Biomedical subjects

J A Van Arendonk

Publications and source records attributed to J A Van Arendonk.

At least 19 recordsLinked to original sources

PubMed2001

Predicting rates of inbreeding for livestock improvement schemes.

This article presents a deterministic method to predict rates of inbreeding (deltaF) for typical livestock improvement schemes. The method is based on a recently developed general theory to predict rates of inbreeding, which uses the concept of long-term genetic contributions. A typical livestock breeding population was modeled, with overlapping generations, BLUP selection, and progeny testing of male selection candidates. Two types of selection were practiced: animals were either selected by truncation on estimated breeding values (EBV) across age classes, or the number of parents selected from each age class was set to a fixed value and truncation selection was practiced within age classes. Bulmer's equilibrium genetic parameters were obtained by iterating on a pseudo-BLUP selection index and deltaF was predicted for the equilibrium situation. Predictions were substantially more accurate than predictions from other available methods, which ignore the effect of selection on deltaF. Predictions were accurate for schemes with up to 20 sires. Predicted deltaF was somewhat too low for schemes with more than 20 sires, which was due to the use of simple linear models to predict genetic contributions. The present method provides a computationally feasible (i.e., deterministic) tool to consider both the rate of inbreeding and the rate of genetic gain when optimizing livestock improvement schemes.

Animals↗

PubMed2001

Impact of area and sire by herd interaction on heritability estimates for somatic cell count in Italian Holstein Friesian cows.

The aim of the paper was to estimate variance components for somatic cell scores for Italian Holsteins using data from three different areas of the country. A total of 2,202,804 first-parity test-day records, collected from 1990 to 1997 in three areas of Italy (Mantova, Milano, and Parmigiano cheese area), were available for study. The areas differ in herd size, feeding systems and especially in milk use. A minimum standard of quality is also required by some specific methods of cheese production, as for example from the Parmigiano Reggiano cheese chain. These reasons, taken together, affect the attention given to the quality of milk production in herds, and, therefore, to the sanitation levels. A pedigree file was extracted from the national database of Holstein Friesian breed. For computational reasons, eight samples of the data were extracted per area. Variance components were estimated by sample using two different test-day repeatability models. The first model included fixed effects of herd-test date, days in milk (30-d intervals) and calving month, and random effects of permanent environment, additive genetic and residual error. Estimated heritabilities in the first model ranged from 0.06 to 0.09 and repeatabilities from 0.36 to 0.45. Only small differences were detected among areas. In the second model, a random sire x herd interaction effect was added. Including the sire x herd effect resulted in heritability estimates ranging between 0.05 and 0.08 and repeatabilities from 0.35 to 0.45. The analysis revealed that only a small fraction of the total variance (0.35 to 1.5%) could be explained by sire x herd interaction effect. Based on this research, it appears that parameter estimates for somatic cell count do not differ by region, and inclusion of a sire x herd interaction effect is unnecessary.

Animals↗

PubMed2000

A general procedure for predicting rates of inbreeding in populations undergoing mass selection.

Predictions of rates of inbreeding (DeltaF), based on the concept of long-term genetic contributions assuming the infinitesimal model, are developed for populations with discrete or overlapping generations undergoing mass selection. Phenotypes of individuals are assumed to be recorded prior to reproductive age and to remain constant over time. The prediction method accounts for inheritance of selective advantage both within and between age classes and for changing selection intensities with age. Terms corresponding to previous methods that assume constant selection intensity with age are identified. Predictions are accurate (relative errors < or =8%), except for cases with extreme selection intensities in females in combination with high heritability. With overlapping generations DeltaF reaches a maximum when parents are equally distributed over age classes, which is mainly due to selection of the same individuals in consecutive years. DeltaF/year decreases much more slowly compared to DeltaF/generation as the number of younger individuals increases, whereas the decrease is more similar as the number of older individuals increases. The minimum DeltaF (per year or per generation) is obtained when most parents were in the later age classes, which is mainly due to an increased number of parents per generation. With overlapping generations, the relationship between heritability and DeltaF is dependent on the age structure of the population.

Inbreeding↗

PubMed2000

The effect of adipocyte and heart fatty acid-binding protein genes on intramuscular fat and backfat content in Meishan crossbred pigs.

