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Genotype by environment interaction in Brazilian Dairy Gir cattle

Daniele Ribeiro de Lima Reis Faza, Marco Antonio Machado, Marta Fonseca Martins, João Cláudio do Carmo Panetto, Marcos Vinicius Gualberto Barbosa Da Silva, L.L. Verardo 
01 Jan 2018-pp 325
TL;DR: Different regions were associated with 305-d milk yield while considering the three production scenarios as observed in chromosomes 11 and 21 that were more strongly associated with milk yield in the low input data set than in the other two.
Abstract: With the objective of exploring genotype by environment interaction in the Brazilian National Dairy Gir Breeding Program, a total of 97,476 lactation records were separated into three data sets, according to the average milk yield within each management group. They were designated as low input, medium input, or high input management groups. Breeding values were predicted for 305-d milk yield using records from those three data sets as three different traits: Low input 305-d milk yield; Medium input 305-d milk yield; and High input 305-d milk yield. Genetic correlations ranged from 0.75, between the low input and high input traits, to 0.97, between the medium input and high input traits. Reordering of ranking of sires has been observed, especially in the comparison between the low input and high input EBVs. SNP genotypes were obtained for a sample of 2,681 animals, including animals with lactation records (own or from their progeny) within the three data sets. The EBVs of the genotyped animals were later deregressed and used in three Genome Wide Association Studies (GWAS). Different regions were associated with 305-d milk yield while considering the three production scenarios as observed in chromosomes 11 and 21 that were more strongly associated with milk yield in the low input data set than in the other two.

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Citations
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Journal Article•DOI•
Genotype–environment interaction for milk production of Gyr cattle in Brazil and Colombia

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A. M. Toro-Ospina, Ricardo Antonio Faria, Pablo Dominguez-Castaño, M.L. Santana, Luis Gabriel Gonzalez, A. C. Espasandin, Josineudson Augusto Ii de Vasconcelos Silva 
11 Jun 2022-Genes & Genomics

1 citations

References
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Journal Article•DOI•
GenABEL: an R library for genome-wide association analysis

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Yurii S. Aulchenko1, Stephan Ripke2, Aaron Isaacs2, C.M. van Duijn2•
Erasmus University Rotterdam1, Max Planck Society2
15 May 2007-Bioinformatics
TL;DR: An R library for genome-wide association (GWA) analysis that implements effective storage and handling of GWA data, fast procedures for genetic data quality control, testing of association of single nucleotide polymorphisms with binary or quantitative traits, visualization of results and also provides easy interfaces to standard statistical and graphical procedures.
Abstract: Here we describe an R library for genome-wide association (GWA) analysis. It implements effective storage and handling of GWA data, fast procedures for genetic data quality control, testing of association of single nucleotide polymorphisms with binary or quantitative traits, visualization of results and also provides easy interfaces to standard statistical and graphical procedures implemented in base R and special R libraries for genetic analysis. We evaluated GenABEL using one simulated and two real data sets. We conclude that GenABEL enables the analysis of GWA data on desktop computers. Availability: http://cran.r-project.org Contact: i.aoultchenko@erasmusmc.nl

1,794 citations

"Genotype by environment interaction..." refers methods in this paper

  • ...(2009), and applied to association analyses between each 305MY trait (LI, MI our HI) and the imputed HD genotype distributions, which were conducted using logistic regression models implemented with the “mlreg” function of the GenABEL package in R software (Aulchenko et al., 2007)....

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  • ...…Garrick et al. (2009), and applied to association analyses between each 305MY trait (LI, MI our HI) and the imputed HD genotype distributions, which were conducted using logistic regression models implemented with the “mlreg” function of the GenABEL package in R software (Aulchenko et al., 2007)....

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Journal Article•DOI•
The sampling variance of the genetic correlation coefficient

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Alan Robertson
01 Sep 1959-Biometrics

1,051 citations

"Genotype by environment interaction..." refers background in this paper

  • ...Robertson (1959) stated that the quantitative expression of genotype-environment interactions in terms on genetic correlation between performances in two or more environments was of value in giving a measure of the practical, rather than the statistical, significance of the results, but he suggested a genetic correlation should fall to a figure around 0....

