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Singh A, Kumar A, Gondro C, Pandey AK, Dutt T, Mishra BP. Genome Wide Scan to Identify Potential Genomic Regions Associated With Milk Protein and Minerals in Vrindavani Cattle. Front Vet Sci 2022; 9:760364. [PMID: 35359668 PMCID: PMC8960298 DOI: 10.3389/fvets.2022.760364] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Accepted: 02/11/2022] [Indexed: 12/02/2022] Open
Abstract
In this study, genome-wide association study (GWAS) was conducted for identifying significantly associated genomic regions/SNPs with milk protein and minerals in the 96 taurine-indicine crossbred (Vrindavani) cows using 50K SNP Chip. After quality control, a total of 41,427 SNPs were retained and were further analyzed using a single-SNP additive linear model. Lactation stage, parity, test day milk yield and proportion of exotic inheritance were included as fixed effects in GWAS model. Across all traits, 13 genome-wide significant (p < 1.20 x 10−06) and 49 suggestive significant (p < 2.41 x 10−05) SNPs were identified which were located on 18 different autosomes. The strongest association for protein percentage, calcium (Ca), phosphorus (P), copper (Cu), zinc (Zn), and iron (Fe) were found on BTA 18, 7, 2, 3, 14, and 2, respectively. No significant SNP was detected for manganese (Mn). Several significant SNPs identified were within or close proximity to CDH13, BHLHE40, EDIL3, HAPLN1, INHBB, USP24, ZFAT, and IKZF2 gene, respectively. Enrichment analysis of the identified candidate genes elucidated biological processes, cellular components, and molecular functions involved in metal ion binding, ion transportation, transmembrane protein, and signaling pathways. This study provided a groundwork to characterize the molecular mechanism for the phenotypic variation in milk protein percentage and minerals in crossbred cattle. Further work is required on a larger sample size with fine mapping of identified QTL to validate potential candidate regions.
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Affiliation(s)
- Akansha Singh
- Animal Genetics Division, Indian Council of Agricultural Research-Indian Veterinary Research Institute, Bareilly, India
| | - Amit Kumar
- Animal Genetics Division, Indian Council of Agricultural Research-Indian Veterinary Research Institute, Bareilly, India
- *Correspondence: Amit Kumar
| | - Cedric Gondro
- Department of Animal Science, Michigan State University, East Lansing, MI, United States
| | - A. K. Pandey
- Animal Genetics Division, Indian Council of Agricultural Research-Indian Veterinary Research Institute, Bareilly, India
| | - Triveni Dutt
- Livestock Production and Management, Indian Council of Agricultural Research-Indian Veterinary Research Institute, Bareilly, India
| | - B. P. Mishra
- Division of Animal Biotechnology, Indian Council of Agricultural Research-Indian Veterinary Research Institute, Bareilly, India
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Sheng B, Thesbjerg MN, Glantz M, Paulsson M, Nielsen SRD, Poulsen NA, Larsen LB. Phosphorylation and glycosylation isoforms of bovine κ-casein variant E in homozygous Swedish Red cow milk detected by liquid chromatography-electrospray ionization mass spectrometry. J Dairy Sci 2022; 105:1959-1965. [PMID: 34998567 DOI: 10.3168/jds.2021-21172] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Accepted: 11/15/2021] [Indexed: 11/19/2022]
Abstract
Variations in the phosphorylation and glycosylation patterns of the common κ-casein (CN) variants A and B have been explored, whereas studies on variant E heterogeneity are scarce. This study reports for the first time the detailed phosphorylation and glycosylation pattern of the κ-CN variant E in comparison with variants A and B. Individual cow milk samples representing κ-CN genotype EE (n = 12) were obtained from Swedish Red cows, and the natural posttranslational modifications of its κ-CN were identified and quantified by liquid chromatography-electrospray mass spectrometry. In total, 12 unique isoform masses of κ-CN variant E were identified. In comparison, AA and BB milk consisted of 14 and 17 unique isoform masses, respectively. The most abundant κ-CN E isoform detected in the EE milk was the monophosphorylated, unglycosylated [1P 0G, ∼70%; where P indicates phosphorylation from single to triple phosphorylation (1-3P), and G indicates glycosylation from single to triple glycosylation (1-3G)] form, followed by diphosphorylated, unglycosylated (2P 0G, ∼12%) form, resembling known patterns from variants A and B. However, a clear distinction was the presence of the rare triphosphorylated, nonglycosylated (3P 0G, ∼0.05%) κ-CN isoform in the EE milk. All isoforms detected in variant E were phosphorylated, giving a phosphorylation degree of 100%. This is comparable with the phosphorylation degree of variants A and B, being also almost 100%, though with very small amounts of nonphosphorylated, glycosylated isoforms detected. The glycosylation degree of variant E was found to be around 17%, a bit higher than observed for variant B (around 14%), and higher than variant A (around 7%). Among glycosylation, the glycan e was the most common type identified for all 3 variants, followed by c/d (straight and branched chain trisaccharides, respectively), and b. In contrast to κ-CN variants A and B, no glycan of type a was found in variant E. Taken together, this study shows that the posttranslational modification pattern of variant E resembles that of known variants to a large extent, but with subtle differences.
