Biomedical subjects

T H Meuwissen

Publications and source records attributed to T H Meuwissen.

14 recordsLinked to original sources

PubMed1999

Genetic variation at the porcine MYF-5 gene locus. Lack Of association with meat production traits.

The number of muscle fibers at birth appears to determine the maximal lean meat growth capacity in pigs and in cattle. Development of muscle fibers is regulated by the MyoD gene family consisting of MyoD1, myf-5, myf-6, and myogenin. Myf-5 is expressed in proliferating myoblasts. Here we report the genomic sequence of the porcine myf-5 gene with three microsatellites and two RFLPs located close to the coding sequences. Two of the microsatellites are located in the promoter region. The allelic distribution differs between breeds and selection lines. In two GY selection lines, 1216 pigs of two-generation families were genotyped for the HinfI RFLP, which was segregating in the GY breed. The other polymorphic loci are physically linked to this RFLP locus, and therefore the results can be extrapolated to these loci. Statistical analysis revealed no association with birth weight, growth rate, weight at slaughter age, carcass meat weight, and backfat thickness. Thus, in this study myf-5 did not explain genetic variation in meat (muscle) development in pigs.

Animals↗

PubMed1999

Effect of genetic variants of the heart fatty acid-binding protein gene on intramuscular fat and performance traits in pigs.

In order to find genetic markers to improve the meat quality of pigs by breeding we studied the relationship between variation in the heart fatty acid-binding protein (H-FABP) gene (FABP3) and intramuscular fat (IMF) content. To estimate the effect of H-FABP, pigs from two Duroc populations were selectively mated in such a way that at least two genotypes were present in each litter. In total, data from 983 pigs and pedigree information from three preceding generations were analyzed. Offspring were tested for IMF content as well as backfat thickness (BFT), BW, and drip loss of the meat (DRIP). All pigs were assigned to H-FABP RFLP genotype classes either by the assessed genotype (75%) or based on a probability score determined according to genotypic information of their relatives (25%). Contrasts were detected between homozygous H-FABP RFLP genotype classes for IMF content (.4%, P < .05), BFT (.6 mm, P < .01), and BW (2.4 kg, P < .10). No significant contrasts were detected for DRIP. Results for IMF content, BFT, and BW were confirmed when only genotyped animals were analyzed. Variation in BFT partially explained the effect on IMF content. Although other closely linked genes on porcine chromosome 6 might be responsible for the observed effect, interference of the halothane gene was excluded because all parental animals were noncarriers. In conclusion, H-FABP RFLP can be used as markers to select for increased IMF content and growth in breeding programs.

Adipose Tissue↗

PubMed1998

The adipocyte fatty acid-binding protein locus: characterization and association with intramuscular fat content in pigs.

The porcine A-FABP gene (FABP4) was isolated and sequenced to study the role of A-FABP in the differentiation of intramuscular fat (IMF) accretion in pigs. The coding sequence of the porcine A-FABP gene is highly conserved across human, mouse, and rat. Moreover, all the functionally important amino acids are conserved. This high similarity extends into the first 270 bp of the 5' upstream region. Within this region, a 56-bp nucleotide sequence was completely identical with the corresponding sequence in the mouse A-FABP gene, which contains the transcription factor binding sites for C/EBP and AP-1, and is implicated in the differentiation-dependent regulation of A-FABP. The A-FABP gene was assigned to porcine Chromosome (Chr) 4 by a porcine sequence-specific PCR on a cell hybrid panel, fully consistent with comparative mapping data with human and mouse. In the first intron of the porcine A-FABP gene, a microsatellite sequence was detected that was polymorphic for all six pig breeds tested. This genetic variation within the A-FABP gene was associated with differences in IMF content and possibly growth in a Duroc population, whereas no effect on backfat thickness and drip loss of the meat were detected. A considerable and significant contrast of approximately 1% IMF was observed between certain genotype classes. We conclude that the A-FABP locus is involved in the regulation of intramuscular fat accretion in Duroc pigs.

Adipose Tissue↗

PubMed1998

Maximizing the response of selection with a predefined rate of inbreeding: overlapping generations.

