Analysis of birth weight variability in pigs with respect to liveborn and total born offspring.

Reduction in the variability of piglet birth weight within litter and increased piglet survival are key objective in schemes aiming to improve sow prolificacy. In previous studies, variation in birth weight was described by the sample standard deviation of birth weights within one litter, and the genetic impact has been proved. In this study, we additionally considered the sex effect on piglet's birth weight and on its variability. The sample variance of birth weights per litter separated by sex was assigned as a trait of the sow. Different transformations of the trait were fitted by linear and generalized linear mixed models. Based on 1111 litters from Landrace sows, the estimates of heritability for the different measures ranged from 11 to 12%. We analysed the influence of including birth weight of stillborn piglets on the variability of birth weight within litter. With omitted stillborns, the heritability was estimated approximately 2% higher than that in investigations of all born piglets, and the impact of sex on birth weight variability was increased. Because the proportion of intrapartum deaths is rather high, it is recommended to consider the total number of piglets born per litter when analysing birth weight variation.

Comparison of statistical models to analyse the genetic effect on within-litter variance in pigs.

Genetics affects not only the weight of piglets at birth but also the variability of birth weight within litter. Previous studies on this topic assigned the sample standard deviation of piglet birth weights within litter as an observation to the sow. However, the contribution of the difference in mean birth weight per sex on the within-litter variance has been neglected so far. This work deals with the genetic effect on within-litter variance when different statistical models with different distributional assumptions are used and considers the sex effect and appropriate weights per trait. Traits were formed from the pooled sample variance of male and female birth weights within litter. A linear model approach was fitted to the logarithmized within-litter variance and the sample standard deviation. A generalized linear model with gamma-distributed residuals and log-link function was applied to the untransformed sample variance. Models were compared by analysing data from 9439 litters from Landrace and Large White of a commercial breeding programme. The estimates of heritability for different traits ranged from 7% to 11%. Although the generalized linear mixed model is preferred from a mathematical view, the rank correlations between breeding values of the linear mixed models and the generalized linear mixed model were relatively high, i.e. 94% to 98%. By residual diagnostics, a linear mixed model using the weighted and pooled within-litter standard deviation was identified as most suitable.

The map expansion obtained with recombinant inbred strains and intermated recombinant inbred populations for finite generation designs.

The generation of special crosses between different inbred lines such as recombinant inbred strains (RIS) and intermated recombinant inbred populations (IRIP) is being used to improve the power of QTL detection techniques, in particular fine mapping. These approaches acknowledge the fact that recombination of linked loci increases with every generation, caused by the accumulation of crossovers appearing between the loci at each meiosis. This leads to an expansion of the map distance between the loci. While the amount of the map expansion of RIS and IRIP is known for infinite inbred generations, it is not known for finite numbers of generations. This gap was closed here. Since the recursive evaluation of the map expansion factors turned out to be complex, a useful approximation was derived.

Simultaneous confidence intervals for ratios with applications to the comparison of several treatments with a control.

OBJECTIVES: In this article, we illustrate and compare exact simultaneous confidence sets with various approximate simultaneous confidence intervals for multiple ratios as applied to many-to-one comparisons. Quite different datasets are analyzed to clarify the points. METHODS: The methods are based on existing probability inequalities (e.g., Bonferroni, Slepian and Sidak), estimation of nuisance parameters and re-sampling techniques. Exact simultaneous confidence sets based on the multivariate t-distribution are constructed and compared with approximate simultaneous confidence intervals. RESULTS: It is found that the coverage probabilities associated with the various methods of constructing simultaneous confidence intervals (for ratios) in manyto-one comparisons depend on the ratios of the coefficient of variation for the mean of the control group to the coefficient of variation for the mean of the treatments. If the ratios of the coefficients of variations are less than one, the Bonferroni corrected Fieller confidence intervals have almost the same coverage probability as the exact simultaneous confidence sets. Otherwise, the use of Bonferroni intervals leads to conservative results. CONCLUSIONS: When the ratio of the coefficient of variation for the mean of the control group to the coefficient of variation for the mean of the treatments are greater than one (e.g., in balanced designs with increasing effects), the Bonferroni simultaneous confidence intervals are too conservative. Therefore, we recommend not using Bonferroni for this kind of data. On the other hand, the plug-in method maintains the intended confidence coefficient quite satisfactorily; therefore, it can serve as the best alternative in any case.