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Affiliation(s)
- Bulei Sheng
- Department of Food Science, Aarhus University, Agro Food Park 48, 8200 Aarhus N, Denmark.
| | - Martin N Thesbjerg
- Department of Food Science, Aarhus University, Agro Food Park 48, 8200 Aarhus N, Denmark
| | - Maria Glantz
- Department of Food Technology, Engineering and Nutrition, Lund University, PO Box 124, SE-221 00, Lund, Sweden
| | - Marie Paulsson
- Department of Food Technology, Engineering and Nutrition, Lund University, PO Box 124, SE-221 00, Lund, Sweden
| | - S Ren D Nielsen
- Department of Food Science, Aarhus University, Agro Food Park 48, 8200 Aarhus N, Denmark
| | - Nina A Poulsen
- Department of Food Science, Aarhus University, Agro Food Park 48, 8200 Aarhus N, Denmark
| | - Lotte B Larsen
- Department of Food Science, Aarhus University, Agro Food Park 48, 8200 Aarhus N, Denmark
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Extract isolated from cranberry pomace as functional ingredient in yoghurt production: Technological properties and digestibility studies. Lebensm Wiss Technol 2021. [DOI: 10.1016/j.lwt.2021.111751] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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Xiang R, Hayes BJ, Vander Jagt CJ, MacLeod IM, Khansefid M, Bowman PJ, Yuan Z, Prowse-Wilkins CP, Reich CM, Mason BA, Garner JB, Marett LC, Chen Y, Bolormaa S, Daetwyler HD, Chamberlain AJ, Goddard ME. Genome variants associated with RNA splicing variations in bovine are extensively shared between tissues. BMC Genomics 2018; 19:521. [PMID: 29973141 PMCID: PMC6032541 DOI: 10.1186/s12864-018-4902-8] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2017] [Accepted: 06/27/2018] [Indexed: 12/12/2022] Open
Abstract
Background Mammalian phenotypes are shaped by numerous genome variants, many of which may regulate gene transcription or RNA splicing. To identify variants with regulatory functions in cattle, an important economic and model species, we used sequence variants to map a type of expression quantitative trait loci (expression QTLs) that are associated with variations in the RNA splicing, i.e., sQTLs. To further the understanding of regulatory variants, sQTLs were compare with other two types of expression QTLs, 1) variants associated with variations in gene expression, i.e., geQTLs and 2) variants associated with variations in exon expression, i.e., eeQTLs, in different tissues. Results Using whole genome and RNA sequence data from four tissues of over 200 cattle, sQTLs identified using exon inclusion ratios were verified by matching their effects on adjacent intron excision ratios. sQTLs contained the highest percentage of variants that are within the intronic region of genes and contained the lowest percentage of variants that are within intergenic regions, compared to eeQTLs and geQTLs. Many geQTLs and sQTLs are also detected as eeQTLs. Many expression QTLs, including sQTLs, were significant in all four tissues and had a similar effect in each tissue. To verify such expression QTL sharing between tissues, variants surrounding (±1 Mb) the exon or gene were used to build local genomic relationship matrices (LGRM) and estimated genetic correlations between tissues. For many exons, the splicing and expression level was determined by the same cis additive genetic variance in different tissues. Thus, an effective but simple-to-implement meta-analysis combining information from three tissues is introduced to increase power to detect and validate sQTLs. sQTLs and eeQTLs together were more enriched for variants associated with cattle complex traits, compared to geQTLs. Several putative causal mutations were identified, including an sQTL at Chr6:87392580 within the 5th exon of kappa casein (CSN3) associated with milk production traits. Conclusions Using novel analytical approaches, we report the first identification of numerous bovine sQTLs which are extensively shared between multiple tissue types. The significant overlaps between bovine sQTLs and complex traits QTL highlight the contribution of regulatory mutations to phenotypic variations. Electronic supplementary material The online version of this article (10.1186/s12864-018-4902-8) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Ruidong Xiang
- Faculty of Veterinary & Agricultural Science, University of Melbourne, Parkville, VIC, 3010, Australia. .,Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC, 3083, Australia.
