Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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    Time-to-event analysis of mastitis at first-lactation in Valle del Belice ewes
    Portolano, B. ; Firlocchiaro, R. ; Kaam, J.B.C.H.M. van; Riggio, V. ; Maizon, D.O. - \ 2007
    Livestock Science 110 (2007)3. - ISSN 1871-1413 - p. 273 - 279.
    somatic-cell counts - clinical mastitis - dairy-cows - bayesian-analysis - survival analysis - norwegian cattle - milk-yield - sheep - lactation - selection
    A time-to-event study for mastitis at first-lactation in Valle del Belice ewes was conducted, using survival analysis with an animal model. The goals were to evaluate the effect of lambing season and level of milk production on the time from lambing to the day when a ewe experienced a test-day with a recorded SCC greater than or equal to 750,000 cells/ml, and to estimate, for this trait, its heritability and the percentage of variation explained by the flock-year of lambing effect. A dataset with 2468 first-lactation records, collected from 1998 to 2003 in Valle del Belice ewes allocated in 17 flocks, was used. The Cox model used included lambing season and total milk yield adjusted for lactation length as fixed effects and flock-year of lambing effect and individual additive genetic effect as random effects. In total 40.5% of the records were censored. Results indicated that ewes lambing from April to July were at a higher risk of mastitis than those lambing from August to November (conventional season), and that ewes in the highest class of milk production were at a higher risk of mastitis than those in the lowest level. The heritability for the time interval between lambing and first test-day with mastitis was 3% on the logarithmic scale and 4% on the real scale. The proportion of variation, in the time interval between lambing and first test-day with mastitis, explained by the flock-year of lambing effect was 19% on the logarithmic scale and 27% on the real scale; this seems to stress the importance of flock management.
    GeneticParameters for Milk Somatic Cell Score and Relationships with Production Traits in Primparous Dairy Sheep
    Riggio, V. ; Finocchiaro, R. ; Kaam, J.B.C.H.M. van; Portolano, B. ; Bovenhuis, H. - \ 2007
    Journal of Dairy Science 90 (2007)4. - ISSN 0022-0302 - p. 1998 - 2003.
    mastitis resistance - protein percentage - lactation curves - animal-model - ewes - yields - count - fat - heritability - selection
    A total of 13,066 first-lactation test-day records of 2,277 Valle del Belice ewes from 17 flocks were used to estimate genetic parameters for somatic cell scores (SCS) and milk production traits, using a repeatability test-day animal model. Heritability estimates were low and ranged from 0.09 to 0.14 for milk, fat, and protein yields, and contents. For SCS, the heritability of 0.14 was relatively high. The repeatabilities were moderate and ranged from 0.29 to 0.47 for milk production traits. The repeatability for SCS was 0.36. Flock-test-day explained a large proportion of the variation for milk production traits, but it did not have a big effect on SCS. The genetic correlations of fat and protein yields with fat and protein percentages were positive and high, indicating a strong association between these traits. The genetic correlations of milk production traits with SCS were positive and ranged from 0.16 to 0.31. The results showed that SCS is a heritable trait in Valle del Belice sheep and that single-trait selection for increased milk production will also increase SCS.
    Bayesian reanalysis of a quantitative trait locus accounting for multiple environments by scaling in broilers
    Kaam, J.B.C.H.M. van; Bink, M.C.A.M. ; Maizon, D.O. ; Arendonk, J.A.M. van; Quaas, R.L. - \ 2006
    Journal of Animal Science 84 (2006)8. - ISSN 0021-8812 - p. 2009 - 2021.
    whole genome scan - linkage analysis - genetic-linkage - model approach - multivariate - efficiency - complexes - chickens - populations - univariate
    A Bayesian method was developed to handle QTL analyses of multiple experimental data of outbred populations with heterogeneity of variance between sexes for all random effects. The method employed a scaled reduced animal model with random polygenic and QTL allelic effects. A parsimonious model specification was applied by choosing assumptions regarding the covariance structure to limit the number of parameters to estimate. Markov chain Monte Carlo algorithms were applied to obtain marginal posterior densities. Simulation demonstrated that joint analysis of multiple environments is more powerful than separate single trait analyses of each environment. Measurements on broiler BW obtained from 2 experiments concerning growth efficiency and carcass traits were used to illustrate the method. The population consisted of 10 full-sib families from a cross between 2 broiler lines. Microsatellite genotypes were determined on generations 1 and 2, and phenotypes were collected on groups of generation 3 animals. The model included a polygenic correlation, which had a posterior mean of 0.70 in the analyses. The reanalysis agreed on the presence of a QTL in marker bracket MCW0058-LEI0071 accounting for 34% of the genetic variation in males and 24% in females in the growth efficiency experiment. In the carcass experiment, this QTL accounted for 19% of the genetic variation in males and 6% in females