In a breeding scheme, the aim is high rates of genetic gain with limited inbreeding. A dynamic selection rule is developed that maximizes selection response in populations with overlapping generations. The rule maximizes the genetic merit of selected animals while limiting the average relationship of the population after the current round of selection. The latter is shown to limit the contribution of the current population to the future inbreeding. The rule accounts for the selection of some candidates during previous selection rounds and for the expected future contributions of the selection candidates. Inputs for the rule are the BLUP breeding values and ages of selection candidates, the relationship matrix of all animals, and contributions of animals during previous selection rounds. Output is the optimal number of offspring for each candidate. Computer simulations of dairy cattle nucleus schemes showed that predefined rates of inbreeding were actually achieved, without compromising long-term selection response, at least up to 20 yr of selection. At the same rates of inbreeding, the dynamic selection rule obtained up to 44% more genetic gain than direct selection for BLUP breeding values. The advantage of the dynamic rule over BLUP selection decreased with increasing population sizes and with greater predefined rates of inbreeding. Consequently, the dynamic rule should be especially useful in small selection schemes in which relatively low rates of inbreeding are desired.

Age Factors↗

PubMed1998

Genetics of the interval from weaning to estrus in first-litter sows: correlated responses.

The objective of this study was to evaluate relationships between rebreeding performance and growth performance (n = 3,777 gilts) and rebreeding performance and reproductive performance (n = 2,242 sows). Our data were from a selection experiment for shorter intervals from weaning to estrus after the first parity (IWE), involving Dutch Landrace pigs, in which a selection line and a control line without selection were maintained for eight generations. Relationships were evaluated before and after transforming IWE to normal interval (NI; IWE < or = 7 d), prolonged interval (PI; IWE > 7 d), and incidence of a prolonged interval (INC). Heritabilities of NI, PI, and INC were .18, .17, and .27. Within-line phenotypic and genetic trends in growth and reproductive performance were not different from zero and did not diverge as a correlated response to the selection applied. Phenotypic correlations between IWE, NI, or PI and growth or reproductive performance were low and ranged from -.14 to .11. Genetic correlations were higher, and, for the majority of traits, the genetic correlations with NI and PI had a different sign. Phenotypic and genetic contrasts between sows with NI and sows with PI different from zero indicated that INC may increase as a correlated response to selection for reproductive performance. Analyses using untransformed IWE or data from populations selected for rebreeding performance may underestimate the correlated response in IWE due to selection on economically important traits.

Animals↗

PubMed1998

Optimizing pure line breeding strategies utilizing reproductive technologies.

The development of new reproductive techniques has had a great effect on schemes for dairy cattle improvement; AI resulted in progeny-testing schemes, and, more recently, multiple ovulation and embryo transfer has resulted in nucleus breeding schemes. In traditional breeding schemes, the use of multiple ovulation and embryo transfer resulted in only small increases of genetic gains because the selection intensity of bull dams was already high, but the selection intensity of cows in nucleus breeding schemes increased considerably. This increase makes nucleus schemes very competitive, especially when in vitro maturation and fertilization is used to increase female reproductive rates further. The increased genetic gain results in the selection of young females (i.e., optimal generation intervals are shortened). The combined effect of multiple ovulation and embryo transfer and shorter generation intervals increases the rate of gain by approximately 15% but also increases the rate of inbreeding and variances of the selection response (i.e., the risk of the breeding scheme) by about 80%. Recently, selection methods have been developed to reduce the rates of inbreeding or the variance of the selection response in breeding schemes. A scheme that maximized the selection differential while constraining the rate of inbreeding yielded about 30 to 60% more selection response than selection for BLUP estimated breeding value at the same rate of inbreeding. For the future, the combination of juvenile predictors of genetic merit (e.g., DNA markers) and techniques that further increase female reproductive rates seem very promising methods to increase the rates of genetic gain. As an example, the genetic gain of an optimized hybrid nucleus scheme could be increased 24% by the combined use of juvenile predictors and in vitro maturation and fertilization. Fertilization of fetal embryos was predicted to increase rates of gain by up to 18%.

Animals↗

PubMed1997

Estimation of effects of quantitative trait loci in large complex pedigrees.

A method was derived to estimate effects of quantitative trait loci (QTL) using incomplete genotype information in large outbreeding populations with complex pedigrees. The method accounts for background genes by estimating polygenic effects. The basic equations used are very similar to the usual linear mixed model equations for polygenic models, and segregation analysis was used to estimate the probabilities of the QTL genotypes for each animal. Method R was used to estimate the polygenic heritability simultaneously with the QTL effects. Also, initial allele frequencies were estimated. The method was tested in a simulated data set of 10,000 animals evenly distributed over 10 generations, where 0, 400 or 10,000 animals were genotyped for a candidate gene. In the absence of selection, the bias of the QTL estimates was < 2%. Selection biased the estimate of the Aa genotype slightly, when zero animals were genotyped. Estimates of the polygenic heritability were 0.251 and 0.257, in absence and presence of selection, respectively, while the simulated value was 0.25. Although not tested in this study, marker information could be accommodated by adjusting the transmission probabilities of the genotypes from parent to offspring according to the marker information. This renders a QTL mapping study in large multi-generation pedigrees possible.

