1
|
Atashi H, Chen Y, Wilmot H, Vanderick S, Hubin X, Soyeurt H, Gengler N. Single-step genome-wide association for selected milk fatty acids in Dual-Purpose Belgian Blue cows. J Dairy Sci 2023; 106:6299-6315. [PMID: 37479585 DOI: 10.3168/jds.2022-22432] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Accepted: 03/17/2023] [Indexed: 07/23/2023]
Abstract
The aim of this study was to estimate genetic parameters and identify genomic regions associated with selected individual and groups of milk fatty acids (FA) predicted by milk mid-infrared spectrometry in Dual-Purpose Belgian Blue cows. The used data were 69,349 test-day records of milk yield, fat percentage, and protein percentage along with selected individual and groups FA of milk (g/dL milk) collected from 2007 to 2020 on 7,392 first-parity (40,903 test-day records), and 5,185 second-parity (28,446 test-day records) cows distributed in 104 herds in the Walloon Region of Belgium. Data of 28,466 SNPs, located on 29 Bos taurus autosomes (BTA), of 1,699 animals (639 males and 1,060 females) 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 best linear unbiased prediction approach. The proportion of genetic variance explained by each 25-SNP sliding window (with an average size of ~2 Mb) was calculated, and regions accounting for at least 1.0% of the total additive genetic variance were used to search for candidate genes. Average daily heritability estimated for the included milk FA traits ranged from 0.01 (C4:0) to 0.48 (C12:0) and 0.01 (C4:0) to 0.42 (C12:0) in the first and second parities, respectively. Genetic correlations found between milk yield and the studied individual milk FA, except for C18:0, C18:1 trans, C18:1 cis-9, were positive. The results showed that fat percentage and protein percentage were positively genetically correlated with all studied individual milk FA. Genome-wide association analyses identified 11 genomic regions distributed over 8 chromosomes [BTA1, BTA4, BTA10, BTA14 (4 regions), BTA19, BTA22, BTA24, and BTA26] associated with the studied FA traits, though those found on BTA14 partly overlapped. The genomic regions identified differed between parities and lactation stages. Although these differences in genomic regions detected may be due to the power of quantitative trait locus detection, it also suggests that candidate genes underlie the phenotypic expression of the studied traits may vary between parities and lactation stages. These findings increase our understanding about the genetic background of milk FA and can be used for the future implementation of genomic evaluation to improve milk FA profile in Dual-Purpose Belgian Blue 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 (F.R.S.-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
| | - H Soyeurt
- TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium
| | - N Gengler
- TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium
| |
Collapse
|
2
|
Buitenhuis AJ, Hein L, Sørensen LP, Kargo M. Correlation between breeding values for milk fatty acids and Nordic Total Merit index traits for Danish Holstein and Danish Jersey. J Dairy Sci 2023:S0022-0302(23)00346-6. [PMID: 37331869 DOI: 10.3168/jds.2022-22575] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Accepted: 02/11/2023] [Indexed: 06/20/2023]
Abstract
Milk fatty acid composition is gaining interest in the Danish dairy industry both to develop new dairy products and as a management tool. To be able to implement milk fatty acid (FA) composition in the breeding program, it is important to know the correlations with the traits in the breeding goal. To estimate these correlations, we measured milk fat composition in Danish Holstein (DH) and Danish Jersey (DJ) cattle breeds using mid-infrared spectroscopy. Breeding values were estimated for specific FA and for groups of FA. Correlations with the estimated breeding values (EBV) underlying the Nordic Total Merit index (NTM) were calculated within breed. For both DH and DJ, we showed that FA EBV had moderate correlations with the NTM and production traits. For both DH and DJ, the correlation of FA EBV and NTM were in the same direction, except for C16:0 (0 in DH, 0.23 in DJ). A few correlations differed between DH and DJ. The correlation between claw health index and C18:0 was negative in DH (-0.09) but positive in DJ (0.12). In addition, some correlations were not significant in DH but were significant in DJ. The correlations between udder health index and long-chain FA, trans FA, C16:0, and C18:0 were not significant in DH (-0.05 to 0.02), but were significant in DJ (-0.17, -0.15, 0.14, and -0.16, respectively). For both DH and DJ, the correlations between FA EBV and nonproduction traits were low. This implies that it is possible to breed for a different fat composition in the milk without affecting the nonproduction traits in the breeding goal.
Collapse
Affiliation(s)
- A J Buitenhuis
- Center for Quantitative Genetics and Genomics, Aarhus University, DK-8000 Aarhus C, Denmark.
| | - L Hein
- SEGES, 8200 Aarhus N, Denmark
| | | | - M Kargo
- Center for Quantitative Genetics and Genomics, Aarhus University, DK-8000 Aarhus C, Denmark
| |
Collapse
|
3
|
Voronina OA, Zaitsev SY, Savina AA, Rykov RA, Kolesnik NS. Seasonal Changes in the Antioxidant Activity and Biochemical Parameters of Goat Milk. Animals (Basel) 2023; 13:ani13101706. [PMID: 37238136 DOI: 10.3390/ani13101706] [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: 04/06/2023] [Revised: 05/15/2023] [Accepted: 05/18/2023] [Indexed: 05/28/2023] Open
Abstract
Goats are ubiquitous, including in hot and dry regions, while also being very sensitive to climate fluctuations, expressed in temperature differences. This affects their productivity and milk quality. Adaptation to heat requires high energy costs, affects "neurohumoral" regulation and is accompanied by oxidative stress with the increased production of free radicals. The aim was to study the main biochemical parameters of goat milk and its antioxidant activity depending on the season of the year. Sampling was carried out in April, June, August and October. Analysis of the biochemical components and antioxidant activity of goat milk was performed using modern analytical systems. From spring to autumn, the mass fraction of true or crude proteins in goat milk increased by 14.6-63.7% or by 12.3-52.1%, and the mass fraction of caseins also increased by 13.6-60.6%. For vitamin C level and the total amount of water-soluble antioxidants, a pronounced gradual decrease from spring to autumn was observed. In the summer period, a small increase in the carotene level in milk (by 3.0-6.1% compared to April) was established. Vitamin A content increased by 86.5% (June) or by 70.3% (October) compared to April. Thus, the numerous significant changes in the major parameters of goat's milk depending on the season were revealed.
