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Search Results: 1 - 10 of 15178 matches for " Bink Marco "
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A Bayesian QTL linkage analysis of the common dataset from the 12th QTLMAS workshop
Bink Marco CAM,van Eeuwijk Fred A
BMC Proceedings , 2009,
Abstract: Background To compare the power of various QTL mapping methodologies, a dataset was simulated within the framework of 12th QTLMAS workshop. A total of 5865 diploid individuals was simulated, spanning seven generations, with known pedigree. Individuals were genotyped for 6000 SNPs across six chromosomes. We present an illustration of a Bayesian QTL linkage analysis, as implemented in the special purpose software FlexQTL. Most importantly, we treated the number of bi-allelic QTL as a random variable and used Bayes Factors to infer plausible QTL models. We investigated the power of our analysis in relation to the number of phenotyped individuals and SNPs. Results We report clear posterior evidence for 12 QTL that jointly explained 30% of the phenotypic variance, which was very close to the total of included simulation effects, when using all phenotypes and a set of 600 SNPs. Decreasing the number of phenotyped individuals from 4665 to 1665 and/or the number of SNPs in the analysis from 600 to 120 dramatically reduced the power to identify and locate QTL. Posterior estimates of genome-wide breeding values for a small set of individuals were given. Conclusion We presented a successful Bayesian linkage analysis of a simulated dataset with a pedigree spanning several generations. Our analysis identified all regions that contained QTL with effects explaining more than one percent of the phenotypic variance. We showed how the results of a Bayesian QTL mapping can be used in genomic prediction.
Bayesian estimation of dispersion parameters with a reduced animal model including polygenic and QTL effects
Marco CAM Bink, Richard L Quaas, Johan AM Van Arendonk
Genetics Selection Evolution , 1998, DOI: 10.1186/1297-9686-30-2-103
Abstract:
Breeding value estimation with incomplete marker data
Marco CAM Bink, Johan AM Van Arendonk, Richard L Quaas
Genetics Selection Evolution , 1998, DOI: 10.1186/1297-9686-30-1-45
Abstract:
Comparison of analyses of the QTLMAS XIII common dataset. I: genomic selection
Bastiaansen John,Bink Marco,Coster Albart,Maliepaard Chris
BMC Proceedings , 2010,
Abstract: Background Genomic selection, the use of markers across the whole genome, receives increasing amounts of attention and is having more and more impact on breeding programs. Development of statistical and computational methods to estimate breeding values based on markers is a very active area of research. A simulated dataset was analyzed by participants of the QTLMAS XIII workshop, allowing a comparison of the ability of different methods to estimate genomic breeding values. Methods A best case scenario was analyzed by the organizers where QTL genotypes were known. Participants submitted estimated breeding values for 1000 unphenotyped individuals together with a description of the applied method(s). The submitted breeding values were evaluated for correlation with the simulated values (accuracy), rank correlation of the best 10% of individuals and error in predictions. Bias was tested by regression of simulated on estimated breeding values. Results The accuracy obtained from the best case scenario was 0.94. Six research groups submitted 19 sets of estimated breeding values. Methods that assumed the same variance for markers showed accuracies, measured as correlations between estimated and simulated values, ranging from 0.75 to 0.89 and rank correlations between 0.58 and 0.70. Methods that allowed different marker variances showed accuracies ranging from 0.86 to 0.94 and rank correlations between 0.69 and 0.82. Methods assuming equal marker variances were generally more biased and showed larger prediction errors. Conclusions The best performing methods achieved very high accuracies, close to accuracies achieved in a best case scenario where QTL genotypes were known without error. Methods that allowed different marker variances generally outperformed methods that assumed equal marker variances. Genomic selection methods performed well compared to traditional, pedigree only, methods; all methods showed higher accuracies than those obtained for breeding values estimated solely on pedigree relationships.
Genomic Selection for Fruit Quality Traits in Apple (Malus×domestica Borkh.)
Satish Kumar, David Chagné, Marco C. A. M. Bink, Richard K. Volz, Claire Whitworth, Charmaine Carlisle
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0036674
Abstract: The genome sequence of apple (Malus×domestica Borkh.) was published more than a year ago, which helped develop an 8K SNP chip to assist in implementing genomic selection (GS). In apple breeding programmes, GS can be used to obtain genomic breeding values (GEBV) for choosing next-generation parents or selections for further testing as potential commercial cultivars at a very early stage. Thus GS has the potential to accelerate breeding efficiency significantly because of decreased generation interval or increased selection intensity. We evaluated the accuracy of GS in a population of 1120 seedlings generated from a factorial mating design of four females and two male parents. All seedlings were genotyped using an Illumina Infinium chip comprising 8,000 single nucleotide polymorphisms (SNPs), and were phenotyped for various fruit quality traits. Random-regression best liner unbiased prediction (RR-BLUP) and the Bayesian LASSO method were used to obtain GEBV, and compared using a cross-validation approach for their accuracy to predict unobserved BLUP-BV. Accuracies were very similar for both methods, varying from 0.70 to 0.90 for various fruit quality traits. The selection response per unit time using GS compared with the traditional BLUP-based selection were very high (>100%) especially for low-heritability traits. Genome-wide average estimated linkage disequilibrium (LD) between adjacent SNPs was 0.32, with a relatively slow decay of LD in the long range (r2 = 0.33 and 0.19 at 100 kb and 1,000 kb respectively), contributing to the higher accuracy of GS. Distribution of estimated SNP effects revealed involvement of large effect genes with likely pleiotropic effects. These results demonstrated that genomic selection is a credible alternative to conventional selection for fruit quality traits.
