Simianer, Henner

[["dc.bibliographiccitation.firstpage","695"],["dc.bibliographiccitation.issue","3"],["dc.bibliographiccitation.journal","Genetics"],["dc.bibliographiccitation.lastpage","708"],["dc.bibliographiccitation.volume","188"],["dc.contributor.author","Ober, Ulrike"],["dc.contributor.author","Erbe, Malena"],["dc.contributor.author","Long, Nanye"],["dc.contributor.author","Porcu, Emilio"],["dc.contributor.author","Schlather, Martin"],["dc.contributor.author","Simianer, Henner"],["dc.date.accessioned","2018-11-07T08:54:41Z"],["dc.date.available","2018-11-07T08:54:41Z"],["dc.date.issued","2011"],["dc.description.abstract","Genomic data provide a valuable source of information for modeling covariance structures, allowing a more accurate prediction of total genetic values (GVs). We apply the kriging concept, originally developed in the geostatistical context for predictions in the low-dimensional space, to the high-dimensional space spanned by genomic single nucleotide polymorphism (SNP) vectors and study its properties in different gene-action scenarios. Two different kriging methods [\"universal kriging\" (UK) and \"simple kriging\" (SK)] are presented. As a novelty, we suggest use of the family of Matern covariance functions to model the covariance structure of SNP vectors. A genomic best linear unbiased prediction (GBLUP) is applied as a reference method. The three approaches are compared in a whole-genome simulation study considering additive, additive-dominance, and epistatic gene-action models. Predictive performance is measured in terms of correlation between true and predicted GVs and average true GVs of the individuals ranked best by prediction. We show that UK outperforms GBLUP in the presence of dominance and epistatic effects. In a limiting case, it is shown that the genomic covariance structure proposed by VanRaden (2008) can be considered as a covariance function with corresponding quadratic variogram. We also prove theoretically that if a specific linear relationship exists between covariance matrices for two linear mixed models, the GVs resulting from BLUP are linked by a scaling factor. Finally, the relation of kriging to other models is discussed and further options for modeling the covariance structure, which might be more appropriate in the genomic context, are suggested."],["dc.identifier.doi","10.1534/genetics.111.128694"],["dc.identifier.isi","000292538900019"],["dc.identifier.pmid","21515573"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/22728"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Genetics Soc Am"],["dc.relation.issn","0016-6731"],["dc.title","Predicting Genetic Values: A Kernel-Based Best Linear Unbiased Prediction With Genomic Data"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","5954"],["dc.bibliographiccitation.issue","9"],["dc.bibliographiccitation.journal","Journal of Dairy Science"],["dc.bibliographiccitation.lastpage","5964"],["dc.bibliographiccitation.volume","96"],["dc.contributor.author","Kramer, M."],["dc.contributor.author","Erbe, Malena"],["dc.contributor.author","Bapst, Beat"],["dc.contributor.author","Bieber, A."],["dc.contributor.author","Simianer, Henner"],["dc.date.accessioned","2018-11-07T09:20:54Z"],["dc.date.available","2018-11-07T09:20:54Z"],["dc.date.issued","2013"],["dc.description.abstract","The aim of this study was to estimate genetic parameters and accuracies of breeding values for a set of functional, behavior, and conformation traits in Brown Swiss cattle. These traits were milking speed, udder depth, position of labia, rank order in herd, general temperament, aggressiveness, milking temperament, and days to first heat. Data of 1,799 phenotyped Brown Swiss cows from 40 Swiss dairy herds were analyzed taking the complete pedigree into account. Estimated heritabilities were within the ranges reported in literature, with results at the high end of the reported values for some traits (e.g., milking speed: 0.42 +/- 0.06, udder depth: 0.42 +/- 0.06), whereas other traits were of low heritability and heritability estimates were of low accuracy (e.g., milking temperament: 0.04 +/- 0.04, days to first heat: 0.02 +/- 0.04). For most behavior traits, we found relatively high heritabilities (general temperament: 0.38 +/- 0.07, aggressiveness: 0.12 +/- 0.08, and rank order in herd: 0.16 +/- 0.06). Position of labia, arguably an indicator trait for pathological urovagina, was genetically analyzed in this study for the first time, and a moderate heritability (0.28 +/- 0.06) was estimated."],["dc.description.sponsorship","European Commission [222623]"],["dc.identifier.doi","10.3168/jds.2012-6236"],["dc.identifier.isi","000323185600050"],["dc.identifier.pmid","23871377"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/28984"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Elsevier Science Inc"],["dc.relation.issn","0022-0302"],["dc.title","Estimation of genetic parameters for novel functional traits in Brown Swiss