Collapse
Affiliation(s)
- Oksana A Voronina
- Federal Research Center for Animal Husbandry Named after Academy Member L.K. Ernst, Dubrovitsy 60, Podolsk Municipal District, Moscow 142132, Russia
| | - Sergei Yu Zaitsev
- Federal Research Center for Animal Husbandry Named after Academy Member L.K. Ernst, Dubrovitsy 60, Podolsk Municipal District, Moscow 142132, Russia
| | - Anastasia A Savina
- Federal Research Center for Animal Husbandry Named after Academy Member L.K. Ernst, Dubrovitsy 60, Podolsk Municipal District, Moscow 142132, Russia
| | - Roman A Rykov
- Federal Research Center for Animal Husbandry Named after Academy Member L.K. Ernst, Dubrovitsy 60, Podolsk Municipal District, Moscow 142132, Russia
| | - Nikita S Kolesnik
- Federal Research Center for Animal Husbandry Named after Academy Member L.K. Ernst, Dubrovitsy 60, Podolsk Municipal District, Moscow 142132, Russia
| |
Collapse
|
4
|
Tiplady KM, Lopdell TJ, Reynolds E, Sherlock RG, Keehan M, Johnson TJJ, Pryce JE, Davis SR, Spelman RJ, Harris BL, Garrick DJ, Littlejohn MD. Sequence-based genome-wide association study of individual milk mid-infrared wavenumbers in mixed-breed dairy cattle. Genet Sel Evol 2021; 53:62. [PMID: 34284721 PMCID: PMC8290608 DOI: 10.1186/s12711-021-00648-9] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Accepted: 06/22/2021] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND Fourier-transform mid-infrared (FT-MIR) spectroscopy provides a high-throughput and inexpensive method for predicting milk composition and other novel traits from milk samples. While there have been many genome-wide association studies (GWAS) conducted on FT-MIR predicted traits, there have been few GWAS for individual FT-MIR wavenumbers. Using imputed whole-genome sequence for 38,085 mixed-breed New Zealand dairy cattle, we conducted GWAS on 895 individual FT-MIR wavenumber phenotypes, and assessed the value of these direct phenotypes for identifying candidate causal genes and variants, and improving our understanding of the physico-chemical properties of milk. RESULTS Separate GWAS conducted for each of 895 individual FT-MIR wavenumber phenotypes, identified 450 1-Mbp genomic regions with significant FT-MIR wavenumber QTL, compared to 246 1-Mbp genomic regions with QTL identified for FT-MIR predicted milk composition traits. Use of mammary RNA-seq data and gene annotation information identified 38 co-localized and co-segregating expression QTL (eQTL), and 31 protein-sequence mutations for FT-MIR wavenumber phenotypes, the latter including a null mutation in the ABO gene that has a potential role in changing milk oligosaccharide profiles. For the candidate causative genes implicated in these analyses, we examined the strength of association between relevant loci and each wavenumber across the mid-infrared spectrum. This revealed shared association patterns for groups of genomically-distant loci, highlighting clusters of loci linked through their biological roles in lactation and their presumed impacts on the chemical composition of milk. CONCLUSIONS This study demonstrates the utility of FT-MIR wavenumber phenotypes for improving our understanding of milk composition, presenting a larger number of QTL and putative causative genes and variants than found from FT-MIR predicted composition traits. Examining patterns of significance across the mid-infrared spectrum for loci of interest further highlighted commonalities of association, which likely reflects the physico-chemical properties of milk constituents.
Collapse
Affiliation(s)
- Kathryn M. Tiplady
- Research and Development, Livestock Improvement Corporation, Private Bag 3016, Hamilton, 3240 New Zealand
- School of Agriculture, Massey University, Ruakura, Hamilton, 3240 New Zealand
| | - Thomas J. Lopdell
- Research and Development, Livestock Improvement Corporation, Private Bag 3016, Hamilton, 3240 New Zealand
| | - Edwardo Reynolds
- School of Agriculture, Massey University, Ruakura, Hamilton, 3240 New Zealand
| | - Richard G. Sherlock
- Research and Development, Livestock Improvement Corporation, Private Bag 3016, Hamilton, 3240 New Zealand
| | - Michael Keehan
- Research and Development, Livestock Improvement Corporation, Private Bag 3016, Hamilton, 3240 New Zealand
| | - Thomas JJ. Johnson
- Research and Development, Livestock Improvement Corporation, Private Bag 3016, Hamilton, 3240 New Zealand
| | - Jennie E. Pryce
- School of Applied Systems Biology, La Trobe University, Bundoora, VIC 3083 Australia
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC 3083 Australia
| | - Stephen R. Davis
- Research and Development, Livestock Improvement Corporation, Private Bag 3016, Hamilton, 3240 New Zealand
| | - Richard J. Spelman
- Research and Development, Livestock Improvement Corporation, Private Bag 3016, Hamilton, 3240 New Zealand
| | - Bevin L. Harris
- Research and Development, Livestock Improvement Corporation, Private Bag 3016, Hamilton, 3240 New Zealand
| | - Dorian J. Garrick
- School of Agriculture, Massey University, Ruakura, Hamilton, 3240 New Zealand
| | - Mathew D. Littlejohn
- Research and Development, Livestock Improvement Corporation, Private Bag 3016, Hamilton, 3240 New Zealand
- School of Agriculture, Massey University, Ruakura, Hamilton, 3240 New Zealand
| |
Collapse
|
5
|
Singh A, Kumar A, Gondro C, da Silva Romero AR, Karthikeyan A, Mehrotra A, Pandey AK, Dutt T, Mishra BP. Identification of genes affecting milk fat and fatty acid composition in Vrindavani crossbred cattle using 50 K SNP-Chip. Trop Anim Health Prod 2021; 53:347. [PMID: 34091779 DOI: 10.1007/s11250-021-02795-z] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Accepted: 05/30/2021] [Indexed: 11/25/2022]
Abstract
The aim of this study was to identify candidate genes associated with milk fat per cent and fatty acid (FA) composition in Vrindavani cattle using the Illumina 50 K single-nucleotide polymorphism (SNP) array. After quality control, a total of 41,427 informative and high-quality SNPs were used for a genome-wide association study (GWAS) for milk fat percentage and 16 different types of fatty acids. Lactation stage, parity, test day milk yield, and proportion of exotic inheritance were included as fixed effects in the GWAS model. A total of 67 genome-wide significant (P < 1.20 × 10-06) SNPs and 176 suggestive significant (P < 2.41 × 10-05) SNPs were identified. Out of these, 15 SNPs were associated with more than one trait. The strongest associations were found on BTA14 for milk fat percentage and on BTA2 and BTA16 for polyunsaturated fatty acids. Several significant SNPs were identified close to or within the genes ELOVL6, FABP4, PMP2, PLIN1, MFGE8, GHRL2, and LDLRAD3 which are known to be associated with fat percentage and FA composition in dairy cattle breeds. This study is a step forward to better characterize the molecular mechanisms of phenotypic variation in milk fatty acids in a taurine-indicine composite cattle breed reared in tropical environments.