Effects of genetic variation in porcine adipocyte and heart fatty acid-binding protein genes, A-FABP and H-FABP, respectively, on intramuscular fat (IMF) content and backfat thickness (BFT) were examined in F2 crossbreds of Meishan and Western pigs. The involvement of each FABP gene in IMF accretion was studied to confirm previous results for Duroc pigs. The F2 crossbred pigs were genotyped for various markers including microsatellite sequences situated within both FABP genes. Linkage analysis assigned the A-FABP and H-FABP genes to marker intervals S0001-S0217 (20 cM) on SSC4 and Sw316-S0003 (16.6 cM) on SSC6, respectively, refining previous chromosomal assignments. Next, the role of both chromosome regions/genes on genetic variation in IMF content and BFT was studied by 1) screening SSC4 and SSC6 for QTL affecting both traits by performing a line-cross analysis and 2) estimation of the effect of individual A-FABP and H-FABP alleles on both traits. In the first analysis, suggestive and chromosome-wise significant evidence for a QTL affecting IMF was detected on SSC6. The H-FABP gene is a candidate gene for this effect because it resides within the large region containing this putative QTL. The second analysis showed a considerable but nonsignificant effect of H-FABP microsatellite alleles on IMF content. Suggestive evidence for a QTL affecting BFT was found on SSC6, but H-FABP was excluded as a candidate gene. In conclusion, present and previous results support involvement of H-FABP gene polymorphisms in IMF accretion independently from BFT in pigs. Therefore, implementation of these polymorphisms in marker-assisted selection to control IMF content independently from BFT may be considered. In contrast to previous findings for Duroc pigs, no evidence was found for an effect of the A-FABP gene on IMF or BFT in this population.

Adipocytes↗

PubMed2000

Whole genome scan to detect quantitative trait loci for conformation and functional traits in dairy cattle.

A granddaughter design was used to locate quantitative trait loci determining conformation and functional traits in dairy cattle. In this granddaughter design, consisting of 20 Holstein Friesian grandsires and 833 sons, genotypes were determined for 277 microsatellite markers covering the whole genome. Breeding values for 27 traits, regarding conformation (18), fertility (2), birth (4), workability (2), and udder health (1), were evaluated in an across-family analysis using multimarker regression. Significance thresholds were determined using a permutation test. The across-family analysis suggested the presence of 61 quantitative trait loci when 27 (i.e., one for each trait) were expected by chance. The test statistic exceeded the genomewise significance threshold for the following traits and chromosomes: chest width on chromosome 2; gestation length on chromosome 4; stature, body capacity, and size on chromosome 5; dairy character on chromosome 6; angularity on chromosome 12; fore udder attachment on chromosome 13; and fore udder attachment and front teat placement on chromosome 19. The quantitative trait loci for size traits on chromosomes 2, 5, and 6 may also have an effect on calving ease. The quantitative trait loci for udder traits on chromosomes 13 and 19 may also affect somatic cell score and mastitis resistance. If there are no negative effects on other economically important traits, marker assisted selection using markers associated with these quantitative trait loci can be applied.

Animals↗

PubMed2000

Modeling extended lactations of dairy cows.

Nine mathematical models were compared for their ability to predict daily milk yields (n = 294,986) in standard 305-d and extended lactations of dairy cows of Costa Rica. Lactations were classified by parity (first and later), lactation length (9 to 10, 11 to 12, 13 to 14, 15 to 16, and 16 to 17 mo), and calving to conception interval (1 to 2, 3 to 4, 5 to 6, 7 to 8, and 9 to 10 mo). Of the nine models, the diphasic model and lactation persistency model resulted in the best goodness of fit as measured by adjusted coefficient of determination, residual standard deviation, and Durbin-Watson coefficient. All other models showed less accuracy and positively correlated residuals. In extended lactations, models were also fitted using only test-day records before 305 d, which resulted in a different ranking. The diphasic model showed the best prediction of milk yield in standard and extended lactations. We concluded that the diphasic model provided accurate estimates of milk yield for standard and extended lactations. Interpretation of parameters deserves further attention because of the large variation observed. As expected, the calving to conception interval was found to have a negative effect on milk yield for cows with a standard lactation length. In extended lactations, these negative effects of pregnancy on milk yield were not observed.

Animals↗

PubMed1999

Detection of quantitative trait loci in outbred populations with incomplete marker data.

Augmentation of marker genotypes for ungenotyped individuals is implemented in a Bayesian approach via the use of Markov chain Monte Carlo techniques. Marker data on relatives and phenotypes are combined to compute conditional posterior probabilities for marker genotypes of ungenotyped individuals. The presented procedure allows the analysis of complex pedigrees with ungenotyped individuals to detect segregating quantitative trait loci (QTL). Allelic effects at the QTL were assumed to follow a normal distribution with a covariance matrix based on known QTL position and identity by descent probabilities derived from flanking markers. The Bayesian approach estimates variance due to the single QTL, together with polygenic and residual variance. The method was empirically tested through analyzing simulated data from a complex granddaughter design. Ungenotyped dams were related to one or more sons or grandsires in the design. Heterozygosity of the marker loci and size of QTL were varied. Simulation results indicated a significant increase in power when ungenotyped dams were included in the analysis.

