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Martinez-Castillero M, Pegolo S, Sartori C, Toledo-Alvarado H, Varona L, Degano L, Vicario D, Finocchiaro R, Bittante G, Cecchinato A. Genetic correlations between fertility traits and milk composition and fatty acids in Holstein-Friesian, Brown Swiss, and Simmental cattle using recursive models. J Dairy Sci 2021; 104:6832-6846. [PMID: 33773778 DOI: 10.3168/jds.2020-19694] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2020] [Accepted: 02/01/2021] [Indexed: 12/11/2022]
Abstract
This study aimed to investigate the genetic and putative causal relationships between fertility traits [i.e., days open (DO) and calving rate (CR)] and milk quality, composition, and fatty acid contents (milk composition traits) in Holstein-Friesian, Brown Swiss, and Simmental cattle, using recursive models within a Bayesian framework. Trivariate animal models were run, each including one fertility trait, one milk composition trait, and, in all models, milk yield. The DO and CR data were merged with the test days closest to the insemination date for milk composition traits. After editing, 16,468 to 23,424 records for Holstein-Friesian, 23,424 to 46,660 for Brown Swiss, and 26,105 to 35,574 for Simmental were available for the analyses. Recursive animal models were applied to investigate the possible causal influences of milk composition traits on fertility and the genetic relationships among these traits. The results suggested a potential cause-and-effect relationship between milk composition traits and fertility traits, with the first trait influencing the latter. We also found greater recursive effects of milk composition traits on DO than on CR, the latter with some putative differences among breeds in terms of sensitivity. For instance, the putative causal effects of somatic cell score on CR (on the observed scale, %) varied from -0.96 to -1.39%, depending on the breed. Concerning fatty acids, we found relevant putative effects of C18:0 on CR, with estimates varying from -7.8 to -9.9%. Protein and casein percentages, and short-chain fatty acid showed larger recursive effects on CR, whereas fat, protein, and casein percentages, C16:0, C18:0, and long-chain fatty acid had larger effects on DO. The results obtained suggested that these milk traits could be considered as effective indicators of the effects of animal metabolic and physiological status on fertility.
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Affiliation(s)
- M Martinez-Castillero
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, viale dell' Università 16 35020, Legnaro PD, Italy
| | - S Pegolo
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, viale dell' Università 16 35020, Legnaro PD, Italy.
| | - C Sartori
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, viale dell' Università 16 35020, Legnaro PD, Italy
| | - H Toledo-Alvarado
- Department of Genetics and Biostatistics, Faculty of Veterinary Medicine and Zootechnics, National Autonomous University of Mexico, Ciudad Universitaria 3000, Mexico City 04510, Mexico
| | - L Varona
- Unidad de Genética Cuantitativa y Mejora Animal, Instituto Agroalimentario de Aragón (IA2), Universidad de Zaragoza, Calle de Miguel Servet 177, 50013 Zaragoza, Spain
| | - L Degano
- Associazione Nazionale Allevatori Razza Pezzata Rossa Italiana (ANAPRI), Udine 33100, Italy
| | - D Vicario
- Associazione Nazionale Allevatori Razza Pezzata Rossa Italiana (ANAPRI), Udine 33100, Italy
| | - R Finocchiaro
- Associazione Nazionale Allevatori bovini della razza Frisona e Jersey Italiana (ANAFIJ), Via Bergamo 292, 26100 Cremona, Italy
| | - G Bittante
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, viale dell' Università 16 35020, Legnaro PD, Italy
| | - A Cecchinato
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, viale dell' Università 16 35020, Legnaro PD, Italy
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Toledo-Alvarado H, Pérez-Cabal MA, Tempelman RJ, Cecchinato A, Bittante G, de Los Campos G, Vazquez AI. Association between days open and milk spectral data in dairy cows. J Dairy Sci 2021; 104:3665-3675. [PMID: 33455800 DOI: 10.3168/jds.2020-19031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2020] [Accepted: 10/22/2020] [Indexed: 11/19/2022]
Abstract
Data on 19,489 Brown Swiss cows reared in northeastern Italy were used to associate absorbances of individual wavenumbers within the mid-infrared range with days open (DO). Different postcalving days in milk (DIM) intervals were studied to determine the most informative milk sampling periods for predicting DO. Milk samples were analyzed using a MilkoScan (Foss Electric, Hillerød, Denmark) Fourier-transform infrared (FTIR) spectrometer for 1,060 wavenumbers (wn) ranging from 5,011 to 925 cm-1. To determine DO, we considered an insemination to lead to conception when there was no return of heat (i.e., no successive insemination) and the cow had a subsequent calving date whereby gestation length was required to be within ±30 d of 290 d. Only milk records within the first 90 DIM were considered. Associations were inferred by (1) fitting linear regression models between the DO and each individual wavenumber or milk component, and (2) fitting a Bayesian regression model that included the complete FTIR spectral data. The effects of including systematic effects (parity number, year-season, herd) in the model on these associations were also studied. These analyses were performed for the complete data (5-90 DIM) and for data stratified by DIM period (5 to 30, 31 to 60, and 61 to 90 DIM). Overall, regions of wavenumbers of the milk FTIR spectra that were associated with DO included wn 2,973 to 2,830 cm-1 [related to fat-B (C-H stretch)], wn 2,217 to 1,769 cm-1 [related to fat-A (C = O stretch)], wn 1,546 cm-1 (related to protein), wn 1,465 cm-1 (related to urea and fat), wn 1,399 to 1,245 cm-1 (related to acetone), and wn 1,110 cm-1 (related to lactose). Estimated effects depended on the DIM period, with milk samples drawn during DIM intervals 31 to 60 d and 61 to 90 d being most strongly associated with DO. These DIM intervals are also typically most associated with negative energy balance and peak lactation.
