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Silva EFP, Gaia RC, Mulim HA, Pinto LFB, Iung LHS, Brito LF, Pedrosa VB. Genome-Wide Association Study of Conformation Traits in Brazilian Holstein Cattle. Animals (Basel) 2024; 14:2472. [PMID: 39272257 PMCID: PMC11394126 DOI: 10.3390/ani14172472] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2024] [Revised: 08/12/2024] [Accepted: 08/20/2024] [Indexed: 09/15/2024] Open
Abstract
The linear conformation of animals exerts an influence on health, reproduction, production, and welfare, in addition to longevity, which directly affects the profitability of milk-producing farms. The objectives of this study were (1) to perform genome-wide association studies (GWASs) of conformation traits, namely the Rump, Feet and Legs, Mammary System, Dairy Strength, and Final Classification traits, and (2) to identify genes and related pathways involved in physiological processes associated with conformation traits in Brazilian Holstein cattle. Phenotypic and genotypic data from 2339 Holstein animals distributed across the states of Rio Grande do Sul, Paraná, São Paulo, and Minas Gerais were used. The genotypic data were obtained with a 100 K SNP marker panel. The single-step genome-wide association study (ssGWAS) method was employed in the analyses. Genes close to a significant SNP were identified in an interval of 100 kb up- and downstream using the Ensembl database available in the BioMart tool. The DAVID database was used to identify the main metabolic pathways and the STRING program was employed to create the gene regulatory network. In total, 36 significant SNPs were found on 15 chromosomes; 27 of these SNPs were linked to genes that may influence the traits studied. Fourteen genes most closely related to the studied traits were identified, as well as four genes that showed interactions in important metabolic pathways such as myogenesis, adipogenesis, and angiogenesis. Among the total genes, four were associated with myogenesis (TMOD2, TMOD3, CCND2, and CTBP2), three with angiogenesis (FGF23, FGF1, and SCG3), and four with adipogenesis and body size and development (C5H12orf4, CCND2, EMILIN1, and FGF6). These results contribute to a better understanding of the biological mechanisms underlying phenotypic variability in conformation traits in Brazilian Holstein cattle.
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Affiliation(s)
- Emanueli F P Silva
- Department of Animal Sciences, State University of Ponta Grossa, Ponta Grossa 84010-330, PR, Brazil
| | - Rita C Gaia
- Department of Animal Sciences, State University of Ponta Grossa, Ponta Grossa 84010-330, PR, Brazil
| | - Henrique A Mulim
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907, USA
| | | | - Laiza H S Iung
- Neogen Corporation, Pindamonhangaba 12412-800, SP, Brazil
| | - Luiz F Brito
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907, USA
| | - Victor B Pedrosa
- Department of Animal Sciences, State University of Ponta Grossa, Ponta Grossa 84010-330, PR, Brazil
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907, USA
- Neogen Corporation, Biotechnology Research, Lincoln, NE 68504, USA
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Fan Y, Jin L, He Z, Wei T, Luo T, Zhang J, Liu C, Dai C, A C, Liang Y, Tao X, Lv X, Gu Y, Li M. A cell transcriptomic profile provides insights into adipocytes of porcine mammary gland across development. J Anim Sci Biotechnol 2023; 14:126. [PMID: 37805503 PMCID: PMC10560433 DOI: 10.1186/s40104-023-00926-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Accepted: 08/03/2023] [Indexed: 10/09/2023] Open
Abstract
BACKGROUND Studying the composition and developmental mechanisms in mammary gland is crucial for healthy growth of newborns. The mammary gland is inherently heterogeneous, and its physiological function dependents on the gene expression of multiple cell types. Most studies focused on epithelial cells, disregarding the role of neighboring adipocytes. RESULTS Here, we constructed the largest transcriptomic dataset of porcine mammary gland cells thus far. The dataset captured 126,829 high-quality nuclei from physiological mammary glands across five developmental stages (d 90 of gestation, G90; d 0 after lactation, L0; d 20 after lactation, L20; 2 d post natural involution, PI2; 7 d post natural involution, PI7). Seven cell types were identified, including epithelial cells, adipocytes, endothelial cells, fibroblasts cells, immune cells, myoepithelial cells and precursor cells. Our data indicate that mammary glands at different developmental stages have distinct phenotypic and transcriptional signatures. During late gestation (G90), the differentiation and proliferation of adipocytes were inhibited. Meanwhile, partly epithelial cells were completely differentiated. Pseudo-time analysis showed that epithelial cells