cattle"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","963"],["dc.bibliographiccitation.issue","5"],["dc.bibliographiccitation.journal","Theoretical and Applied Genetics"],["dc.bibliographiccitation.lastpage","976"],["dc.bibliographiccitation.volume","129"],["dc.contributor.author","Martini, Johannes W. R."],["dc.contributor.author","Wimmer, Valentin"],["dc.contributor.author","Erbe, Malena"],["dc.contributor.author","Simianer, Henner"],["dc.date.accessioned","2018-11-07T10:15:21Z"],["dc.date.available","2018-11-07T10:15:21Z"],["dc.date.issued","2016"],["dc.description.abstract","Key message Models based on additive marker effects and on epistatic interactions can be translated into genomic relationship models. This equivalence allows to perform predictions based on complex gene interaction models and reduces computational effort significantly. In the theory of genome-assisted prediction, the equivalence of a linear model based on independent and identically normally distributed marker effects and a model based on multivariate Gaussian distributed breeding values with genomic relationship as covariance matrix is well known. In this work, we demonstrate equivalences of marker effect models incorporating epistatic interactions and corresponding mixed models based on relationship matrices and show how to exploit these equivalences computationally for genome-assisted prediction. In particular, we show how models with epistatic interactions of higher order (e.g., three-factor interactions) translate into linear models with certain covariance matrices and demonstrate how to construct epistatic relationship matrices for the linear mixed model, if we restrict the model to interactions defined a priori. We illustrate the practical relevance of our results with a publicly available data set on grain yield of wheat lines growing in four different environments. For this purpose, we select important interactions in one environment and use this knowledge on the network of interactions to increase predictive ability of grain yield under other environmental conditions. Our results provide a guide for building relationship matrices based on knowledge on the structure of trait-related gene networks."],["dc.description.sponsorship","KWS SAAT SE"],["dc.identifier.doi","10.1007/s00122-016-2675-5"],["dc.identifier.isi","000374478600008"],["dc.identifier.pmid","26883048"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/40794"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Springer"],["dc.relation.issn","1432-2242"],["dc.relation.issn","0040-5752"],["dc.title","Epistasis and covariance: how gene interaction translates into genomic relationship"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","339"],["dc.bibliographiccitation.issue","2"],["dc.bibliographiccitation.journal","Theoretical and Applied Genetics"],["dc.bibliographiccitation.lastpage","350"],["dc.bibliographiccitation.volume","123"],["dc.contributor.author","Albrecht, Theresa"],["dc.contributor.author","Wimmer, Valentin"],["dc.contributor.author","Auinger, Hans-Juergen"],["dc.contributor.author","Erbe, Malena"],["dc.contributor.author","Knaak, Carsten"],["dc.contributor.author","Ouzunova, Milena"],["dc.contributor.author","Simianer, Henner"],["dc.contributor.author","Schoen, Chris-Carolin"],["dc.date.accessioned","2018-11-07T08:54:53Z"],["dc.date.available","2018-11-07T08:54:53Z"],["dc.date.issued","2011"],["dc.description.abstract","This is the first large-scale experimental study on genome-based prediction of testcross values in an advanced cycle breeding population of maize. The study comprised testcross progenies of 1,380 doubled haploid lines of maize derived from 36 crosses and phenotyped for grain yield and grain dry matter content in seven locations. The lines were genotyped with 1,152 single nucleotide polymorphism markers. Pedigree data were available for three generations. We used best linear unbiased prediction and stratified cross-validation to evaluate the performance of prediction models differing in the modeling of relatedness between inbred lines and in the calculation of genome-based coefficients of similarity. The choice of similarity coefficient did not affect prediction accuracies. Models including genomic information yielded significantly higher prediction accuracies than the model based on pedigree information alone. Average prediction accuracies based on genomic data were high even for a complex trait like grain yield (0.72-0.74) when the cross-validation scheme allowed for a high degree of relatedness between the estimation and the test set. When predictions were performed across distantly related families, prediction accuracies decreased significantly (0.47-0.48). Prediction accuracies decreased with decreasing sample size but were still high when the population size was halved (0.67-0.69). The results from this study are encouraging with respect to genome-based prediction of the genetic value of untested lines in advanced cycle