Collapse
Affiliation(s)
- Akansha Singh
- Animal Genetics Division, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly, India
| | - Amit Kumar
- Animal Genetics Division, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly, India.
| | - Cedric Gondro
- Department of Animal Science, Michigan State University, East Lansing, MI, USA
| | | | - A Karthikeyan
- Animal Genetics Division, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly, India
| | - Arnav Mehrotra
- Animal Genetics Division, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly, India
| | - A K Pandey
- Animal Genetics Division, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly, India
| | - Triveni Dutt
- Livestock Production and Management Division, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly, India
| | - B P Mishra
- Animal Biotechnology Division, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly, India
| |
Collapse
|
6
|
Ghavi Hossein-Zadeh N. A meta-analysis of heritability estimates for milk fatty acids and their genetic relationship with milk production traits in dairy cows using a random-effects model. Livest Sci 2021. [DOI: 10.1016/j.livsci.2020.104388] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
|
7
|
Bulk milk quality as affected by cattle breed composition of the herd in mountain area. ANNALS OF ANIMAL SCIENCE 2021. [DOI: 10.2478/aoas-2020-0067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
Abstract
The aim of this study was to investigate the variation of gross composition, somatic cell count, urea content, and fatty acids (FA) composition of bulk milk from single-breed and multi-breed farms in alpine area, keeping either Brown Swiss (BS), Holstein Friesian (HF), Simmental (SI), or their combinations. Gross milk composition, urea content, and FA composition were predicted using mid-infrared spectroscopy. Observations were grouped in 7 combinations consisting of 3 singlebreed and 4 multi-breed types of herd. A mixed linear model was used for data analysis, accounting for the fixed effects of herd composition (7 combinations), month of sampling, year of sampling, and the interactions between herd composition and month of sampling, and between herd composition and year of sampling. Farm was included as random effect. Results highlighted that about two thirds of South Tyrolean farms were single-breed and herds with more than 20 lactating cows changed herd structure over time, switching from multi- to single-breed. Single-breed BS farms produced milk with greater fat, protein, casein, lactose, and FA content than single-breed HF and SI farms. Further, multi-breed herds including BS cows produced milk with greater fat, protein, casein, and polyunsaturated FA content than multi-breed HF+SI herds. Overall, single-breed SI farms produced milk with lower somatic cell count than other herd combinations. Despite the number of BS cows in South Tyrol has decreased in favor of SI in the last years, this breed is still the most interesting for alpine dairy farming to achieve optimal milk quality in both single- and multi-breed scenarios. The tendency to move to SI is mainly related to good milk performance of SI cows coupled with their robustness, high carcass value, high market value of calves, and adaptability to mountain farming system.
Collapse
|
8
|
Palombo V, Pegolo S, Conte G, Cesarani A, Macciotta NPP, Stefanon B, Ajmone Marsan P, Mele M, Cecchinato A, D'Andrea M. Genomic prediction for latent variables related to milk fatty acid composition in Holstein, Simmental and Brown Swiss dairy cattle breeds. J Anim Breed Genet 2020; 138:389-402. [PMID: 33331079 DOI: 10.1111/jbg.12532] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2020] [Revised: 11/27/2020] [Accepted: 12/02/2020] [Indexed: 12/19/2022]
Abstract
Genomic selection (GS) reports on milk fatty acid (FA) profiles have been published quite recently and are still few despite this trait represents the most important aspect of milk nutritional and sensory quality. Reasons for this can be found in the high costs of phenotype recording but also in issues related to its nature of complex trait constituted by multiple genetically correlated variables with low heritabilities. One possible strategy to deal with such constraint is represented by the use of dimension reduction methods. We analysed 40 individual FAs from Italian Brown Swiss, Holstein and Simmental milk through multivariate factor analysis (MFA) to study the genetics of milk FA-related latent variables (factors) and assess their potential use in breeding. A total of nine factors were obtained, and their genetic parameters were inferred under a Bayesian framework using two statistical approaches: the classical pedigree best linear unbiased prediction (ABLUP) and the single-step genomic BLUP (ssGBLUP). The resulting factorial solutions were able to represent groups of FAs with common origin and function and can be considered concise pathway-level phenotypes. The heritability (h2 ) values showed relevant variations across different factors in each breed (0.03 ≤ h2 ≤ 0.38). The accuracies of breeding values predicted were low to high, ranging from 0.13 to 0.72 and from 0.18 to 0.74 considering the pedigree and the genomic model, respectively. The gain in accuracy in genetic prediction due to the addition of genomic information was ~30% and ~5% in validation and training groups respectively, confirming the contribution of genomic information in yielding more accurate predictions compared to the traditional ABLUP methodology. Our results suggest that MFA in combination with GS can be a valuable tool in dairy cattle breeding and deserves to be further investigated for use in future breeding programs to improve cow's milk FA-related traits.