undergo three stages to achieve lactation, including cellular differentiation, hormone sensing, and metabolic activation. During lactation (L0 and L20), adipocytes area accounts for less than 0.5% of mammary glands. To maintain their own survival, the adipocyte exhibited a poorly differentiated state and a proliferative capacity. Epithelial cells initiate lactation upon hormonal stimulation. After fulfilling lactation mission, their undergo physiological death under high intensity lactation. Interestingly, the physiological dead cells seem to be actively cleared by immune cells via CCL21-ACKR4 pathway. This biological process may be an important mechanism for maintaining homeostasis of the mammary gland. During natural involution (PI2 and PI7), epithelial cell populations dedifferentiate into mesenchymal stem cells to maintain the lactation potential of mammary glands for the next lactation cycle. CONCLUSION The molecular mechanisms of dedifferentiation, proliferation and redifferentiation of adipocytes and epithelial cells were revealed from late pregnancy to natural involution. This cell transcriptomic profile constitutes an essential reference for future studies in the development and remodeling of the mammary gland at different stages.
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Affiliation(s)
- Yongliang Fan
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130 China
- Key Laboratory of Qinghai-Tibetan Plateau Animal Genetic Resource Reservation and Utilization, Southwest Minzu University, Chengdu, 610041 China
| | - Long Jin
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130 China
| | - Zhiping He
- Animal Breeding and Genetics Key Laboratory of Sichuan Province, Sichuan Animal Science Academy, Chengdu, 610000 China
| | - Tiantian Wei
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130 China
| | - Tingting Luo
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130 China
| | - Jiaman Zhang
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130 China
| | - Can Liu
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130 China
| | - Changjiu Dai
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130 China
| | - Chao A
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130 China
| | - Yan Liang
- Animal Breeding and Genetics Key Laboratory of Sichuan Province, Sichuan Animal Science Academy, Chengdu, 610000 China
| | - Xuan Tao
- Animal Breeding and Genetics Key Laboratory of Sichuan Province, Sichuan Animal Science Academy, Chengdu, 610000 China
| | - Xuebin Lv
- Animal Breeding and Genetics Key Laboratory of Sichuan Province, Sichuan Animal Science Academy, Chengdu, 610000 China
| | - Yiren Gu
- Key Laboratory of Qinghai-Tibetan Plateau Animal Genetic Resource Reservation and Utilization, Southwest Minzu University, Chengdu, 610041 China
- Animal Breeding and Genetics Key Laboratory of Sichuan Province, Sichuan Animal Science Academy, Chengdu, 610000 China
| | - Mingzhou Li
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130 China
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Vijayakumar P, Singaravadivelan A, Mishra A, Jagadeesan K, Bakyaraj S, Suresh R, Sivakumar T. Whole-Genome comparative analysis reveals genetic mechanisms of disease resistance and heat tolerance of tropical Bos indicus cattle breeds. Genome 2021; 65:241-254. [PMID: 34914549 DOI: 10.1139/gen-2021-0030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
The Bos indicus cattle breeds have been naturally selected over thousands of years for disease resistance and thermo-tolerance. However, a genetic mechanism of these specific inherited characteristics needs to be discovered. Hence, in this study, the whole-genome comparative analysis of Bos indicus cattle breeds of Kangayam, Tharparkar, Sahiwal, Red Sindhi, and Hariana of the Indian subcontinent was conducted. The genetic variants identification analysis revealed a total of 15,58,51,012 SNPs and 1,00,62,805 InDels in the mapped reads across all Bos indicus cattle breeds. The functional annotation of 17,252 genes that comprised both, SNPs and InDels, of high functional impact on proteins, has been carried out. The functional annotation results revealed the pathways that were involved in the innate immune response including toll-like receptors, a retinoic acid-inducible gene I like receptors, NOD-like receptors, Jak-STAT signaling pathways, and the non-synonymous variants in the candidate immune genes. Further, we also identified several pathways involved in heat shock response, hair and skin properties, oxidative stress response, osmotic stress response, thermal sweating, feed intake, metabolism, and the non-synonymous variants in the candidate thermo-tolerant genes. These pathways and genes were directly or indirectly contributing to the disease resistance and thermo-tolerance adaptations of Bos indicus cattle breeds.
