Biomedical subjects

H H Swalve

Publications and source records attributed to H H Swalve.

9 recordsLinked to original sources

PubMed2006

Identification and analysis of putative regulatory sequences for the MYF5/MYF6 locus in different vertebrate species.

The myogenic factors (MYF) 5 and 6 are integral to the initiation and development of skeletal muscle and to the maintenance of its phenotype. Thus, they are candidate genes for growth- and meat quality-related traits. We performed a comparative sequence analysis of the MYF5/MYF6 locus in swine, cattle, dog, chicken and zebrafish on the basis of structural and functional information from human and mouse. Beside the characterization of upstream regulatory elements recently identified in mice, we demonstrate the existence of further highly conserved elements (E1 to E4) which may play a role in the regulation of MYF5 and MYF6 expression. Comparative sequence analysis of putative regulatory sequences in swine revealed a total of 21 single nucleotide polymorphisms (SNP) including 1 and 6 SNPs new for the promoters of MYF5 and MYF6, respectively. The conserved organization of the locus in vertebrates indicates a common basic mechanism of muscle development. However, the existence of numerous regulatory elements at large distances to MYF5 and MYF6 points to a very complex pattern of the gene regulation with significant differences between species.

Animals↗

PubMed2006

Association of a melanocortin 4 receptor (MC4R) polymorphism with performance traits in Lithuanian White pigs.

The melanocortin 4 receptor is expressed in virtually all brain regions of mammals and plays an important role in energy homeostasis. Polymorphisms in this gene may thus be related to growth and obesity. In pigs, a non-synonymous polymorphic site was described (Asp298Asn) and demonstrated to affect cAMP production and to alter adenylyl cyclase signalling. Association studies revealed significant linkage of this mutation with production trait in pigs. In this study, 207 Lithuanian White pigs were genotyped at the MC4R locus and analysed on relationships between genotype and breeding values for several performance traits. The observed allele and genotype frequencies did not deviate significantly from Hardy-Weinberg equilibrium (wildtype allele 0.59; mutant allele 0.41) and are comparable with those described in other Large White populations. The mutant Asn298 allele of the MC4R gene was significantly associated with increased test daily gain, higher lean meat percentage and lower backfat thickness. There was a trend towards an improved feed conversion ratio (p = 0.065) in animals with the mutant allele whereas no significant effect was found on lifetime daily gain. These results indicate that the MC4R polymorphism should be integrated in selection programmes in the Lithuanian White to improve carcass composition.

Adenylyl Cyclases↗

PubMed2005

Genetic relationships for dairy performance between large-scale and small-scale farm conditions.

Genotype by environment interaction can be detected via the estimation of genetic correlations between environments under an animal model based on data comprising genetic links between the strata. Genetic correlations were estimated for protein yield of Holstein cows within and across regions of Germany using REML under an animal model for lactation and test-day records. Subsets of the entire data were created, stratified by region or herd size within region, and comprised between 16,307 and 132,972 cows with first-lactation records. Substantial heterogeneity exists between regions in Western and Eastern Germany. In Western states, most farms are small, with typical herd sizes of 30 to 60 cows, whereas in Eastern states, mostly large herds with herd sizes of 500 to 2000 cows are common. The results show drastic differences for residual and permanent environmental variance components between Eastern and Western regions with increases of around 30% for Eastern regions. Additive genetic variances were of similar magnitude in both regions. Genetic correlations between Eastern and Western states were between 0.90 and 0.95 but dropped to 0.79 when data from an Eastern state were reduced to contain large herds only. The results indicate that differences in herd size account for more of the differences in genetic correlation than do geographic regional differences.

Animals↗

PubMed2002

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.

Animals↗

PubMed2001

Analysis of survival in dairy cows with supplementary data on type scores and housing systems from a region of northwest Germany.