Animals↗

PubMed1999

Whole genome scan in chickens for quantitative trait loci affecting carcass traits.

An experiment was conducted to enable quantitative trait loci (QTL) mapping for carcass traits. The population consisted of 10 full-sib families originating from a cross between male and female founders chosen from two different outcross broiler lines. Founder animals, parents, offspring, and grandoffspring are denoted as generation (G) 0, 1, 2, and 3 animals, respectively. Microsatellite marker genotypes were collected on G1 and G2 animals. Phenotypic observations were collected on G3 animals. Recorded traits were BW at 48 d, carcass weight, carcass percentage, breast meat color, and leg score. Average adjusted progeny trait values were calculated for each G2 animal and for each trait after adjusting phenotypic observations on G3 animals for fixed effects, covariables, the additive genetic contribution of the other parent, and differences between sexes. The average adjusted progeny trait values were used as the dependent variable in the QTL analysis. A QTL analysis was undertaken by modeling the segregation from G1 to G2, using a full-sib across family regression interval mapping approach. In total, 27 autosomal linkage groups covered with 420 markers were analyzed. Genomewise significance thresholds were derived using the permutation test and a Bonferroni correction. Two QTL, affecting two of the five analyzed traits, exceeded suggestive linkage. The most significant QTL was located on Chromosome 1 at 466 cM and showed an effect on carcass percentage. The other QTL, which affected meat color, was located on Chromosome 2 and gave a peak at 345 and 369 cM.

Animals↗

PubMed1999

Combining selection for carcass quality, body weight, and milk traits in dairy cattle.

Alternative selection strategies were evaluated for breeding for carcass quality, body weight, and milk traits in dairy cattle. The efficiency of different alternatives was evaluated by comparing predicted genetic responses in individual traits as well as in the aggregate genotype. Particular interest was paid to the loss of response with indices that partially or totally ignored genetic correlations between traits, reflecting selection on single-trait evaluations. Simplified indices gave almost the same total response as a full multiple-trait index, but relative responses in carcass and milk traits differed between indices. Also studied were the consequences of restricting increase in body weight of dairy cows, while selecting for carcass and milk production traits. Restriction of body weight of cows resulted in considerable loss of predicted total response.

Animals↗

PubMed1999

Optimal replacement and insemination policies for Holstein cattle in the southeastern region of Brazil: the effect of selling animals for production.

Dynamic programming was used to determine optimal replacement and insemination policies for Holstein-Friesian cattle in the southeastern region of Brazil. Optimal insemination and replacement decisions were determined for two disposal alternatives: selling all cows exclusively for slaughter (A) or selling the cows either for slaughter or to other farmers for production (B). Disposal alternative B reflects the common practice among dairy farmers to sell some of their cows to other farmers at a higher price than the carcass price. In the model, cows were described in terms of lactation number, stage of lactation, calving interval, and milk produced during present and previous lactation. For disposal alternative A, the optimal average herd life was 54.9 mo, corresponding to annual replacement and voluntary culling rates of 21.8 and 4.1%, respectively. For disposal alternative B, the optimal average herd life was 44.0 mo, which corresponded to annual replacement and voluntary culling rates of 27.3 and 10.0%, respectively. In this case, from the total of voluntarily culled cows, 70% were sold to other farmers for production. Sensitivity analyses showed that changes in the disposal value of cows and replacement heifer prices strongly influenced the optimal insemination and replacement policy.

Abattoirs↗

PubMed1998

A mixture model approach to the mapping of quantitative trait loci in complex populations with an application to multiple cattle families.

A mixture model approach is presented for the mapping of one or more quantitative trait loci (QTLs) in complex populations. In order to exploit the full power of complete linkage maps the simultaneous likelihood of phenotype and a multilocus (all markers and putative QTLs) genotype is computed. Maximum likelihood estimation in our mixture models is implemented via an Expectation-Maximization algorithm: exact, stochastic or Monte Carlo EM by using a simple and flexible Gibbs sampler. Parameters include allele frequencies of markers and QTLs, discrete or normal effects of biallelic or multiallelic QTLs, and homogeneous or heterogeneous residual variances. As an illustration a dairy cattle data set consisting of twenty half-sib families has been reanalyzed. We discuss the potential which our and other approaches have for realistic multiple-QTL analyses in complex populations.