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Affiliation(s)
- Periyasamy Vijayakumar
- Veterinary College and Research Institute, TANUVAS, Animal Genetics and Breeding, Livestock Farm Comlex, Orathanadu, Tamil Nadu, India, 6145 625;
| | - Arunasalam Singaravadivelan
- Veterinary College and Research Institute, TANUVAS, Livestock Production Management, VCRI, Orathanadu, Orathanadu, Tamil Nadu, India, 614 625;
| | - Anamika Mishra
- High Security Animal Disease laboratory, Indian Veterinary Research Institute, Anand Nagar, Bhopal, Madhya Pradesh, India, 462021;
| | - Krishnan Jagadeesan
- University Training and Research Centre, Pillayarpatty - 613 403, , Animal Genetics and Breeding, Thanjavur, Tamil Nadu, India;
| | - Sanniyasi Bakyaraj
- College of Poultry Production and Management, TANUVAS, Hosur, Tamil nadu, India;
| | - Ramalingam Suresh
- Veterinary College and Research Institute, TANUVAS, Animal Genetics and Breeding, VETERINARY COLLEGE AND RESEARCH INSTITUTE, Orathanadu, Tamil Nadu, India, 243122.,Indian Veterinary Research Institute, 30072, 117, Salihothra Hostel (4th hostel), IVRI, BAREILLY, Izatnagar, UTTAR PRADESH, India, 243122;
| | - Thiagarajan Sivakumar
- Veterinary College and Research Institute, TANUVAS, Livestock Production Management, Orathanadu, Tamil Nadu, India;
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Jia R, Fu Y, Xu L, Li H, Li Y, Liu L, Ma Z, Sun D, Han B. Associations between polymorphisms of SLC22A7, NGFR, ARNTL and PPP2R2B genes and Milk production traits in Chinese Holstein. BMC Genom Data 2021; 22:47. [PMID: 34732138 PMCID: PMC8567656 DOI: 10.1186/s12863-021-01002-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Accepted: 10/22/2021] [Indexed: 12/27/2022] Open
Abstract
Background Our preliminary work confirmed that, SLC22A7 (solute carrier family 22 member 7), NGFR (nerve growth factor receptor), ARNTL (aryl hydrocarbon receptor nuclear translocator like) and PPP2R2B (protein phosphatase 2 regulatory subunit Bβ) genes were differentially expressed in dairy cows during different stages of lactation, and involved in the lipid metabolism through insulin, PI3K-Akt, MAPK, AMPK, mTOR, and PPAR signaling pathways, so we considered these four genes as the candidates affecting milk production traits. In this study, we detected polymorphisms of the four genes and verified their genetic effects on milk yield and composition traits in a Chinese Holstein cow population. Results By resequencing the whole coding region and part of the flanking region of SLC22A7, NGFR, ARNTL and PPP2R2B, we totally found 20 SNPs, of which five were located in SLC22A7, eight in NGFR, three in ARNTL, and four in PPP2R2B. Using Haploview4.2, we found three haplotype blocks including five SNPs in SLC22A7, eight in NGFR and three in ARNTL. Single-SNP association analysis showed that 19 out of 20 SNPs were significantly associated with at least one of milk yield, fat yield, fat percentage, protein yield or protein percentage in the first and second lactations (P < 0.05). Haplotype-based association analysis showed that the three haplotypes were significantly associated with at least one of milk yield, fat yield, fat percentage, protein yield or protein percentage (P < 0.05). Further, we used SOPMA software to predict a SNP, 19:g.37095131C > T in NGFR, changed the structure of NGFR protein. In addition, we used Jaspar software to found that four SNPs, 19:g.37113872C > G,19:g.37113157C > T, and 19:g.37112276C > T in NGFR and 15:g.39320936A > G in ARNTL, could change the transcription factor binding sites and might affect the expression of the corresponding genes. These five SNPs might be the potential functional mutations for milk production traits in dairy cattle. Conclusions In summary, we proved that SLC22A7, NGFR, ARNTL and PPP2R2B have significant genetic effects on milk production traits. The valuable SNPs can be used as candidate genetic markers for genomic selection of dairy cattle, and the effects of these SNPs on other traits need to be further verified. Supplementary Information The online version contains supplementary material available at 10.1186/s12863-021-01002-0.
