1
|
Atashi H, Chen Y, Wilmot H, Bastin C, Vanderick S, Hubin X, Gengler N. Single-step genome-wide association analyses for selected infrared-predicted cheese-making traits in Walloon Holstein cows. J Dairy Sci 2023; 106:7816-7831. [PMID: 37567464 DOI: 10.3168/jds.2022-23206] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Accepted: 05/01/2023] [Indexed: 08/13/2023]
Abstract
This study aimed to perform genome-wide association study to identify genomic regions associated with milk production and cheese-making properties (CMP) in Walloon Holstein cows. The studied traits were milk yield, fat percentage, protein percentage, casein percentage (CNP), calcium content, somatic cell score (SCS), coagulation time, curd firmness after 30 min from rennet addition, and titratable acidity. The used data have been collected from 2014 to 2020 on 78,073 first-parity (485,218 test-day records), 48,766 second-parity (284,942 test-day records), and 21,948 third-parity (105,112 test-day records) Holstein cows distributed in 671 herds in the Walloon Region of Belgium. Data of 565,533 single nucleotide polymorphisms (SNP), located on 29 Bos taurus autosomes (BTA) of 6,617 animals (1,712 males), were used. Random regression test-day models were used to estimate genetic parameters through the Bayesian Gibbs sampling method. The SNP solutions were estimated using a single-step genomic BLUP approach. The proportion of the total additive genetic variance explained by windows of 50 consecutive SNPs (with an average size of ∼216 KB) was calculated, and regions accounting for at least 1.0% of the total additive genetic variance were used to search for positional candidate genes. Heritability estimates for the studied traits ranged from 0.10 (SCS) to 0.53 (CNP), 0.10 (SCS) to 0.50 (CNP), and 0.12 (SCS) to 0.49 (CNP) in the first, second, and third parity, respectively. Genome-wide association analyses identified 6 genomic regions (BTA1, BTA14 [4 regions], and BTA20) associated with the considered traits. Genes including the SLC37A1 (BTA1), SHARPIN, MROH1, DGAT1, FAM83H, TIGD5, MROH6, NAPRT, ADGRB1, GML, LYPD2, JRK (BTA14), and TRIO (BTA20) were identified as positional candidate genes for the studied CMP. The findings of this study help to unravel the genomic background of a cow's ability for cheese production and can be used for the future implementation and use of genomic evaluation to improve the cheese-making traits in Walloon Holstein cows.
Collapse
Affiliation(s)
- H Atashi
- TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium; Department of Animal Science, Shiraz University, 71441-13131 Shiraz, Iran.
| | - Y Chen
- TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium
| | - H Wilmot
- TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium; National Fund for Scientific Research (FRS-FNRS), 1000 Brussels, Belgium
| | - C Bastin
- National Fund for Scientific Research (FRS-FNRS), 1000 Brussels, Belgium
| | - S Vanderick
- TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium
| | - X Hubin
- Elevéo asbl Awé Group, 5590 Ciney, Belgium
| | - N Gengler
- TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium
| |
Collapse
|
2
|
Nadugala BH, Pagel CN, Raynes JK, Ranadheera C, Logan A. Review: The effect of casein genetic variants, glycosylation and phosphorylation on bovine milk protein structure, technological properties, nutrition and product manufacture. Int Dairy J 2022. [DOI: 10.1016/j.idairyj.2022.105440] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
|
3
|
Padilla-Doval J, Zambrano-Arteaga JC, Echeverri-Zuluaga JJ, López-Herrera A. Análisis genético de cinco polimorfismos de nucleótido simple de caseínas lácteas obtenidos con chips genómicos en ganado Holstein de Antioquia, Colombia. Rev Med Vet Zoot 2021. [DOI: 10.15446/rfmvz.v68n2.98026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
