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Tribout T, Minéry S, Vallée R, Saille S, Saunier D, Martin P, Ducrocq V, Faverdin P, Boichard D. Genetic relationships between weight loss in early lactation and daily milk production throughout the lactation in Holstein cows. J Dairy Sci 2023:S0022-0302(23)00217-5. [PMID: 37164861 DOI: 10.3168/jds.2022-22813] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Accepted: 01/07/2023] [Indexed: 05/12/2023]
Abstract
After calving, high-yielding dairy cows mobilize body reserves for energy, sometimes to the detriment of health and fertility. This study aimed to estimate the genetic correlation between body weight loss until nadir and daily milk production (MY24) in first- (L1) and second-lactation (L2) Holstein cows. The data set included 859,020 MY24 records and 570,651 daily raw body weight (BWr) phenotypes from 3,989 L1 cows, and 665,361 MY24 records and 449,449 BWr phenotypes from 3,060 L2 cows, recorded on 36 French commercial farms equipped with milking robots that included an automatic weighing platform. To avoid any bias due to change in digestive content, BWr was adjusted for variations in feed intake, estimated from milk production and BWr. Adjusted body weight was denoted BW. The genetic parameters of BW and MY24 in L1 and L2 cows were estimated using a 4-trait random regression model. In this model, the random effects were fitted by second-order Legendre polynomials on a weekly basis from wk 1 to 44. Nadir of BW was found to be earlier than reported in the literature, at 29 d in milk, and BW loss from calving to nadir was also lower than generally assumed, close to 29 kg. To estimate genetic correlations between body weight loss and production, we defined BWL5 as the loss of weight between wk 1 and 5 after calving. Genetic correlations between BWL5 and MY24 ranged from -0.26 to 0.05 in L1 and from -0.11 to 0.10 in L2, according to days in milk. These moderate to low values suggest that it may be possible to select for milk production without increasing early body mobilization.
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Affiliation(s)
- T Tribout
- Université Paris Saclay, INRAE, AgroParisTech, GABI, 78350 Jouy-en-Josas, France.
| | - S Minéry
- Institut de l'Elevage, 75012 Paris, France
| | - R Vallée
- Institut de l'Elevage, 75012 Paris, France
| | - S Saille
- INNOVAL, CS 10040, 35538 Noyal sur Vilaine, France
| | | | - P Martin
- Université Paris Saclay, INRAE, AgroParisTech, GABI, 78350 Jouy-en-Josas, France
| | - V Ducrocq
- Université Paris Saclay, INRAE, AgroParisTech, GABI, 78350 Jouy-en-Josas, France
| | - P Faverdin
- INRAE, AgroCampus Ouest, PEGASE, 35590 Saint-Gilles, France
| | - D Boichard
- Université Paris Saclay, INRAE, AgroParisTech, GABI, 78350 Jouy-en-Josas, France
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Comparison of fixed and random regression models for the analysis of milk production traits in South African Holstein dairy cattle under two production systems. Livest Sci 2022. [DOI: 10.1016/j.livsci.2022.105125] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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Al Kalaldeh M, Swaminathan M, Gaundare Y, Joshi S, Aliloo H, Strucken EM, Ducrocq V, Gibson JP. Genomic evaluation of milk yield in a smallholder crossbred dairy production system in India. Genet Sel Evol 2021; 53:73. [PMID: 34507523 PMCID: PMC8431883 DOI: 10.1186/s12711-021-00667-6] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Accepted: 08/30/2021] [Indexed: 11/30/2022] Open
Abstract
BACKGROUND India is the largest milk producer globally, with the largest proportion of cattle milk production coming from smallholder farms with an average herd size of less than two milking cows. These cows are mainly undefined multi-generation crosses between exotic dairy breeds and indigenous Indian cattle, with no performance or pedigree recording. Therefore, implementing genetic improvement based on genetic evaluation has not yet been possible. We present the first results from a large smallholder performance recording program in India, using single nucleotide polymorphism (SNP) genotypes to estimate genetic parameters for monthly test-day (TD) milk records and to obtain and validate genomic estimated breeding values (GEBV). RESULTS The average TD milk yield under the high, medium, and low production environments were 9.64, 6.88, and 4.61 kg, respectively. In the high production environment, the usual profile of a lactation curve was evident, whereas it was less evident in low and medium production environments. There was a clear trend of an increasing milk yield with an increasing Holstein Friesian (HF) proportion in the high production environment, but no increase above intermediate grades in the medium and low production environments. Trends for Jersey were small but yield estimates had a higher standard error than HF. Heritability estimates for TD yield across the lactation ranged from 0.193 to 0.250, with an average of 0.230. The additive genetic correlations between TD yield at different times in lactation were high, ranging from 0.846 to 0.998. The accuracy of phenotypic validation of GEBV from the method that is believed to be the least biased was 0.420, which was very similar to the accuracy obtained from the average prediction error variance of the GEBV. CONCLUSIONS The results indicate strong potential for genomic selection to improve milk production of smallholder crossbred cows in India. The performance of cows with different breed compositions can be determined in different Indian environments, which makes it possible to provide better advice to smallholder farmers on optimum breed composition for their environment.