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  • ...Robertson (1959) stated that the quantitative expression of genotype-environment interactions in terms on genetic correlation between performances in two or more environments was of value in giving a measure of the practical, rather than the statistical, significance of the results, but he…...

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Journal Article•DOI•
WOMBAT: a tool for mixed model analyses in quantitative genetics by restricted maximum likelihood (REML).

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Karin Meyer1•
University of New England (Australia)1
01 Nov 2007-Journal of Zhejiang University-science B
TL;DR: WOMBAT is a software package for quantitative genetic analyses of continuous traits, fitting a linear, mixed model; estimates of covariance components and the resulting genetic parameters are obtained by restricted maximum likelihood.
Abstract: WOMBAT is a software package for quantitative genetic analyses of continuous traits, fitting a linear, mixed model; estimates of covariance components and the resulting genetic parameters are obtained by restricted maximum likelihood. A wide range of models, comprising numerous traits, multiple fixed and random effects, selected genetic covariance structures, random regression models and reduced rank estimation are accommodated. WOMBAT employs up-to-date numerical and computational methods. Together with the use of efficient compilers, this generates fast executable programs, suitable for large scale analyses. Use of WOMBAT is illustrated for a bivariate analysis. The package consists of the executable program, available for LINUX and WINDOWS environments, manual and a set of worked example, and can be downloaded free of charge from (http://agbu. une.edu.au/~kmeyer/wombat.html).

721 citations

"Genotype by environment interaction..." refers methods in this paper

  • ...The Wombat software (Meyer, 2007) was used to estimate (co)variances, heritabilities, genetic correlations and breeding values (EBV), with the REML approach....

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Journal Article•DOI•
Deregressing estimated breeding values and weighting information for genomic regression analyses

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Dorian J. Garrick1, Dorian J. Garrick2, Jeremy F. Taylor3, Rohan L. Fernando2•
Massey University1, Iowa State University2, University of Missouri3
31 Dec 2009-Genetics Selection Evolution
TL;DR: A logical approach to using information for genomic prediction is introduced, which demonstrates the appropriate weights for analyzing observations with heterogeneous variance and explains the need for and the manner in which EBV should have parent average effects removed, be deregressed and weighted.
Abstract: Background Genomic prediction of breeding values involves a so-called training analysis that predicts the influence of small genomic regions by regression of observed information on marker genotypes for a given population of individuals. Available observations may take the form of individual phenotypes, repeated observations, records on close family members such as progeny, estimated breeding values (EBV) or their deregressed counterparts from genetic evaluations. The literature indicates that researchers are inconsistent in their approach to using EBV or deregressed data, and as to using the appropriate methods for weighting some data sources to account for heterogeneous variance.

553 citations

Journal Article•DOI•
Genome-wide association analysis of thirty one production, health, reproduction and body conformation traits in contemporary U.S. Holstein cows

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John B. Cole1, G.R. Wiggans1, Li Ma2, Tad S. Sonstegard1, T.J. Lawlor, Brian A Crooker2, Curtis P. Van Tassell1, Jing Yang2, Shengwen Wang2, Lakshmi K. Matukumalli1, Yang Da2 •
Agricultural Research Service1, University of Minnesota2
11 Aug 2011-BMC Genomics
TL;DR: A genome-wide analysis of predicted transmitting ability (PTA) of 31 production, health, reproduction and body conformation traits in contemporary Holstein cows provides useful information for annotating phenotypic effects on the dairy genome and for building consensus of dairy QTL effects.
Abstract: Genome-wide association analysis is a powerful tool for annotating phenotypic effects on the genome and knowledge of genes and chromosomal regions associated with dairy phenotypes is useful for genome and gene-based selection. Here, we report results of a genome-wide analysis of predicted transmitting ability (PTA) of 31 production, health, reproduction and body conformation traits in contemporary Holstein cows.

331 citations

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