breeding populations and the implementation of genomic selection in the breeding process."],["dc.description.sponsorship","German Federal Ministry of Education and Research (BMBF) [FKZ: 0315528A]"],["dc.identifier.doi","10.1007/s00122-011-1587-7"],["dc.identifier.isi","000291600800012"],["dc.identifier.pmid","21505832"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/22778"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Springer"],["dc.relation.issn","0040-5752"],["dc.title","Genome-based prediction of testcross values in maize"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","83"],["dc.bibliographiccitation.issue","2"],["dc.bibliographiccitation.journal","Journal of Animal Breeding and Genetics"],["dc.bibliographiccitation.lastpage","84"],["dc.bibliographiccitation.volume","131"],["dc.contributor.author","Simianer, Henner"],["dc.contributor.author","Erbe, Malena"],["dc.date.accessioned","2018-11-07T09:42:07Z"],["dc.date.available","2018-11-07T09:42:07Z"],["dc.date.issued","2014"],["dc.identifier.doi","10.1111/jbg.12072"],["dc.identifier.isi","000332780900001"],["dc.identifier.pmid","24628722"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/33884"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Wiley-blackwell"],["dc.relation.issn","1439-0388"],["dc.relation.issn","0931-2668"],["dc.title","Genetics, genomics, breeding - why scale matters"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dc.type.subtype","letter_note"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","3"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","Journal of Animal Breeding and Genetics"],["dc.bibliographiccitation.lastpage","14"],["dc.bibliographiccitation.volume","128"],["dc.contributor.author","Erbe, Malena"],["dc.contributor.author","Ytournel, Florence"],["dc.contributor.author","Pimentel, E. C. G."],["dc.contributor.author","Sharifi, Ahmad Reza"],["dc.contributor.author","Simianer, Henner"],["dc.date.accessioned","2018-11-07T08:59:29Z"],["dc.date.available","2018-11-07T08:59:29Z"],["dc.date.issued","2011"],["dc.description.abstract","P>Selection is known to influence the linkage disequilibrium (LD) pattern in livestock populations. Spurious LD may lead to a higher number of false-positive signals in whole genome association mapping experiments. We compared three approaches for whole genome association mapping in a simulation study: single marker regression (SMR), a two-step approach, which analyses residuals corrected for family effects with an SMR (GRAMMAR), and a combined linkage and LD approach, which applies the quantitative transmission disequilibrium test to the Mendelian sampling term (MTDT). Three different scenarios were simulated: idealized random mating, limited number of parents and directional selection. The number of false-positive associations increased when the number of parents was limited. Mapping accuracy was the worst in the scenario with directional selection for all approaches. As SMR produced a high number of false-positive signals in small populations, results of whole genome scans in livestock analysed with SMR should be considered with caution. GRAMMAR was the most accurate approach, but also the least powerful one. The Bonferroni-corrected significance threshold seemed to be too stringent for this approach. Results obtained with MTDT changed only slightly with selected populations. MTDT combined sufficient power with a manageable number of false-positive associations in all scenarios."],["dc.identifier.doi","10.1111/j.1439-0388.2010.00885.x"],["dc.identifier.isi","000285967900002"],["dc.identifier.pmid","21214639"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/23911"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Wiley-blackwell"],["dc.relation.issn","0931-2668"],["dc.title","Power and robustness of three whole genome association mapping approaches in selected populations"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","5618"],["dc.bibliographiccitation.issue","12"],["dc.bibliographiccitation.journal","Journal of Animal Science"],["dc.bibliographiccitation.lastpage","5630"],["dc.bibliographiccitation.volume","93"],["dc.contributor.author","Fangmann, A."],["dc.contributor.author","Bergfelder-Drueing, Sarah"],["dc.contributor.author","Tholen, Ernst"],["dc.contributor.author","Simianer, Henner"],["dc.contributor.author","Erbe, Malena"],["dc.date.accessioned","2018-11-07T09:48:25Z"],["dc.date.available","2018-11-07T09:48:25Z"],["dc.date.issued","2015"],["dc.description.abstract","In most countries and for most livestock species, genomic evaluations are obtained from within-breed analyses. To achieve reliable breeding values, however, a sufficient reference sample size is essential. To increase this size, the use of multibreed reference populations for small populations is considered a suitable option in other species. Over decades, the separate breeding work of different pig breeding organizations in Germany has led to stratified subpopulations in the