Animals↗

PubMed1997

Maximizing the response of selection with a predefined rate of inbreeding.

A method was derived that maximizes the genetic level of selected animals while constraining their average coancestry to a predefined value. The average coancestry of the selected parents equals the inbreeding level in the next generation, so that rates of inbreeding were controlled. When this method was applied for several generations of selection, stable rates of genetic gain were attained, which indicates that the method could control the short- and long-term effects of selection on inbreeding. At equal rates of inbreeding, genetic gains were 21 to 60% greater than that with selection for BLUP-EBV, because of increased selection differentials. The difference was larger when the desirable rate of inbreeding was smallest. Selection with a constraint on inbreeding required only EBV of, and relationships between, the selection candidates and is therefore easy to apply in practice. The optimal solution is expressed in genetic contributions of selection candidates to the next generation, which is equivalent to numbers of offspring per candidate. These optimal numbers of offspring may be difficult to attain because of female reproductive limitations. The optimal method could be adapted to situations with additional reproductive constraints. The method can also be used to constrain the variance of response by restricting the average prediction error variance of the selected animals.

Animal Husbandry↗

PubMed1995

Maximizing selection efficiency for categorical traits.

Genetic improvement of categorically recorded traits is hampered because information content of categorical records is low and ordinary linear breeding value estimation methods do not apply theoretically. The ordinary animal or linear mixed model (LMM), which ignored the categorical nature of the trait, is compared to a generalized linear mixed model (GLMMp) that assumes a linear mixed model for an underlying continuous variable. The GLMMp takes full account of the categorical nature of the trait and is a straightforward extension of LMM. In a closed nucleus breeding scheme (e.g., cattle, pigs, or poultry), rates of genetic gain increased by 1 to 2%, when GLMMp was used instead of LMM. Rates of genetic gain increased by 7 to 20%, when the best sires were used on the best herds (i.e., when there was some confounding between sire and herd effects). When considering a binary trait (e.g., disease incidence) initial incidences of 25% could be reduced to 2.8% within 10 generations of selection. Rates of gain can be increased by up to 84% by gathering more information on high-incidence categories (i.e., by dividing these categories into subcategories). Subdividing low-incidence categories (e.g., splitting diseased animals into moderately and severely diseased) hardly increased rates of gain. Direct recording of the underlying variable, which requires uncovering of the physiological background of the categorical trait, yielded 109 to 278% more genetic gain than selection for a binary trait.

Animals↗

PubMed1994

Maximizing genetic response in breeding schemes of dairy cattle with constraints on variance of response.

Predicted genetic progress in dairy cattle breeding schemes was maximized with the variances of selection responses constrained, i.e., restricted effective population sizes. This restriction would also lead to schemes with acceptable rates of inbreeding (< .5%/yr). If the required coefficient of variation of the annual selection response was reduced from .32 to .16, numbers of animals selected, openness of schemes, and generation intervals increased. When elite cows produced 8 offspring annually, this reduction of the coefficient of variation tended toward a conventional progeny-testing scheme. If the number of donor cows was optimized, responses increased < or = 2%, and the breeding schemes became virtually closed. Variances of responses were reduced by selecting fewer, but proven, bulls, as is done in hybrid multiple ovulation and embryo transfer schemes, which select progeny-tested bulls and young elite cows. In spite of the constrained coefficients of variation, maximized genetic gains were high and were only reduced from .300 to .293 genetic standard deviations per year, when coefficients of variation were reduced from .32 to .16. Adoption of breeding schemes with low coefficients of variation is recommended, because responses are high and coefficients of variation are sensitive to accidental changes in the breeding structure.

Algorithms↗

PubMed1994

Effects of correction for heterogeneity of variance on bias and accuracy of breeding value estimation for Dutch dairy cattle.