Evaluation and interpretation of results for three cross-over designs.

In cross-over designs, individual sequences of treatments are applied to the animals. Within such designs it is possible that every treatment could modify the effect of the subsequent treatment applied to the same animal. We compared three cross-over designs each with three treatments, three periods, and two blocks. This comparison was done with respect to the variance of the estimations of the effects and its biases caused by the interactions between the treatment and the carry over effect of the foregoing treatment. Moreover, different methods of estimating variance components and calculating the degrees of freedom were compared by means of simulation. If the animal variance component is small, then the bias of the REML estimator of the variance components is greater than one of the widespread ANOVA-estimator called 'TYPE3'. But nevertheless, the mean squared error of this estimation is smaller in the case of REML in comparison to ANOVA. Therefore, the REML method should be preferred. For calculating the degrees of freedom, the Kenward-Roger method should be used. After applying this method, the true significance level is almost equal to its required value, but if the Satterthwaite method is used, the true significance level will be too high. If the interaction (treatment x carry over) is ignored in the model although it exists, the standard error of the treatment effect estimation is too great, and, therefore, the true significance level is too small. The methods which have been evaluated are available in the SAS-procedure MIXED (SAS Institute, 1999a). To assist the investigation of cross-over designs by using this software, we developed programs for data management and data analysis. These programs are available from the first author.

Comparison of methods used for recovering the line origin of alleles in a cross between outbred lines.

Here, we introduce the idea of probabilities of line origins for alleles in general pedigrees as found in crosses between outbred lines. We also present software for calculating these probabilities. The proposed algorithm is based on the linear regression method of Haley, Knott and Elsen (1994) combined with the Markov chain Monte Carlo (MCMC) method for estimating quantitative trait locus coefficients used as regressors. We compared the relative precision of our method and the original method as proposed by Haley et al. (1994). The scenarios studied varied in the allelic distribution of marker alleles in parental lines and in the frequency of missing marker genotypes. We found that the MCMC method achieves a higher accuracy in all scenarios considered. The benefits of using MCMC approximation are substantial if the frequency of missing marker data is high or the number of marker alleles is low and the allelic frequency distribution is similar in both parental lines.

Dynamics of meiosis and protein kinase activities in bovine oocytes correlated to prolactin treatment and follicle size.

Oocyte developmental competence depends on the size of the original follicle and is affected by compounds like prolactin. We wished to investigate nuclear and cytoplasmic maturation of bovine oocytes correlated to their origin and response to prolactin treatment, by monitoring at frequent intervals meiotic configuration of chromosomes and activity of histone H1 and MAP-kinase. Bovine ovaries were obtained from a slaughterhouse and oocytes were recovered by follicle isolation. Oocytes (n = 1,397) with a compact cumulus were selected from small (2 to 3 mm) and large (4 to 5 mm in diameter) follicles and cultured up to 28 h in TCM 199+20% bull serum with or without 50 ng/mL bovine prolactin. Four groups of oocytes were formed: originating from small or large follicles, and treated or not treated with prolactin. At the scheduled time intervals for in vitro maturation, cumulus oocyte complexes from the 4 groups were randomly selected and the oocytes were analyzed for histone H1 and MAP-kinase, and for chromatin configuration. The first meiotic division took longer to complete in oocytes from large follicles (P < 0.01). Under the influence of prolactin the meiosis was prolonged in oocytes both from small and large follicles (P < 0.05). Histone H1 and MAP-kinases started to be activated at approximately the same time, around 6 h after beginning maturation. But after this time, significantly lower levels of both kinase activities were found in oocytes treated with prolactin, especially those treated during Meiosis I (P < 0.05). Our results indicate a correlation of chromatin configuration and histone H1/MAP-kinase activities.

Models for chromatid interference with applications to recombination data.