    Bayesian re-analysis of a quantitative trait locus in broilers accounting for multiple environments by scaling
    Kaam, J.B.C.H.M. van; Bink, M.C.A.M. ; Arendonk, J.A.M. van; Quaas, R.L. - \ 2004
    A Bayesian method was developed to handle QTL analyses of multiple experimental data of outbred populations with heterogeneity of variance between sexes for all random effects. The method employed a scaled reduced animal model with random polygenic and QTL allelic effects. A parsimonious model specification was applied by choosing assumptions regarding the covariance structure to limit the number of parameters to estimate. Markov chain Monte Carlo algorithms were applied to obtain marginal posterior densities. Simulation demonstrated that joint analysis of multiple environments is more powerful than separate single trait analyses of each environment. Measurements on broiler BW obtained from 2 experiments concerning growth efficiency and carcass traits were used to illustrate the method. The population consisted of 10 full-sib families from a cross between 2 broiler lines. Microsatellite genotypes were determined on generations 1 and 2, and phenotypes were collected on groups of generation 3 animals. The model included a polygenic correlation, which had a posterior mean of 0.70 in the analyses. The reanalysis agreed on the presence of a QTL in marker bracket MCW0058-LEI0071 accounting for 34% of the genetic variation in males and 24% in females in the growth efficiency experiment. In the carcass experiment, this QTL accounted for 19% of the genetic variation in males and 6% in females.
    Scaling to account for heterogeneous variances in multiple trait Bayesian QTL analysis
    Kaam, J.B.C.H.M. van; Bink, M.C.A.M. ; Arendonk, J.A.M. van; Quaas, R.L. - \ 2002
    In: Proceedings 7th World Congress on Genetics Applied to Livestock Production, Montpellier, France, 30 August, 2002 - p. 609 - 612.
    Scaling to account for heterogeous variances in a Bayesian analysis of broiler quantitative trait loci
    Kaam, J.B.C.H.M. van; Bink, M.C.A.M. ; Bovenhuis, H. ; Quaas, R.L. - \ 2002
    Journal of Animal Science 80 (2002). - ISSN 0021-8812 - p. 45 - 56.
    A Bayesian method for QTL analysis that is capable of accounting for heterogeneity of variance between sexes, is introduced. The Bayesian method uses a parsimonious model that includes scaling parameters for polygenic and QTL allelic effects per sex. Furthermore, the method employs a reduced animal model to increase computational efficiency. Markov Chain Monte Carlo techniques were applied to obtain estimates of genetic parameters. In comparison with previous regression analyses, the Bayesian method 1) estimates dispersion parameters and polygenic effects, 2) uses individual observations instead of offspring averages, and 3) estimates fixed effect levels and covariates and heterogeneity of variance between sexes simultaneously with other parameters, taking uncertainties fully into account. Broiler data collected in a feed efficiency and a carcass experiment were used to illustrate QTL analysis based on the Bayesian method. The experiments were conducted in a population consisting of 10 full-sib families of a cross between two broiler lines. Microsatellite genotypes were determined on generation 1 and 2 animals and phenotypes were collected on third-generation offspring from mating members from different families. Chromosomal regions that seemed to contain a QTL in previous regression analyses and showed heterogeneity of variance were chosen. Traits analyzed in the feed efficiency experiment were BW at 48 d and growth, feed intake, and feed intake corrected for BW between 23 and 48 d. In the carcass experiment, carcass percentage was analyzed. The Bayesian method was successful in finding QTL in all regions previously detected.
    Detection of genes on the Z-chromosome affecting growth and feathering in broilers
    Hamoen, F.F.A. ; Kaam, J.B.H.C.M. van; Groenen, M.A.M. ; Vereijken, A.L.J. ; Bovenhuis, H. - \ 2001
    Poultry Science 80 (2001). - ISSN 0032-5791 - p. 527 - 534.
    Detection of genes located on the Z-chromosome differs from the detection of genes located on autosomal chromosomes. In the present study, the chicken Z-chromosome is scanned for genes affecting growth traits and feathering. For this purpose, data from a three-generation full-sib-half-sib design was available: parents, full-sib offspring, and half-sib grandoffspring. The parents and full-sib offspring were genotyped for 17 markers on the Z-chromosome. Phenotypic data were only available for grandoffspring. Only the segregation of male chromosomes provides information on the presence of genes, and therefore, a half-sib interval mapping approach was used. The feathering gene was detected significantly and was located between markers ADL0022 and MCW0331. No significant indications were found for the presence of quantitative trait loci affecting growth traits on the Z-chromosome.
    Detection of quantitative trait loci in broilers
    Kaam, J.T. van - \ 2000
    Agricultural University. Promotor(en): E.W. Brascamp; J.A.M. van Arendonk; R.L. Quaas. - S.l. : S.n. - ISBN 9789058082633 - 175
    vleeskuikens - genen - kwantitatieve kenmerken - lichaamsgewicht - groei - voeropname - genetische kartering - genetische merkers - regressieanalyse - broilers - genes - quantitative traits - body weight - growth - feed intake - genetic mapping - genetic markers - regression analysis