| | - Ben J Hayes
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC, 3083, Australia.,Queensland Alliance for Agriculture and Food Innovation, Centre for Animal Science, University of Queensland, St. Lucia, QLD, 4067, Australia
| | - Christy J Vander Jagt
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC, 3083, Australia
| | - Iona M MacLeod
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC, 3083, Australia
| | - Majid Khansefid
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC, 3083, Australia
| | - Phil J Bowman
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC, 3083, Australia.,School of Applied Systems Biology, La Trobe University, Bundoora, VIC, 3083, Australia
| | - Zehu Yuan
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC, 3083, Australia
| | | | - Coralie M Reich
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC, 3083, Australia
| | - Brett A Mason
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC, 3083, Australia
| | - Josie B Garner
- Agriculture Victoria, Dairy Production Science, Ellinbank, VIC, 3821, Australia
| | - Leah C Marett
- Agriculture Victoria, Dairy Production Science, Ellinbank, VIC, 3821, Australia
| | - Yizhou Chen
- Elizabeth Macarthur Agricultural Institute, New South Wales Department of Primary Industries, Camden, NSW, 2570, Australia
| | - Sunduimijid Bolormaa
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC, 3083, Australia
| | - Hans D Daetwyler
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC, 3083, Australia.,School of Applied Systems Biology, La Trobe University, Bundoora, VIC, 3083, Australia
| | - Amanda J Chamberlain
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC, 3083, Australia
| | - Michael E Goddard
- Faculty of Veterinary & Agricultural Science, University of Melbourne, Parkville, VIC, 3010, Australia.,Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC, 3083, Australia
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Ketto IA, Øyaas J, Ådnøy T, Johansen AG, Schüller RB, Narvhus J, Skeie SB. The influence of milk protein genetic polymorphism on the physical properties of cultured milk. Int Dairy J 2018. [DOI: 10.1016/j.idairyj.2017.11.009] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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Poulsen NA, Glantz M, Rosengaard AK, Paulsson M, Larsen LB. Comparison of milk protein composition and rennet coagulation properties in native Swedish dairy cow breeds and high-yielding Swedish Red cows. J Dairy Sci 2017; 100:8722-8734. [DOI: 10.3168/jds.2017-12920] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2017] [Accepted: 08/02/2017] [Indexed: 11/19/2022]
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Xiang R, MacLeod IM, Bolormaa S, Goddard ME. Genome-wide comparative analyses of correlated and uncorrelated phenotypes identify major pleiotropic variants in dairy cattle. Sci Rep 2017; 7:9248. [PMID: 28835686 PMCID: PMC5569018 DOI: 10.1038/s41598-017-09788-9] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2017] [Accepted: 07/31/2017] [Indexed: 11/10/2022] Open
Abstract
While single nucleotide polymorphisms (SNPs) associated with multiple phenotype have been reported, the knowledge of pleiotropy of uncorrelated phenotype is minimal. Principal components (PCs) and uncorrelated Cholesky transformed traits (CT) were constructed using 25 raw traits (RTs) of 2841 dairy bulls. Multi-trait meta-analyses of single-trait genome-wide association studies for RT, PC and CT in bulls were validated in 6821 cows. Most PCs and CTs had substantial estimates of heritability, suggesting that genes affect phenotype via diverse pathways. Phenotypic orthogonalizations did not eliminate pleiotropy: the meta-analysis achieved an agreement of significant pleiotropic SNPs (p < 1 × 10-5, n = 368) between RTs (416), PCs (466) and CTs (425). From this overlap we identified 21 lead SNPs with 100% validation rate containing two clusters: one consisted of DGAT1 (chr14:1.8 M+), MGST1 (chr5:93 M+), PAEP (chr11:103 M+) and GPAT4 (chr27:36 M+) affecting protein, milk and fat yield and the other included CSN2 (chr6:87 M+), MUC1 (chr3:15.6 M), GHR (chr20:31.2 M+) and SDC2 (chr14:70 M+) affecting protein and milk yield. Combining beef cattle data identified correlated SNPs representing CAPN1 (chr29:44 M+) and CAST (chr 7:96 M+) loci affecting beef tenderness, showing pleiotropic effects in dairy cattle. Our findings show that SNPs with a large effect on one trait are likely to have small effects on other uncorrelated traits.
