The use of ultrasonography in the reproductive evaluation of boars

The objective was to study the use of ultrasound as a complementary test in the breeding soundness evaluation in male pigs and study the pattern of echogenicity of the testicular parenchyma in boars of different racial groups. Twenty‐six adult boars from four different racial groups were used, 10 from the Piau breed (group 1), four from the commercial and finishing group (group 2), six Pietrain breed (group 3) and six from the Duroc breed (group 4). All animals were evaluated for breeding soundness evaluation and the ultrasound examination of the testicles. The groups of animals that were evaluated showed no difference in the main semen parameters that were evaluated, except for the sperm volume, concentration of the ejaculated sperm and the supravital staining; the lowest figures were for the animals from the Piau breed (group 1). In relation to the testicular biometrics, Duroc animals (group 4) had a greater scrotal width compared to the other groups. But when we assessed the intensity of pixels of the testicles, there was a difference between groups. The groups 2 (finishing animals), 3 (Pietrain) and 4 had no difference between themselves. Group 3 had greater pixel intensity in relation to group 1. Of the 26 animals studied, five showed an abnormality during ultrasound evaluation, like hydrocele, hyperechoic mass in the testicular parenchyma, cyst in the head of the epididymis and the presence of fluid in the head and tail of the epididymis. The various animal groups studied did not differ in the principal reproductive parameters evaluated, showing that despite the great variability of reproductive traits between breeds and within the same breed, the breeding soundness evaluation, the more complete it is, is essential for the selection of breeders and the ultrasonography of the reproductive system becomes an important addition in this examination.     

Correlations among selected pork quality traits

Establishing relationships among specific quality traits is important if significant progress toward developing improved pork quality is to be realized. As part of a study to examine the individual effects of genes on meat quality traits in pigs, a three-generation resource family was developed. Two Berkshire sires and nine Yorkshire dams were used to produce nine F1 litters. Sixty-five matings were made from the F1 litters to produce four sets of F2 offspring, for a total of 525 F2 animals used in the study. These F2 animals were slaughtered at a commercial facility upon reaching approximately 110 kg. Carcass composition traits, pH measurements, and subjective quality scores were made at 24 h postmortem. Loin samples (n = 525) were collected at 48 h postmortem, and meat quality traits were evaluated. These traits included pH (48 h), Hunter L-values, drip loss, glycolytic potential, ratio of type IIa/IIb myosin heavy chains (IIa/IIb), total lipid, instrumental measures of tenderness using the Star Probe attachment of the Instron, cook loss measurements, and sensory evaluations. Significant phenotypic correlations were found between many carcass, instrumental, and biochemical measurements, and sensory quality traits. Star Probe measurements were significantly correlated with drip loss (0.29), glycolytic potential (0.30), pH (-0.29), total lipid (-0.14), and Hunter L-values (0.28). Drip loss was significantly correlated with glycolytic potential (0.36), pH (-0.28), IIa/IIb (-0.10), and Hunter L-values (0.33). Hunter L-values were also significantly correlated with total lipid (0.33) and IIa/ IIb (-0.11). Sensory tenderness, flavor, and off-flavor scores were significantly correlated with drip loss, pH, and glycolytic potential measurements. Marbling score, total lipid, and drip loss were not significantly correlated with sensory juiciness scores, but cooking loss was. Marbling and total lipid were significantly correlated with firmness scores (0.37 and 0.31, respectively). Taken together, the data in this study suggest that changes in some meat quality traits can affect many other meat quality attributes. The correlations yield information that could aid in directing future studies aimed at understanding the underlying biological mechanisms behind the development of many quality traits.     

Prediction of response to marker-assisted and genomic selection using selection index theory

Selection index methods can be used for deterministic assessment of the potential benefit of including marker information in genetic improvement programmes using marker-assisted selection (MAS). By specifying estimates of breeding values derived from marker information (M-EBV) as a correlated trait with heritability equal to 1, it was demonstrated that marker information can be incorporated in standard software for selection index predictions of response and rates of inbreeding, which requires specifying phenotypic traits and their genetic parameters. Path coefficient methods were used to derive genetic and phenotypic correlations between M-EBV and the phenotypic data. Methods were extended to multi-trait selection and to the case when M-EBV are based on high-density marker genotype data, as in genomic selection. Methods were applied to several example scenarios, which confirmed previous results that MAS substantially increases response to selection but also demonstrated that MAS can result in substantial reductions in the rates of inbreeding. Although further validation by stochastic simulation is required, the developed methodology provides an easy means of deterministically evaluating the potential benefits of MAS and to optimize selection strategies with availability of marker data.     