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Affiliation(s)
- Ruike Jia
- Department of Animal Genetics and Breeding, 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, No. 2 Yuanmingyuan West Road, Haidian District, Beijing, 100193, China
| | - Yihan Fu
- Department of Animal Genetics and Breeding, 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, No. 2 Yuanmingyuan West Road, Haidian District, Beijing, 100193, China
| | - Lingna Xu
- Department of Animal Genetics and Breeding, 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, No. 2 Yuanmingyuan West Road, Haidian District, Beijing, 100193, China
| | - Houcheng Li
- Department of Animal Genetics and Breeding, 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, No. 2 Yuanmingyuan West Road, Haidian District, Beijing, 100193, China
| | - Yanhua Li
- Department of Animal Genetics and Breeding, 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, No. 2 Yuanmingyuan West Road, Haidian District, Beijing, 100193, China.,Beijing Dairy Cattle Center, Beijing, 100192, China
| | - Lin Liu
- Beijing Dairy Cattle Center, Beijing, 100192, China
| | - Zhu Ma
- Beijing Dairy Cattle Center, Beijing, 100192, China
| | - Dongxiao Sun
- Department of Animal Genetics and Breeding, 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, No. 2 Yuanmingyuan West Road, Haidian District, Beijing, 100193, China
| | - Bo Han
- Department of Animal Genetics and Breeding, 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, No. 2 Yuanmingyuan West Road, Haidian District, Beijing, 100193, China.
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5
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Fu S, Shen X, Wang X, Zhou Y, Zhang J, Miao J. RNA-seq and nuclear proteomics provide insights into the lactation regulation mechanism of goat transfected IGF-I and GH recombinant vectors. Growth Horm IGF Res 2021; 60-61:101428. [PMID: 34507252 DOI: 10.1016/j.ghir.2021.101428] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/05/2021] [Revised: 06/21/2021] [Accepted: 08/31/2021] [Indexed: 11/20/2022]
Abstract
There exists little available information on the mechanisms of lactation regulation until now. In order to explore the underlying mechanism, we injected IGF-I and GH recombinant vectors into the mammary gland, then RNA-seq analysis and nuclear proteomics were used for rapid high-throughput screening of DEGs and DEPs in the two groups linked to lactation regulation. KEGG analysis of 206 DEGs showed that the same 4 of top 10 enrichment pathways (ECM receptor interaction, protein digestion and absorption, focal adhesion and phagosome) involved in 4 co-expressed genes (IDO, BTG1, ITGB6 and keratin 83), the two groups enriched different metabolic pathways yet. Nuclear proteomics analysis showed 75 and 36 DEPs in the IGF-I and GH group respectively; Sixteen common proteins were identified between the IGF-I group and GH group, four of which (ALB, TPT1, CXXC-5 and ACTR2) significantly decreased and three of which (PRP1, PAG-9 and Hsp70) significantly increased. Similarly, DEPs in the two groups were enriched in same one of top 10 enrichment pathways (PI3K-Akt signaling pathway). Protein-protein interaction networks highlighted the contribution of glycosphingolipid biosynthesis, porphyrin and chlorophyll metabolism and the Jak-STAT signaling pathway to lactation regulation of GH and IGFI. GH and IGF-I improve milk yield, which may be linked to important nodal proteins (ALB and ACTB). Our research advances the understanding of the mammary gland transcriptome and nuclear proteomics during GH and IGF-I overexpression. Individual genes, proteins and pathways in this study point towards potential targets for lactation regulation.