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Affiliation(s)
- Mohammad Al Kalaldeh
- Centre for Genetic Analysis and Applications, School of Environmental and Rural Science, University of New England, Armidale, NSW 2350 Australia
| | - Marimuthu Swaminathan
- BAIF Development Research Foundation and Central Research Station, Uruli Kanchan, Pune, Maharashtra 412202 India
| | - Yuvraj Gaundare
- BAIF Development Research Foundation and Central Research Station, Uruli Kanchan, Pune, Maharashtra 412202 India
| | - Sachin Joshi
- BAIF Development Research Foundation and Central Research Station, Uruli Kanchan, Pune, Maharashtra 412202 India
| | - Hassan Aliloo
- Centre for Genetic Analysis and Applications, School of Environmental and Rural Science, University of New England, Armidale, NSW 2350 Australia
| | - Eva M. Strucken
- Centre for Genetic Analysis and Applications, School of Environmental and Rural Science, University of New England, Armidale, NSW 2350 Australia
| | - Vincent Ducrocq
- Université Paris-Saclay, INRAE, AgroParisTech, UMR GABI, 78350 Jouy-en-Josas, France
| | - John P. Gibson
- Centre for Genetic Analysis and Applications, School of Environmental and Rural Science, University of New England, Armidale, NSW 2350 Australia
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Heat stress level as an alternative to fixed regression modeling for fat and protein yield traits in Holstein cattle. Livest Sci 2021. [DOI: 10.1016/j.livsci.2021.104615] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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Genetic relationship among somatic cell score and some milking traits in Holstein-Friesian primiparous cows milked by an automated milking system. Animal 2020; 15:100094. [PMID: 33573967 DOI: 10.1016/j.animal.2020.100094] [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: 02/10/2020] [Revised: 09/16/2020] [Accepted: 09/21/2020] [Indexed: 11/22/2022] Open
Abstract
The automated milking system provides breeders with a large amount of automatically collected information about each cow in herd that cannot be easily obtained in non-robotised systems. This knowledge can be used in breeding programs improving somatic cell count (SCC) level. The objective of this study was to estimate heritabilities and genetic correlations among test-day (TD) somatic cell score (SCS) and selected milking traits, such as daily milk yield (MY), milking frequency (MF), milking time (MT) and milking speed (MS), attachment time (AT) to single teat cups, electrical conductivity (EC) and milk temperature (MTEMP). Data were collected for 1899 Polish Holstein-Friesian primiparous cows milked in an automatic milking system. Genetic parameters of the studied traits were estimated using Bayesian method via Gibbs sampling and two-trait random regression animal model with fixed effect of herd x TD, fixed regressions on days in milk (DIM) nested within age at calving by season of calving and RR for additive genetic and permanent environmental effects. Both fixed and RR were fitted with fourth-order Legendre polynomials on DIM. The estimated daily heritabilities were in the following ranges: MY - 0.162-0.338, MF - 0.156-0.444, MT - 0.090-0.320, MS - 0.252-0.665, AT - 0.105-0.394, EC - 0.269-0.466, MTEMP - 0.135-0.304 and SCS - 0.155-0.321. The heritabilities for traits expressed on a 305-d basis were moderate to high: 0.460 for MY, 0.514 for MF, 0.315 for MT, 0.431 for MS, 0.256 for AT, 0.386 for EC, 0.407 for MTEMP and 0.359 for SCS. Genetic correlations between traits on a 305-d basis showed that SCS was most strongly genetically correlated with MTEMP (0.572) and MS (0.480), whereas genetic relationships of SCS with MT (0.221) and EC (-0.216) were moderate. Phenotypic correlations between traits on a 305-d basis were moderate or low. Somatic cell score was negatively phenotypically correlated with MY, MF and MT, with the highest relationship with MT (-0.302). The largest positive phenotypic correlations were observed between SCS and MS (0.311) and with MTEMP (0.286). In summary, it is concluded that there is a chance to carry out effective selection for lower SCS and for some other traits, in particular MS and MTEMP. The obtained results are promising enough to conduct further research to evaluate how these traits can be used both to increase the accuracy of genetic evaluations of SCC and to improve udder health.
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Li J, Gao H, Madsen P, Li R, Liu W, Bao P, Xue G, Gao Y, Di X, Su G. Impact of the Order of Legendre Polynomials in Random Regression Model on Genetic Evaluation for Milk Yield in Dairy Cattle Population. Front Genet 2020; 11:586155. [PMID: 33250923 PMCID: PMC7674963 DOI: 10.3389/fgene.2020.586155] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Accepted: 09/24/2020] [Indexed: 11/30/2022] Open
Abstract
The random regression test-day model has become the most commonly adopted model for routine genetic evaluations in dairy populations, which allows accurately accounting for genetic and environmental effects over lactation. The objective of this study was to explore appropriate random regression test-day models for genetic evaluation of milk yield in a Holstein population with a relatively small size, which is the common situation in regional or independent breeding companies to preform genetic evaluation. Data included 419,567 test-day records from 54,417 cows from the first lactation. Variance components and breeding values were estimated using a random regression test-day model with different orders (from first to fifth) of Legendre polynomials (LP) and accounted for homogeneous or heterogeneous residual variance across the lactation. Models were compared based on Akaike information criterion (AIC), Bayesian information criterion (BIC), and predictive ability. In general, models with a higher order of LP showed better goodness of fit based on AIC and BIC values. However, models with third, fourth, and fifth order of LP led to similar estimates of genetic parameters and predictive ability. Models with assumption of heterogeneous residual variances achieved better goodness of fit but yielded similar predictive ability compared with those with assumption of homogeneous residual variances. Therefore, a random regression model with third order of LP is suggested to be an appropriate model for genetic evaluation of milk yield in local Chinese Holstein populations.
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Affiliation(s)
- Jianbin Li
- Dairy Cattle Research Center, Shandong Academy of Agricultural Sciences, Jinan, China
| | - Hongding Gao
- Center for Quantitative Genetics and Genomics, Aarhus University, Tjele, Denmark
| | - Per Madsen
- Center for Quantitative Genetics and Genomics, Aarhus University, Tjele, Denmark
| | - Rongling Li
- Dairy Cattle Research Center, Shandong Academy of Agricultural Sciences, Jinan, China
| | - Wenhao Liu
- Dairy Cattle Research Center, Shandong Academy of Agricultural Sciences, Jinan, China
| | - Peng Bao
- Shandong OX Livestock Breeding Industry Co., Ltd, Jinan, China
| | - Guanghui Xue
- Shandong OX Livestock Breeding Industry Co., Ltd, Jinan, China
| | - Yundong Gao
- Dairy Cattle Research Center, Shandong Academy of Agricultural Sciences, Jinan, China
| | - Xueke Di
- Linqing Rutai Animal Husbandry Co., Ltd, Liaocheng, China
| | - Guosheng Su
- Center for Quantitative Genetics and Genomics, Aarhus University, Tjele, Denmark
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Moreira FF, Oliveira HR, Volenec JJ, Rainey KM, Brito LF. Integrating High-Throughput Phenotyping and Statistical Genomic Methods to Genetically Improve Longitudinal Traits in Crops. FRONTIERS IN PLANT SCIENCE 2020; 11:681. [PMID: 32528513 PMCID: PMC7264266 DOI: 10.3389/fpls.2020.00681] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/26/2020] [Accepted: 04/30/2020] [Indexed: 05/28/2023]
Abstract
The rapid development of remote sensing in agronomic research allows the dynamic nature of longitudinal traits to be adequately described, which may enhance the genetic improvement of crop efficiency. For traits such as light interception, biomass accumulation, and responses to stressors, the data generated by the various high-throughput phenotyping (HTP) methods requires adequate statistical techniques to evaluate phenotypic records throughout time. As a consequence, information about plant functioning and activation of genes, as well as the interaction of gene networks at different stages of plant development and in response to environmental stimulus can be exploited. In this review, we outline the current analytical approaches in quantitative genetics that are applied to longitudinal traits in crops throughout development, describe the advantages and pitfalls of each approach, and indicate future research directions and opportunities.