Microsatellite allele dose and configuration establishment (MADCE): an integrated approach for genetic studies in allopolyploids
Thijs van Dijk, Yolanda Noordijk, Tiphaine Dubos, Marco CAM Bink, Bert J Meulenbroek, Richard GF Visser, Eric van de Weg
BMC Plant Biology , 2012, DOI: 10.1186/1471-2229-12-25
Abstract: Two case studies are presented to demonstrate the power and robustness of the MADCE method. In the mapping case, five microsatellites were analysed. These microsatellites amplified 35 different alleles based on size. Using MADCE, we uncovered 30 highly informative segregating alleles. A conventional approach would have yielded only 19 fully informative and six partially informative alleles. Of the ten alleles that were present in all progeny (and thereby ignored or considered homozygous when using conventional approaches), six were found to segregate by dosage when analysed with MADCE. Moreover, the full allelic configuration of the mapping parents could be established, including null alleles, homozygous loci, and alleles that were present on multiple homoeologues. In the second case, 21 pedigreed cultivars were analysed using MADCE, resulting in the establishment of the full allelic configuration for all 21 cultivars and a tracing of allele flow over multiple generations.The procedure described in this study (MADCE) enhances the efficiency and information content of mapping studies in allopolyploids. More importantly, it is the first technique to allow the determination of the full allelic configuration in pedigreed breeding germplasm from allopolyploid plants. This enables pedigree-based marker-trait association studies the use of algorithms developed for diploid crops, and it may increase the effectiveness of LD-based association studies. The MADCE method therefore enables researchers to tackle many of the genotyping problems that arise when performing mapping, pedigree, and association studies in allopolyploids. We discuss the merits of MADCE in comparison to other marker systems in polyploids, including SNPs, and how MADCE could aid in the development of SNP markers in allopolyploids.Polyploidy is an integral part of the evolution of all plant species [1]. Several important crop species are polyploids, including bread wheat (Triticum aestivum, allohexaploid), c
Compara??o de diferentes estratégias para a análise de características de crescimento e de carca?a de suínos cruzados: modelos finito e infinitesimal poligênico
Gon?alves, Tarcísio de Moraes;Oliveira, Henrique Nunes de;Bovenhuis, Henk;Bink, Marco;Van Arendonk, Johan;
Revista Brasileira de Zootecnia , 2005, DOI: 10.1590/S1516-35982005000500013
Abstract: a bayesian marker-free segregation analysis was applied for the estimation of variance components and to search for evidence of segregation genes affecting two carcass traits: intramuscular fat (imf), %, and backfat thickness (bf), mm ; and one growth trait: body weight gain (lg) from 25 to 90 kg, approximately, g/day. in this study, 1,257 animals from the f2 design produced by breeding among pigs meishan (male) and dutch large white and landrace lines (female) were used. in animal breeding, finite polygenic models (fpm) may be an alternative to the infinitesimal polygenic model (ipm) for genetic evaluation of populations with multiple-generations pedigree for quantitative traits. fpm, ipm and fpm combined with ipm were empirically tested for estimation of variance components and number of genes in fpm. estimation of marginal posteriori means of variance components and parameters were performed by using markov chain monte carlo techniques with the gibbs sampler and the reversible jump sampler (metropolis-hastings). the results showed evidence for four major genes (mg), i.e., two for imf and two bf. for bf, the mg explained almost all of genetic variance, while for imf, mg reduced the polygenic variance significantly. the lg was not likely influenced by mg. the polygenic heritability estimates for imf, bf and lg were 0.37, 0.24 and 0.37, respectively. further molecular genetic research, based on the same experimental data, aiming to map the major genes estimated for imf and bf has a high probability of success.