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Affiliation(s)
- Shaodong Fu
- MOE Joint International Research Laboratory of Animal Health and Food Safety, Key Laboratory of Physiology & Biochemistry, College of Veterinary Medicine, Nanjing Agricultural University, Nanjing 210095, China
| | - Xuehuai Shen
- Institute of Animal Husbandry and Veterinary Science, Anhui Academy of Agricultural Sciences, Livestock and Poultry Epidemic Diseases Research Center of Anhui Province, Hefei 230001, China
| | - Xudong Wang
- MOE Joint International Research Laboratory of Animal Health and Food Safety, Key Laboratory of Physiology & Biochemistry, College of Veterinary Medicine, Nanjing Agricultural University, Nanjing 210095, China
| | - Yilin Zhou
- MOE Joint International Research Laboratory of Animal Health and Food Safety, Key Laboratory of Physiology & Biochemistry, College of Veterinary Medicine, Nanjing Agricultural University, Nanjing 210095, China
| | - Jinqiu Zhang
- Institute of Veterinary Immunology & Engineering, Jiangsu Academy of Agricultural Sciences,Nanjing 210014, China.
| | - Jinfeng Miao
- MOE Joint International Research Laboratory of Animal Health and Food Safety, Key Laboratory of Physiology & Biochemistry, College of Veterinary Medicine, Nanjing Agricultural University, Nanjing 210095, China.
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Honerlagen H, Reyer H, Oster M, Ponsuksili S, Trakooljul N, Kuhla B, Reinsch N, Wimmers K. Identification of Genomic Regions Influencing N-Metabolism and N-Excretion in Lactating Holstein- Friesians. Front Genet 2021; 12:699550. [PMID: 34335696 PMCID: PMC8318802 DOI: 10.3389/fgene.2021.699550] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Accepted: 06/18/2021] [Indexed: 12/03/2022] Open
Abstract
Excreted nitrogen (N) of dairy cows contribute to environmental eutrophication. The main N-excretory metabolite of dairy cows is urea, which is synthesized as a result of N-metabolization in the liver and is excreted via milk and urine. Genetic variation in milk urea (MU) has been postulated but the complex physiology behind the trait as well as the tremendous diversity of processes regulating the N-metabolism impede the consistent determination of causal regions in the bovine genome. In order to map the genetic determinants affecting N-excretion, MU and eight other N-excretory metabolites in milk and urine were assessed in a genome-wide association study. Therefore phenotypes of 371 Holstein- Friesians were obtained in a trial on a dairy farm under near commercial conditions. Genotype data comprised SNP information of the Bovine 50K MD Genome chip (45,613 SNPs). Significantly associated genomic regions for MU concentration revealed GJA1 (BTA 9), RXFP1, and FRY1 (both BTA 12) as putative candidates. For milk urea yield (MUY) a promising QTL on BTA 17 including SH3D19 emerged, whereas RCAN2, CLIC5, ENPP4, and ENPP5 (BTA 23) are suggested to influence urinary urea concentration. Minor N-fractions in milk (MN) may be regulated by ELF2 and SLC7A11 (BTA 17), whilst ITPR2 and MYBPC1 (BTA 5), STIM2 (BTA 6), SGCD (BTA 7), SLC6A2 (BTA 18), TMCC2 and MFSD4A (BTA 16) are suggested to have an impact on various non-urea-N (NUN) fractions excreted via urine. Our results highlight genomic regions and candidate genes for N-excretory metabolites and provide a deeper insight into the predisposed component to regulate the N-metabolism in dairy cows.