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Affiliation(s)
- Fabiana F. Moreira
- Department of Agronomy, Purdue University, West Lafayette, IN, United States
| | - Hinayah R. Oliveira
- Department of Animal Sciences, Purdue University, West Lafayette, IN, United States
| | - Jeffrey J. Volenec
- Department of Agronomy, Purdue University, West Lafayette, IN, United States
| | - Katy M. Rainey
- Department of Agronomy, Purdue University, West Lafayette, IN, United States
| | - Luiz F. Brito
- Department of Animal Sciences, Purdue University, West Lafayette, IN, United States
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Silva DA, Costa CN, Silva AA, Silva HT, Lopes PS, Silva FF, Veroneze R, Thompson G, Aguilar I, Carvalheira J. Autoregressive and random regression test‐day models for multiple lactations in genetic evaluation of Brazilian Holstein cattle. J Anim Breed Genet 2019; 137:305-315. [DOI: 10.1111/jbg.12459] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2019] [Revised: 10/31/2019] [Accepted: 11/03/2019] [Indexed: 12/16/2022]
Affiliation(s)
- Delvan Alves Silva
- Department of Animal Science Universidade Federal de Viçosa Viçosa Brazil
| | | | | | | | - Paulo Sávio Lopes
- Department of Animal Science Universidade Federal de Viçosa Viçosa Brazil
| | | | - Renata Veroneze
- Department of Animal Science Universidade Federal de Viçosa Viçosa Brazil
| | - Gertrude Thompson
- Research Center in Biodiversity and Genetic Resources (CIBIO‐InBio) University of Porto Vairão Portugal
- Institute of Biomedical Sciences Abel Salazar (ICBAS) University of Porto Vairão Portugal
| | - Ignacio Aguilar
- Instituto Nacional de Investigación Agropecuaria Montevideo Uruguay
| | - Júlio Carvalheira
- Research Center in Biodiversity and Genetic Resources (CIBIO‐InBio) University of Porto Vairão Portugal
- Institute of Biomedical Sciences Abel Salazar (ICBAS) University of Porto Vairão Portugal
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Buaban S, Puangdee S, Duangjinda M, Boonkum W. Estimation of genetic parameters and trends for production traits of dairy cattle in Thailand using a multiple-trait multiple-lactation test day model. ASIAN-AUSTRALASIAN JOURNAL OF ANIMAL SCIENCES 2019; 33:1387-1399. [PMID: 32054206 PMCID: PMC7468173 DOI: 10.5713/ajas.19.0141] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/19/2019] [Accepted: 10/28/2019] [Indexed: 12/02/2022]
Abstract
Objective The objective of this study was to estimate the genetic parameters and trends for milk, fat, and protein yields in the first three lactations of Thai dairy cattle using a 3-trait,-3-lactation random regression test-day model. Methods Data included 168,996, 63,388, and 27,145 test-day records from the first, second, and third lactations, respectively. Records were from 19,068 cows calving from 1993 to 2013 in 124 herds. (Co) variance components were estimated by Bayesian methods. Gibbs sampling was used to obtain posterior distributions. The model included herd-year-month of testing, breed group-season of calving-month in tested milk group, linear and quadratic age at calving as fixed effects, and random regression coefficients for additive genetic and permanent environmental effects, which were defined as modified constant, linear, quadratic, cubic and quartic Legendre coefficients. Results Average daily heritabilities ranged from 0.36 to 0.48 for milk, 0.33 to 0.44 for fat and 0.37 to 0.48 for protein yields; they were higher in the third lactation for all traits. Heritabilities of test-day milk and protein yields for selected days in milk were higher in the middle than at the beginning or end of lactation, whereas those for test-day fat yields were high at the beginning and end of lactation. Genetics correlations (305-d yield) among production yields within lactations (0.44 to 0.69) were higher than those across lactations (0.36 to 0.68). The largest genetic correlation was observed between the first and second lactation. The genetic trends of 305-d milk, fat and protein yields were 230 to 250, 25 to 29, and 30 to 35 kg per year, respectively. Conclusion A random regression model seems to be a flexible and reliable procedure for the genetic evaluation of production yields. It can be used to perform breeding value estimation for national genetic evaluation in the Thai dairy cattle population.
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Affiliation(s)
- Sayan Buaban
- The Bureau of Biotechnology in Livestock Production, Department of Livestock Development, Pratumtani 12000, Thailand
| | - Somsook Puangdee
- Academic and Curriculum unit, Mahidol University, Nakhonsawan Campus, Nakhonsawan 60130, Thailand
| | - Monchai Duangjinda
- Department of Animal Science, Khon Kaen University, Meaung, Khon Kaen 40002, Thailand
| | - Wuttigrai Boonkum
- Department of Animal Science, Khon Kaen University, Meaung, Khon Kaen 40002, Thailand.,Thermo-tolerance Dairy Cattle Research Group, Khon Kaen University, Khon Kaen 40002, Thailand
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Abstract
The link between phenotypic plasticity and heterosis is a broad fundamental question, with stakes in breeding. We report a case-study evaluating temporal series of wood ring traits of hybrid larch (Larix decidua × L. kaempferi and reciprocal) in relation to soil water availability. Growth rings record the tree plastic responses to past environmental conditions, and we used random regressions to estimate the reaction norms of ring width and wood density with respect to water availability. We investigated the role of phenotypic plasticity on the construction of hybrid larch heterosis and on the expression of its quantitative genetic parameters. The data came from an intra-/interspecific diallel mating design between both parental species. Progenies were grown in two environmentally contrasted sites, in France. Ring width plasticity with respect to water availability was confirmed, as all three taxa produced narrower rings under the lowest water availability. Hybrid larch appeared to be the most plastic taxon as its superiority over its parental species increased with increasing water availability. Despite the low heritabilities of the investigated traits, we found that the expression of a reliable negative correlation between them was conditional to the water availability environment. Finally, by means of a complementary simulation, we demonstrated that random regression can be applied to model the reaction norms of non-repeated records of phenotypic plasticity bound by a family structure. Random regression is a powerful tool for the modeling of reaction norms in various contexts, especially perennial species.
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Padilha AH, Alfonzo EPM, Daltro DS, Torres HAL, Neto JB, Cobuci JA. Genetic trends and genetic correlations between 305-day milk yield, persistency and somatic cell score of Holstein cows in Brazil using random regression model. ANIMAL PRODUCTION SCIENCE 2019. [DOI: 10.1071/an16835] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
The objective was to estimate genetic correlations for persistency, milk yield and somatic cell score (SCS) in Holstein cattle in Brazil. A dataset with 190389 records of test-day milk and of test-day SCS from 21824 cows was used. Two-trait random regression model with a fourth order Legendre polynomial was used. Persistency (PS) was defined as the difference between estimated breeding values (EBV) along different days in milk using two formulae: and PS2=(EBV290–EBV90). Larger values for PS2 or lower ones for PS1 indicate higher persistency. Heritability was 0.24 for 305-day milk yield, 0.14 for SCS up to 305 days, 0.15 for PS1 and 0.14 for PS2. Genetic correlation between 305-day milk yield and SCS up to 305 days was –0.47. Genetic correlation of 305-day milk yield with PS1 and PS2 was –0.32 and 0.30, respectively. Genetic correlation of SCS up to 305 days was 0.25 with PS1 and –0.20 with PS2. The additive genetic correlations between milk yield, SCS and persistency showed that selection for higher persistency or for low somatic cell score will increase 305-day milk yield.
