Genetic analysis of milk citrate predicted by milk mid-infrared spectra of Holstein cows in early lactation.

QTL candidate genes milk citrate negative energy balance

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:
04 Dec 2023
Historique:
received: 26 06 2023
accepted: 08 11 2023
medline: 7 12 2023
pubmed: 7 12 2023
entrez: 6 12 2023
Statut: aheadofprint

Résumé

Milk citrate is regarded as an early biomarker of negative energy balance (NEB) in dairy cows during early lactation and serves as a suitable candidate phenotype for genomic selection due to its wide availability across a large number of cows through milk mid-infrared spectra prediction. However, its genetic background is not well known. Therefore, the objectives of this study were to (1) analyze the genetic parameters of milk citrate; (2) identify genomic regions associated with milk citrate; (3) analyze the functional annotation of candidate genes and quantitative trait loci (QTL) related to milk citrate in Walloon Holstein cows. In total, 134,517 test-day milk citrate phenotypes (mmol/L) collected within the first 50 d in milk (DIM) on 52,198 Holstein cows were used. These milk citrate phenotypes, predicted by milk mid-infrared spectra, were divided into 3 traits according to the first (citrate1), second (citrate2), and third to fifth parity (citrate3+). Genomic information for 566,170 SNPs was available for 4,479 animals. A multiple-trait repeatability model was used to estimate genetic parameters. A single-step genome-wide association study (GWAS) was used to identify candidate genes for citrate and post-GWAS analysis was done to investigate relationship and function of the identified candidate genes. The heritabilities estimated for citrate1, citrate2 and citrate3+ were 0.40, 0.37 and 0.35, respectively. The genetic correlations between the 3 traits ranged from 0.98 to 0.99. The genomic correlations between the 3 traits were also nearly 1.00 across the genomic regions (1 Mb) in the whole genome, which means that citrate can be considered as a single trait in the first 5 parities. In total, 603 significant SNPs located on 3 genomic regions (chromosome7 68.569 - 68.575 Mb, 14 1.31 - 3.05 Mb, and 20 54.00 - 64.28 Mb), were identified to be associated with milk citrate. We identified 89 candidate genes including GPT, ANKH, PPP1R16A and 32 QTL reported in the literature related to the identified significant SNPs. These identified QTL were mainly reported associated with milk fatty acids and metabolic diseases in dairy cows. This study suggests that milk citrate in Holstein cows is highly heritable and has the potential to be used as an early proxy for the NEB of Holstein cows in a breeding objective.

Identifiants

pubmed: 38056571
pii: S0022-0302(23)00826-3
doi: 10.3168/jds.2023-23903
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© 2024, 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

Yansen Chen (Y)

TERRA Teaching and Research Center, University of Liège, Gembloux Agro-Bio Tech (ULiège-GxABT), 5030 Gembloux, Belgium. Electronic address: yansen.chen@uliege.be.

Hongqing Hu (H)

TERRA Teaching and Research Center, University of Liège, Gembloux Agro-Bio Tech (ULiège-GxABT), 5030 Gembloux, Belgium.

Hadi Atashi (H)

TERRA Teaching and Research Center, University of Liège, Gembloux Agro-Bio Tech (ULiège-GxABT), 5030 Gembloux, Belgium; Department of Animal Science, Shiraz University, 71441-13131 Shiraz, Iran.

Clément Grelet (C)

Walloon Agricultural Research Center (CRA-W), 5030 Gembloux, Belgium.

Katrien Wijnrocx (K)

TERRA Teaching and Research Center, University of Liège, Gembloux Agro-Bio Tech (ULiège-GxABT), 5030 Gembloux, Belgium.

Pauline Lemal (P)

TERRA Teaching and Research Center, University of Liège, Gembloux Agro-Bio Tech (ULiège-GxABT), 5030 Gembloux, Belgium.

Nicolas Gengler (N)

TERRA Teaching and Research Center, University of Liège, Gembloux Agro-Bio Tech (ULiège-GxABT), 5030 Gembloux, Belgium.

Classifications MeSH