    This dissertation deals with the development and application of methods for the detection of genes with a substantial influence on quantitative traits, so called quantitative trait loci (QTLs) in broilers. For the purpose of detection of QTLs, an experiment was initiated. A three generation full sib-half sib experimental population consisting of 10 full sib families originating from a cross between two broiler dam lines was set up. Genotypes of up to 437 microsatellite markers on 28 linkage groups were determined on all 20 generation one and 451 generation two full sib animals. Generation three half sib animals were divided in hatches and phenotypic observations on several traits were collected in different experiments. Data from a feed efficiency and a carcass experiment were used in the QTL analyses. In both experiments approximately 2,000 phenotypic observations were collected per trait.

    The data were analysed using a two step procedure: first average adjusted progeny trait values were calculated, and secondly QTL analysis was performed using the average adjusted progeny trait values as the dependent variable. Large differences in mean and variance of male and female body weight were found. Prior adjustment of these differences is necessary to ensure that each observation has a similar effect within the QTL analysis. Therefore, a bivariate analysis was used to estimate variances, fixed and genetic effects. These estimated effects were used to calculate average adjusted progeny trait values for all generation two animals by averaging progeny observations, which were standardised after adjusting for fixed and maternal genetic effects and for the additive genetic contribution of the other parent. A full sib regression interval mapping approach was applied, because it enables a quick initial scan of the entire genome and simultaneously includes the segregation of alleles from both generation one parents. The QTL analyses were across family and average adjusted progeny trait values were weighted to account for the number of third generation observations included. In total, 24 autosomal linkage groups were analysed in this chapter. The most likely QTL position was found between markers MCW0058 and LEI0071 on chromosome 1.

