Predictive ability of host genetics and rumen microbiome for subclinical ketosis.


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:
May 2020
Historique:
received: 31 10 2019
accepted: 28 01 2020
pubmed: 22 3 2020
medline: 24 9 2020
entrez: 22 3 2020
Statut: ppublish

Résumé

Subclinical metabolic disorders such as ketosis cause substantial economic losses for dairy farmers in addition to the serious welfare issues they pose for dairy cows. Major hurdles in genetic improvement against metabolic disorders such as ketosis include difficulties in large-scale phenotype recording and low heritability of traits. Milk concentrations of ketone bodies, such as acetone and β-hydroxybutyric acid (BHB), might be useful indicators to select cows for low susceptibility to ketosis. However, heritability estimates reported for milk BHB and acetone in several dairy cattle breeds were low. The rumen microbial community has been reported to play a significant role in host energy homeostasis and metabolic and physiologic adaptations. The current study aims at investigating the effects of cows' genome and rumen microbial composition on concentrations of acetone and BHB in milk, and identifying specific rumen microbial taxa associated with variation in milk acetone and BHB concentrations. We determined the concentrations of acetone and BHB in milk using nuclear magnetic resonance spectroscopy on morning milk samples collected from 277 Danish Holstein cows. Imputed high-density genotype data were available for these cows. Using genomic and microbial prediction models with a 10-fold resampling strategy, we found that rumen microbial composition explains a larger proportion of the variation in milk concentrations of acetone and BHB than do host genetics. Moreover, we identified associations between milk acetone and BHB with some specific bacterial and archaeal operational taxonomic units previously reported to have low to moderate heritability, presenting an opportunity for genetic improvement. However, higher covariation between specific microbial taxa and milk acetone and BHB concentrations might not necessarily indicate a causal relationship; therefore further validation is needed before considering implementation in selection programs.

Identifiants

pubmed: 32197852
pii: S0022-0302(20)30215-0
doi: 10.3168/jds.2019-17824
pii:
doi:

Substances chimiques

Ketone Bodies 0
Acetone 1364PS73AF
3-Hydroxybutyric Acid TZP1275679

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

4557-4569

Informations de copyright

The Authors. Published by FASS Inc. and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Auteurs

Grum Gebreyesus (G)

Center for Quantitative Genetics and Genomics, Aarhus University, DK-8830 Tjele, Denmark.

Gareth F Difford (GF)

Center for Quantitative Genetics and Genomics, Aarhus University, DK-8830 Tjele, Denmark; Nofima (Norwegian Institute of Food, Fisheries and Aquaculture Research), 1432 Ås, Norway.

Bart Buitenhuis (B)

Center for Quantitative Genetics and Genomics, Aarhus University, DK-8830 Tjele, Denmark.

Jan Lassen (J)

Center for Quantitative Genetics and Genomics, Aarhus University, DK-8830 Tjele, Denmark.

Samantha Joan Noel (SJ)

Department of Animal Science, Aarhus University, DK-8830 Tjele, Denmark.

Ole Højberg (O)

Department of Animal Science, Aarhus University, DK-8830 Tjele, Denmark.

Damian R Plichta (DR)

Center for Biological Sequence Analysis, Denmark Technical University, DK-2800 Lyngby, Denmark.

Zhigang Zhu (Z)

Department of Animal Science, Aarhus University, DK-8830 Tjele, Denmark.

Nina A Poulsen (NA)

Department of Food Science, Aarhus University, DK-8830 Tjele, Denmark.

Ulrik K Sundekilde (UK)

Department of Food Science, Aarhus University, DK-5792 Arslev, Denmark.

Peter Løvendahl (P)

Center for Quantitative Genetics and Genomics, Aarhus University, DK-8830 Tjele, Denmark.

Goutam Sahana (G)

Center for Quantitative Genetics and Genomics, Aarhus University, DK-8830 Tjele, Denmark.

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Classifications MeSH