Modelos alternativos para detec??o de locos de características quantitativas (QTL) de carca?a e crescimento nos cromossomos 4, 5 e 7 de suínos
Gon?alves, Tarcísio de Moraes;Oliveira, Henrique Nunes de;Bovenhuis, Henk;Bink, Marco;Van Arendonk, Johan;
Revista Brasileira de Zootecnia , 2005, DOI: 10.1590/S1516-35982005000500014
Abstract: genome scans can be used to identify chromosomal regions and eventually genes that control quantitative traits (qtl) of economic importance. in an experimental cross between meishan (male) and dutch large white and landrace lines (female), 298 f1 and 831 f2 animals were evaluated for intramuscular fat (gim), % and growth trait: body weight gain (gp) from approximately 25 to 90 kg, g/day and 324 f1 and 805 f2 for backfat thickness, mm (et). the animals of generations f1 and f2 were typed for 29 microsatellite markers. linkage was studied among chromosomes 4, 6, 7 and gim, etand gp. qtl analyses using bayesian methodology was applied under three genetic models: infinitesimal polygenic model (mpi); finite polygenic model (mpf) with three loci and mpf combined with mpi. the number of qtl, their map positions in the three chromosomes, and phenotypic effects were all estimated simultaneously within the same framework. the summaries of the estimated parameters were based on the marginal posterior distributions, that were obtained through markov chain monte carlo (mcmc) methods. the results showed two qtls for gim on chromosomes 4 and 6 and two for et on chromosomes 4 and 7. qtls on chromosome 4 for et and gim were detected only under the pmi. failure of theses approaches to detect weight gain qtl was possibly due to insufficient power from marker data or due to absence of segregating qtl on the chromosomes 4, 6 and 7 for this population. this study shows the benefit of analyzing experimental data under different genetic models and these analyses clearly illustrate the utility and wide applicability of bayesian methodology.
Bayesian Markov Random Field Analysis for Protein Function Prediction Based on Network Data
Yiannis A. I. Kourmpetis,Aalt D. J. van Dijk,Marco C. A. M. Bink,Roeland C. H. J. van Ham,Cajo J. F. ter Braak
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0009293
Abstract: Inference of protein functions is one of the most important aims of modern biology. To fully exploit the large volumes of genomic data typically produced in modern-day genomic experiments, automated computational methods for protein function prediction are urgently needed. Established methods use sequence or structure similarity to infer functions but those types of data do not suffice to determine the biological context in which proteins act. Current high-throughput biological experiments produce large amounts of data on the interactions between proteins. Such data can be used to infer interaction networks and to predict the biological process that the protein is involved in. Here, we develop a probabilistic approach for protein function prediction using network data, such as protein-protein interaction measurements. We take a Bayesian approach to an existing Markov Random Field method by performing simultaneous estimation of the model parameters and prediction of protein functions. We use an adaptive Markov Chain Monte Carlo algorithm that leads to more accurate parameter estimates and consequently to improved prediction performance compared to the standard Markov Random Fields method. We tested our method using a high quality S.cereviciae validation network with 1622 proteins against 90 Gene Ontology terms of different levels of abstraction. Compared to three other protein function prediction methods, our approach shows very good prediction performance. Our method can be directly applied to protein-protein interaction or coexpression networks, but also can be extended to use multiple data sources. We apply our method to physical protein interaction data from S. cerevisiae and provide novel predictions, using 340 Gene Ontology terms, for 1170 unannotated proteins and we evaluate the predictions using the available literature.
Consistency between hydrological model, large aperture scintillometer and remote sensing based evapotranspiration estimates for a heterogeneous catchment
B. Samain, G. W. H. Simons, M. P. Voogt, W. Defloor, N.-J. Bink,V. R. N. Pauwels
Hydrology and Earth System Sciences (HESS) & Discussions (HESSD) , 2012,
Abstract: The catchment averaged actual evapotranspiration rate is a hydrologic model variable that is difficult to quantify. Evapotranspiration rates – up till present – cannot be continuously observed at the catchment scale. The objective of this paper is to estimate the evapotranspiration rates (or its energy equivalent, the latent heat fluxes LE) for a heterogeneous catchment of 102.3 km2 in Belgium using three fundamentally different algorithms. One possible manner to observe this variable could be the continuous measurement of sensible heat fluxes (H) across large distances (in the order of kilometers) using a large aperture scintillometer (LAS), and converting these observations into evapotranspiration rates. Latent heat fluxes are obtained through the energy balance equation using a series of sensible heat fluxes measured with a LAS over a distance of 9.5 km in the catchment, and point measurements of net radiation (Rn) and ground heat flux (G) upscaled to catchment average through the use of TOPLATS, a physically based land surface model. The resulting LE-values are then compared to results from the remote sensing based surface energy balance algorithm ETLook and the land surface model. Firstly, the performance of ETLook for the energy balance terms has been assessed at the point scale and at the catchment scale. Secondly, consistency between daily evapotranspiration rates from ETLook, TOPLATS and LAS is shown.
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