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Kang H, Ning C, Zhou L, Zhang S, Yan Q, Liu JF. Short communication: Single-step genomic evaluation of milk production traits using multiple-trait random regression model in Chinese Holsteins. J Dairy Sci 2018; 101:11143-11149. [DOI: 10.3168/jds.2018-15090] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2018] [Accepted: 08/14/2018] [Indexed: 12/31/2022]
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Guzzo N, Sartori C, Mantovani R. Heterogeneity of variance for milk, fat and protein yield in small cattle populations: The Rendena breed as a case study. Livest Sci 2018. [DOI: 10.1016/j.livsci.2018.05.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/16/2022]
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Ning C, Wang D, Zheng X, Zhang Q, Zhang S, Mrode R, Liu JF. Eigen decomposition expedites longitudinal genome-wide association studies for milk production traits in Chinese Holstein. Genet Sel Evol 2018; 50:12. [PMID: 29576014 PMCID: PMC5868076 DOI: 10.1186/s12711-018-0383-0] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2017] [Accepted: 03/01/2018] [Indexed: 11/16/2022] Open
Abstract
Background Pseudo-phenotypes, such as 305-day yields, estimated breeding values or deregressed proofs, are usually used as response variables for genome-wide association studies (GWAS) of milk production traits in dairy cattle. Computational inefficiency challenges the direct use of test-day records for longitudinal GWAS with large datasets. Results We propose a rapid longitudinal GWAS method that is based on a random regression model. Our method uses Eigen decomposition of the phenotypic covariance matrix to rotate the data, thereby transforming the complex mixed linear model into weighted least squares analysis. We performed a simulation study that showed that our method can control type I errors well and has higher power than a longitudinal GWAS method that does not include time-varied additive genetic effects. We also applied our method to the analysis of milk production traits in the first three parities of 6711 Chinese Holstein cows. The analysis for each trait was completed within 1 day with known variances. In total, we located 84 significant single nucleotide polymorphisms (SNPs) of which 65 were within previously reported quantitative trait loci (QTL) regions. Conclusions Our rapid method can control type I errors in the analysis of longitudinal data and can be applied to other longitudinal traits. We detected QTL that were for the most part similar to those reported in a previous study in Chinese Holstein. Moreover, six additional SNPs for fat percentage and 13 SNPs for protein percentage were identified by our method. These additional 19 SNPs could be new candidate quantitative trait nucleotides for milk production traits in Chinese Holstein. Electronic supplementary material The online version of this article (10.1186/s12711-018-0383-0) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Chao Ning
- National 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
| | - Dan Wang
- National 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
| | - Xianrui Zheng
- National 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
| | - Qin Zhang
- National 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
| | - Shengli Zhang
- National 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
| | - Raphael Mrode
- Animal Biosciences, International Livestock Research Institute, Nairobi, 00100, Kenya
| | - Jian-Feng Liu
- National 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.
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Sasaki O, Aihara M, Nishiura A, Takeda H. Genetic correlations between the cumulative pseudo-survival rate, milk yield, and somatic cell score during lactation in Holstein cattle in Japan using a random regression model. J Dairy Sci 2017; 100:7282-7294. [DOI: 10.3168/jds.2016-12311] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2016] [Accepted: 05/23/2017] [Indexed: 11/19/2022]
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16
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Ben Zaabza H, Ben Gara A, Rekik B. Genetic analysis of milk production traits of Tunisian Holsteins using random regression test-day model with Legendre polynomials. ASIAN-AUSTRALASIAN JOURNAL OF ANIMAL SCIENCES 2017; 31:636-642. [PMID: 28823122 PMCID: PMC5930273 DOI: 10.5713/ajas.17.0332] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 04/29/2017] [Revised: 07/28/2017] [Accepted: 08/09/2017] [Indexed: 11/27/2022]
Abstract
OBJECTIVE The objective of this study was to estimate genetic parameters of milk, fat, and protein yields within and across lactations in Tunisian Holsteins using a random regression test-day (TD) model. METHODS A random regression multiple trait multiple lactation TD model was used to estimate genetic parameters in the Tunisian dairy cattle population. Data were TD yields of milk, fat, and protein from the first three lactations. Random regressions were modeled with third-order Legendre polynomials for the additive genetic, and permanent environment effects. Heritabilities, and genetic correlations were estimated by Bayesian techniques using the Gibbs sampler. RESULTS All variance components tended to be high in the beginning and the end of lactations. Additive genetic variances for milk, fat, and protein yields were the lowest and were the least variable compared to permanent variances. Heritability values tended to increase with parity. Estimates of heritabilities for 305-d yield-traits were low to moderate, 0.14 to 0.2, 0.12 to 0.17, and 0.13 to 0.18 for milk, fat, and protein yields, respectively. Within-parity, genetic correlations among traits were up to 0.74. Genetic correlations among lactations for the yield traits were relatively high and ranged from 0.78±0.01 to 0.82±0.03, between the first and second parities, from 0.73±0.03 to 0.8±0.04 between the first and third parities, and from 0.82±0.02 to 0.84±0.04 between the second and third parities. CONCLUSION These results are comparable to previously reported estimates on the same population, indicating that the adoption of a random regression TD model as the official genetic evaluation for production traits in Tunisia, as developed by most Interbull countries, is possible in the Tunisian Holsteins.
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Affiliation(s)
- Hafedh Ben Zaabza
- Institut National Agronomique 43, Avenue Charles Nicoles 1082-Tunis-Mahrajène, Tunisia
| | - Abderrahmen Ben Gara
- Département des Productions Animales, Ecole Supérieure d'Agriculture de Mateur, Mateur 7030, Tunisia
| | - Boulbaba Rekik
- Département des Productions Animales, Ecole Supérieure d'Agriculture de Mateur, Mateur 7030, Tunisia
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Torshizi ME, Farhangfar H, Mashhadi MH. Application of random regression models for genetic analysis of 305-d milk yield over different lactations of Iranian Holsteins. ASIAN-AUSTRALASIAN JOURNAL OF ANIMAL SCIENCES 2017; 30:1382-1387. [PMID: 28427258 PMCID: PMC5582321 DOI: 10.5713/ajas.16.0885] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/17/2016] [Revised: 03/02/2017] [Accepted: 04/11/2017] [Indexed: 11/30/2022]
Abstract
Objective During the last decade, genetic evaluation of dairy cows using longitudinal data (test day milk yield or 305- day milk yield) using random regression method has been officially adopted in several countries. The objectives of this study were to estimate covariance functions for genetic and permanent environmental effects and to obtain genetic parameters of 305-day milk yield over seven parities. Methods Data including 60,279 total 305–day milk yield of 17,309 Iranian Holstein dairy cows in 7 parities calved between 20 to 140 months between 2004 and 2011. Residual variances were modeled by homogeneous and step functions with 7 and 10 classes. Results The results showed that a third order polynomial for additive genetic and permanent environmental effects plus a step function with 10 classes for the residual variance was the most adequate and parsimonious model to describe the covariance structure of the data. Heritability estimates obtained by this model varied from 0.17 to 0.28. The performance of this model was better than repeatability model. Moreover, 10 classes of residual variance produce the more accurate result than 7 classes or homogeneous residual effect. Conclusion A quadratic Legendre polynomial for additive genetic and permanent environmental effects with 10 step function residual classes are sufficient to produce a parsimonious model that explained the change in 305-day milk yield over consecutive parities of Iranian Holstein cows.