Generalized marker regression and interval QTL mapping methods for binary traits in half-sib family designs

A Generalized Marker Regression Mapping (GMR) approach was developed for mapping Quantitative Trait Loci (QTL) affecting binary polygenic traits in a single-family half-sib design. The GMR is based on threshold-liability model theory and regression of offspring phenotype on expected marker genotypes at flanking marker loci. Using simulation, statistical power and bias of QTL mapping for binary traits by GMR was compared with full QTL interval mapping based on a threshold model (GIM) and with a linear marker regression mapping method (LMR). Empirical significance threshold values, power and estimates of QTL location and effect were identical for GIM and GMR when QTL mapping was restricted to within the marker interval. These results show that the theory of the marker regression method for QTL mapping is also applicable to binary traits and possibly for traits with other non-normal distributions. The linear and threshold models based on marker regression (LMR and GMR) also resulted in similar estimates and power for large progeny group sizes, indicating that LMR can be used for binary data for balanced designs with large families, as this method is computationally simpler than GMR. GMR may have a greater potential than LMR for QTL mapping for binary traits in complex situations such as QTL mapping with complex pedigrees, random models and models with interactions.     

Computed leaching of pesticides from soil under field conditions

With a computer model, pesticide behavior in soil after spring application to a sandy loam field with a potato crop, was simulated. Special attention was paid to the risk of leaching through the upper meter of soil in catchment areas. Unsaturated water flow resulting from rainfall was modeled in some detail. Uptake of water and solute by the developing root system of the annual crop was included in the model. The computations were carried out for hypothetical pesticides with first-order decomposition rate constants in soil of 0.03, 0.01, 0.003, and 0.001 day^–1 at 20°C. Adsorption decreased with increasing soil depth and the adsorption coefficient for the top layer ranged from 0.0 to 10.0. For 20 combinations of decomposition rates and adsorption strengths, the extent of leaching from a top layer 1 m thick was computed. With a decomposition rate constant at 20°C of 0.03 day^–1 or higher, leaching was extremely low; with 0.01 days^–1 leaching was 1.7% of the dosage or lower. For compounds with a high persistence and mobility, leaching from the soil ranged up to about 10% of the dosage or more. Besides decomposition, uptake by plants was an important factor in reducing leaching, particularly for the weakly adsorbed and comparatively persistent compounds.     

The value of a bulk-tank milk ELISA and individual serological and faecal examination for diagnosing (sub)clinical Dictyocaulus viviparus infection in dairy cows