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Affiliation(s)
- H Toledo-Alvarado
- Department of Genetics and Biostatistics, Faculty of Veterinary Medicine and Zootechnics, National Autonomous University of Mexico, 04510, Mexico City, Mexico; Department of Animal Production, Complutense University of Madrid, 28040 Madrid, Spain.
| | - M A Pérez-Cabal
- Department of Animal Production, Complutense University of Madrid, 28040 Madrid, Spain
| | - R J Tempelman
- Department of Animal Science, Michigan State University, East Lansing 48824
| | - A Cecchinato
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell'Università 16, 35020, Legnaro PD, Italy
| | - G Bittante
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell'Università 16, 35020, Legnaro PD, Italy
| | - G de Los Campos
- Department of Epidemiology and Biostatistics, Michigan State University, East Lansing 48824; Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing 48824
| | - A I Vazquez
- Department of Epidemiology and Biostatistics, Michigan State University, East Lansing 48824; Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing 48824
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Martinez-Castillero M, Toledo-Alvarado H, Pegolo S, Vazquez AI, de Los Campos G, Varona L, Finocchiaro R, Bittante G, Cecchinato A. Genetic parameters for fertility traits assessed in herds divergent in milk energy output in Holstein-Friesian, Brown Swiss, and Simmental cattle. J Dairy Sci 2020; 103:11545-11558. [PMID: 33222858 DOI: 10.3168/jds.2020-18934] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Accepted: 09/02/2020] [Indexed: 11/19/2022]
Abstract
In this study, we aimed to investigate differences in the genetics of fertility traits (heritability of traits and correlations between traits in divergent environments) in dairy cows of different production levels defined on the basis of the herd-average daily milk energy output (herd-dMEO). Data were obtained from Holstein-Friesian (n = 37,359 for fertility traits, 381,334 for dMEO), Brown Swiss (n = 79,638 for fertility traits, 665,697 for dMEO), and Simmental cows (n = 63,048 for fertility traits, 448,445 for dMEO) reared in northeastern Italy. Fertility traits under study were interval from calving to first service, interval from first service to conception, days open, calving interval, calving rate, and nonreturn rate at d 56. We classified herds into low and high productivity based on the herd-average dMEO (inferred using mixed effects models). We estimated genetic parameters using Bayesian bivariate animal models, where expressions of a phenotype in the low and high dMEO herds were taken as being different-albeit correlated-traits. Fertility traits were more favorable in Simmental than in Holstein-Friesian cows, whereas for all traits, Holstein-Friesian had the highest estimates of intraherd heritability [ranging from 0.021 (0.006-0.038) to 0.126 (0.10-0.15)] and Simmental the lowest [ranging from 0.008 (0.001-0.017) to 0.101 (0.08-0.12)]. The genetic correlations between fertility traits and dMEO were moderate and unfavorable, ranging, in absolute values, from 0.527 (0.37-0.68) to 0.619 (0.50-0.73) in Holstein-Friesian; from 0.339 (0.20-0.47) to 0.556 (0.45-0.66) in Brown Swiss; and from 0.340 (0.10-0.60) to 0.475 (0.33-0.61) in Simmental cattle. The only exception was the nonreturn rate at d 56, which had weak genetic correlations with dMEO in all 3 breeds. The herd correlations between fertility and dMEO tended to be modest and favorable and the residual correlations modest and variable. The heritability of fertility traits tended to be greater in the low dMEO than in the high dMEO herds in the case of the Holstein-Friesians, but not in the case of the Brown Swiss or Simmentals. The additive genetic correlations between fertility traits in the low and high dMEO herds were always lower than 1 [0.329 (-0.17 to 0.85) to 0.934 (0.86 to 0.99)] for all traits considered in all breeds. The correlation was particularly low for the threshold characters and the interval from first service to conception in Holstein-Friesian, suggesting that the relative performances of genotypes vary significantly between herds of different dMEO levels. Although there was large variability in the estimates, results might support making separate genetic evaluations of fertility in the different herd production groups. Our results also indicate that Simmental, a dual-purpose breed, has higher fertility and lower environmental sensitivity than Holstein-Friesian, with Brown Swiss being intermediate.