Collapse
Affiliation(s)
- Valentino Palombo
- Dipartimento Agricoltura, Ambiente e Alimenti, Università degli Studi del Molise, Campobasso, Italy
| | - Sara Pegolo
- Dipartimento di Agronomia, Animali, Alimenti, Risorse naturali e Ambiente (DAFNAE), Università di Padova, Padova, Italy
| | - Giuseppe Conte
- Dipartimento di Scienze Agrarie, Alimentari e Agro-ambientali, Università di Pisa, Pisa, Italy
| | - Alberto Cesarani
- Dipartimento di Agraria, Sezione Scienze Zootecniche, Università degli Studi di Sassari, Sassari, Italy.,Department of Animal and Dairy Science, University of Georgia, Athens, GA, USA
| | | | - Bruno Stefanon
- Dipartimento di Scienze Agroambientali, Alimentari e Animali, Università di Udine, Udine, Italy
| | - Paolo Ajmone Marsan
- Dipartimento di Scienze Animali, degli Alimenti e della Nutrizione - DIANA e Centro di Ricerca Nutrigenomica e Proteomica - PRONUTRIGEN, Università Cattolica del Sacro Cuore, Piacenza, Italy
| | - Marcello Mele
- Dipartimento di Scienze Agrarie, Alimentari e Agro-ambientali, Università di Pisa, Pisa, Italy
| | - Alessio Cecchinato
- Dipartimento di Agronomia, Animali, Alimenti, Risorse naturali e Ambiente (DAFNAE), Università di Padova, Padova, Italy
| | - Mariasilvia D'Andrea
- Dipartimento Agricoltura, Ambiente e Alimenti, Università degli Studi del Molise, Campobasso, Italy
| |
Collapse
|
9
|
Bobbo T, Penasa M, Cassandro M. Genetic Parameters of Bovine Milk Fatty Acid Profile, Yield, Composition, Total and Differential Somatic Cell Count. Animals (Basel) 2020; 10:E2406. [PMID: 33339148 PMCID: PMC7765606 DOI: 10.3390/ani10122406] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2020] [Revised: 12/09/2020] [Accepted: 12/13/2020] [Indexed: 11/16/2022] Open
Abstract
The growing interest of consumers for milk and dairy products of high nutritional value has pushed researchers to evaluate the feasibility of including fatty acids (FA) in selection programs to modify milk fat profile and improve its nutritional quality. Therefore, the aim of this study was to estimate genetic parameters of FA profile predicted by mid-infrared spectroscopy, milk yield, composition, and total and differential somatic cell count. Edited data included 35,331 test-day records of 25,407 Italian Holstein cows from 652 herds. Variance components and heritability were estimated using single-trait repeatability animal models, whereas bivariate repeatability animal models were used to estimate genetic and phenotypic correlations between traits, including the fixed effects of stage of lactation, parity, and herd-test-date, and the random effects of additive genetic animal, cow permanent environment and the residual. Heritabilities and genetic correlations obtained in the present study reflected both the origins of FA (extracted from the blood or synthesized de novo by the mammary gland) and their grouping according to saturation or chain length. In addition, correlations among FA groups were in line with correlation among individual FA. Moderate negative genetic correlations between FA and milk yield and moderate to strong positive correlations with fat, protein, and casein percentages suggest that actual selection programs are currently affecting all FA groups, not only the desired ones (e.g., polyunsaturated FA). The absence of association with differential somatic cell count and the weak association with somatic cell score indicate that selection on FA profile would not affect selection on resistance to mastitis and vice versa. In conclusion, our findings suggest that genetic selection on FA content is feasible, as FA are variable and moderately heritable. Nevertheless, in the light of correlations with other milk traits estimated in this study, a clear breeding goal should first be established.
Collapse
Affiliation(s)
- Tania Bobbo
- Department of Agronomy, Food, Natural resources, Animals and Environment (DAFNAE), University of Padova, Viale dell’Università 16, 35020 Legnaro, Italy; (M.P.); (M.C.)
| | | | | |
Collapse
|
10
|
Dettmann F, Warner D, Buitenhuis B, Kargo M, Kjeldsen AMH, Nielsen NH, Lefebvre DM, Santschi DE. Fatty Acid Profiles from Routine Milk Recording as a Decision Tool for Body Weight Change of Dairy Cows after Calving. Animals (Basel) 2020; 10:E1958. [PMID: 33114197 PMCID: PMC7690826 DOI: 10.3390/ani10111958] [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: 09/15/2020] [Revised: 10/15/2020] [Accepted: 10/20/2020] [Indexed: 01/31/2023] Open
Abstract
Cows mobilize body reserves during early lactation, which is reflected in the milk fatty acid (FA) profile. Milk FA can be routinely predicted by Fourier-transform infrared (FTIR) spectroscopy, and be, thus, used to develop an early indicator for bodyweight change (BWC) in early lactating cows in commercial dairy farms. Cow records from 165 herds in Denmark between 2015 and 2017 were used with bodyweight (BW) records at each milking from floor scales in automatic milking systems. Milk FA in monthly test-day samples was predicted by FTIR. Predictions of BWC were based on a random forest model and included parity, stage of lactation, and test day milk production and components (fat, protein, and FA). Bodyweight loss was mainly explained by decreased short-chain FA (C4:0-C10:0) and increased C18:0 FA. The root mean square error (RMSE) of prediction after cross-validation was 1.79 g/kg of BW (R2 of 0.94). Model evaluation with previously unseen BWC records resulted in reduced prediction performance (RMSE of 2.33 g/kg of BW; R2 of 0.31). An early warning system may be implemented for cows with a large BW loss during early lactation based on milk FA profiles, but model performance should be improved, ideally by using the full FTIR milk spectra.
Collapse
Affiliation(s)
- Franziska Dettmann
- Lactanet, Sainte-Anne-de-Bellevue, QC H9X3R4, Canada; (F.D.); (D.W.); (D.M.L.)
- LKV Niedersachsen e.V., 26789 Leer, Germany
| | - Daniel Warner
- Lactanet, Sainte-Anne-de-Bellevue, QC H9X3R4, Canada; (F.D.); (D.W.); (D.M.L.)
| | - Bart Buitenhuis
- Center for Quantitative Genetics and Genomics, Aarhus University, 8830 Tjele, Denmark; (B.B.); (M.K.)
| | - Morten Kargo
- Center for Quantitative Genetics and Genomics, Aarhus University, 8830 Tjele, Denmark; (B.B.); (M.K.)
- SEGES, 8200 Aarhus N, Denmark;
| | | | | | - Daniel M. Lefebvre
- Lactanet, Sainte-Anne-de-Bellevue, QC H9X3R4, Canada; (F.D.); (D.W.); (D.M.L.)
| | - Debora E. Santschi
- Lactanet, Sainte-Anne-de-Bellevue, QC H9X3R4, Canada; (F.D.); (D.W.); (D.M.L.)
| |
Collapse
|
11
|
Freitas P, Oliveira H, Silva F, Fleming A, Miglior F, Schenkel F, Brito L. Genomic analyses for predicted milk fatty acid composition throughout lactation in North American Holstein cattle. J Dairy Sci 2020; 103:6318-6331. [DOI: 10.3168/jds.2019-17628] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2019] [Accepted: 03/12/2020] [Indexed: 12/12/2022]
|
12
|
Lopez-Villalobos N, Spelman RJ, Melis J, Davis SR, Berry SD, Lehnert K, Sneddon NW, Holroyd SE, MacGibbon AK, Snell RG. Genetic correlations of milk fatty acid contents predicted from milk mid-infrared spectra in New Zealand dairy cattle. J Dairy Sci 2020; 103:7238-7248. [PMID: 32534926 DOI: 10.3168/jds.2019-17971] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2019] [Accepted: 04/02/2020] [Indexed: 12/29/2022]
Abstract
The objective of this study was to estimate genetic correlations among milk fatty acid (FA) concentrations in New Zealand dairy cattle. Concentrations of each of the most common FA, expressed as a percentage of the total FA, were determined by gas chromatography on a specific cohort of animals. Using this data set, prediction equations were derived using mid-infrared (MIR) spectroscopy data collected from the same samples. These prediction equations were applied to a large data set of MIR measurements in 34,141 milk samples from 3,445 Holstein-Friesian, 2,935 Jersey, and 3,609 crossbred Holstein-Friesian × Jersey cows, sampled an average of 3.42 times during the 2007-2008 season. Data were analyzed using univariate and bivariate repeatability animal models. Heritability of predicted FA concentration in milk fat ranged from 0.21 to 0.42, indicating that genetic selection could be used to change the FA composition of milk. The de novo synthesized FA (C6:0, C8:0, C10:0, C12:0, and C14:0) showed strong positive genetic correlations with each other, ranging from 0.24 to 0.99. Saturated FA were negatively correlated with unsaturated (-0.93) and polyunsaturated (-0.84) FA. The saturated FA were positively correlated with milk fat yield and fat percentage, whereas the unsaturated FA were negatively associated with fat yield and fat percentage. Our results indicate that bovine milk FA composition can be changed through genetic selection using MIR as a phenotypic proxy.