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Affiliation(s)
- Ruidong Xiang
- Faculty of Veterinary & Agricultural Science, University of Melbourne, Parkville, Victoria, 3010, Australia.
- AgriBio, Department Economic Development, Jobs, Transport & Resources, Bundoora, Victoria, 3083, Australia.
| | - Iona M MacLeod
- AgriBio, Department Economic Development, Jobs, Transport & Resources, Bundoora, Victoria, 3083, Australia
| | - Sunduimijid Bolormaa
- AgriBio, Department Economic Development, Jobs, Transport & Resources, Bundoora, Victoria, 3083, Australia
- Cooperative Research Centre for Sheep Industry Innovation, Armidale, NSW 2351, Australia
| | - Michael E Goddard
- Faculty of Veterinary & Agricultural Science, University of Melbourne, Parkville, Victoria, 3010, Australia
- AgriBio, Department Economic Development, Jobs, Transport & Resources, Bundoora, Victoria, 3083, Australia
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Bedere N, Bovenhuis H. Characterizing a region on BTA11 affecting β-lactoglobulin content of milk using high-density genotyping and haplotype grouping. BMC Genet 2017; 18:17. [PMID: 28222684 PMCID: PMC5320657 DOI: 10.1186/s12863-017-0483-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2016] [Accepted: 02/11/2017] [Indexed: 11/13/2022] Open
Abstract
Background Milk β-lactoglobulin (β-LG) content is of interest as it is associated with nutritional and manufacturing properties. It is known that milk β-LG content is strongly affected by genetic factors. In cattle, most of the genetic differences are associated with a chromosomal region on BTA11, which contains the β-LG gene. The aim of this study was to characterize this region using 777 k SNP data (BovineHDbeadChip) and perform a haplotype-based association study. A statistical approach was developed to build haplotypes that capture the genetic variation associated with this genomic region. Results The SNP with the most significant effect on β-lactoglobulin content was one of the 2 causal mutations responsible for the β-lactoglobulin protein variants A/B. Haplotypes based on 2 to 5 selected lead SNP were clustered in groups with different effects on β-lactoglobulin content. Four different groups were identified suggesting that β-lactoglobulin variant A and B can be further refined in A1, A2, B1 and B2. Conclusions This study showed that β-lactoglobulin protein variants A/B do not explain all genetic variation associated with the tail part of BTA11 but this region contains more than one mutation with an effect on β-lactoglobulin content. These findings can be used for selection of cows with higher cheese yield, which is desirable for the dairy industry.
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Affiliation(s)
- Nicolas Bedere
- Present address: PEGASE, Agrocampus Ouest, INRA, 35590, Saint-Gilles, France
| | - Henk Bovenhuis
- Animal Breeding and Genomics Centre, Wageningen University, P.O. Box 338, 6700, AH, Wageningen, The Netherlands.
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Bertelsen HP, Gregersen VR, Poulsen N, Nielsen RO, Das A, Madsen LB, Buitenhuis AJ, Holm LE, Panitz F, Larsen LB, Bendixen C. Detection of genetic variation affecting milk coagulation properties in Danish Holstein dairy cattle by analyses of pooled whole-genome sequences from phenotypically extreme samples (pool-seq)1. J Anim Sci 2016; 94:1365-76. [DOI: 10.2527/jas.2015-9884] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Affiliation(s)
- H. P. Bertelsen
- Department of Molecular Biology and Genetics, Aarhus University, Tjele, Denmark
| | - V. R. Gregersen
- Department of Molecular Biology and Genetics, Aarhus University, Tjele, Denmark
| | - N. Poulsen
- Department of Food Science, Aarhus University, Tjele, Denmark
| | - R. O. Nielsen
- Department of Molecular Biology and Genetics, Aarhus University, Tjele, Denmark
| | - A. Das
- Department of Molecular Biology and Genetics, Aarhus University, Tjele, Denmark
| | - L. B. Madsen
- Department of Molecular Biology and Genetics, Aarhus University, Tjele, Denmark
| | - A. J. Buitenhuis
- Department of Molecular Biology and Genetics, Aarhus University, Tjele, Denmark
| | - L.-E. Holm
- Department of Molecular Biology and Genetics, Aarhus University, Tjele, Denmark
| | - F. Panitz
- Department of Molecular Biology and Genetics, Aarhus University, Tjele, Denmark
| | - L. B. Larsen
- Department of Food Science, Aarhus University, Tjele, Denmark
| | - C. Bendixen
- Department of Molecular Biology and Genetics, Aarhus University, Tjele, Denmark
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