and 0·79, respectively, indicating substantial lower growth relative to growth of the total empty body. Lean tissue allometric growth rate of different primal cuts ranged from b=1·02 (neck) to 1·28 (belly), whereas rates of components associated with fat tissue growth rate ranged from b=0·62 (rind of belly) to 1·79 (backfat). For organs, allometric growth rate ranged from b=0·61 (liver) to 0·90 (spleen). For the entire empty body, allometric accretion rate was 1·01, 1·75, 1·02 and 0·85 for protein, lipid, ash and water, respectively. Extreme increase in lipid deposition was obtained during growth from 120 to 140 kg growth. This was strongly associated with an increase in backfat and leaf fat in this period. Interestingly, breeds selected for high leanness such as Piétrain sired progeny showed an extreme increase in lipid accretion at a range of LW from 120 to 140 kg, which indicates that selection has only postponed the lipid deposition to an higher weight compared with the normally used final weight of 100 kg on the performance test. The estimates obtained for allometric growth rates of primal carcass cuts, body tissue and chemical body composition can be used to predict changes in weight of carcass cuts, determine selection goals concerning lean tissue growth, food intake capacity, etc. and generally as input parameters for pig growth models that can be used to improve the efficiency of the entire pig production system for pigs highly selected for lean content.
The objective of this study was to develop accurate mathematical-statistical functions to estimate body composition of live pigs between 20 and 140 kg weight from total body water (TBWA) determined by the deuterium dilution technique. Chemical body compositions during the growth period are essential input parameters for biological pig growth models, which are used to estimated the nutrient requirements, improve the entire production system, determine optimal slaughter weight, optimize selection for food intake, etc. In the present study, 48 pigs (17 female and 31 castrated males) were used in an experimental station to obtain protein, lipid, ash and water content at 20, 30, 60, 90, 120 and 140 kg live weight. At each target weight, body water of the animals was determined by the deuterium dilution technique. Eight pigs of each live-weight group were slaughtered and chemically analysed. Water content of the empty body decreased from 74 to 53%, whereas lipid content rose from 7 to 30%. Between 20 and 30 kg body weight, protein content increased from 16 to 17% and thereafter decreased to 16%. Ash content was constant at 3%. To estimate body composition of the remaining animals from TBWA (%) determined by deuterium dilution technique, two sets of exponential prediction functions were used to describe the relationship between chemically analysed body components and TBWA (%). The first set of prediction functions fitted one intercept for the entire growth period and the second set of prediction functions fitted a different intercept for each weight class. Correlation coefficients between estimated and chemically determined empty body water, lipid, protein and ash for the first set of functions were 0·93, 0·86, 0·83 and 0·65, respectively. The second set of prediction functions showed higher accuracy (2 to 10%), but had the disadvantage of non-continuous estimates over the entire growth period. In contrast, by using the first set of prediction functions, a continuous accurate estimation of body composition of live pigs was obtained over a large range of growth (20 to 140 kg) based on deuterium dilution space.
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.
Ultrasonic probe data were available on 199 crossbred pigs (98 females, 101 barrows). These animals were probed at approximately 30, 50, 70, 100 and 120 kg live weight with two probing instruments (Krautkramer USM2, Combison 310) at three sites along the back. The measurements were examined as predictors of the proportion of valuable cuts (part dissection) and estimated lean concentration (at 100 and 120 kg live weight).
The standard deviations for proportion of valuable cuts (after correcting for sex effects) were 24·8, 26·7, 23·4, 27·1 and 29·4 g/kg at 30, 50, 70, 100 and 120 kg. Residual s.d. for predicting proportion of valuable cuts from live weight and ultrasonic probes (Combison, quotient fat to muscle area) were 190, 20·9, 19·3, 213 and 19·6. For the USM2, the residual s.d.s were 19·2, 26·3, 19·9, 25·1 and 24·6. Thus the Combison probe provided a better prediction of proportion of valuable cuts. The standard deviations of estimated lean concentration as determined by a Fat-O-Meater reflectance probe were 28·9 and 39·3 at 100 and 120 kg live weight. The residual s.d.s from live weight and ultrasonic measurements were 15·4 and 19·2 for the Combison probe and 21·5 and 20·5 for the USM2 probe. If the estimated lean concentration is accepted as a selection objective the value of ultrasonic probes as criteria in selection indices will increase.
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