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Affiliation(s)
- M Martinez-Castillero
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell' Università 16, 35020, Legnaro PD, Italy
| | - H Toledo-Alvarado
- Department of Genetics and Biostatistics, School of Veterinary Medicine and Zootechnics, National Autonomous University of Mexico, Ciudad Universitaria, 0451, Mexico City, México
| | - S Pegolo
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell' Università 16, 35020, Legnaro PD, Italy.
| | - A I Vazquez
- Department of Epidemiology and Biostatistics, Michigan State University, 909 Fee Road, East Lansing 48824; Institute for Quantitative Health Science and Engineering, Michigan State University, 775 Woodlot Drive, East Lansing 48824
| | - G de Los Campos
- Department of Epidemiology and Biostatistics, Michigan State University, 909 Fee Road, East Lansing 48824; Institute for Quantitative Health Science and Engineering, Michigan State University, 775 Woodlot Drive, East Lansing 48824; Department of Statistics and Probability, Michigan State University, 619 Red Cellar Road, East Lansing 48824
| | - L Varona
- Unidad de Genética Cuantitativa y Mejora Animal, Instituto Agroalimentario de Aragón (IA2), Universidad de Zaragoza, Calle de Miguel Servet, 177, 50013, Zaragoza, Zaragoza, Spain
| | - R Finocchiaro
- Associazione Nazionale Allevatori bovini della razza Frisona e Jersey Italiana (ANAFIJ), Via Bergamo 292, 26100 Cremona, Italy
| | - G Bittante
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell' Università 16, 35020, Legnaro PD, Italy
| | - A Cecchinato
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell' Università 16, 35020, Legnaro PD, Italy
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Rovere G, de Los Campos G, Tempelman RJ, Vazquez AI, Miglior F, Schenkel F, Cecchinato A, Bittante G, Toledo-Alvarado H, Fleming A. A landscape of the heritability of Fourier-transform infrared spectral wavelengths of milk samples by parity and lactation stage in Holstein cows. J Dairy Sci 2018; 102:1354-1363. [PMID: 30580946 DOI: 10.3168/jds.2018-15109] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2018] [Accepted: 09/28/2018] [Indexed: 11/19/2022]
Abstract
Fourier-transform near- and mid-infrared (FTIR) milk spectral data are routinely collected in many countries worldwide. Establishing an optimal strategy to use spectral data in genetic evaluations requires knowledge of the heritabilities of individual FTIR wavelength absorbances. Previous FTIR heritability estimates have been based on relatively small sample sizes and have not considered the possibility that heritability may vary across parities and stages of the lactation. We used data from ∼370,000 test-day records of Canadian Holstein cows to produce a landscape of the heritability of FTIR spectra, 1,060 wavelengths in the near- and mid-infrared spectrum (5,011-925 cm-1), by parity and month of the lactation (mo 1 to 3 and mo 1 to 6, respectively). The 2 regions of the spectrum associated with absorption of electromagnetic energy by water molecules were estimated to have very high phenotypic variances, very low heritabilities, and very low proportion of variance explained by herd-year-season (HYS) subclasses. The near- or short-wavelength infrared (SWIR: 5,066-3,672 cm-1) region was also characterized by low heritability estimates, whereas the estimated proportion of the variance explained by HYS was high. The mid-wavelength infrared region (MWIR: 3,000-2,500 cm-1) and the transition between mid and long-wavelength infrared region (MWIR-LWIR: 1,500-925 cm-1) harbor several waves characterized by moderately high (≥0.4) heritabilities. Most of the high-heritability regions contained wavelengths that are reported to be associated with important milk metabolites and components. Interestingly, these 2 same regions tended to show more variability in heritabilities between parity and lactation stage. Second parity showed heritability patterns that were distinctly different from those of the first and third parities, whereas the first 2 mo of the lactation had clearly distinct heritability patterns compared with mo 3 to 6.
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Affiliation(s)
- G Rovere
- Department of Animal Science, Michigan State University, East Lansing 48824; Department of Epidemiology and Biostatistics, Michigan State University, East Lansing 48824; Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing 48824.
| | - G de Los Campos
- Department of Epidemiology and Biostatistics, Michigan State University, East Lansing 48824; Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing 48824; Department of Statistics and Probability, Michigan State University, East Lansing 48824
| | - R J Tempelman
- Department of Animal Science, Michigan State University, East Lansing 48824
| | - A I Vazquez
- Department of Epidemiology and Biostatistics, Michigan State University, East Lansing 48824; Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing 48824
| | - F Miglior
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, Ontario, Canada, N1G 2W1; Canadian Dairy Network, Guelph, Ontario, Canada N1K 1E5
| | - F Schenkel
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, Ontario, Canada, N1G 2W1
| | - A Cecchinato
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, 35020 Legnaro, Italy
| | - G Bittante
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, 35020 Legnaro, Italy
| | - H Toledo-Alvarado
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, 35020 Legnaro, Italy
| | - A Fleming
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, Ontario, Canada, N1G 2W1; Canadian Dairy Network, Guelph, Ontario, Canada N1K 1E5
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