Genome-wide association scan for heterotic quantitative trait loci in multi-breed and crossbred beef cattle

[1]  Zhiquan Wang,et al.  Modeling heterotic effects in beef cattle using genome-wide SNP-marker genotypes. , 2018, Journal of animal science.

[2]  G. Even,et al.  Genome-wide association study for birth, weaning and yearling weight in Colombian Brahman cattle , 2017, Genetics and molecular biology.

[3]  G. Plastow,et al.  Genomic prediction of breed composition and heterosis effects in Angus, Charolais, and Hereford crosses using 50K genotypes , 2017, Canadian Journal of Animal Science.

[4]  C. Gondro,et al.  Genomewide association analysis of growth traits in Charolais beef cattle. , 2016, Journal of animal science.

[5]  M. Stumvoll,et al.  Repin1 deficiency improves insulin sensitivity and glucose metabolism in db/db mice by reducing adipose tissue mass and inflammation. , 2016, Biochemical and biophysical research communications.

[6]  R. Carvalheiro,et al.  Genome-Wide Association Study of Meat Quality Traits in Nellore Cattle , 2016, PloS one.

[7]  Huijiang Gao,et al.  Genome-wide association study identifies loci and candidate genes for meat quality traits in Simmental beef cattle , 2016, Mammalian Genome.

[8]  F. Schenkel,et al.  Accuracy of genomic predictions for feed efficiency traits of beef cattle using 50K and imputed HD genotypes. , 2016, Journal of animal science.

[9]  Z. Weng,et al.  Genome-wide association study of growth and body composition traits in Brangus beef cattle , 2016 .

[10]  F. Baldi,et al.  Genetic association of growth traits with carcass and meat traits in Nellore cattle. , 2015, Genetics and molecular research : GMR.

[11]  M. Lopes,et al.  Estimation of Additive, Dominance, and Imprinting Genetic Variance Using Genomic Data , 2015, G3: Genes, Genomes, Genetics.

[12]  G. Plastow,et al.  Genome-wide association for heifer reproduction and calf performance traits in beef cattle. , 2015, Genome.

[13]  M. Goddard,et al.  Non-additive genetic variation in growth, carcass and fertility traits of beef cattle , 2015, Genetics Selection Evolution.

[14]  S. Kachman,et al.  Estimation of Breed-specific Heterosis Effects for Birth , Weaning and Yearling Weight in Cattle , 2014 .

[15]  E. J. Pollak,et al.  QTLs associated with dry matter intake, metabolic mid-test weight, growth and feed efficiency have little overlap across 4 beef cattle studies , 2014, BMC Genomics.

[16]  Henk Bovenhuis,et al.  A Genome-Wide Association Study Reveals Dominance Effects on Number of Teats in Pigs , 2014, PloS one.

[17]  F. Schenkel,et al.  A new approach for efficient genotype imputation using information from relatives , 2014, BMC Genomics.

[18]  R. Schnabel,et al.  Large-effect pleiotropic or closely linked QTL segregate within and across ten US cattle breeds , 2014, BMC Genomics.

[19]  Stephen D. Turner,et al.  qqman: an R package for visualizing GWAS results using Q-Q and manhattan plots , 2014, bioRxiv.

[20]  F. Schenkel,et al.  Genome-Wide Association for Growth Traits in Canchim Beef Cattle , 2014, PloS one.

[21]  Luis Varona,et al.  On the Additive and Dominant Variance and Covariance of Individuals Within the Genomic Selection Scope , 2013, Genetics.

[22]  B. Kinghorn,et al.  Prediction of heterosis using genome-wide SNP-marker data: application to egg production traits in white Leghorn crosses , 2013, Heredity.

[23]  S. Moore,et al.  Genome-wide association analyses for carcass quality in crossbred beef cattle , 2013, BMC Genetics.

[24]  L. Andersson,et al.  Modelling of genetic interactions improves prediction of hybrid patterns--a case study in domestic fowl. , 2012, Genetics research.

[25]  P. Arvan,et al.  Islet autoantigens: structure, function, localization, and regulation. , 2012, Cold Spring Harbor perspectives in medicine.

[26]  S. Moore,et al.  Linkage disequilibrium in Angus, Charolais, and Crossbred beef cattle , 2012, Front. Gene..

[27]  R. Fernando,et al.  Accuracies of genomic breeding values in American Angus beef cattle using K-means clustering for cross-validation , 2011, Genetics Selection Evolution.

[28]  N. Reinsch,et al.  Including non-additive genetic effects in Bayesian methods for the prediction of genetic values based on genome-wide markers , 2011, BMC Genetics.

[29]  Paul Stothard,et al.  In-depth annotation of SNPs arising from resequencing projects using NGS-SNP , 2011, Bioinform..

[30]  J. K. Bertrand,et al.  Estimation of breed and heterosis effects for growth and carcass traits in cattle using published crossbreeding studies. , 2010, Journal of animal science.

[31]  M. Goddard,et al.  Reliability of Genomic Predictions Across Multiple Populations , 2009, Genetics.

[32]  David H. Alexander,et al.  Fast model-based estimation of ancestry in unrelated individuals. , 2009, Genome research.

[33]  Timothy P. L. Smith,et al.  Development and Characterization of a High Density SNP Genotyping Assay for Cattle , 2009, PloS one.

[34]  David R. Kelley,et al.  A whole-genome assembly of the domestic cow, Bos taurus , 2009, Genome Biology.

[35]  M. McCarthy,et al.  Genome-wide association studies for complex traits: consensus, uncertainty and challenges , 2008, Nature Reviews Genetics.

[36]  W. G. Hill,et al.  Data and Theory Point to Mainly Additive Genetic Variance for Complex Traits , 2008, PLoS genetics.

[37]  H. Piepho,et al.  Genetic Basis of Heterosis for Growth-Related Traits in Arabidopsis Investigated by Testcross Progenies of Near-Isogenic Lines Reveals a Significant Role of Epistasis , 2007, Genetics.

[38]  Yurii S. Aulchenko,et al.  BIOINFORMATICS APPLICATIONS NOTE doi:10.1093/bioinformatics/btm108 Genetics and population analysis GenABEL: an R library for genome-wide association analysis , 2022 .

[39]  D H Crews,et al.  Test duration for growth, feed intake, and feed efficiency in beef cattle using the GrowSafe System. , 2006, Journal of animal science.

[40]  Sa Barwick,et al.  Development successes and issues for the future in deriving and applying selection indexes for beef breeding , 2005 .

[41]  J. Thompson.  The effects of marbling on flavour and juiciness scores of cooked beef, after adjusting to a constant tenderness , 2004 .

[42]  G. Jordaan,et al.  Estimation of additive, maternal and non-additive genetic effects of preweaning growth traits in a multibreed beef cattle project , 2003 .

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

[44]  Colin T. Whittemore,et al.  Impact of biotechnology on (cross)breeding programmes in pigs , 2000 .

[45]  J. K. Bertrand,et al.  Studies on the value of incorporating the effect of dominance in genetic evaluations of dairy cattle, beef cattle and swine , 1998 .

[46]  Ross Ihaka,et al.  Gentleman R: R: A language for data analysis and graphics , 1996 .

[47]  J Li,et al.  Dominance is the major genetic basis of heterosis in rice as revealed by QTL analysis using molecular markers. , 1995, Genetics.

[48]  Y. Benjamini,et al.  Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .

[49]  Cedric A. B. Smith,et al.  Introduction to Quantitative Genetics , 1960 .

[50]  G. Shull.  The composition of a field of maize , 1908 .