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Affiliation(s)
- Hanne Honerlagen
- Genomics Unit, Institute for Genome Biology, Leibniz Institute for Farm Animal Biology (FBN), Dummerstorf, Germany
| | - Henry Reyer
- Genomics Unit, Institute for Genome Biology, Leibniz Institute for Farm Animal Biology (FBN), Dummerstorf, Germany
| | - Michael Oster
- Genomics Unit, Institute for Genome Biology, Leibniz Institute for Farm Animal Biology (FBN), Dummerstorf, Germany
| | - Siriluck Ponsuksili
- Genomics Unit, Institute for Genome Biology, Leibniz Institute for Farm Animal Biology (FBN), Dummerstorf, Germany
| | - Nares Trakooljul
- Genomics Unit, Institute for Genome Biology, Leibniz Institute for Farm Animal Biology (FBN), Dummerstorf, Germany
| | - Björn Kuhla
- Metabolism Efficiency Unit, Institute of Nutritional Physiology "Oskar Kellner," Leibniz Institute for Farm Animal Biology (FBN), Dummerstorf, Germany
| | - Norbert Reinsch
- Livestock Genetics and Breeding Unit, Institute of Genetics and Biometry, Leibniz Institute for Farm Animal Biology (FBN), Dummerstorf, Germany
| | - Klaus Wimmers
- Genomics Unit, Institute for Genome Biology, Leibniz Institute for Farm Animal Biology (FBN), Dummerstorf, Germany.,Faculty of Agricultural and Environmental Sciences, University of Rostock, Rostock, Germany
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Identification of Genomic Regions Associated with Concentrations of Milk Fat, Protein, Urea and Efficiency of Crude Protein Utilization in Grazing Dairy Cows. Genes (Basel) 2021; 12:genes12030456. [PMID: 33806889 PMCID: PMC8004844 DOI: 10.3390/genes12030456] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Revised: 03/16/2021] [Accepted: 03/19/2021] [Indexed: 01/01/2023] Open
Abstract
The objective of this study was to identify genomic regions associated with milk fat percentage (FP), crude protein percentage (CPP), urea concentration (MU) and efficiency of crude protein utilization (ECPU: ratio between crude protein yield in milk and dietary crude protein intake) using grazing, mixed-breed, dairy cows in New Zealand. Phenotypes from 634 Holstein Friesian, Jersey or crossbred cows were obtained from two herds at Massey University. A subset of 490 of these cows was genotyped using Bovine Illumina 50K SNP-chips. Two genome-wise association approaches were used, a single-locus model fitted to data from 490 cows and a single-step Bayes C model fitted to data from all 634 cows. The single-locus analysis was performed with the Efficient Mixed-Model Association eXpedited model as implemented in the SVS package. Single nucleotide polymorphisms (SNPs) with genome-wide association p-values ≤ 1.11 × 10−6 were considered as putative quantitative trait loci (QTL). The Bayes C analysis was performed with the JWAS package and 1-Mb genomic windows containing SNPs that explained > 0.37% of the genetic variance were considered as putative QTL. Candidate genes within 100 kb from the identified SNPs in single-locus GWAS or the 1-Mb windows were identified using gene ontology, as implemented in the Ensembl Genome Browser. The genes detected in association with FP (MGST1, DGAT1, CEBPD, SLC52A2, GPAT4, and ACOX3) and CPP (DGAT1, CSN1S1, GOSR2, HERC6, and IGF1R) were identified as candidates. Gene ontology revealed six novel candidate genes (GMDS, E2F7, SIAH1, SLC24A4, LGMN, and ASS1) significantly associated with MU whose functions were in protein catabolism, urea cycle, ion transportation and N excretion. One novel candidate gene was identified in association with ECPU (MAP3K1) that is involved in post-transcriptional modification of proteins. The findings should be validated using a larger population of New Zealand grazing dairy cows.
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