Data on 305-d milk yield from the Dutch dairy evaluation were used to obtain breeding value estimates from an animal model for 1984 to 1992. Changes in sire evaluations were investigated for bias and realized accuracy. Evaluations based on progeny records were generally lower than their expectation based on parent average. The average decrease was 157 kg for Black and White bulls and 73 kg for Red and White bulls. Evaluations based on test daughters changed about -50 kg when second and third lactations became available, but estimates for breeding value changed insignificantly when records on daughters from the breeding period of the bull were used. The standard deviation of changes from evaluations for first to second batch was about 14% larger than expected from population parameters. Breeding values of imported bulls, based on Dutch data, decreased 75 kg when more information became available in subsequent evaluations. Heterogeneity of variance was estimated by a quasi-likelihood approach with a model that accounted for sampling variance on estimates of variances within herd. The coefficient of variation of the variances within herd-year was 31%. A simple method for standardization of variances within herd-year decreased bias of parent averages by about 20%, and fluctuations of breeding values were within the expected range. A correction for heterogeneity of variance within herd may not remove all bias of parent averages, but a general improvement of bias and accuracy of breeding values can be expected.

Analysis of Variance↗

PubMed1993

Genetic and statistical properties of residual feed intake.

Residual feed intake is defined as the difference between actual feed intake and that predicted on the basis of requirements for production and maintenance of body weight. Formulas were developed to obtain genetic parameters of residual feed intake from knowledge of the genetic and phenotypic parameters of the component traits. Genetic parameters of residual feed intake were determined for a range of heritabilities (h2 = .1, .3, or .5) for component traits of feed intake and production, and genetic (rg = .1, .5, or .9) and environmental (re = .1, .5, or .9) correlations between them. Resulting heritability of residual feed intake ranged from .03 to .84 and the genetic correlation between residual feed intake and production ranged from -.90 to .87. Heritability of residual feed intake depends considerably on the environmental correlation between feed intake and production. Residual feed intake based on phenotypic regression of feed intake on production usually contains a genetic component due to production. Residual feed intake based on genotypic regression of feed intake on production is genetically independent of production and its use is equivalent to use of a selection index restricted to hold production constant. Multiple-trait selection on residual feed intake, based on either phenotypic or genetic regressions, and production is equivalent to multiple-trait selection on feed intake and production. Residual energy intake in dairy cattle was examined as an example. Heritability of residual energy intake based on genotypic regression was close to zero and indicated that measurement of feed intake provides little additional genetic information over and above that provided by milk production and body weight. The principles outlined in this study have broader application than just to residual feed intake and apply to any trait that is defined as a linear function of other traits.

Animals↗

PubMed1992

Potential improvements in rate of genetic gain from marker-assisted selection in dairy cattle breeding schemes.

The value of marker-assisted selection in dairy cattle breeding schemes is predicted by a deterministic model. In these schemes, associations between markers and milk production were assessed from production records of daughters of a grandsire by a multiple regression model with random marker effects. By tracing markers from the grandsire to grandoffspring, deviations of grandoffspring from their full-sib family mean were predicted. Predictions of the within-family variance of the grandoffspring accounted for by markers amounted to up to 13.3%. This figure decreased when the number of daughters of the grandsire analyzed decreased and, less markedly, when the distance between flanking markers increased. Prediction of within-family deviations hardly improved rates of genetic gain in conventional progeny testing schemes; equal numbers of young bulls were born annually. Genetic gain and improvement of genetic gain because of prediction of within-family deviations were much higher in nucleus schemes. In these shemes, with short optimized generation intervals, conventional selection was mainly for pedigree information and did not use the within-family variance. Analysis of highly polymorphic markers in daughters of both grandsires accounted for 4.1 to 13.3% of the within-family variance, which increased rates of gain by 9.5 to 25.8% and 7.7 to 22.4% in open and closed nucleus schemes, respectively. Risk of breeding schemes, measured by the variance of the selection response, was not increased by the use of markers.

Animals↗

PubMed1991

Reduction of selection differentials in finite populations with a nested full-half sib family structure.

The effect of family structure is of increasing importance in modern breeding schemes, because increased intraclass correlations between relatives due to improved breeding value estimation methods use all family information, and increased family sizes are possible with improved reproduction rates. In addition, reduction of the generation intervals in modern breeding schemes leads to increased intraclass (family) correlations, because young animals have little information on individual or on progeny performance. This paper derives an approximation for the selection differential in a population divided into families. The result is then extended to an approximation for the selection differentials in populations that are divided into full sib families within paternal half sib families. The approximation is compared with Monte Carlo results, from which it is concluded that the approximation is satisfactory (i.e., rarely more than 5% in error). In some practical situations the approximation is shown to be not more than 2% in error. With high intraclass correlations and few animals selected, the reduction of the selection differentials is maximal. When breeding values are based on family information and the family structure is not accounted for, overestimation of the selection differentials can be up to 61%.

Animal Husbandry↗