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Affiliation(s)
- Mahdi Elahi Torshizi
- Department of Animal Science, Mashhad Branch, Islamic Azad University, Mashhad 918714578, Iran
| | - Homayoun Farhangfar
- Department of Animal Science, Faculty of Agriculture, University of Birjand, Birjand 9719113944, Iran
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Mazza S, Guzzo N, Sartori C, Mantovani R. Genetic correlations between type and test-day milk yield in small dual-purpose cattle populations: The Aosta Red Pied breed as a case study. J Dairy Sci 2016; 99:8127-8136. [PMID: 27448852 DOI: 10.3168/jds.2016-11116] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2016] [Accepted: 06/17/2016] [Indexed: 11/19/2022]
Abstract
This study aimed at estimating the relationships between linear type traits and milk production in the dual-purpose Aosta Red Pied (ARP) cattle breed, by expressing type traits as factor scores with the same biological meaning of the individual traits. Factor analysis was applied to individual type traits for muscularity and udder of 32,275 first-parity ARP cows, obtaining 3 factor scores for individual muscularity (F1), udder side (F2), and udder conformation (F3). Data from 169,008 test-day records of milk, fat, and protein yield (kg), belonging to the first 3 lactations of 16,605 cows, were also analyzed. After obtaining genetic parameters for both morphological factors and milk production traits through a series of AIREML single-trait models, bivariate analyses were performed on a data set accounting for 201,283 records of 35,530 cows, to assess the phenotypic and genetic correlations among all factor scores and milk yield traits. The heritability estimates obtained proved to be moderate for both groups of traits, ranging from 0.132 (fat) to 0.314 (F1). Muscularity factor showed moderate and negative genetic correlations (ra) with udder size (-0.376) and udder conformation (0.214) factors. A low and negative ra was found between udder factors. Strong and positive ra were found among all the 3 milk production traits and F 0010 (ra≥0.597). Negative ra with milk traits were obtained for both F 0005 and F3, ranging from -0.417 to -0.221. Phenotypic correlations were lower than the genetic ones, and sometimes close to zero. The antagonism between milk production and meat attitude traits suggests that great attention should be paid in assigning proper weight to the traits, comprising functional traits such as udder conformation, included in selection indices for the dual-purpose breed. The ra obtained for factor scores are consistent with previous estimates for the corresponding individual type traits, and this confirms the possible use of factor analysis to improve type traits relevant to beef attitude.
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Affiliation(s)
- Serena Mazza
- Department of Agronomy, Food, Natural Resources, Animals and Environment, University of Padova, Viale dell'Università 16, 35020 Legnaro (PD), Italy
| | - Nadia Guzzo
- Department of Agronomy, Food, Natural Resources, Animals and Environment, University of Padova, Viale dell'Università 16, 35020 Legnaro (PD), Italy
| | - Cristina Sartori
- Department of Agronomy, Food, Natural Resources, Animals and Environment, University of Padova, Viale dell'Università 16, 35020 Legnaro (PD), Italy.
| | - Roberto Mantovani
- Department of Agronomy, Food, Natural Resources, Animals and Environment, University of Padova, Viale dell'Università 16, 35020 Legnaro (PD), Italy
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Padilha AH, Cobuci JA, Costa CN, Neto JB. Random Regression Models Are Suitable to Substitute the Traditional 305-Day Lactation Model in Genetic Evaluations of Holstein Cattle in Brazil. ASIAN-AUSTRALASIAN JOURNAL OF ANIMAL SCIENCES 2016; 29:759-67. [PMID: 26954176 PMCID: PMC4852241 DOI: 10.5713/ajas.15.0498] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/09/2015] [Revised: 08/03/2015] [Accepted: 09/06/2015] [Indexed: 12/02/2022]
Abstract
The aim of this study was to compare two random regression models (RRM) fitted by fourth (RRM4) and fifth-order Legendre polynomials (RRM5) with a lactation model (LM) for evaluating Holstein cattle in Brazil. Two datasets with the same animals were prepared for this study. To apply test-day RRM and LMs, 262,426 test day records and 30,228 lactation records covering 305 days were prepared, respectively. The lowest values of Akaike’s information criterion, Bayesian information criterion, and estimates of the maximum of the likelihood function (−2LogL) were for RRM4. Heritability for 305-day milk yield (305MY) was 0.23 (RRM4), 0.24 (RRM5), and 0.21 (LM). Heritability, additive genetic and permanent environmental variances of test days on days in milk was from 0.16 to 0.27, from 3.76 to 6.88 and from 11.12 to 20.21, respectively. Additive genetic correlations between test days ranged from 0.20 to 0.99. Permanent environmental correlations between test days were between 0.07 and 0.99. Standard deviations of average estimated breeding values (EBVs) for 305MY from RRM4 and RRM5 were from 11% to 30% higher for bulls and around 28% higher for cows than that in LM. Rank correlations between RRM EBVs and LM EBVs were between 0.86 to 0.96 for bulls and 0.80 to 0.87 for cows. Average percentage of gain in reliability of EBVs for 305-day yield increased from 4% to 17% for bulls and from 23% to 24% for cows when reliability of EBVs from RRM models was compared to those from LM model. Random regression model fitted by fourth order Legendre polynomials is recommended for genetic evaluations of Brazilian Holstein cattle because of the higher reliability in the estimation of breeding values.
