Weighted single-step genomic BLUP improves accuracy of genomic breeding values for protein content in French dairy goats: a quantitative trait influenced by a major gene

[1]  G. Tosser-Klopp,et al.  A genome scan for milk production traits in dairy goats reveals two new mutations in Dgat1 reducing milk fat content , 2017, Scientific Reports.

[2]  Jeffrey R. O’Connell,et al.  Selecting sequence variants to improve genomic predictions for dairy cattle , 2017, Genetics Selection Evolution.

[3]  G. Wiens,et al.  Genomic selection models double the accuracy of predicted breeding values for bacterial cold water disease resistance compared to a traditional pedigree-based model in rainbow trout aquaculture , 2017, Genetics Selection Evolution.

[4]  Stephen P. Miller,et al.  Prediction of genomic breeding values for growth, carcass and meat quality traits in a multi-breed sheep population using a HD SNP chip , 2017, BMC Genetics.

[5]  Ignacy Misztal,et al.  Weighting Strategies for Single-Step Genomic BLUP: An Iterative Approach for Accurate Calculation of GEBV and GWAS , 2016, Front. Genet..

[6]  C. Robert-Granié,et al.  Including αs1casein gene information in genomic evaluations of French dairy goats , 2016, Genetics Selection Evolution.

[7]  H. Piepho,et al.  Quantitative genetics theory for genomic selection and efficiency of breeding value prediction in open-pollinated populations , 2016 .

[8]  Andrés Legarra,et al.  Genetic evaluation with major genes and polygenic inheritance when some animals are not genotyped using gene content multiple-trait BLUP , 2015, Genetics Selection Evolution.

[9]  J. McEwan,et al.  Genomic prediction of breeding values in the New Zealand sheep industry using a 50K SNP chip. , 2014, Journal of animal science.

[10]  M. Lund,et al.  Comparison of genomic predictions using genomic relationship matrices built with different weighting factors to account for locus-specific variances. , 2014, Journal of dairy science.

[11]  M. Coffey,et al.  Estimation of genomic breeding values for milk yield in UK dairy goats. , 2014, Journal of dairy science.

[12]  C. Robert-Granié,et al.  Comparison of joint versus purebred genomic evaluation in the French multi-breed dairy goat population , 2014, Genetics Selection Evolution.

[13]  A Legarra,et al.  Assessment of accuracy of genomic prediction for French Lacaune dairy sheep. , 2014, Journal of dairy science.

[14]  C. Robert-Granié,et al.  A first step toward genomic selection in the multi-breed French dairy goat population. , 2013, Journal of dairy science.

[15]  D. Gianola Priors in Whole-Genome Regression: The Bayesian Alphabet Returns , 2013, Genetics.

[16]  Ben J Hayes,et al.  Accuracy of pedigree and genomic predictions of carcass and novel meat quality traits in multi-breed sheep data assessed by cross-validation , 2012, Genetics Selection Evolution.

[17]  A Legarra,et al.  Genomic selection in the French Lacaune dairy sheep breed. , 2012, Journal of dairy science.

[18]  W. Muir,et al.  Genome-wide association mapping including phenotypes from relatives without genotypes. , 2012, Genetics research.

[19]  C. Lawley,et al.  Goat genome assembly, Availability of an international 50K SNP chip and RH panel : an update of the International Goat Genome Consortium projects , 2012 .

[20]  M. Goddard,et al.  Using the genomic relationship matrix to predict the accuracy of genomic selection. , 2011, Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie.

[21]  I Misztal,et al.  Bias in genomic predictions for populations under selection. , 2011, Genetics research.

[22]  Zhe Zhang,et al.  Genomic selection for QTL-MAS data using a trait-specific relationship matrix , 2011, BMC proceedings.

[23]  Rohan L. Fernando,et al.  Extension of the bayesian alphabet for genomic selection , 2011, BMC Bioinformatics.

[24]  L. Journaux,et al.  Genomic selection in French dairy cattle , 2011 .

[25]  R. Fernando,et al.  Genomic prediction of simulated multibreed and purebred performance using observed fifty thousand single nucleotide polymorphism genotypes. , 2010, Journal of animal science.

[26]  I Misztal,et al.  Hot topic: a unified approach to utilize phenotypic, full pedigree, and genomic information for genetic evaluation of Holstein final score. , 2010, Journal of dairy science.

[27]  M. Lund,et al.  Genomic prediction when some animals are not genotyped , 2010, Genetics Selection Evolution.

[28]  I Misztal,et al.  A relationship matrix including full pedigree and genomic information. , 2009, Journal of dairy science.

[29]  D. Garrick,et al.  Technical note: Derivation of equivalent computing algorithms for genomic predictions and reliabilities of animal merit. , 2009, Journal of dairy science.

[30]  M. Goddard Genomic selection: prediction of accuracy and maximisation of long term response , 2009, Genetica.

[31]  M. Goddard,et al.  Invited review: Genomic selection in dairy cattle: progress and challenges. , 2009, Journal of dairy science.

[32]  P. VanRaden,et al.  Efficient methods to compute genomic predictions. , 2008, Journal of dairy science.

[33]  Hans D. Daetwyler,et al.  Accuracy of Predicting the Genetic Risk of Disease Using a Genome-Wide Approach , 2008, PloS one.

[34]  R. Fernando,et al.  The Impact of Genetic Relationship Information on Genome-Assisted Breeding Values , 2007, Genetics.

[35]  N Gengler,et al.  A simple method to approximate gene content in large pedigree populations: application to the myostatin gene in dual-purpose Belgian Blue cattle. , 2007, Animal : an international journal of animal bioscience.

[36]  M. Goddard,et al.  Prediction of total genetic value using genome-wide dense marker maps. , 2001, Genetics.

[37]  E. Manfredi,et al.  Genetic parameters of dairy traits in the Alpine and Saanen goat breeds , 1999, Genetics Selection Evolution.

[38]  P M VanRaden,et al.  Derivation, calculation, and use of national animal model information. , 1991, Journal of dairy science.

[39]  M. Mahé,et al.  A Mendelian polymorphism underlying quantitative variations of goat αs1-casein , 1987, Génétique, sélection, évolution.

[40]  E. J. Williams The Comparison of Regression Variables , 1959 .

[41]  S. Andonov,et al.  Accuracy of breeding values in small genotyped populations using different sources of external information-A simulation study. , 2017, Journal of dairy science.

[42]  H. Piepho,et al.  Quantitative genetics theory for genomic selection and efficiency of genotypic value , 2016 .

[43]  D. Boichard,et al.  National genetic evaluations in dairy sheep and goats in France , 2011 .

[44]  P. VanRaden,et al.  Invited review: reliability of genomic predictions for North American Holstein bulls. , 2009, Journal of dairy science.