Novel genetic parameters for genetic residual feed intake in dairy cattle using time series data from multiple parities and countries in North America and Europe.

genetic residual feed intake multi-trait analysis random regression variance component estimation

Journal

Journal of dairy science
ISSN: 1525-3198
Titre abrégé: J Dairy Sci
Pays: United States
ID NLM: 2985126R

Informations de publication

Date de publication:
05 Sep 2023
Historique:
received: 03 02 2023
accepted: 06 07 2023
medline: 8 9 2023
pubmed: 8 9 2023
entrez: 7 9 2023
Statut: aheadofprint

Résumé

Residual feed intake is viewed as an important trait in breeding programs that could be used to enhance genetic progress in feed efficiency. In particular, improving feed efficiency could improve both economic and environmental sustainability in the dairy cattle industry. However, data remain sparse, limiting the development of reliable genomic evaluations across lactation and parity for residual feed intake. Here, we estimated novel genetic parameters for genetic residual feed intake (gRFI) across the first, second, and third parity, using a random regression model. Research data on the measured feed intake, milk production, and body weight of 7,379 cows (271,080 records) from 6 countries in 2 continents were shared through the Horizon 2020 project GenTORE and Resilient Dairy Genome Project. The countries included Canada (1,053 cows with 47,130 weekly records), Denmark (1,045 cows with 72,760 weekly records), France (329 cows with 16,888 weekly records), Germany (938 cows with 32,614 weekly records), the Netherlands (2,051 cows with 57,830 weekly records), and United States (1,963 cows with 43,858 weekly records). Each trait had variance components estimated from first to third parity, using a random regression model across countries. Genetic residual feed intake was found to be heritable in all 3 parities, with first parity being predominant (range: 22-34%). Genetic residual feed intake was highly correlated across parities for mid- to late lactation; however, genetic correlation across parities was lower during early lactation, especially when comparing first and third parity. We estimated a genetic correlation of 0.77 ± 0.37 between North America and Europe for dry matter intake at first parity. Published literature on genetic correlations between high input countries/continents for dry matter intake support a high genetic correlation for dry matter intake. In conclusion, our results demonstrate the feasibility of estimating variance components for gRFI across parities, and the value of sharing data on scarce phenotypes across countries. These results can potentially be implemented in genetic evaluations for gRFI in dairy cattle.

Identifiants

pubmed: 37678762
pii: S0022-0302(23)00589-1
doi: 10.3168/jds.2023-23330
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© 2023, The Authors. Published by Elsevier Inc. and Fass Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Auteurs

R B Stephansen (RB)

Center for Quantitative Genetics and Genomics, Aarhus University, C. F. M⊘llers Allé 3, 8000 Aarhus, Denmark. Electronic address: rasmus.stephansen@qgg.au.dk.

P Martin (P)

Université Paris-Saclay, INRAE, AgroParisTech, UMR GABI, 78350 Jouy-en-Josas, France.

C I V Manzanilla-Pech (CIV)

Center for Quantitative Genetics and Genomics, Aarhus University, C. F. M⊘llers Allé 3, 8000 Aarhus, Denmark.

B Gredler-Grandl (B)

Wageningen University & Research Animal Breeding and Genomics, PO Box 338, 6700 AH Wageningen, the Netherlands.

G Sahana (G)

Center for Quantitative Genetics and Genomics, Aarhus University, C. F. M⊘llers Allé 3, 8000 Aarhus, Denmark.

P Madsen (P)

Center for Quantitative Genetics and Genomics, Aarhus University, C. F. M⊘llers Allé 3, 8000 Aarhus, Denmark.

K Weigel (K)

Department of Animal and Dairy Sciences, University of Wisconsin, Madison 53706.

R J Tempelman (RJ)

Department of Animal Science, Michigan State University East Lansing 48824-1226.

F Peñagaricano (F)

Department of Animal and Dairy Sciences, University of Wisconsin, Madison 53706.

K L Parker Gaddis (KLP)

Council on Dairy Cattle Breeding, Bowie, MD 20716.

H M White (HM)

Department of Animal and Dairy Sciences, University of Wisconsin, Madison 53706.

J E P Santos (JEP)

Department of Animal Science, University of Florida, Gainesville 32608.

J E Koltes (JE)

Department of Animal Science, Iowa State University, Ames 50011.

F Schenkel (F)

Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON, N1G 2W1, Canada 2 Institute of Genetics.

D Hailemariam (D)

Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB T6G 2P5, Canada.

G Plastow (G)

Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB T6G 2P5, Canada.

E Abdalla (E)

Vereinigte Informationssysteme Tierhaltung w.V. (vit), Heideweg 1, 27283, Verden, Germany.

M VandeHaar (M)

Department of Animal Science, Michigan State University East Lansing 48824-1226.

R F Veerkamp (RF)

Wageningen University & Research Animal Breeding and Genomics, PO Box 338, 6700 AH Wageningen, the Netherlands.

C Baes (C)

Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON, N1G 2W1, Canada 2 Institute of Genetics,; Department of Clinical Research and Veterinary Public Health, University of Bern, Bern, 3001, Switzerland.

J Lassen (J)

Center for Quantitative Genetics and Genomics, Aarhus University, C. F. M⊘llers Allé 3, 8000 Aarhus, Denmark; Viking Genetics, Ebeltoftvej 16, Assentoft, 8960-Randers, Denmark.

Classifications MeSH