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Affiliation(s)
- Alessandro Haiduck Padilha
- Department of Animal Science, Federal University of Rio Grande do Sul, Porto Alegre, RS, 91540-000, Brazil
| | - Jaime Araujo Cobuci
- Department of Animal Science, Federal University of Rio Grande do Sul, Porto Alegre, RS, 91540-000, Brazil
| | | | - José Braccini Neto
- Department of Animal Science, Federal University of Rio Grande do Sul, Porto Alegre, RS, 91540-000, Brazil
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Guzzo N, Sartori C, Mantovani R. Test day-milk yields variance component estimation using repeatability or random regression models in the Rendena breed. ITALIAN JOURNAL OF ANIMAL SCIENCE 2016. [DOI: 10.4081/ijas.2009.s3.71] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Affiliation(s)
- Nadia Guzzo
- Dipartimento di Scienze AnimaliUniversità di Padova, Italy
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Canavesi F, Biffani S, Bramante G, Finocchiaro R. Improving the stability of test day model evaluation for production traits in the Italian Holstein. ITALIAN JOURNAL OF ANIMAL SCIENCE 2016. [DOI: 10.4081/ijas.2009.s2.39] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Affiliation(s)
- Fabiola Canavesi
- Associazione Nazionale Allevatori Frisona Italiana (ANAFI), Cremona, Italy
| | - Stefano Biffani
- Associazione Nazionale Allevatori Frisona Italiana (ANAFI), Cremona, Italy
| | - Grazia Bramante
- Associazione Nazionale Allevatori Frisona Italiana (ANAFI), Cremona, Italy
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Tullo E, Frigo E, Rossoni A, Finocchiaro R, Serra M, Rizzi N, Samorè AB, Canavesi F, Strillacci MG, Prinsen RTMM, Bagnato A. Genetic Parameters of Fatty Acids in Italian Brown Swiss and Holstein Cows. ITALIAN JOURNAL OF ANIMAL SCIENCE 2016. [DOI: 10.4081/ijas.2014.3208] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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Damane MM, Fozi MA, Mehrgardi AA. Influence of milking frequency on genetic parameters associated with the milk production in the first and second lactations of Iranian Holstein dairy cows using random regression test day models. JOURNAL OF ANIMAL SCIENCE AND TECHNOLOGY 2016; 58:5. [PMID: 26835155 PMCID: PMC4734863 DOI: 10.1186/s40781-016-0087-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/03/2014] [Accepted: 01/06/2016] [Indexed: 11/10/2022]
Abstract
BACKGROUND The milk yield can be affected by the frequency of milking per day, in dairy cows. Previous studies have shown that the milk yield is increased by 6-25 % per lactation when the milking frequency is increased from 2 to 3 times per day while the somatic cell count is decreased. To investigate the effect of milking frequency (3X vs. 4X) on milk yield and it's genetic parameters in the first and second lactations of the Iranian Holstein dairy cows, a total of 142,604 test day (TD) records of milk yield were measured on 20,762 cows. RESULTS Heritability estimates of milk yield were 0.25 and 0.19 for 3X milking frequency and 0.34 and 0.26 for 4X milking frequency throughout the first and second lactations, respectively. Repeatability estimates of milk yield were 0.70 and 0.71 for 3X milking frequency and 0.76 and 0.77 for 4X milking frequency, respectively. In comparison with 3X milking frequency, the milk yield of the first and second lactations was increased by 11.6 and 12.2 %, respectively when 4X was used (p < 0.01). CONCLUSIONS Results of this research demonstrated that increasing milking frequency led to an increase in heritability and repeatability of milk yield. The current investigation provided clear evidences for the benefits of using 4X milking frequency instead of 3X in Iranian Holstein dairy cows.
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Affiliation(s)
- Moslem Moghbeli Damane
- Department of Animal Science, Faculty of Agriculture, University of Jiroft, Jiroft, Iran
| | - Masood Asadi Fozi
- Department of Animal Science, Faculty of Agriculture, Shahid Bahonar University of Kerman, Kerman, Iran
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Tiezzi F, Valente BD, Cassandro M, Maltecca C. Causal relationships between milk quality and coagulation properties in Italian Holstein-Friesian dairy cattle. Genet Sel Evol 2015; 47:45. [PMID: 25968045 PMCID: PMC4429925 DOI: 10.1186/s12711-015-0123-7] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2014] [Accepted: 04/21/2015] [Indexed: 11/29/2022] Open
Abstract
Background Recently, selection for milk technological traits was initiated in the Italian dairy cattle industry based on direct measures of milk coagulation properties (MCP) such as rennet coagulation time (RCT) and curd firmness 30 min after rennet addition (a30) and on some traditional milk quality traits that are used as predictors, such as somatic cell score (SCS) and casein percentage (CAS). The aim of this study was to shed light on the causal relationships between traditional milk quality traits and MCP. Different structural equation models that included causal effects of SCS and CAS on RCT and a30 and of RCT on a30 were implemented in a Bayesian framework. Results Our results indicate a non-zero magnitude of the causal relationships between the traits studied. Causal effects of SCS and CAS on RCT and a30 were observed, which suggests that the relationship between milk coagulation ability and traditional milk quality traits depends more on phenotypic causal pathways than directly on common genetic influence. While RCT does not seem to be largely controlled by SCS and CAS, some of the variation in a30 depends on the phenotypes of these traits. However, a30 depends heavily on coagulation time. Our results also indicate that, when direct effects of SCS, CAS and RCT are considered simultaneously, most of the overall genetic variability of a30 is mediated by other traits. Conclusions This study suggests that selection for RCT and a30 should not be performed on correlated traits such as SCS or CAS but on direct measures because the ability of milk to coagulate is improved through the causal effect that the former play on the latter, rather than from a common source of genetic variation. Breaking the causal link (e.g. standardizing SCS or CAS before the milk is processed into cheese) would reduce the impact of the improvement due to selective breeding. Since a30 depends heavily on RCT, the relative emphasis that is put on this trait should be reconsidered and weighted for the fact that the pure measure of a30 almost double-counts RCT. Electronic supplementary material The online version of this article (doi:10.1186/s12711-015-0123-7) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Francesco Tiezzi
- Department of Animal Science, North Carolina State University, Raleigh, NC, 27695, USA.
| | - Bruno D Valente
- Department of Animal Science, University of Wisconsin, Madison, WI, 53706, USA.
| | - Martino Cassandro
- Department of Agronomy, Food, Natural Resources, Animals and Environment, University of Padova, 35020, Legnaro, (PD), Italy.
| | - Christian Maltecca
- Department of Animal Science, North Carolina State University, Raleigh, NC, 27695, USA.
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Alam M, Cho CI, Choi TJ, Park B, Choi JG, Choy YH, Lee SS, Cho KH. Estimation of Genetic Parameters for Somatic Cell Scores of Holsteins Using Multi-trait Lactation Models in Korea. ASIAN-AUSTRALASIAN JOURNAL OF ANIMAL SCIENCES 2015; 28:303-10. [PMID: 25656194 PMCID: PMC4341072 DOI: 10.5713/ajas.13.0627] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/04/2013] [Revised: 11/21/2013] [Accepted: 11/22/2014] [Indexed: 11/27/2022]
Abstract
The study was conducted to analyze the genetic parameters of somatic cell score (SCS) of Holstein cows, which is an important indicator to udder health. Test-day records of somatic cell counts (SCC) of 305-day lactation design from first to fifth lactations were collected on Holsteins in Korea during 2000 to 2012. Records of animals within 18 to 42 months, 30 to 54 months, 42 to 66 months, 54 to 78 months, and 66 to 90 months of age at the first, second, third, fourth and fifth parities were analyzed, respectively. Somatic cell scores were calculated, and adjusted for lactation production stages by Wilmink's function. Lactation averages of SCS (LSCS1 through LSCS5) were derived by further adjustments of each test-day SCS for five age groups in particular lactations. Two datasets were prepared through restrictions on number of sires/herd and dams/herd, progenies/sire, and number of parities/cow to reduce data size and attain better relationships among animals. All LSCS traits were treated as individual trait and, analyzed through multiple-trait sire models and single trait animal models via VCE 6.0 software package. Herd-year was fitted as a random effect. Age at calving was regressed as a fixed covariate. The mean LSCS of five lactations were between 3.507 and 4.322 that corresponded to a SCC range between 71,000 and 125,000 cells/mL; with coefficient of variation from 28.2% to 29.9%. Heritability estimates from sire models were within the range of 0.10 to 0.16 for all LSCS. Heritability was the highest at lactation 2 from both datasets (0.14/0.16) and lowest at lactation 5 (0.11/0.10) using sire model. Heritabilities from single trait animal model analyses were slightly higher than sire models. Genetic correlations between LSCS traits were strong (0.62 to 0.99). Very strong associations (0.96 to 0.99) were present between successive records of later lactations. Phenotypic correlations were relatively weaker (<0.55). All correlations became weaker at distant lactations. The estimated breeding values (EBVs) of LSCS traits were somewhat similar over the years for a particular lactation, but increased with lactation number increment. The lowest EBV in first lactation indicated that selection for SCS (mastitis resistance) might be better with later lactation records. It is expected that results obtained from these multi-trait lactation model analyses, being the first large scale SCS data analysis in Korea, would create a good starting step for application of advanced statistical tools for future genomic studies focusing on selection for mastitis resistance in Holsteins of Korea.