Animals↗

PubMed1998

Restricted maximum likelihood analysis of linkage between genetic markers and quantitative trait loci for a granddaughter design.

A REML for the estimation of location and variance of a single quantitative trait locus, together with polygenic and residual variance, is described for the analysis of a granddaughter design. The method is based on a mixed linear model that includes the allelic effects of the quantitative trait locus, which are assumed to be normally distributed. Information from four marker loci situated on a single chromosome was available to derive the covariances at the linked quantitative trait locus. A derivative-free algorithm is described that makes use of the specific structure of the granddaughter design. The procedure has been applied to simulated data for a granddaughter design with 50 grandsire families of 40 sires each. Error variance was 60, and total additive genetic variance equaled 40; the quantitative trait locus explained either 10 or 25% of the latter variance. The size of the marker bracket containing the quantitative trait locus was either 10 or 30 cM. The power of detecting the quantitative trait locus ranged from 19 to 99%. Estimates of total genetic variance and variance explained by the quantitative trait locus were found to be empirically unbiased. A small bias was found in location estimates, especially when markers were not fully informative. The accuracy of parameter estimates was greatly improved by the use of information from individual daughters.

Animals↗

PubMed1998

Analysis of test day yield data of Costa Rican dairy cattle.

Estimates of variance components for test day records in an animal model that considered multiple traits over multiple lactations were calculated using REML methodology. Test day records were classified into 11 periods within first and later lactations. Missing ancestors in the relationship matrix were classified in genetic groups. Data were collected from Costa Rican dairy farms. Estimates of components for total and additive genetic variance were clearly heterogeneous during the lactation. Heritabilities for traits in later parities were slightly higher than those for traits in first parity. Heritabilities were highest for records of midlactation. Phenotypic and genetic correlations for adjacent test days were close to 1. Phenotypic correlations were lower than genetic correlations. Heterogeneity of variances during the lactation suggests the adequacy of the multiple-trait test day model to describe milk yield during the lactation. When missing ancestors were allocated to a single base population instead of genetic groups, the estimates of residual variance were lower, and the estimates of genetic variance and genetic correlations were higher. When standardized records were used instead of actual test day records, the estimates of residual and total variance were lower, and the estimates of genetic variance were higher. Consequently, estimates of heritability and genetic correlations were also higher. Use of standardized data obtained by interpolation procedures is not advised for estimation of genetic variance components in a test day model.

Animals↗

PubMed1998

Influence of production circumstances and economic evaluation criteria on economic comparison of breeds and breed crosses.

The ranking of genotypes (i.e., breeds and breed crosses) for economic performance depends on the production circumstances of the herd and the criteria for economic evaluation. In this study, the effects of evaluation criteria and production circumstance are quantified using data from the literature on six genotypes. The economic evaluation criteria measured at herd level included lifetime profit and lifetime profit expressed per day of calving interval, per day of productive lifetime, per day of total herd life, per unit of milk, and per unit of feed energy. Four production circumstances were studied; these circumstances included constraints on the output of milk and on herd use of concentrates, roughages, and both concentrates and roughages. Profit was determined based on the sale of milk, calves, cull cows, and heifers and the expenses incurred for concentrates and roughages, animal deaths, milking time, interest, and other inputs. Results indicate that production circumstances and evaluation criteria largely influence the ranking of genotypes and, therefore, the outcome of economic comparisons. The genotype that ranks the best under a certain criteria and circumstance ranks differently when these situations are altered. In economic comparisons of genotypes aimed at offering recommendations for implementation in smallholder dairy production systems in the tropics, the choice of the evaluation criteria should be determined by the limitation or constraint that characterizes the area where the genotypes are to produce or are currently producing. For example, for situations in which feed availability is limiting, genotypes should be ranked on total profit per unit of feed energy.

Animal Feed↗

PubMed1998

Event-time analysis of reproductive traits of dairy heifers.

