TY - JOUR
T1 - Genome-wide association for metabolic clusters in early-lactation Holstein dairy cows
AU - Atashi, H.
AU - Salavati, M.
AU - De Koster, J.
AU - Crowe, M. A.
AU - Opsomer, G.
AU - Hostens, M.
AU - Niamh, McLoughlin
AU - Alan, Fahey
AU - Fiona, Carter
AU - Elizabeth, Matthews
AU - Andreia, Santoro
AU - Colin, Byrne
AU - Pauline, Rudd
AU - Roisin, O'Flaherty
AU - Sinead, Hallinan
AU - Claire, Wathes
AU - Zhangrui, Cheng
AU - Ali, Fouladi
AU - Geoff, Pollott
AU - Dirk, Werling
AU - Beatriz Sanz, Bernardo S.
AU - Conrad, Ferris
AU - Alistair, Wylie
AU - Matt, Bell
AU - Mieke, Vaneetvelde
AU - Kristof, Hermans
AU - Sander, Moerman
AU - Hannes, Bogaert
AU - Jan, Vandepitte
AU - Leila, Vandevelde
AU - Bonny, Vanranst
AU - Klaus, Ingvartsen
AU - Martin Tang, Sorensen T.
AU - Johanna, Hoglund
AU - Susanne, Dahl
AU - Soren, Ostergaard
AU - Janne, Rothmann
AU - Mogens, Krogh
AU - Else, Meyer
AU - Leslie, Foldager
AU - Charlotte, Gaillard
AU - Jehan, Ettema
AU - Tine, Rousing
AU - Torben, Larsen
AU - de, de Oliveira
AU - Cinzia, Marchitelli
AU - Federica, Signorelli
AU - Francesco, Napolitano
AU - Bianca, Moioli
AU - Alessandra, Crisà
AU - Luca, Buttazzoni
AU - Jennifer, McClure
AU - Daragh, Matthews
AU - Francis, Kearney
AU - Andrew, Cromie
AU - Matt, McClure
AU - Shujun, Zhang
AU - Xing, Chen
AU - Huanchun, Chen
AU - Junlong, Zhao
AU - Liguo, Yang
AU - Guohua, Hua
AU - Chen, Tan
AU - Guiqiang, Wang
AU - Michel, Bonneau
AU - Marlène, Sciarretta
AU - Armin, Pearn
AU - Arnold, Evertson
AU - Linda, Kosten
AU - Anders, Fogh
AU - Thomas, Andersen
AU - Matthew, Lucy
AU - Chris, Elsik
AU - Gavin, Conant
AU - Jerry, Taylor
AU - Deborah, Triant
AU - Nicolas, Gengler
AU - Michel, Georges
AU - Frederic, Colinet
AU - Marilou Ramos, Pamplona R.
AU - the GplusE Consortium
N1 - Copyright © 2020 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.
PY - 2020/7
Y1 - 2020/7
N2 - The aim of this study was to detect the genomic region or regions associated with metabolic clusters in early-lactation Holstein cows. This study was carried out in 2 experiments. In experiment I, which was carried out on 105 multiparous Holstein cows, animals were classified through k-means clustering on log-transformed and standardized concentrations of blood glucose, insulin-like growth factor I, free fatty acids, and β-hydroxybutyrate at 14 and 35 d in milk (DIM), into metabolic clusters, either balanced (BAL) or other (OTR). Forty percent of the animals were categorized in the BAL group, and the remainder were categorized as OTR. The cows were genotyped for a total of 777,962 SNP. A genome-wide association study was performed, using a case-control approach through the GEMMA software, accounting for population structure. We found 8 SNP (BTA11, BTA23, and BTAX) associated with the predicted metabolic clusters. In experiment II, carried out on 4,267 second-parity Holstein cows, milk samples collected starting from the first week until 50 DIM were used to determine Fourier-transform mid-infrared (FT-MIR) spectra and subsequently to classify the animals into the same metabolic clusters (BAL vs. OTR). Twenty-eight percent of the animals were categorized in the BAL group, and the remainder were classified in the OTR category. Although daily milk yield was lower in BAL cows, we found no difference in daily fat- and protein-corrected milk yield in cows from the BAL metabolic cluster compared with those in the OTR metabolic cluster. In the next step, a single-step genomic BLUP was used to identify the genomic region(s) associated with the predicted metabolic clusters. The results revealed that prediction of metabolic clusters is a highly polygenic trait regulated by many small-sized effects. The region of 36,258 to 36,295 kb on BTA27 was the highly associated region for the predicted metabolic clusters, with the closest genes to this region (ANK1 and miR-486) being related to hematopoiesis, erythropoiesis, and mammary gland development. The heritability for metabolic clustering was 0.17 (SD 0.03), indicating that the use of FT-MIR spectra in milk to predict metabolic clusters in early-lactation across a large number of cows has satisfactory potential to be included in genetic selection programs for modern dairy cows.