breed German Large White. Due to this fact and the limited number of Large White animals available in each organization, there was a pressing need for ascertaining if multi-subpopulation genomic prediction is superior compared with within-subpopulation prediction in pigs. Direct genomic breeding values were estimated with genomic BLUP for the trait \"number of piglets born alive\" using genotype data (Illumina Porcine 60K SNP BeadChip) from 2,053 German Large White animals from five different commercial pig breeding companies. To assess the prediction accuracy of within- and multi-subpopulation reference sets, a random 5-fold cross-validation with 20 replications was performed. The five subpopulations considered were only slightly differentiated from each other. However, the prediction accuracy of the multi-subpopulations approach was not better than that of the within-subpopulation evaluation, for which the predictive ability was already high. Reference sets composed of closely related multi-subpopulation sets performed better than sets of distantly related subpopulations but not better than the within-subpopulation approach. Despite the low differentiation of the five subpopulations, the genetic connectedness between these different subpopulations seems to be too small to improve the prediction accuracy by applying multi-subpopulation reference sets. Consequently, resources should be used for enlarging the reference population within subpopulation, for example, by adding genotyped females."],["dc.identifier.doi","10.2527/jas.2015-9508"],["dc.identifier.isi","000366327000015"],["dc.identifier.pmid","26641171"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/35300"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Amer Soc Animal Science"],["dc.relation.issn","1525-3163"],["dc.relation.issn","0021-8812"],["dc.title","Can multi-subpopulation reference sets improve the genomic predictive ability for pigs?"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","77"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","Züchtungskunde"],["dc.bibliographiccitation.lastpage","87"],["dc.bibliographiccitation.volume","82"],["dc.contributor.author","Erbe, Malena"],["dc.contributor.author","Ytournel, Florence"],["dc.contributor.author","Pimentel, E. C. G."],["dc.contributor.author","Sharifi, Ahmad Reza"],["dc.contributor.author","Simianer, Henner"],["dc.date.accessioned","2018-11-07T08:48:44Z"],["dc.date.available","2018-11-07T08:48:44Z"],["dc.date.issued","2010"],["dc.description.abstract","Selection is known to influence the linkage disequilibrium (LD) pattern in livestock populations. Spurious LD may lead to a higher number of false positive signals in whole genome association mapping experiments. We compared three approaches for whole genome association mapping in a simulation study: single marker regression (SMR), a two-step approach, which analyzes residuals corrected for family effects with an SMR (GRAMMAR), and a combined linkage and LD approach, which applies the quantitative transmission disequilibrium test to the Mendelian sampling term (MTDT). Three different scenarios were simulated: idealized random mating, limited number of parents and directional selection. The number of false positive associations increased when the number of parents was limited. Since SMR produced a high number of false positive signals in small populations, results of whole genome scans in livestock analyzed with SMR should be considered with caution. GRAMMAR was the most accurate, but also the least powerful approach. The Bonferroni corrected significance threshold seemed to be too stringent for this approach. Results obtained with MTDT changed only slightly with selected populations. MTDT combined sufficient power with a manageable number of false positive associations in all scenarios."],["dc.identifier.isi","000274913300011"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/21293"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Eugen Ulmer Gmbh Co"],["dc.relation.issn","0044-5401"],["dc.title","Comparison of three whole genome association mapping approaches in selected populations"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1774"],["dc.bibliographiccitation.issue","3"],["dc.bibliographiccitation.journal","Journal of Dairy Science"],["dc.bibliographiccitation.lastpage","1781"],["dc.bibliographiccitation.volume","97"],["dc.contributor.author","Kramer, M."],["dc.contributor.author","Erbe, Malena"],["dc.contributor.author","Seefried, Franz Reinhold"],["dc.contributor.author","Gredler, Birgit"],["dc.contributor.author","Bapst, Beat"],["dc.contributor.author","Bieber, A."],["dc.contributor.author","Simianer, Henner"],["dc.date.accessioned","2018-11-07T09:43:27Z"],["dc.date.available","2018-11-07T09:43:27Z"],["dc.date.issued","2014"],["dc.description.abstract","In this study, direct genomic values for the functional traits general temperament, milking temperament, aggressiveness, rank order in herd, milking