    This approach was applied on all traits in a feed efficiency experiment. These traits were body weight at 23 and 48 days, growth between 23 and 48 days, feed intake between 23 and 48 days, the same feed intake adjusted for body weight, and feed efficiency. In total 27 autosomal linkage groups were analysed and four QTLs for body weight, growth and feed intake traits were found. The most significant QTL was located between markers UMA1.107 and MCW0058 on chromosome 1 and had a 4% genomewise significance for feed intake between 23 and 48 days. Furthermore, this QTL exceeded suggestive linkage for growth between 23 and 48 days and body weight at 48 days. The other QTLs showed suggestive linkage. The second QTL, affecting feed intake between 23 and 48 days, was located between markers ADL0289 and ADL0262 on linkage group WAU26. On chromosome 4, between markers MCW0085 and LEI0122, a third QTL was found, which had an effect on both feed intake traits. Finally, a fourth QTL, which affected feed intake adjusted for body weight, was located between markers MCW0082 and MCW0341 on chromosome 2.

    In a similar way, the analyses of all traits in a carcass experiment were performed. These traits were body weight at 48 days, carcass weight, carcass percentage, breast meat colour unadjusted and adjusted for body weight, original leg scores, transformed leg scores and transformed leg scores adjusted for body weight. Two suggestive QTLs for carcass percentage and meat colour were detected. The QTL affecting carcass percentage was located between markers ADL0183 and LEI0079 on chromosome 1. The QTL for meat colour was located on chromosome 2 and gave a peak between markers MCW0185 and MCW0234 and between markers MCW0264 and ADL0164.

    The sex chromosomes were omitted from the previous genome scans. Later the Z chromosome was analysed for growth and carcass traits. Additionally, feathering was analysed. For the Z chromosome, only the segregation of male chromosomes provides information on the presence of genes and therefore a half sib interval mapping approach was used. No QTLs were found which affected growth or carcass traits. For feathering, however, a huge QTL effect was found. The feathering gene was located between markers ADL0022 and MCW0331.

    For a more detailed analysis, an existing Bayesian method is extended to enable the analysis of the experimental broiler data accounting for the heterogeneity of variance between sexes. Heterogeneity is accounted for by including separate scale parameters for the polygenic and QTL allelic effects per sex and by separate error variances per sex. A Bayesian analysis is undertaken on chromosomal regions where QTLs were found with the initial regression analyses. Advantages of the Bayesian method in comparison with the regression analysis are that normally distributed random polygenic and QTL effects are modelled and dispersion parameters are estimated for all random terms in the model. Furthermore, individual observations are used instead of offspring averages and mate correction is no longer necessary, because all genetic relations are taken into account through relationship matrices. By simultaneous sampling of all model parameters, uncertainties are taken into account. The use of a reduced animal model enables the analysis of complex populations. Markov Chain Monte Carlo algorithms were applied to obtain solutions. The Bayesian method was successful in finding QTLs in all regions previously detected.

    The Bayesian method is extended even further to enable a bivariate analysis of body weight data obtained in both experiments. Combining data from both experiments is expected to improve the QTL detection power and estimation accuracy. For each sex-trait combination separate error variances and separate scale parameters for the polygenic and QTL allelic effects were included. Furthermore, a polygenic correlation was included. Broiler body weight data measured at 48 days was used to illustrate the method. The QTL on chromosome 1 found previously in the feed efficiency experiment but not in the carcass experiment, was now detected in both experiments demonstrating that the QTL detection power indeed increased. The most likely QTL location, however, was in a different marker bracket for both experiments.

    Finally, the number of QTLs and the power of the design are discussed. Differences between the regression and the Bayesian method are mentioned and potential extensions on both methods are discussed. With the regression method, a two QTL analysis was applied to increase the power and bootstrapping was used to provide confidence intervals of the QTL position. For the Bayesian method, the most important extensions to be implemented are the sampling of the QTL position, the inclusion of correlated residuals, which would enable bivariate analysis of traits measured on the same individuals, and the ability to handle imprinting.