AB - The aim of this study was to detect the genomic region or regions associated with metabolic clusters in early-lactation Holstein cows. This study was carried out in 2 experiments. In experiment I, which was carried out on 105 multiparous Holstein cows, animals were classified through k-means clustering on log-transformed and standardized concentrations of blood glucose, insulin-like growth factor I, free fatty acids, and β-hydroxybutyrate at 14 and 35 d in milk (DIM), into metabolic clusters, either balanced (BAL) or other (OTR). Forty percent of the animals were categorized in the BAL group, and the remainder were categorized as OTR. The cows were genotyped for a total of 777,962 SNP. A genome-wide association study was performed, using a case-control approach through the GEMMA software, accounting for population structure. We found 8 SNP (BTA11, BTA23, and BTAX) associated with the predicted metabolic clusters. In experiment II, carried out on 4,267 second-parity Holstein cows, milk samples collected starting from the first week until 50 DIM were used to determine Fourier-transform mid-infrared (FT-MIR) spectra and subsequently to classify the animals into the same metabolic clusters (BAL vs. OTR). Twenty-eight percent of the animals were categorized in the BAL group, and the remainder were classified in the OTR category. Although daily milk yield was lower in BAL cows, we found no difference in daily fat- and protein-corrected milk yield in cows from the BAL metabolic cluster compared with those in the OTR metabolic cluster. In the next step, a single-step genomic BLUP was used to identify the genomic region(s) associated with the predicted metabolic clusters. The results revealed that prediction of metabolic clusters is a highly polygenic trait regulated by many small-sized effects. The region of 36,258 to 36,295 kb on BTA27 was the highly associated region for the predicted metabolic clusters, with the closest genes to this region (ANK1 and miR-486) being related to hematopoiesis, erythropoiesis, and mammary gland development. The heritability for metabolic clustering was 0.17 (SD 0.03), indicating that the use of FT-MIR spectra in milk to predict metabolic clusters in early-lactation across a large number of cows has satisfactory potential to be included in genetic selection programs for modern dairy cows.
KW - dairy cow
KW - genome-wide association study
KW - metabolic adaptation
KW - transition period
KW - Lactation/physiology
KW - Genome-Wide Association Study
KW - Blood Glucose/metabolism
KW - Fatty Acids, Nonesterified/blood
KW - Milk/chemistry
KW - Case-Control Studies
KW - Pregnancy
KW - Cattle/metabolism
KW - Animals
KW - Female
KW - Gene Expression Regulation/physiology
KW - Milk Proteins/analysis
KW - 3-Hydroxybutyric Acid/blood
KW - Cluster Analysis
UR - http://www.scopus.com/inward/record.url?scp=85083712607&partnerID=8YFLogxK
U2 - 10.3168/jds.2019-17369
DO - 10.3168/jds.2019-17369
M3 - Article
C2 - 32331880
AN - SCOPUS:85083712607
SN - 0022-0302
VL - 103
SP - 6392
EP - 6406
JO - Journal of Dairy Science
JF - Journal of Dairy Science
IS - 7
ER -