Collapse
Affiliation(s)
- N Lopez-Villalobos
- School of Agriculture and Environment, Massey University, Private Bag 11-222, Palmerston North 4442, New Zealand.
| | - R J Spelman
- Livestock Improvement Corporation, Private Bag 3016, Hamilton 3240, New Zealand
| | - J Melis
- Livestock Improvement Corporation, Private Bag 3016, Hamilton 3240, New Zealand
| | - S R Davis
- Livestock Improvement Corporation, Private Bag 3016, Hamilton 3240, New Zealand
| | - S D Berry
- School of Biological Sciences, The University of Auckland, Private Bag 92019, Auckland 1142, New Zealand
| | - K Lehnert
- School of Biological Sciences, The University of Auckland, Private Bag 92019, Auckland 1142, New Zealand
| | - N W Sneddon
- School of Agriculture and Environment, Massey University, Private Bag 11-222, Palmerston North 4442, New Zealand; Fonterra Research and Development Centre, Palmerston North 4442, New Zealand
| | - S E Holroyd
- Fonterra Research and Development Centre, Palmerston North 4442, New Zealand
| | - A K MacGibbon
- Fonterra Research and Development Centre, Palmerston North 4442, New Zealand
| | - R G Snell
- School of Biological Sciences, The University of Auckland, Private Bag 92019, Auckland 1142, New Zealand
| |
Collapse
|
13
|
Tiplady KM, Lopdell TJ, Littlejohn MD, Garrick DJ. The evolving role of Fourier-transform mid-infrared spectroscopy in genetic improvement of dairy cattle. J Anim Sci Biotechnol 2020; 11:39. [PMID: 32322393 PMCID: PMC7164258 DOI: 10.1186/s40104-020-00445-2] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2019] [Accepted: 03/09/2020] [Indexed: 11/22/2022] Open
Abstract
Over the last 100 years, significant advances have been made in the characterisation of milk composition for dairy cattle improvement programs. Technological progress has enabled a shift from labour intensive, on-farm collection and processing of samples that assess yield and fat levels in milk, to large-scale processing of samples through centralised laboratories, with the scope extended to include quantification of other traits. Fourier-transform mid-infrared (FT-MIR) spectroscopy has had a significant role in the transformation of milk composition phenotyping, with spectral-based predictions of major milk components already being widely used in milk payment and animal evaluation systems globally. Increasingly, there is interest in analysing the individual FT-MIR wavenumbers, and in utilising the FT-MIR data to predict other novel traits of importance to breeding programs. This includes traits related to the nutritional value of milk, the processability of milk into products such as cheese, and traits relevant to animal health and the environment. The ability to successfully incorporate these traits into breeding programs is dependent on the heritability of the FT-MIR predicted traits, and the genetic correlations between the FT-MIR predicted and actual trait values. Linking FT-MIR predicted traits to the underlying mutations responsible for their variation can be difficult because the phenotypic expression of these traits are a function of a diverse range of molecular and biological mechanisms that can obscure their genetic basis. The individual FT-MIR wavenumbers give insights into the chemical composition of milk and provide an additional layer of granularity that may assist with establishing causal links between the genome and observed phenotypes. Additionally, there are other molecular phenotypes such as those related to the metabolome, chromatin accessibility, and RNA editing that could improve our understanding of the underlying biological systems controlling traits of interest. Here we review topics of importance to phenotyping and genetic applications of FT-MIR spectra datasets, and discuss opportunities for consolidating FT-MIR datasets with other genomic and molecular data sources to improve future dairy cattle breeding programs.
Collapse
Affiliation(s)
- K M Tiplady
- 1Research and Development, Livestock Improvement Corporation, Private Bag 3016, Hamilton, 3240 New Zealand.,2School of Agriculture, Massey University, Ruakura, Hamilton, 3240 New Zealand
| | - T J Lopdell
- 1Research and Development, Livestock Improvement Corporation, Private Bag 3016, Hamilton, 3240 New Zealand
| | - M D Littlejohn
- 1Research and Development, Livestock Improvement Corporation, Private Bag 3016, Hamilton, 3240 New Zealand.,2School of Agriculture, Massey University, Ruakura, Hamilton, 3240 New Zealand
| | - D J Garrick
- 2School of Agriculture, Massey University, Ruakura, Hamilton, 3240 New Zealand
| |
Collapse
|
14
|
Freitas PHF, Oliveira HR, Silva FF, Fleming A, Schenkel FS, Miglior F, Brito LF. Short communication: Time-dependent genetic parameters and single-step genome-wide association analyses for predicted milk fatty acid composition in Ayrshire and Jersey dairy cattle. J Dairy Sci 2020; 103:5263-5269. [PMID: 32307163 DOI: 10.3168/jds.2019-17820] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2019] [Accepted: 01/28/2020] [Indexed: 12/27/2022]
Abstract
Milk fat content and fatty acid (FA) composition have great economic value to the dairy industry as they are directly associated with taste and chemical-physical characteristics of milk and dairy products. In addition, consumers' choices are not only based on the nutritional aspects of food, but also on products known to promote better health. Milk FA composition is also related to the metabolic status and physiological stages of cows and thus can also be used as indicator for other novel traits of interest (e.g., metabolic diseases and methane yield). Genetic selection is a promising alternative to manipulate milk FA composition. In this study, we aimed to (1) estimate time-dependent genetic parameters for 5 milk FA groups (i.e., short-chain, medium-chain, long-chain, saturated, and unsaturated) predicted based on milk mid-infrared spectroscopy, for Canadian Ayrshire and Jersey breeds, and (2) conduct a time-dependent, single-step genome-wide association study to identify genomic regions, candidate genes, and metabolic pathways associated with milk FA. We analyzed 31,709 test-day records of 9,648 Ayrshire cows from 268 herds, and 34,341 records of 11,479 Jersey cows from 883 herds. The genomic database contained a total of 2,330 Ayrshire and 1,019 Jersey animals. The average daily heritability ranged from 0.18 (long-chain FA) to 0.34 (medium-chain FA) in Ayrshire, and from 0.25 (long-chain and unsaturated FA) to 0.52 (medium-chain and saturated FA) in Jersey. Important genomic regions were identified in Bos taurus autosomes BTA3, BTA5, BTA12, BTA13, BTA14, BTA16, BTA18, BTA20, and BTA21. The proportion of the variance explained by 20 adjacent SNP ranged from 0.71% (saturated FA) to 1.11% (long-chain FA) in Ayrshire, and from 0.70% (unsaturated FA) to 3.09% (medium-chain FA) in Jersey cattle. Important candidate genes and pathways were also identified, such as the PTK2 and TRAPPC9 genes, associated with milk fat percentage, and HMGCS, FGF10, and C6 genes, associated with fertility traits and immune response. Our findings on the genetic parameters and candidate genes contribute to a better understanding of the genetic architecture of milk FA composition in Ayrshire and Jersey dairy cattle.