In survival analysis, type traits can be included as covariates to evaluate their use as predictors for survival. One problem in such an analysis is the availability of suitable data. Whereas data on the length of productive life (LPL) of individual cows can be retrieved from milk recording data, for type traits, all cows in the population must be scored for type at least once. In the present analysis, a dataset from the Osnabruck region in northwestern Germany, which fulfilled this requirement in recent years, was used. Data consisted of 169,733 cows with information on LPL for calving years 1980 to 1996 (dataset I) and of 39,233 cows with information on LPL and type for calving years 1990 to 1996 (dataset II). A further dataset (III) contained 43,116 cows from calving years 1987 to 1996 and included information on the housing system for each herd. The basic model included stage of lactation, relative production within herd, change of herd size, and year-season as time dependent effects; age at calving as a time-independent effect; and herd-year-season and sire as random effects. Other effects (information on type, housing system) were included additionally. For data-set II, the scores for 15 linear type traits were also included as corrected phenotypic values, estimated breeding values, and residuals from a previous BLUP analysis. The package Survival Kit 3.0 was used for all analyses. The results indicate a moderate heritability of 0.17 and 0.18 for true and functional LPL (dataset I). Almost all type traits analyzed (dataset II) exceeded a 0.001 level of significance in their effect on survival. The strongest relationships between survival and type were found for udder depth, fore udder attachment, and front teat placement. The main result from the comparison of housing systems (dataset III) was that bedding has a positive effect on survival.

Age Factors↗

PubMed2000

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.

Animals↗

PubMed2000

Theoretical basis and computational methods for different test-day genetic evaluation methods.

In test-day (TD) models, records from individual test days are used to determine lactation production instead of aggregating records. Test-day models have recently gained considerable interest because they are more flexible in handling records from different recording schemes. Compared with only using records of complete lactations, they can reduce the generation interval through frequent genetic evaluations with the latest data. Test-day models can predict total production more accurately by accounting for time-dependent environmental effects. Test-day models may be separated into three groups: First, two-step models under which corrections are carried out at TD level and subsequently corrected TD records are processed in an aggregated form as lactation records. Second, fixed regression models assume that TD records within a lactation are repeated records. Because yields in the course of the lactation follow a curvilinear pattern, this curve can be considered by using suitable covariates. Third, random regression models additionally define the animal's genetic effect by using regression coefficients and allowing for covariances among them. The difference between random regression and fixed regression models is that the genetic merit of an individual is allowed to differ in the course of the lactation in random regression models. Random regressions are related to the approach of defining covariance functions for longitudinal data. Computationally, TD models are very demanding. For evaluations on a national scale, the size of the equation system can go to hundreds of millions of equations, depending on the size of the database and the specific model defined.

Animals↗

PubMed1995

The effect of test day models on the estimation of genetic parameters and breeding values for dairy yield traits.

The present study estimated genetic parameters for yields of milk, fat, and protein applying REML procedures under test day animal models. The data consisted of 155,494 test day records from 15,756 Friesian cows in first lactation from one region in northern Germany. The models applied included a traditional herd-year-season model for the analysis of single test days and 305-d records and two test day models differing by the definition of contemporary groups, either as herd-year-season of calving or as herd-test day. For single test days, heritabilities were highest for midlactation yields. For test day models, estimates of heritability varied with the number of test day records included for each cow. Estimates of .32, .19, and .20 for yields of milk, fat, and protein, respectively, were highest when only test d 3 to 7 were included; the corresponding estimates for 305-d records were .39, .32, and .30. Estimates of residual variances were reduced when test day records were converted to records of average yield in standardized intervals of 30 d. Breeding values were estimated for 305-d and test day models. A comparison of both sets of breeding values indicates only minor changes in sire rank, but more drastic reranking for individual cows.

Animals↗

PubMed1991

Detection of bovine somatotropin treatment in dairy cattle performance records.

Effectiveness of cluster analysis in detecting application of bST was examined. Field data were manipulated by adding a specified percentage of the true performance to original test day records to simulate application of bST. The partly manipulated data then were analyzed using cluster analysis. Test day milk production data came from 42,779 cows of the Bretagne (Northwestern France) that had test days between 1986 and 1989. As criteria in the cluster analysis for differentiation between treated and untreated cows, parameters of the incomplete gamma function along with other variables calculated from test day records were used. The best differentiation was achieved when a persistency parameter, defined as the ratio of second divided by first trimester production, was used as a variable in the cluster analysis. For the assumed scenario of bST application, more than 80% of all cows were classified correctly under random use of bST. Systematic treatment led to improved results.

Algorithms↗