To test the value of a recently developed bulk-tank milk (BTM) ELISA for diagnosing (sub)clinical Dictyocaulus viviparus infection in lactating dairy herds under field conditions, bulk milk samples were collected from farms with or without clinical symptoms suspected to be caused by lungworm infection. Results of the BTM ELISA were compared against individual examinations for lungworm larvae in faeces and lungworm antibodies in serum from up to 20 heifers (parity 1) and up to 20 cows (parity ≥ 2) on the same farms. This also allowed, for the first time, to examine the value of individual faecal and serological examinations in the diagnosis of (sub)clinical lungworm infections. In total, 33 farms participated. Of these, 16 reported clinical symptoms possibly related to lungworm infection (defined as a suspected positive clinical status or CS(+)) and 17 reported having no such symptoms (CS(-)). In total, 503 heifers and 649 cows were sampled. Of all faeces samples positive for lungworm larvae, 94 were from heifers (18.9% of all heifers) and 75 from cows (11.7% of all cows) (P<0.001). Of all sera positive for lungworm antibodies, 130 were from heifers (26.1% of all heifers) and 113 from cows (17.5% of all cows) (P<0.001). Of the CS(-) farms 41% had at least one heifer or cow shedding larvae and 71% had at least one seropositive heifer or cow. Of the CS(+) farms this was 81% and 94%, respectively. There were only 4 farms, all CS(-), where none of the animals were found shedding larvae and all animals tested seronegative. This implies that on 76% of the CS(-) farms lungworm infection circulated unnoticed. On all CS(+) farms the suspicion that lungworm caused the respiratory symptoms was confirmed by the individual faecal and serological examinations, whereas the BTM ELISA confirmed presence of lungworm on half of the CS(+) farms. The latter in particular occurred on farms with the more severe outbreaks. Overall, of 32 available BTM samples 10 tested positive (8 of 15 CS(+) and 2 of 17 CS(-) farms). For diagnosing suspected lungworm disease it was concluded that testing a BTM sample might suffice in case of moderate to severe outbreaks. However, in case of a mild outbreak with just a few animals coughing, examining individual animals has to be preferred over testing a BTM sample. The likelihood to detect lungworm infection is higher if heifers are sampled compared to cows. Sensitivity of the BTM ELISA was 35.7% if the presence of at least one seropositive and/or one larvae shedding animal in the herd was used to define lungworm positive farms. On average, at least 30% of the herd had to be seropositive before the BTM ELISA was found positive for lungworm antibodies. Results indicate that the BTM ELISA in its current form does not appear to be suitable for surveys on the prevalence of lungworm presence on farms. However, this BTM ELISA might be used in large-scale surveys to detect, for instance, annual changes in percentage positive farms, as long as it is recognized that positivity is more closely related to incidence of lungworm disease than to prevalence of lungworm infection.     

Effect of selection for residual feed intake on feeding behavior and daily feed intake patterns in Yorkshire swine

Residual feed intake (RFI) is a measure of feed efficiency defined as the difference between observed and predicted feed intake based on average requirements for growth and maintenance. The objective of this study was to evaluate the effect of selection for decreased RFI on feeding behavior traits and to estimate their relationships with RFI. Three data sets from the 4th and 5th generations of a selection experiment with a line selected for reduced RFI (LRFI) and a randomly selected control line (CTRL) were analyzed. Lines were mixed in pens of 16 and evaluated for feeding behavior traits obtained from a single-space electronic feeder over a growing period of ~3 mo before ~115 kg. The following traits were evaluated as averages over the entire test period and over the first and second half of the test period: number of visits per day and hour; occupation time per day, visit, and hour; feed intake (FI) per day, visit, and hour; and FI rate per visit. Models used included fixed effects of line and feeder, covariates of on-test age and FI per day, and random effects of pen, on-test group, sire, and litter. Repeated measures models were used to analyze feeding patterns during the day. The LRFI pigs had significantly less FI per day than CTRL pigs for all 3 data sets. With adjustment for FI per day, line differences of all traits were in the same direction for all 3 data sets but differed in significance and size. Feed intake per visit and hour and visits per day and hour did not differ between lines, but the trend was for LRFI pigs to have fewer visits, in particular during peak eating times. The LRFI pigs had a greater feeding rate and less occupation time per day, visit, and hour than CTRL pigs, but this was not significant for all data sets. Correlations of RFI with FI per day and visit and visits per day were positive. Average daily gain was positively correlated with FI per day and visit and occupation time per visit but negatively correlated with visits per day. Feed intake per day was positively correlated with backfat. In conclusion, feed efficiency may be affected by FI behavior because selection for decreased RFI has resulted in pigs that spend less time eating and eat faster.     

Selection on multiple QTL with control of gene diversity and inbreeding for long-term benefit

The purpose of this study was to develop and investigate selection strategies that aim at maximizing long-term genetic response while conserving gene diversity and controlling inbreeding in populations of limited effective size, assuming complete knowledge of all genes affecting a quantitative trait. Three selection strategies were proposed to select on 100 quantitative trait loci (QTL) and compared with truncation selection on breeding value. Alternative selection strategies aimed at maximizing the average breeding value of parents with a penalty on (1) the number of unfavourable QTL genotypes among parents (OS-I), (2) the negative of the logarithm of the frequency of the favourable allele at each QTL among parents (OS-II), and (3) the average pedigree relationship among parents (OS-III). When all QTL and their effects were known, the strategies examined were able to obtain extra long-term responses, conserve QTL diversity and reduce inbreeding, compared with truncation selection. Strategy OS-II was the most effective in conserving QTL diversity and OS-III in reducing inbreeding. By changing the magnitude of the penalties applied, the impact on long-term response, inbreeding and diversity can be controlled. Extra long-term responses over truncation selection of OS-I and OS-II were even greater when effects of QTL were estimated rather than assumed known, indicating the applicability of results to practical strategies for marker-assisted selection. Extra responses are expected to be reduced for larger population sizes.     

