Fine mapping of a QTL affecting levels of skatole on pig chromosome 7

Abstract Background Previous studies in the Norwegian pig breeds Landrace and Duroc have revealed a QTL for levels of skatole located in the region 74.7–80.5 Mb on SSC7. Skatole is one of the main components causing boar taint, which gives an undesirable smell and taste to the pig meat when heated. Surgical castration of boars is a common practice to reduce the risk of boar taint, however, a selection for boars genetically predisposed for low levels of taint would help eliminating the need for castration and be advantageous for both economic and welfare reasons. In order to identify the causal mutation(s) for the QTL and/or identify genetic markers for selection purposes we performed a fine mapping of the SSC7 skatole QTL region. Results A dense set of markers on SSC7 was obtained by whole genome re-sequencing of 24 Norwegian Landrace and 23 Duroc boars. Subsets of 126 and 157 SNPs were used for association analyses in Landrace and Duroc, respectively. Significant single markers associated with skatole spanned a large 4.4 Mb region from 75.9–80.3 Mb in Landrace, with the highest test scores found in a region between the genes NOVA1 and TGM1 (p < 0.001). The same QTL was obtained in Duroc and, although less significant, with associated SNPs spanning a 1.2 Mb region from 78.9–80.1 Mb (p < 0.01). The highest test scores in Duroc were found in genes of the granzyme family (GZMB and GZMH-like) and STXBP6. Haplotypes associated with levels of skatole were identified in Landrace but not in Duroc, and a haplotype block was found to explain 2.3% of the phenotypic variation for skatole. The SNPs in this region were not associated with levels of sex steroids. Conclusions Fine mapping of a QTL for skatole on SSC7 confirmed associations of this region with skatole levels in pigs. The QTL region was narrowed down to 4.4 Mb in Landrace and haplotypes explaining 2.3% of the phenotypic variance for skatole levels were identified. Results confirmed that sex steroids are not affected by this QTL region, making these markers attractive for selection against boar taint

Determination of protein and amino acid requirements of lactating sows using a population-based factorial approach.

Determination of appropriate nutritional requirements is essential to optimize the productivity and longevity of lactating sows. The current recommendations for requirements do not consider the large variation between animals. Therefore, the aim of this study was to determine the amino acid recommendations for lactating sows using a stochastic modeling approach that integrates population variation and uncertainty of key parameters into establishing nutritional recommendations for lactating sows. The requirement for individual sows was calculated using a factorial approach by adding the requirement for maintenance and milk. The energy balance of the sows was either negative or zero depending on feed intake being a limiting factor. Some parameters in the model were sow-specific and others were population-specific, depending on state of knowledge. Each simulation was for 1000 sows repeated 100 times using Monte Carlo simulation techniques. BW, back fat thickness of the sow, litter size (LS), average litter gain (LG), dietary energy density and feed intake were inputs to the model. The model was tested using results from the literature, and the values were all within ±1 s.d. of the estimated requirements. Simulations were made for a group of low- (LS=10 (s.d.=1), LG=2 kg/day (s.d.=0.6)), medium- (LS=12 (s.d.=1), LG=2.5 kg/day (s.d.=0.6)) and high-producing (LS=14 (s.d.=1), LG=3.5 kg/day (s.d.=0.6)) sows, where the average requirement was the result. In another simulation, the requirements were estimated for each week of lactation. The results were given as the median and s.d. The average daily standardized ileal digestible (SID) protein and lysine requirements for low-, medium- and high-producing sows were 623 (CV=2.5%) and 45.1 (CV=4.8%); 765 (CV=4.9%) and 54.7 (CV=7.0%); and 996 (CV=8.5%) and 70.8 g/day (CV=9.6%), respectively. The SID protein and lysine requirements were lowest at week 1, intermediate at week 2 and 4 and the highest at week 3 of lactation. The model is a valuable tool to develop new feeding strategies by taking into account the variable requirement between groups of sows and changes during lactation. The inclusion of between-sow variation gives information on safety margins when developing new dietary recommendations of amino acids and protein for lactating sows

Determination of protein and amino acid requirements of lactating sows using a population-based factorial approach.