Collapse
Affiliation(s)
- P H F Freitas
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907; Department of Animal Sciences, Federal University of Viçosa, Viçosa, Minas Gerais, 36570-000, Brazil
| | - H R Oliveira
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907
| | - F F Silva
- Department of Animal Sciences, Federal University of Viçosa, Viçosa, Minas Gerais, 36570-000, Brazil
| | - A Fleming
- Lactanet Canada, Guelph, Ontario, N1K 1E5, Canada
| | - F S Schenkel
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, Ontario, N1G 2W1, Canada
| | - F Miglior
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, Ontario, N1G 2W1, Canada
| | - L F Brito
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907.
| |
Collapse
|
15
|
Poulsen NA, Hein L, Kargo M, Buitenhuis AJ. Realization of breeding values for milk fatty acids in relation to seasonal variation in organic milk. J Dairy Sci 2020; 103:2434-2441. [PMID: 31980227 DOI: 10.3168/jds.2019-17065] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2019] [Accepted: 11/20/2019] [Indexed: 11/19/2022]
Abstract
Prediction of detailed milk fatty acid (FA) composition by mid-infrared spectroscopy (MIRS) offers possibilities for high-throughput indirect measurements of detailed milk compositional parameters through the milk testing system, which can be used to differentiate the FA profile by genetics or specific management or on dairies for milk quality evaluation. Since 2015, milk samples from all Danish dairy cows under milk testing have been recorded using MIRS. The MIRS software from the FOSS Application Note 64 was used to predict contents of 7 FA groups and 4 individual FA. Data generated from the application note have been used to estimate breeding values for sires for percentage of saturated fat (SFA%) in milk. To investigate whether extreme SFA% breeding values of sires were reflected in the detailed milk FA profile from their daughters, milk samples from 194 cows in 7 organic herds were collected and the detailed FA composition measured by gas chromatography. From each cow, milk samples were collected twice to explore specific seasonal effects of pasture-based diets in relation to sires' estimated breeding value (EBV) for MIRS-predicted SFA% (MIRS-SFA%). The results showed a significant difference in SFA% measured from GC (GC-SFA%) in milk from daughters of sires having high SFA% EBV compared with daughters of sires having low SFA% EBV. The EBV group (low or high) also significantly affected most FA except C13:0, C15:0, C17:0, and C18:1 trans-11. Contents of SFA with even chain-lengths were all higher in the high EBV group, whereas C14:1, C16:1, and the other unsaturated C18 FA had a higher content in the low EBV group. All FA were significantly affected by season. The SFA% decreased from indoor spring feeding to summer pasture, as did FA with chain length ≤16 carbons, whereas long-chain FA (>C17) all increased during summer pasture. The results show that use of MIRS-predicted EBV for SFA% will most likely display a correlated response on the detailed FA composition in milk. In the current study, the combined action of feeding and genetics resulted in a 10 percentage-point difference on average when comparing milk SFA% from daughters of high SFA% EBV sires during indoor spring feeding from one farm to milk SFA% from daughters of low SFA% EBV sires during summer from another farm.
Collapse
Affiliation(s)
- Nina A Poulsen
- Department of Food Science, Science and Technology, Aarhus University, Blichers Allé 20, PO Box 50, DK-8830 Tjele, Denmark.
| | - Lisa Hein
- SEGES, Agro Food Park 15, 8200 Aarhus N, Denmark
| | - Morten Kargo
- Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, Blichers Allé 20, PO Box 50, DK-8830 Tjele, Denmark
| | - Albert J Buitenhuis
- Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, Blichers Allé 20, PO Box 50, DK-8830 Tjele, Denmark
| |
Collapse
|
16
|
Ho PN, Marett LC, Wales WJ, Axford M, Oakes EM, Pryce JE. Predicting milk fatty acids and energy balance of dairy cows in Australia using milk mid-infrared spectroscopy. ANIMAL PRODUCTION SCIENCE 2020. [DOI: 10.1071/an18532] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
Mid-infrared spectroscopy (MIRS) is traditionally used for analysing milk fat, protein and lactose concentrations in dairy production, but there is growing interest in using it to predict difficult, or expensive-to-measure, phenotypes on a large scale. The resulting prediction equations can be applied to MIRS data from commercial herd-testing, to facilitate management and feeding decisions, or for genomic selection purposes. We investigated the ability of MIRS of milk samples to predict milk fatty acids (FAs) and energy balance (EB) of dairy cows in Australia. Data from 240 Holstein lactating cows that were part of two 32-day experiments, were used. Milk FAs were measured twice during the experimental period. Prediction models were developed using partial least-square regression with a 10-fold cross-validation. Measures of prediction accuracy included the coefficient of determination (R2cv) and root mean-square error. Milk FAs with a chain length of ≤16 were accurately predicted (0.89 ≤ R2cv ≤ 0.95), while prediction accuracy for FAs with a chain length of ≥17 was slightly lower (0.72 ≤ R2cv ≤ 0.82). The accuracy of the model prediction was moderate for EB, with the value of R2cv of 0.48. In conclusion, the ability of MIRS to predict milk FAs was high, while EB was moderately predicted. A larger dataset is needed to improve the accuracy and the robustness of the prediction models.