Genetic interference means that the occurrence of one crossover affects the occurrence and/or location of other crossovers in its neighborhood. Of the three components of genetic interference, two are well modeled: the distribution of the number and the locations of chiasmata. For the third component, chromatid interference, there exists only one model. Its application to real data has not yet been published. A further, new model for chromatid interference is presented here. In contrast to the existing model, it is assumed that chromatid interference acts only in the neighborhood of a chiasma. The appropriateness of this model is demonstrated by its application to three sets of recombination data. Both models for chromatid interference increased fit significantly compared to assuming no chromatid interference, at least for parts of the chromosomes. Interference does not necessarily act homogeneously. After extending both models to allow for heterogeneity of chromatid interference, a further improvement in fit was achieved.

Molecular mechanisms controlling constitutive and IFN-gamma-inducible HLA-G expression in various cell types.

HLA-G molecule is thought to play a major role in down-regulating the maternal immune response by inhibiting NK and T cell cytolytic activities. We examined the molecular regulatory mechanisms that may control the restricted expression pattern of the HLA-G gene. We first analyzed protein interactions between nuclear extracts from the HLA-G-positive JEG-3 choriocarcinoma and the HLA-G-negative NK-like YT2C2 cell lines to a 244 bp regulatory element located 1.2 kb from the HLA-G gene, previously shown to direct HLA-G expression in transgenic mouse placenta. This allowed characterization of cell-specific DNA-protein interactions that could account for differential cell-specific expression of the HLA-G gene. In particular two DNA-protein complexes were exclusively observed in YT2C2, suggesting that this HLA-G regulatory element is a target for putative cell-specific repressor factors. We further mapped nuclear factor binding sites to a 70 bp fragment in the upstream region of the regulatory element. We then investigated the effect of IFN-gamma on HLA-G gene expression. HLA-G cell surface expression was enhanced by IFN-gamma treatment in JEG-3 and U937 cell lines and peripheral blood monocytes while no effect was observed in tera-2 teratocarcinoma cell line. HLA-G transcriptional activity was increased only in JEG-3 and U937 cell lines. Activity of the 1.4-kb HLA-G promoter region was unchanged after IFN-gamma treatment in JEG-3 and Tera-2. These results suggest that both post-transcriptional and transcriptional mechanisms implicating IFN-responsive regulatory sequences outside the 1.4 kb-region are involved in IFN-gamma gene activation of the HLA-G gene.

IL-10 selectively induces HLA-G expression in human trophoblasts and monocytes.

HLA-G plays an essential role in feto-maternal tolerance by inhibiting lysis by maternal NK cells. The factors that allow tissue-specific activation of HLA-G gene expression in trophoblasts remain to be characterized. We investigated the potential effect of IL-10, a cytokine which is secreted in placenta, on HLA-G gene transcription in trophoblasts. Using Northern blot, RNase protection assay and RT-PCR analysis, we demonstrated that IL-10 enhances steady-state levels of HLA-G transcription in cultured trophoblast cells. We further tested the effect of IL-10 on HLA-G gene transcription and protein expression in peripheral blood monocytes, showing that IL-10 can up-regulate HLA-G cell surface expression in this cell type. This effect of IL-10 is selective, since classical MHC class I products and MHC class II are down-regulated in monocytes following IL-10 treatment. Induction of HLA-G expression by IL-10 on monocytes may thus play a role in down-regulation of the immune response. We propose that IL-10 secretion by trophoblasts during pregnancy may also influence the HLA class I expression pattern at the feto-maternal barrier, thus protecting the fetus from rejection. This should be taken into consideration in the design of treatment for pathologies of pregnancy.

Co-segregation of alleles at a microsatellite locus within the macrophage expressed lysozyme gene and levels of serum lysozyme activity in two half-sib families of Polish black and white lowland cattle.

Alleles at a microsatellite locus within the macrophage expressed lysozyme gene were shown to co-segregate with lysozyme activity in two half-sib families of Polish Black and White Lowland cattle. The bimodal distribution of lysozyme activities in both progeny groups is concordant with the occurrence of the alternative paternal alleles. The microsatellite is linked to a locus for high lysozyme activity that accounts for 70-95% of the phenotypic variation of both offspring groups considering the lysozyme activities of animals being older than 1 month.