Literature DB >> 26805988

Short communication: Multi-trait estimation of genetic parameters for milk protein composition in the Danish Holstein.

G Gebreyesus1, M S Lund2, L Janss2, N A Poulsen3, L B Larsen3, H Bovenhuis4, A J Buitenhuis5.   

Abstract

Genetic parameters were estimated for the major milk proteins using bivariate and multi-trait models based on genomic relationships between animals. The analyses included, apart from total protein percentage, αS1-casein (CN), αS2-CN, β-CN, κ-CN, α-lactalbumin, and β-lactoglobulin, as well as the posttranslational sub-forms of glycosylated κ-CN and αS1-CN-8P (phosphorylated). Standard errors of the estimates were used to compare the models. In total, 650 Danish Holstein cows across 4 parities and days in milk ranging from 9 to 481d were selected from 21 herds. The multi-trait model generally resulted in lower standard errors of heritability estimates, suggesting that genetic parameters can be estimated with high accuracy using multi-trait analyses with genomic relationships for scarcely recorded traits. The heritability estimates from the multi-trait model ranged from low (0.05 for β-CN) to high (0.78 for κ-CN). Genetic correlations between the milk proteins and the total milk protein percentage were generally low, suggesting the possibility to alter protein composition through selective breeding with little effect on total milk protein percentage.
Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  genetic parameter; genomic relationship; milk protein; multi-trait model

Mesh:

Substances:

Year:  2016        PMID: 26805988     DOI: 10.3168/jds.2015-10501

Source DB:  PubMed          Journal:  J Dairy Sci        ISSN: 0022-0302            Impact factor:   4.034


  7 in total

1.  Estimation of genetic parameters and detection of chromosomal regions affecting the major milk proteins and their post translational modifications in Danish Holstein and Danish Jersey cattle.

Authors:  Bart Buitenhuis; Nina A Poulsen; Grum Gebreyesus; Lotte B Larsen
Journal:  BMC Genet       Date:  2016-08-02       Impact factor: 2.797

2.  Modeling heterogeneous (co)variances from adjacent-SNP groups improves genomic prediction for milk protein composition traits.

Authors:  Grum Gebreyesus; Mogens S Lund; Bart Buitenhuis; Henk Bovenhuis; Nina A Poulsen; Luc G Janss
Journal:  Genet Sel Evol       Date:  2017-12-05       Impact factor: 4.297

3.  Within-breed and multi-breed GWAS on imputed whole-genome sequence variants reveal candidate mutations affecting milk protein composition in dairy cattle.

Authors:  Marie-Pierre Sanchez; Armelle Govignon-Gion; Pascal Croiseau; Sébastien Fritz; Chris Hozé; Guy Miranda; Patrice Martin; Anne Barbat-Leterrier; Rabia Letaïef; Dominique Rocha; Mickaël Brochard; Mekki Boussaha; Didier Boichard
Journal:  Genet Sel Evol       Date:  2017-09-18       Impact factor: 4.297

4.  Multi-population GWAS and enrichment analyses reveal novel genomic regions and promising candidate genes underlying bovine milk fatty acid composition.

Authors:  G Gebreyesus; A J Buitenhuis; N A Poulsen; M H P W Visker; Q Zhang; H J F van Valenberg; D Sun; H Bovenhuis
Journal:  BMC Genomics       Date:  2019-03-06       Impact factor: 3.969

5.  COVID-19 Pandemic, Determinants of Food Insecurity, and Household Mitigation Measures: A Case Study of Punjab, Pakistan.

Authors:  Muhammad Aamir Shahzad; Ping Qing; Muhammad Rizwan; Amar Razzaq; Muhammad Faisal
Journal:  Healthcare (Basel)       Date:  2021-05-22

6.  SERPINA1 gene identified in RNA-Seq showed strong association with milk protein concentration in Chinese Holstein cows.

Authors:  Cong Li; Wentao Cai; Shuli Liu; Chenghao Zhou; Hongwei Yin; Dongxiao Sun; Shengli Zhang
Journal:  PeerJ       Date:  2020-02-24       Impact factor: 2.984

7.  A Novel SNPs in Alpha-Lactalbumin Gene Effects on Lactation Traits in Chinese Holstein Dairy Cows.

Authors:  Fan Yang; Manling Zhang; Yuewen Rong; Zaiqun Liu; Shuai Yang; Wei Zhang; Jun Li; Yafei Cai
Journal:  Animals (Basel)       Date:  2019-12-29       Impact factor: 2.752

  7 in total

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