Collapse
|
17
|
Klein SL, Scheper C, Brügemann K, Swalve HH, König S. Phenotypic relationships, genetic parameters, genome-wide associations, and identification of potential candidate genes for ketosis and fat-to-protein ratio in German Holstein cows. J Dairy Sci 2019; 102:6276-6287. [PMID: 31056336 DOI: 10.3168/jds.2019-16237] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2019] [Accepted: 03/14/2019] [Indexed: 12/21/2022]
Abstract
Energy demand for milk production in early lactation exceeds energy intake, especially in high-yielding Holstein cows. Energy deficiency causes increasing susceptibility to metabolic disorders. In addition to several blood parameters, the fat-to-protein ratio (FPR) is suggested as an indicator for ketosis, because a FPR >1.5 refers to high lipolysis. The aim of this study was to analyze phenotypic, quantitative genetic, and genomic associations between FPR and ketosis. In this regard, 8,912 first-lactation Holstein cows were phenotyped for ketosis according to a veterinarian diagnosis key. Ketosis was diagnosed if the cow showed an abnormal carbohydrate metabolism with increased content of ketone bodies in the blood or urine. At least one entry for ketosis in the first 6 wk after calving implied a score = 1 (diseased); otherwise, a score = 0 (healthy) was assigned. The FPR from the first test-day was defined as a Gaussian distributed trait (FPRgauss), and also as a binary response trait (FPRbin), considering a threshold of FPR = 1.5. After imputation and quality controls, 45,613 SNP markers from the 8,912 genotyped cows were used for genomic studies. Phenotypically, an increasing ketosis incidence was associated with significantly higher FPR, and vice versa. Hence, from a practical trait recording perspective, first test-day FPR is suggested as an indicator for ketosis. The ketosis heritability was slightly larger when modeling the pedigree-based relationship matrix (pedigree-based: 0.17; SNP-based: 0.11). For FPRbin, heritabilities were larger when modeling the genomic relationship matrix (pedigree-based: 0.09; SNP-based: 0.15). For FPRgauss, heritabilities were almost identical for both pedigree and genomic relationship matrices (pedigree-based: 0.14; SNP-based: 0.15). Genetic correlations between ketosis with FPRbin and FPRgauss using either pedigree- or genomic-based relationship matrices were in a moderate range from 0.39 to 0.71. Applying genome-wide association studies, we identified the specific SNP rs109896020 (BTA 5, position: 115,456,438 bp) significantly contributing to ketosis. The identified potential candidate gene PARVB in close chromosomal distance is associated with nonalcoholic fatty liver disease in humans. The most important SNP contributing to FPRbin was located within the DGAT1 gene. Different SNP significantly contributed to ketosis and FPRbin, indicating different mechanisms for both traits genomically.
Collapse
Affiliation(s)
- S-L Klein
- Institute of Animal Breeding and Genetics, Justus-Liebig-University Gießen, 35390 Gießen, Germany.
| | - C Scheper
- Institute of Animal Breeding and Genetics, Justus-Liebig-University Gießen, 35390 Gießen, Germany
| | - K Brügemann
- Institute of Animal Breeding and Genetics, Justus-Liebig-University Gießen, 35390 Gießen, Germany
| | - H H Swalve
- Institute of Agricultural and Nutritional Sciences, Martin Luther University Halle-Wittenberg, 06120 Halle (Saale), Germany
| | - S König
- Institute of Animal Breeding and Genetics, Justus-Liebig-University Gießen, 35390 Gießen, Germany
| |
Collapse
|
18
|
Cecchinato A, Macciotta NPP, Mele M, Tagliapietra F, Schiavon S, Bittante G, Pegolo S. Genetic and genomic analyses of latent variables related to the milk fatty acid profile, milk composition, and udder health in dairy cattle. J Dairy Sci 2019; 102:5254-5265. [PMID: 30904297 DOI: 10.3168/jds.2018-15867] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2018] [Accepted: 03/04/2019] [Indexed: 12/31/2022]
Abstract
The aim of this study was to perform genetic, genome-wide association (GWAS), and gene-set enrichment analyses with latent variables related to milk fatty acid profile (i.e., fatty acids factor scores; FAF), milk composition, and udder health in a cohort of 1,158 Italian Brown Swiss cows. The phenotypes under study were 12 FAF previously identified through factor analysis and classified as follows: de novo FA (F1), branched-chain FA-milk yield (F2), biohydrogenation (F3), long-chain fatty acids (F4), desaturation (F5), short-chain fatty acids (F6), milk protein and fat contents (F7), odd fatty acids (F8), conjugated linoleic acids (F9), linoleic acid (F10), udder health (F11) and vaccelenic acid (F12). (Co)variance components were estimated for factor scores using a Bayesian linear animal model via Gibbs sampling. The animals were genotyped with the Illumina BovineSNP50 BeadChip v.2 (Illumina Inc., San Diego, CA). A single marker regression model was fitted for GWAS analysis. The gene-set enrichment analysis was run on the GWAS results using the Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes pathway databases to identify the ontologies and pathways associated with the FAF. Marginal posterior means of the heritabilities of the aforementioned FAF ranged from 0.048 for F12 to 0.310 for F5. Factors F1 and F6 had the highest number of relevant genetic correlations with the other traits. The genomic analysis detected a total of 39 significant SNP located on 17 Bos taurus autosomes. All latent variables produced signals except for F2 and F10. The traits with the highest number of significant associations were F11 (17) and F12 (7). Gene-set enrichment analyses identified significant pathways (false discovery rate 5%) for F3 and F7. In particular, systemic lupus erythematosus was enriched for F3, whereas the MAPK (mitogen-activated protein kinase) signaling pathway was overrepresented for F7. The results support the existence of important and exploitable genetic and genomic variation in these latent explanatory phenotypes. Information acquired might be exploited in selection programs and when designing further studies on the role of the putative candidate genes identified in the regulation of milk composition and udder health.