Determination of appropriate nutritional requirements is essential to optimize the productivity and longevity of lactating sows. The current recommendations for requirements do not consider the large variation between animals. Therefore, the aim of this study was to determine the amino acid recommendations for lactating sows using a stochastic modeling approach that integrates population variation and uncertainty of key parameters into establishing nutritional recommendations for lactating sows. The requirement for individual sows was calculated using a factorial approach by adding the requirement for maintenance and milk. The energy balance of the sows was either negative or zero depending on feed intake being a limiting factor. Some parameters in the model were sow-specific and others were population-specific, depending on state of knowledge. Each simulation was for 1000 sows repeated 100 times using Monte Carlo simulation techniques. BW, back fat thickness of the sow, litter size (LS), average litter gain (LG), dietary energy density and feed intake were inputs to the model. The model was tested using results from the literature, and the values were all within ±1 s.d. of the estimated requirements. Simulations were made for a group of low- (LS=10 (s.d.=1), LG=2 kg/day (s.d.=0.6)), medium- (LS=12 (s.d.=1), LG=2.5 kg/day (s.d.=0.6)) and high-producing (LS=14 (s.d.=1), LG=3.5 kg/day (s.d.=0.6)) sows, where the average requirement was the result. In another simulation, the requirements were estimated for each week of lactation. The results were given as the median and s.d. The average daily standardized ileal digestible (SID) protein and lysine requirements for low-, medium- and high-producing sows were 623 (CV=2.5%) and 45.1 (CV=4.8%); 765 (CV=4.9%) and 54.7 (CV=7.0%); and 996 (CV=8.5%) and 70.8 g/day (CV=9.6%), respectively. The SID protein and lysine requirements were lowest at week 1, intermediate at week 2 and 4 and the highest at week 3 of lactation. The model is a valuable tool to develop new feeding strategies by taking into account the variable requirement between groups of sows and changes during lactation. The inclusion of between-sow variation gives information on safety margins when developing new dietary recommendations of amino acids and protein for lactating sows

Bayesian simultaneous equation models for the analysis of energy intake and partitioning in growing pigs

The objective of the current study was to develop Bayesian simultaneous equation models for modelling energy intake and partitioning in growing pigs. A key feature of the Bayesian approach is that parameters are assigned prior distributions, which may reflect the current state of nature. In the models, rates of metabolizable energy (ME) intake, protein deposition (PD) and lipid deposition (LD) were treated as dependent variables accounting for residuals being correlated. Two complementary equation systems were used to model ME intake (MEI), PD and LD. Informative priors were developed, reflecting current knowledge about metabolic scaling and partial efficiencies of PD and LD rates, whereas flat non-informative priors were used for the reminder of the parameters. The experimental data analysed originate from a balance and respiration trial with 17 cross-bred pigs of three genders (barrows, boars and gilts) selected on the basis of similar birth weight. The pigs were fed four diets based on barley, wheat and soybean meal supplemented with crystalline amino acids to meet or exceed Danish nutrient requirement standards. Nutrient balances and gas exchanges were measured at c. 25, 75, 120 and 150 kg body weight (BW) using metabolic cages and open circuit respiration chambers. A total of 56 measurements were performed. The sensitivity analysis showed that only the maintenance component was sensitive to the prior specification, and hence the maintenance estimate of 0·91 MJ ME/kg0·60 per day (0·95 credible interval (CrI): 0·78-1·09) should be interpreted with caution. It was shown that boars' ability to deposit protein was superior to that of barrows and gilts, as these had an estimated maximum PD (PDmax) of 250 g/day (0·95 CrI: 237-263), whereas the barrows and gilts had a PDmax of 210 g/day (0·95 CrI: 198-220). Furthermore, boars reached PDmax at 109 kg BW (0·95 CrI: 93·6-130), whereas barrows and gilts maximized PD at 81·7 kg BW (0·95 CrI: 75·6-89·5). At 25 kg BW, the boars partitioned on average 5-6% more of the ME above maintenance into PD than barrows and gilts, and this was progressively increased to 10-11% more than barrows and gilts at 150 kg BW. The Bayesian modelling framework can be used to further refine the analysis of data from metabolic studies in growing pigs. © Cambridge University Press 2012

Energy and nutrient deposition and excretion in the reproducing sow: model development and evaluation.

Air and nutrient emissions from swine operations raise environmental concerns. During the reproduction phase, sows consume and excrete large quantities of nutrients. The objective of this study was to develop a mathematical model to describe energy and nutrient partitioning and predict manure excretion and composition and methane emissions on a daily basis. The model was structured to contain gestation and lactation modules, which can be run separately or sequentially, with outputs from the gestation module used as inputs to the lactation module. In the gestating module, energy and protein requirements for maintenance, and fetal and maternal growth were described. In the lactating module, a factorial approach was used to estimate requirements for maintenance, milk production, and maternal growth. The priority for nutrient partitioning was assumed to be in the order of maintenance, milk production, and maternal growth with body tissue losses constrained within biological limits. Global sensitivity analysis showed that nonlinearity in the parameters was small. The model outputs considered were the total protein and fat deposition, average urinary and fecal N excretion, average methane emission, manure carbon excretion, and manure production. The model was evaluated using independent data sets from the literature using root mean square prediction error (RMSPE) and concordance correlation coefficients. The gestation module predicted body fat gain better than body protein gain, which was related to predictions of body fat and protein loss from the lactation model. Nitrogen intake, urine N, fecal N, and milk N were predicted with RMSPE as percentage of observed mean of 9.7, 17.9, 10.0, and 7.7%, respectively. The model provided a framework, but more refinements and improvements in accuracy of prediction (particularly urine N) are required before the model can be used to assess environmental mitigation options from sow operations