Data on the reproductive traits of dairy heifers were analyzed using event-time techniques. Traits analyzed were age at first calving (n = 4631), days to first breeding, and days open (n = 1992) during the first lactation. A proportional hazard model was used that included fixed effects of herd-year, year-season, breed type, herd weight, and heifer weight. Body weights were recorded at 390 d of age, on average. The model for days open and days to first breeding included two additional fixed effects of herd and heifer milk yield at 100 d. A significant effect of heifer weight category on age at first calving was found. The chance of calving was consistently higher for herds and heifers with higher body weight at 390 d and decreased linearly from the top to the lowest quartiles. The effects of herd weight category on days to first breeding and days open were significant. Heifers in herds with a higher average body weight were less likely to be bred, and heifers in herds with lower average body weight were less likely to get pregnant. The effect of heifer weight category on days to first breeding or days open was not significant. The effect of herd milk yield on days to first breeding was significant. Heifers in herds with lower yield were more likely to be bred. The effect of heifer milk yield category on days to first breeding and days open was significant, but no linear trend was found for the estimates of the hazard ratios. The chance of a heifer being bred and becoming pregnant was similar among the first three quartiles and was lower for heifers in the lowest quartile. The probability of a heifer reaching a first calving can be improved by increasing the body weight at 390 d. Body weight at 390 d did not appear to have a large effect on reproductive performance after first calving. High milk yield appears not to have a large negative effect on days open, at least for the milk yield levels analyzed in this study.

Aging↗

PubMed1997

Breeding value and variance component estimation from data containing inbred individuals: application to gynogenetic families in common carp (Cyprinus carpio L.).

Under gynogenetic reproduction, offspring receive genes only from their dams and completely homozygous offspring are produced within one generation. When gynogenetic reproduction is applied to fully inbred individuals, homozygous clone lines are produced. A mixed model method was developed for breeding value and variance component estimation in gynogenetic families, which requires the inverse of the numerator relationship matrix. A general method for creating the inverse for a population with unusual relationships between animals is presented, which reduces to simple rules as is illustrated for gynogenetic populations. The presence of clones in gynogenetic populations causes singularity of the numerator relationship matrix. However, clones can be regarded as repeated observations of the same genotype, which can be accommodated by modifying the incidence matrix, and by considering only unique genotypes in the estimation procedure. Optimum gynogenetic sib family sizes for estimating heritabilities and estimates of their accuracy were derived and compared to those for conventional full-sib designs. This was done by means of a deterministic derivation and by stochastic simulation using Gibbs sampling. Optimum family sizes were smallest for gynogenetic families. Only for low heritabilities, there was a small advantage in accuracy under the gynogenetic design.

Animals↗

PubMed1997

Segregation analyses for presence of major genes affecting growth, backfat, and litter size in Dutch Meishan crossbreds.

Presence of major genes was investigated for two growth traits, backfat thickness, and two litter size traits in the F1 and F2 population of a cross between Meishan and European "White" pig lines. Segregation analyses were performed in a Bayesian setting, estimating the contribution of background polygenes and the contribution of a possible major gene to the expression of the traits considered. In a first analysis, F1 and F2 crossbred data were evaluated; different error variances were fitted for F1 and F2 observations. In the first analysis, significant contributions of major-gene variance were found for the two growth traits, backfat thickness, and litter size at first parity. In a second analysis, F2 data were evaluated to determine whether biases were introduced in the joint analysis of F1 and F2 data. In the second analysis, no major genes were found for growth traits. Major genes affecting backfat and litter size at first parity were confirmed. The gene identified to affect backfat is a dominant gene; the homozygous recessive genotype has approximately 6 mm of additional backfat. The gene identified to affect litter size at first parity also is a dominant gene; the homozygous recessive genotype produces five to six fewer pigs per litter.

Animals↗

PubMed1994

Use of multiple genetic markers in prediction of breeding values.

Genotypes at a marker locus give information on transmission of genes from parents to offspring and that information can be used in predicting the individuals' additive genetic value at a linked quantitative trait locus (MQTL). In this paper a recursive method is presented to build the gametic relationship matrix for an autosomal MQTL which requires knowledge on recombination rate between the marker locus and the MQTL linked to it. A method is also presented to obtain the inverse of the gametic relationship matrix. This information can be used in a mixed linear model for simultaneous evaluation of fixed effects, gametic effects at the MQTL and additive genetic effects due to quantitative trait loci unlinked to the marker locus (polygenes). An equivalent model can be written at the animal level using the numerator relationship matrix for the MQTL and a method for obtaining the inverse of this matrix is presented. Information on several unlinked marker loci, each of them linked to a different locus affecting the trait of interest, can be used by including an effect for each MQTL. The number of equations per animal in this case is 2m + 1 where m is the number of MQTL. A method is presented to reduce the number of equations per animal to one by combining information on all MQTL and polygenes into one numerator relationship matrix. It is illustrated how the method can accommodate individuals with partial or no marker information. Numerical examples are given to illustrate the methods presented. Opportunities to use the presented model in constructing genetic maps are discussed.

Animals↗