Marker-assisted breeding value estimation for mastitis resistance in Finnish Ayrshire cattle
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TLDR
Combining data of genotyped and ungenotyped animals in a large pedigree population using either identical-by-descent (IBD) or identical- by-state (IBS) haplotypes for some previously identified QTL regions for somatic cell score and clinical mastitis in Finnish Ayrshire cattle showed greater accuracy and predictive ability than conventional breeding value estimation.About:
This article is published in Journal of Dairy Science.The article was published on 2011-08-01 and is currently open access. It has received 6 citations till now. The article focuses on the topics: Population & Heritability.read more
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The mammary gland in domestic ruminants: a systems biology perspective.
TL;DR: This paper reviews the major contributions that genomics, transcriptomics, metabolomics and proteomics approaches have provided to understand the regulation of the mammary gland in health, disease and production and addresses how modern research approaches may help to understand long-known issues in mammary development, lactation biology and dairy production.
Journal ArticleDOI
Including α s1 casein gene information in genomic evaluations of French dairy goats
TL;DR: Including the αs1casein effect in a genomic evaluation model for French dairy goats is possible and useful to improve accuracy and difficulties in predicting the genotypes for ungenotyped animals limited the improvement in accuracy of the obtained estimated breeding values.
Journal ArticleDOI
Whole-genome regulation analysis of histone H3 lysin 27 trimethylation in subclinical mastitis cows infected by Staphylococcus aureus
TL;DR: A novel insight is provided into the interaction between S. aureus and lymphocytes in lactating cows by histone H3 methylation regulation and the differentially expressed genes in bovine lymphocytes regulated by H3K27me3 on upstream 2 kb regions (IL10, PTX3 and etc.) may relate to S.aureus mastitis susceptibility.
Distribution and location of genetic effects for dairy traits.
John B. Cole,Paul M. VanRaden,Jeffrey R. O'Connell,C.P. Van Tassell,Tad S. Sonstegard,Robert D. Schnabel,Jeremy F. Taylor,G.R. Wiggans,J. D. Sattler +8 more
TL;DR: Results validate quantitative genetic assumptions that most traits are due to the contributions of a large number of genes of small additive effect, rather than support the finite locus model.
Journal ArticleDOI
Polymorphism of LEP and TNF-α Genes in the Dairy Cattle Populations of Ukrainian Selection
Roman Kulibaba,Yuriy Liashenko,Polina Yurko,Mykola Sakhatskyi,Yulia Osadcha,Hamza Alshamaileh +5 more
TL;DR: It was shown that the LEP gene was polymorphic in both experimental populations by HphI-polymorphism in the third exon of the gene (A59V mutation) and this population had a deviation from the Hardy-Weinberg equilibrium state.
References
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Journal ArticleDOI
Prediction of Total Genetic Value Using Genome-Wide Dense Marker Maps
TL;DR: It was concluded that selection on genetic values predicted from markers could substantially increase the rate of genetic gain in animals and plants, especially if combined with reproductive techniques to shorten the generation interval.
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Efficiency of marker-assisted selection in the improvement of quantitative traits.
Russell Lande,Robin Thompson +1 more
TL;DR: This work derives selection indices that maximize the rate of improvement in quantitative characters under different schemes of MAS combining information on molecular genetic polymorphisms (marker loci) with data on phenotypic variation among individuals (and their relatives).
Book
Linear models for the prediction of animal breeding values
TL;DR: A genetic evaluation with different sources of records and the best linear unbiased prediction of breeding value - univariate models with one random effect, non-additive animal models and dominance relationship matrix animal model for rapid inversion of the dominance matrix epistatis.
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Marker assisted selection using best linear unbiased prediction
Rohan L. Fernando,M. Grossman +1 more
TL;DR: This approach allows simultaneous evaluation of fixed effects, effects of MQTL alleles, and effects of alleles at the remaining QTLs, using known relationships and phenotypic and marker information.