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Affiliation(s)
| | | | | | | | | | | | | | - K. H. Cho
- Corresponding Author: Kwang-Hyeon Cho. Tel: +82-41-580-3362, Fax: +82-41-580-3369, E-mail:
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Pretto D, Vallas M, Pärna E, Tänavots A, Kiiman H, Kaart T. Short communication: Genetic correlation and heritability of milk coagulation traits within and across lactations in Holstein cows using multiple-lactation random regression animal models. J Dairy Sci 2014; 97:7980-4. [DOI: 10.3168/jds.2014-8270] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2014] [Accepted: 09/03/2014] [Indexed: 11/19/2022]
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Kheirabadi K, Rashidi A, Alijani S, Imumorin I. Modeling lactation curves and estimation of genetic parameters in Holstein cows using multiple-trait random regression models. Anim Sci J 2014; 85:925-34. [DOI: 10.1111/asj.12185] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2013] [Accepted: 11/15/2013] [Indexed: 11/27/2022]
Affiliation(s)
| | - Amir Rashidi
- Department of Animal Science; University of Kurdistan; Kurdistan Iran
| | - Sadegh Alijani
- Department of Animal Science; University of Tabriz; Tabriz Iran
| | - Ikhide Imumorin
- Animal Genetics and Genomics Laboratory; International Programs; College of Agriculture and Life Sciences; Cornell University; Ithaca NY USA
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Accounting for heterogeneity of phenotypic variance in Iranian Holstein test-day milk yield records. Livest Sci 2014. [DOI: 10.1016/j.livsci.2014.05.012] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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Minozzi G, Nicolazzi EL, Stella A, Biffani S, Negrini R, Lazzari B, Ajmone-Marsan P, Williams JL.. Genome wide analysis of fertility and production traits in Italian Holstein cattle. PLoS One 2013; 8:e80219. [PMID: 24265800 PMCID: PMC3827211 DOI: 10.1371/journal.pone.0080219] [Citation(s) in RCA: 59] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2013] [Accepted: 09/29/2013] [Indexed: 11/23/2022] Open
Abstract
A genome wide scan was performed on a total of 2093 Italian Holstein proven bulls genotyped with 50K single nucleotide polymorphisms (SNPs), with the objective of identifying loci associated with fertility related traits and to test their effects on milk production traits. The analysis was carried out using estimated breeding values for the aggregate fertility index and for each trait contributing to the index: angularity, calving interval, non-return rate at 56 days, days to first service, and 305 day first parity lactation. In addition, two production traits not included in the aggregate fertility index were analysed: fat yield and protein yield. Analyses were carried out using all SNPs treated separately, further the most significant marker on BTA14 associated to milk quality located in the DGAT1 region was treated as fixed effect. Genome wide association analysis identified 61 significant SNPs and 75 significant marker-trait associations. Eight additional SNP associations were detected when SNP located near DGAT1 was included as a fixed effect. As there were no obvious common SNPs between the traits analyzed independently in this study, a network analysis was carried out to identify unforeseen relationships that may link production and fertility traits.
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Affiliation(s)
| | - Ezequiel L. Nicolazzi
- Parco Tecnologico Padano, Lodi, Italy
- Institute of Zootechnics, Università Cattolica del Sacro Cuore, Piacenza, Italy
| | - Alessandra Stella
- Parco Tecnologico Padano, Lodi, Italy
- Istituto di Biologia e Biotecnologia Agraria, Consiglio Nazionale delle Ricerche, Lodi, Italy
| | - Stefano Biffani
- Istituto di Biologia e Biotecnologia Agraria, Consiglio Nazionale delle Ricerche, Lodi, Italy
- Associazione Nazionale Allevatori Frisona Italiana, Cremona, Italy
| | - Riccardo Negrini
- Institute of Zootechnics, Università Cattolica del Sacro Cuore, Piacenza, Italy
- Associazione Italiana Allevatori, Rome, Italy
| | | | - Paolo Ajmone-Marsan
- Institute of Zootechnics, Università Cattolica del Sacro Cuore, Piacenza, Italy
- Nutrigenomics Research Center, Università Cattolica del Sacro Cuore, Piacenza, Italy
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Borquis RRA, Neto FRDA, Baldi F, Hurtado-Lugo N, de Camargo GM, Muñoz-Berrocal M, Tonhati H. Multiple-trait random regression models for the estimation of genetic parameters for milk, fat, and protein yield in buffaloes. J Dairy Sci 2013; 96:5923-32. [DOI: 10.3168/jds.2012-6023] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2012] [Accepted: 04/04/2013] [Indexed: 11/19/2022]
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Cho KH, Choy YH, Kong HS, Lee HK, Kim SH, Park KD. Effect of Number of Lactation Records on the Selection Rates in Holstein Dairy Cattle. JOURNAL OF ANIMAL SCIENCE AND TECHNOLOGY 2013. [DOI: 10.5187/jast.2013.55.2.81] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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33
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Genetic correlations between milk production traits and somatic cell scores on test day within and across first and second lactations in Holstein cows. Livest Sci 2013. [DOI: 10.1016/j.livsci.2012.12.015] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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Cho KH, Park B, Choi J, Choi T, Choy Y, Lee S, Cho C. Development of International Genetic Evaluation Models for Dairy Cattle. JOURNAL OF ANIMAL SCIENCE AND TECHNOLOGY 2013. [DOI: 10.5187/jast.2013.55.1.1] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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Cho C, Cho K, Choy Y, Choi J, Choi T, Park B, Lee S. Estimation of Genetic Parameters for Milk Production Traits in Holstein Dairy Cattle. JOURNAL OF ANIMAL SCIENCE AND TECHNOLOGY 2013. [DOI: 10.5187/jast.2013.55.1.7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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Dadpasand M, Zamiri MJ, Atashi H, Akhlaghi A. Genetic relationship of conformation traits with average somatic cell score at 150 and 305 days in milk in Holstein cows of Iran. J Dairy Sci 2012; 95:7340-5. [PMID: 22999283 DOI: 10.3168/jds.2011-5002] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2011] [Accepted: 08/10/2012] [Indexed: 11/19/2022]
Abstract
Genetic, environmental, and phenotypic correlations among average somatic cell score (SCS) at different stages of lactation and conformation traits were estimated. Data consisted of the lactational average of SCS at 150 (SCS(150)) and 305 (SCS(305)) d in milk and 19 conformation traits recorded on 57,154 primiparous Holstein cows, that calved from 1996 to 2009 in 119 herds in Iran. Variance components were estimated using the restricted maximum likelihood procedure based on multiple-trait animal models. Udder depth (-0.32), fore udder attachment (-0.22), and udder width (0.34) showed moderate genetic correlation with SCS(150). Heart girth (0.17), body depth (0.14), chest width (0.26), and angularity (0.19), showed modest genetic correlation with SCS(150). The estimated heritabilities for SCS(150) and SCS(305) were 0.06 and 0.08, respectively. The heritability of the conformation traits ranged from 0.09 to 0.29. Genetic and environmental correlations between SCS(150) and SCS(305) were very high (means ± SE; 0.99±0.01 and 0.89±0.01, respectively), which indicates that recording SCS over a shorter period of lactation is an alternative approach for involving many herds in SCS data collection. The low heritability of SCS indicated that indirect selection for some of udder and body traits might be helpful to reduce the SCS. Additionally, selection for udder traits may help reduce SCS in developing countries where SCS data are sparsely recorded.