Los polimorfismos genéticos asociados con las caseínas de la leche son de gran importancia, ya que pueden ser usados como marcadores genéticos para mejorar el rendimiento productivo en los hatos lecheros. El objetivo de este estudio fue evaluar la diversidad y estructura genética de 5 SNP de caseínas de la leche, obtenidos con chips genómicos en vacas y toros de raza Holstein en Antioquia (Colombia). Fueron muestreados 113 animales de raza Holstein en 3 regiones del departamento de Antioquia (norte, centro y oriente) y un cuarto grupo de sementales comerciales. Los animales fueron genotipificados con chips genómicos de alta densidad (Illumina BovineHD e Illumina SNP50 v2), a partir de los cuales se identificaron 5 SNP (ARS-BFGL-NGS-8140, BTA-77380-no-rs, BTA-32346-no-rs, BTB-00821654 y ARS-BFGL-NGS-15809). Para cada SNP se realizó un análisis genético mediante un análisis de varianza molecular (Amova) usando el software GenAIEx 6.501. Los SNP con mayor heterocigosidad total (HT) fueron ARS-BFGL-NGS-8140 y BTA-32346-no-rs, con resultados cercanos al 45%; sin embargo, la HT para ARS-BFGL-NGS-15809, BTA-77380-no-rs y BTB-00821654 estuvo por debajo del 15%. El SNP con mayor diversidad genética fue BTA-32346-no-rs (Ho – He = 0,06; p < 0,05). En esta investigación se evaluó una subpoblación de toros comerciales extranjeros, en la cual se obtuvieron frecuencias alélicas y genotípicas similares a las obtenidas para las subpoblaciones locales, sugiriendo que los alelos de los toros muy posiblemente están fijados en dichas subpoblaciones, por lo que la estructura y diversidad genética tienden a ser bajas en la muestra de estudio.
Collapse
|
4
|
Duchemin SI, Nilsson K, Fikse WF, Stålhammar H, Buhelt Johansen L, Stenholdt Hansen M, Lindmark-Månsson H, de Koning DJ, Paulsson M, Glantz M. Genetic parameters for noncoagulating milk, milk coagulation properties, and detailed milk composition in Swedish Red Dairy Cattle. J Dairy Sci 2020; 103:8330-8342. [PMID: 32600755 DOI: 10.3168/jds.2020-18315] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2020] [Accepted: 04/21/2020] [Indexed: 12/23/2022]
Abstract
The rennet-induced coagulation ability of milk is important in cheese production. For Swedish Red Dairy Cattle (RDC), this ability is reduced because of a high prevalence of noncoagulating (NC) milk. In this study, we simultaneously combined genetic parameters for NC milk, milk coagulation properties, milk composition, physical traits, and milk protein composition. Our aim was to estimate heritability and genetic and phenotypic correlations for NC milk and 24 traits (milk coagulation properties, milk composition, physical traits, and milk protein composition). Phenotypes and ∼7,000 SNP genotypes were available for all 600 Swedish RDC. The genotypes were imputed from ∼7,000 SNP to 50,000 SNP. Variance components and genetic parameters were estimated with an animal model. In Swedish RDC, a moderate heritability estimate of 0.28 was found for NC milk. For the other 24 traits, heritability estimates ranged from 0.12 to 0.77 (standard errors from 0.08 to 0.18). A total of 300 phenotypic and genetic correlations were estimated. For phenotypic and genetic correlations, 172 and 95 were significant, respectively. In general, most traits showing significant genetic correlations also showed significant phenotypic correlations. In this study, phenotypic and genetic correlations with NC milk suggest that many correlations between traits exist, making it difficult to predict the real consequences on the composition of milk, if selective breeding is applied on NC milk. We speculate that some of these consequences may lead to changes in the composition of milk, most likely affecting its physical and organoleptic properties. However, our results suggest that κ-casein could be used as an indicator trait to predict the occurrence of NC milk at the herd level.