Collapse
Affiliation(s)
- A Cecchinato
- Department of Agronomy, Food, Natural resources, Animals and Environment (DAFNAE), University of Padova, Viale dell'Università 16, 35020 Legnaro, Padova, Italy.
| | - N P P Macciotta
- Dipartimento di Agraria, Sezione Scienze Zootecniche, Università di Sassari, Via de Nicola 9, 07100 Sassari, Italy
| | - M Mele
- Dipartimento di Scienze Agrarie, Alimentari, Agro-ambientali, Università di Pisa, Via del Borghetto, 80, 56124 Pisa, Italy
| | - F Tagliapietra
- Department of Agronomy, Food, Natural resources, Animals and Environment (DAFNAE), University of Padova, Viale dell'Università 16, 35020 Legnaro, Padova, Italy
| | - S Schiavon
- Department of Agronomy, Food, Natural resources, Animals and Environment (DAFNAE), University of Padova, Viale dell'Università 16, 35020 Legnaro, Padova, Italy
| | - G Bittante
- Department of Agronomy, Food, Natural resources, Animals and Environment (DAFNAE), University of Padova, Viale dell'Università 16, 35020 Legnaro, Padova, Italy
| | - S Pegolo
- Department of Agronomy, Food, Natural resources, Animals and Environment (DAFNAE), University of Padova, Viale dell'Università 16, 35020 Legnaro, Padova, Italy
| |
Collapse
|
19
|
Wang Z, Zhu B, Niu H, Zhang W, Xu L, Xu L, Chen Y, Zhang L, Gao X, Gao H, Zhang S, Xu L, Li J. Genome wide association study identifies SNPs associated with fatty acid composition in Chinese Wagyu cattle. J Anim Sci Biotechnol 2019; 10:27. [PMID: 30867906 PMCID: PMC6399853 DOI: 10.1186/s40104-019-0322-0] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2018] [Accepted: 01/14/2019] [Indexed: 12/29/2022] Open
Abstract
Background Fatty acids are important traits that affect meat quality and nutritive values in beef cattle. Detection of genetic variants for fatty acid composition can help to elucidate the genetic mechanism underpinning these traits and promote the improvement of fatty acid profiles. In this study, we performed a genome-wide association study (GWAS) on fatty acid composition using high-density single nucleotide polymorphism (SNP) arrays in Chinese Wagyu cattle. Results In total, we detected 15 and 8 significant genome-wide SNPs for individual fatty acids and fatty acid groups in Chinese Wagyu cattle, respectively. Also, we identified nine candidate genes based on 100 kb regions around associated SNPs. Four SNPs significantly associated with C14:1 cis-9 were embedded with stearoyl-CoA desaturase (SCD), while three SNPs in total were identified for C22:6 n-3 within Phospholipid scramblase family member 5 (PLSCR5), Cytoplasmic linker associated protein 1 (CLASP1), and Chymosin (CYM). Notably, we found the top candidate SNP within SCD can explain ~ 7.37% of phenotypic variance for C14:1 cis-9. Moreover, we detected several blocks with high LD in the 100 kb region around SCD. In addition, we found three significant SNPs within a 100 kb region showing pleiotropic effects related to multiple FA groups (PUFA, n-6, and PUFA/SFA), which contains BAI1 associated protein 2 like 2 (BAIAP2L2), MAF bZIP transcription factor F (MAFF), and transmembrane protein 184B (TMEM184B). Conclusions Our study identified several significant SNPs and candidate genes for individual fatty acids and fatty acid groups in Chinese Wagyu cattle, and these findings will further assist the design of breeding programs for meat quality in cattle.
Collapse
Affiliation(s)
- Zezhao Wang
- 1Innovation Team of Cattle Genetic Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193 China.,2National Engineering Laboratory for Animal Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing, 100193 China
| | - Bo Zhu
- 1Innovation Team of Cattle Genetic Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
| | - Hong Niu
- 1Innovation Team of Cattle Genetic Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
| | - Wengang Zhang
- 1Innovation Team of Cattle Genetic Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
| | - Ling Xu
- 1Innovation Team of Cattle Genetic Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
| | - Lei Xu
- 1Innovation Team of Cattle Genetic Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193 China.,3Institute of Animal Husbandry and Veterinary Research, Anhui Academy of Agricultural Sciences, Hefei, 230031 China
| | - Yan Chen
- 1Innovation Team of Cattle Genetic Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
| | - Lupei Zhang
- 1Innovation Team of Cattle Genetic Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
| | - Xue Gao
- 1Innovation Team of Cattle Genetic Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
| | - Huijiang Gao
- 1Innovation Team of Cattle Genetic Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
| | - Shengli Zhang
- 2National Engineering Laboratory for Animal Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing, 100193 China
| | - Lingyang Xu
- 1Innovation Team of Cattle Genetic Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
| | - Junya Li
- 1Innovation Team of Cattle Genetic Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
| |
Collapse
|
20
|
Hanuš O, Samková E, Křížová L, Hasoňová L, Kala R. Role of Fatty Acids in Milk Fat and the Influence of Selected Factors on Their Variability-A Review. Molecules 2018; 23:E1636. [PMID: 29973572 PMCID: PMC6100482 DOI: 10.3390/molecules23071636] [Citation(s) in RCA: 95] [Impact Index Per Article: 15.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2018] [Revised: 06/29/2018] [Accepted: 07/02/2018] [Indexed: 11/16/2022] Open
Abstract
Fatty acids (FAs) of milk fat are considered to be important nutritional components of the diets of a significant portion of the human population and substantially affect human health. With regard to dairy farming, the FA profile is also seen as an important factor in the technological quality of raw milk. In this sense, making targeted modifications to the FA profile has the potential to significantly contribute to the production of dairy products with higher added value. Thus, FAs also have economic importance. Current developments in analytical methods and their increasing efficiency enable the study of FA profiles not only for scientific purposes but also in terms of practical technological applications. It is important to study the sources of variability of FAs in milk, which include population genetics, type of farming, and targeted animal nutrition. It is equally important to study the health and technological impacts of FAs. This review summarizes current knowledge in the field regarding sources of FA variability, including the impact of factors such as: animal nutrition, seasonal feed changes, type of animal farming (conventional and organic), genetic parameters (influence of breed), animal individuality, lactation, and milk yield. Potential practical applications (to improve food technology and consumer health) of FA profile information are also reviewed.
Collapse
Affiliation(s)
- Oto Hanuš
- Dairy Research Institute Ltd., 16000 Prague, Czech Republic.
| | - Eva Samková
- Department of Food Biotechnologies and Agricultural Products´ Quality, Faculty of Agriculture, University of South Bohemia, 37005 České Budějovice, Czech Republic.
| | - Ludmila Křížová
- Department of Animal Nutrition, Faculty of Veterinary Hygiene and Ecology, University of Veterinary and Pharmaceutical Sciences Brno, 61242 Brno, Czech Republic.
| | - Lucie Hasoňová
- Department of Food Biotechnologies and Agricultural Products´ Quality, Faculty of Agriculture, University of South Bohemia, 37005 České Budějovice, Czech Republic.
| | - Robert Kala
- Department of Food Biotechnologies and Agricultural Products´ Quality, Faculty of Agriculture, University of South Bohemia, 37005 České Budějovice, Czech Republic.
| |
Collapse
|