Impact of fitting dominance and additive effects on accuracy of genomic prediction of breeding values in layers

Most genomic prediction studies fit only additive effects in models to estimate genomic breeding values (GEBV). However, if dominance genetic effects are an important source of variation for complex traits, accounting for them may improve the accuracy of GEBV. We investigated the effect of fitting dominance and additive effects on the accuracy of GEBV for eight egg production and quality traits in a purebred line of brown layers using pedigree or genomic information (42K single‐nucleotide polymorphism (SNP) panel). Phenotypes were corrected for the effect of hatch date. Additive and dominance genetic variances were estimated using genomic‐based [genomic best linear unbiased prediction (GBLUP)‐REML and BayesC] and pedigree‐based (PBLUP‐REML) methods. Breeding values were predicted using a model that included both additive and dominance effects and a model that included only additive effects. The reference population consisted of approximately 1800 animals hatched between 2004 and 2009, while approximately 300 young animals hatched in 2010 were used for validation. Accuracy of prediction was computed as the correlation between phenotypes and estimated breeding values of the validation animals divided by the square root of the estimate of heritability in the whole population. The proportion of dominance variance to total phenotypic variance ranged from 0.03 to 0.22 with PBLUP‐REML across traits, from 0 to 0.03 with GBLUP‐REML and from 0.01 to 0.05 with BayesC. Accuracies of GEBV ranged from 0.28 to 0.60 across traits. Inclusion of dominance effects did not improve the accuracy of GEBV, and differences in their accuracies between genomic‐based methods were small (0.01–0.05), with GBLUP‐REML yielding higher prediction accuracies than BayesC for egg production, egg colour and yolk weight, while BayesC yielded higher accuracies than GBLUP‐REML for the other traits. In conclusion, fitting dominance effects did not impact accuracy of genomic prediction of breeding values in this population.     

Identification of recombination hotspots and quantitative trait loci for recombination rate in layer chickens

Background: The frequency of recombination events varies across the genome and between individuals, which may be related to some genomic features. The objective of this study was to assess the frequency of recombination events and to identify QTL(quantitative trait loci) for recombination rate in two purebred layer chicken lines.Methods: A total of 1200 white-egg layers(WL) were genotyped with 580 K SNPs and 5108 brown-egg layers(BL)were genotyped with 42 K SNPs(single nucleotide polymorphisms). Recombination events were identified within half-sib families and both the number of recombination events and the recombination rate was calculated within each0.5 Mb window of the genome. The 10% of windows with the highest recombination rate on each chromosome were considered to be recombination hotspots. A BayesB model was used separately for each line to identify genomic regions associated with the genome-wide number of recombination event per meiosis. Regions that explained more than 0.8% of genetic variance of recombination rate were considered to harbor QTL.Results: Heritability of recombination rate was estimated at 0.17 in WL and 0.16 in BL. On average, 11.3 and 23.2 recombination events were detected per individual across the genome in 1301 and 9292 meioses in the WL and BL,respectively. The estimated recombination rates differed significantly between the lines, which could be due to differences in inbreeding levels, and haplotype structures. Dams had about 5% to 20% higher recombination rates per meiosis than sires in both lines. Recombination rate per 0.5 Mb window had a strong negative correlation with chromosome size and a strong positive correlation with GC content and with CpG island density across the genome in both lines. Different QTL for recombination rate were identified in the two lines. There were 190 and 199 non-overlapping recombination hotspots detected in WL and BL respectively, 28 of which were common to both lines.Conclusions: Differences in the recombination rates, hotspot locations, and QTL regions associated with genomewide recombination were observed between lines, indicating the breed-specific feature of detected recombination events and the control of recombination events is a complex polygenic trait.