speed, udder depth, position of labia, and days to first heat in Brown Swiss dairy cattle were estimated based on similar to 777,000 (777K) single nucleotide polymorphism (SNP) information from 1,126 animals Accuracy of direct genomic values was assessed by a 5-fold cross-validation with 10 replicates. Correlations between deregressed proofs and direct genomic values were 0.63 for general temperament, 0.73 for milking temperament, 0.69 for aggressiveness, 0.65 for rank order in herd, 0.69 for milking speed, 0.71 for udder depth, 0.66 for position of labia, and 0.74 for days to first heat. Using the information of similar to 54,000 (54K) SNP led to only marginal deviations in the observed accuracy. Trying to predict the 20% youngest bulls led to correlations of 0.55, 0.77, 0.73, 0.55, 0.64, 0.59, 0.67, and 0.77, respectively, for the traits listed above. Using a novel method to estimate the accuracy of a direct genomic value (defined as correlation between direct genomic value and true breeding value and accounting for the correlation between direct genomic values and conventional breeding values) revealed accuracies of 0.37, 0.20, 0.19, 0.27, 0.48, 0.45, 0.36, and 0.12, respectively, for the traits listed above. These values are much smaller but probably also more realistic than accuracies based on correlations, given the heritabilities and samples sizes in this study. Annotation of the largest estimated SNP effects revealed 2 candidate genes affecting the traits general temperament and days to first heat."],["dc.identifier.doi","10.3168/jds.2013-7054"],["dc.identifier.isi","000331495200058"],["dc.identifier.pmid","24440263"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/34189"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Elsevier Science Inc"],["dc.relation.issn","1525-3198"],["dc.relation.issn","0022-0302"],["dc.title","Accuracy of direct genomic values for functional traits in Brown Swiss cattle"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","456"],["dc.bibliographiccitation.issue","6"],["dc.bibliographiccitation.journal","Journal of Animal Breeding and Genetics"],["dc.bibliographiccitation.lastpage","467"],["dc.bibliographiccitation.volume","130"],["dc.contributor.author","Haberland, A. M."],["dc.contributor.author","Pimentel, E. C. G."],["dc.contributor.author","Ytournel, Florence"],["dc.contributor.author","Erbe, Malena"],["dc.contributor.author","Simianer, Henner"],["dc.date.accessioned","2018-11-07T09:16:46Z"],["dc.date.available","2018-11-07T09:16:46Z"],["dc.date.issued","2013"],["dc.description.abstract","The availability of genomic information demands proper evaluation on how the kind (phenotypic versus genomic) and the amount of information influences the interplay of heritability (h(2)), genetic correlation (rGiGj) and economic weighting of traits with regard to the standard deviation of the index (sigma(I)). As sigma(I) is directly proportional to response to selection, it was the chosen parameter for comparing the indices. Three selection indices incorporating conventional and genomic information for a two trait (i and j) breeding goal were compared. Information sources were chosen corresponding to pig breeding applications. Index I incorporating an own performance in trait j served as reference scenario. In index II, additional information in both traits was contributed by a varying number of full-sibs (2, 7, 50). In index III, the conventional own performance in trait j was combined with genomic information for both traits. The number of animals in the reference population (N-P=1000, 5000, 10000) and thus the accuracy of GBVs were varied. With more information included in the index, sigma(I) became more independent of r(GiGj), h(j)(2) and relative economic weighting. This applied for index II (more full-sibs) and for index III (more accurate GBVs). Standard deviations of index II with seven full-sibs and index III with N-P=1000 were similar when both traits had the same heritability. If the heritability of trait j was reduced (h(j)(2=)0.1), sigma(I) of index III with N-P=1000 was clearly higher than for index II with seven full-sibs. When enhancing the relative economic weight of trait j, the decrease in sigma(I) of the conventional full-sib index was much stronger than for index III. Our results imply that N-P=1000 can be considered a minimum size for a reference population in pig breeding. These conclusions also hold for comparing the accuracies of the indices."],["dc.identifier.doi","10.1111/jbg.12051"],["dc.identifier.isi","000330131700006"],["dc.identifier.pmid","24236608"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/28009"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Wiley-blackwell"],["dc.relation.issn","1439-0388"],["dc.relation.issn","0931-2668"],["dc.title","Interplay between heritability, genetic correlation and economic weighting in a selection index with and without genomic information"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]