    Analysis of quantitative trait loci in broilers using a Bayesian mixed model
    Kaam, J.B.C.H.M. van; Bink, M.C.A.M. ; Groenen, M.A.M. ; Bovenhuis, H. ; Arendonk, J.A.M. van - \ 1999
    In: From Jay L. Lush to genomics: Visions for animal breeding and genetics
    Whole genome scan in chickens for quantitative trait loci affecting growth and feed efficiency
    Kaam, J.B.C.H.M. van; Groenen, M.A.M. ; Bovenhuis, H. ; Veenendaal, A. ; Vereijken, A.L.J. ; Arendonk, J.A.M. van - \ 1999
    Poultry Science 78 (1999)1. - ISSN 0032-5791 - p. 15 - 23.
    Analysis of quantitative trait loci in broilers using a Bayesian mixed model
    Kaam, J.B.C.H.M. van; Bink, M.C.A.M. ; Groenen, M.A.M. ; Bovenhuis, H. ; Arendonk, J.A.M. van - \ 1999
    In: Book of Abstracts of the 50th Annual Meeting of the European Association for Animal Production. Wageningen: Wageningen Pers, 1999 - p. 38 - 38.
    Whole genome scan in chickens for quantitative trait loci affecting carcass traits
    Kaam, J.B.C.H.M. van; Groenen, M.A.M. ; Bovenhuis, H. ; Veenendaal, A. ; Vereijken, A.L.J. ; Arendonk, J.A.M. van - \ 1999
    Poultry Science 78 (1999)8. - ISSN 0032-5791 - p. 1091 - 1099.
    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.
    Objective Plant Quality Measurement by Image Processing
    Meuleman, J. ; Hofstee, J.W. ; Kaam, C. van - \ 1998
    In: Proceedings Sensoral 1998, 23-26 February 1998, Montpellier, France, 8 pp
    Whole genome scan for quantitative trait loci affecting growth and feed efficiency traits in chicken using a three generation design.
    Kaam, J.B.C.H.M. van; Arendonk, J.A.M. van; Groenen, M.A.M. ; Bovenhuis, H. ; Vereijken, A.L.J. - \ 1998
    In: Proc. 6th World Congress on Genetics Applied to Livestock Production, Armidale, Australia, Volume 24 - p. 310 - 313.
    Whole genome scan for quantitative trait loci affecting body weight in chickens using a three generation design.
    Kaam, J.B.C.H.M. van; Arendonk, J.A.M. van; Groenen, M.A.M. ; Bovenhuis, H. ; Vereijken, A.L.J. ; Crooijmans, R.P.M.A. ; Poel, J.J. van der; Veenendaal, A. - \ 1998
    Livestock Production Science 54 (1998). - ISSN 0301-6226 - p. 133 - 150.
    Objective plant quality measurement by digital image processing.
    Meuleman, J. ; Hofstee, J.W. ; Kaam, C. van - \ 1998
    In: Sensoral '98, Montpellier, France (1998)
    QTL mapping in chicken using a three generation full sib family structure of an extreme broiler x broiler cross.
    Groenen, M.A.M. ; Crooijmans, R.P.M.A. ; Veenendaal, A. ; Kaam, J.B.C.H.M. van; Vereijken, A.L.J. ; Arendonk, J.A.M. van; Poel, J.J. van der - \ 1997
    Animal Biotechnology 8 (1997). - ISSN 1049-5398 - p. 41 - 46.
    Gene hunting in chicken: Dissection of complex traits using automated fluorescent genotyping of microsatellite loci.
    Groenen, M.A.M. ; Crooijmans, R.P.M.A. ; Veenendaal, A. ; Kaam, J.B.C.H.M. van; Vereijken, A. ; Arendonk, J.A.M. van; Herbergs, P.J. ; Poel, J.J. van der - \ 1997
    In: Proc. Plant & Animal Genome V, San Diego, January 12-16 - p. 20 - 20.
    Neural networks for classication of potted plants.
    Kaam, C. van - \ 1997
    In: 3rd International Symposium on Sensors in Horticulture, Tiberias, Israel - p. 28 - 29.
    Neural networks for classication of potted plants.
    Kaam, C. van - \ 1997
    In: 3rd International Symposium on Sensors in Horticulture, Tiberias, Israel (1997) 8 pp
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