Collapse
Affiliation(s)
- S I Duchemin
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, PO Box 7023, SE-750 07 Uppsala, Sweden.
| | - K Nilsson
- Department of Food Technology, Engineering and Nutrition, Lund University, PO Box 124, SE-221 00, Lund, Sweden
| | - W F Fikse
- Växa Sverige, PO Box 288, SE-751 05 Uppsala, Sweden
| | - H Stålhammar
- Viking Genetics, PO Box 64, SE-532 21, Skara, Sweden
| | | | | | - H Lindmark-Månsson
- Department of Food Technology, Engineering and Nutrition, Lund University, PO Box 124, SE-221 00, Lund, Sweden
| | - D-J de Koning
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, PO Box 7023, SE-750 07 Uppsala, Sweden
| | - M Paulsson
- Department of Food Technology, Engineering and Nutrition, Lund University, PO Box 124, SE-221 00, Lund, Sweden
| | - M Glantz
- Department of Food Technology, Engineering and Nutrition, Lund University, PO Box 124, SE-221 00, Lund, Sweden
| |
Collapse
|
5
|
Han B, Yuan Y, Liang R, Li Y, Liu L, Sun D. Genetic Effects of LPIN1 Polymorphisms on Milk Production Traits in Dairy Cattle. Genes (Basel) 2019; 10:genes10040265. [PMID: 30986988 PMCID: PMC6523124 DOI: 10.3390/genes10040265] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2019] [Revised: 03/27/2019] [Accepted: 03/28/2019] [Indexed: 12/16/2022] Open
Abstract
Our initial RNA sequencing work identified that lipin 1 (LPIN1) was differentially expressed during dry period, early lactation, and peak of lactation in dairy cows, and it was enriched into the fat metabolic Gene Ontology (GO) terms and pathways, thus we considered LPIN1 as the candidate gene for milk production traits. In this study, we detected the polymorphisms of LPIN1 and verified their genetic effects on milk yield and composition in a Chinese Holstein cow population. We found seven SNPs by re-sequencing the entire coding region and partial flanking region of LPIN1, including one in 5′ flanking region, four in exons, and two in 3′ flanking region. Of these, four SNPs, c.637T > C, c.708A > G, c.1521C > T, and c.1555A > C, in the exons were predicted to result in the amino acid replacements. With the Haploview 4.2, we found that seven SNPs in LPIN1 formed two haplotype blocks (D′ = 0.98–1.00). Single-SNP association analyses showed that SNPs were significantly associated with milk yield, fat yield, fat percentage, or protein yield in the first or second lactation (p = < 0.0001–0.0457), and only g.86049389C > T was strongly associated with protein percentage in both lactations (p = 0.0144 and 0.0237). The haplotype-based association analyses showed that the two haplotype blocks were significantly associated with milk yield, fat yield, protein yield, or protein percentage (p = < 0.0001–0.0383). By quantitative real-time PCR (qRT-PCR), we found that LPIN1 had relatively high expression in mammary gland and liver tissues. Furthermore, we predicted three SNPs, c.637T > C, c.708A > G, and c.1521C > T, using SOPMA software, changing the LPIN1 protein structure that might be potential functional mutations. In summary, we demonstrated the significant genetic effects of LPIN1 on milk production traits, and the identified SNPs could serve as genetic markers for dairy breeding.
Collapse
Affiliation(s)
- Bo Han
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, Key Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, National Engineering Laboratory for Animal Breeding, China Agricultural University, Beijing 100193, China.
| | - Yuwei Yuan
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, Key Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, National Engineering Laboratory for Animal Breeding, China Agricultural University, Beijing 100193, China.
| | - Ruobing Liang
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, Key Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, National Engineering Laboratory for Animal Breeding, China Agricultural University, Beijing 100193, China.
| | - Yanhua Li
- Beijing Dairy Cattle Center, Qinghe'nanzhen Deshengmenwai Street, Chaoyang District, Beijing 100192, China.
| | - Lin Liu
- Beijing Dairy Cattle Center, Qinghe'nanzhen Deshengmenwai Street, Chaoyang District, Beijing 100192, China.
| | - Dongxiao Sun
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, Key Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, National Engineering Laboratory for Animal Breeding, China Agricultural University, Beijing 100193, China.
| |
Collapse
|