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Affiliation(s)
- M Dadpasand
- Department of Animal Science, College of Agriculture, Shiraz University, Shiraz, Iran.
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Abstract
In order to describe the temporal evolution of milk yield (MY) and composition in extended lactations, 21 658 lactations of Italian Holstein cows were analyzed. Six empirical mathematical models currently used to fit 305 standard lactations (Wood, Wilmink, Legendre, Ali and Schaeffer, quadratic and cubic splines) and one function developed specifically for extended lactations (a modification of the Dijkstra model) were tested to identify a suitable function for describing patterns until 1000 days in milk (DIM). Comparison was performed on individual patterns and on average curves grouped according to parity (primiparous and multiparous) and lactation length (standard ≤305 days, and extended from 600 to 1000 days). For average patterns, polynomial models showed better fitting performances when compared with the three or four parameters models. However, LEG and spline regression, showed poor prediction ability at the extremes of the lactation trajectory. The Ali and Schaeffer polynomial and Dijkstra function were effective in modelling average curves for MY and protein percentage, whereas a reduced fitting ability was observed for fat percentage and somatic cell score. When individual patterns were fitted, polynomial models outperformed nonlinear functions. No detectable differences were observed between standard and extended patterns in the initial phase of lactation, with similar values of peak production and time at peak. A considerable difference in persistency was observed between 200 and 305 DIM. Such a difference resulted in an estimated difference between standard and extended cycle of about 7 and 9 kg/day for daily yield at 305 DIM and of 463 and 677 kg of cumulated milk production at 305 DIM for the first- and second-parity groups, respectively. For first and later lactation animals, peak yield estimates were nearly 31 and 38 kg, respectively, and occurred at around 65 and 40 days. The asymptotic level of production was around 9 kg for multiparous cows, whereas the estimate was negative for first parity.
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38
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Genetic parameters for test-day yield of milk, fat and protein in buffaloes estimated by random regression models. J DAIRY RES 2012; 79:272-9. [PMID: 22444071 DOI: 10.1017/s0022029912000143] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
The test-day yields of milk, fat and protein were analysed from 1433 first lactations of buffaloes of the Murrah breed, daughters of 113 sires from 12 herds in the state of São Paulo, Brazil, born between 1985 and 2007. For the test-day yields, 10 monthly classes of lactation days were considered. The contemporary groups were defined as the herd-year-month of the test day. Random additive genetic, permanent environmental and residual effects were included in the model. The fixed effects considered were the contemporary group, number of milkings (1 or 2 milkings), linear and quadratic effects of the covariable cow age at calving and the mean lactation curve of the population (modelled by third-order Legendre orthogonal polynomials). The random additive genetic and permanent environmental effects were estimated by means of regression on third- to sixth-order Legendre orthogonal polynomials. The residual variances were modelled with a homogenous structure and various heterogeneous classes. According to the likelihood-ratio test, the best model for milk and fat production was that with four residual variance classes, while a third-order Legendre polynomial was best for the additive genetic effect for milk and fat yield, a fourth-order polynomial was best for the permanent environmental effect for milk production and a fifth-order polynomial was best for fat production. For protein yield, the best model was that with three residual variance classes and third- and fourth-order Legendre polynomials were best for the additive genetic and permanent environmental effects, respectively. The heritability estimates for the characteristics analysed were moderate, varying from 0·16±0·05 to 0·29±0·05 for milk yield, 0·20±0·05 to 0·30±0·08 for fat yield and 0·18±0·06 to 0·27±0·08 for protein yield. The estimates of the genetic correlations between the tests varied from 0·18±0·120 to 0·99±0·002; from 0·44±0·080 to 0·99±0·004; and from 0·41±0·080 to 0·99±0·004, for milk, fat and protein production, respectively, indicating that whatever the selection criterion used, indirect genetic gains can be expected throughout the lactation curve.
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Samoré A, Román-Ponce S, Vacirca F, Frigo E, Canavesi F, Bagnato A, Maltecca C. Bimodality and the genetics of milk flow traits in the Italian Holstein-Friesian breed. J Dairy Sci 2011; 94:4081-9. [DOI: 10.3168/jds.2010-3611] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2010] [Accepted: 02/16/2011] [Indexed: 11/19/2022]
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40
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Jamrozik J, Schaeffer L. Alternative parameterizations of the multiple-trait random regression model for milk yield and somatic cell score via recursive links between phenotypes. J Anim Breed Genet 2011; 128:258-66. [DOI: 10.1111/j.1439-0388.2011.00918.x] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Miglior F, Gong W, Wang Y, Kistemaker GJ, Sewalem A, Jamrozik J. Short communication: Genetic parameters of production traits in Chinese Holsteins using a random regression test-day model. J Dairy Sci 2009; 92:4697-706. [PMID: 19700734 DOI: 10.3168/jds.2009-2212] [Citation(s) in RCA: 26] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
The objective of this study was to estimate genetic parameters of production traits in the first 3 parities in Chinese Holsteins. Data were a random sample of complete herds (109,005 test-day records of 9,706 cows from 54 herds) extracted from the original data set, which included 362,304 test-day records of 30,942 Holstein cows from 105 herds. A test-day animal model with multiple-trait random regression and the Gibbs sampling method were used for parameter estimation. Regression curves were modeled using Legendre polynomials of order 4. The multiple-trait analysis included milk, fat, and protein yield, and somatic cell score (SCS). Average daily heritabilities ranged between 0.222 and 0.346 for the yield traits and between 0.092 and 0.187 for SCS. Heritabilities were higher in the third lactation for all traits. Within-parity genetic correlations were very high among the yield traits (>0.806) and were close to zero between SCS and yield traits, especially for first-parity cows. Results were similar to previous literature estimates from studies that used the same model as applied to this study. The estimates found in this study will be used to perform breeding value estimation for national genetic evaluations in Chinese Holsteins.
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Affiliation(s)
- F Miglior
- Agriculture and Agri-Food Canada, Dairy and Swine Research and Development Centre, Sherbrooke, Quebec, Canada.
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Hammami H, Rekik B, Soyeurt H, Bastin C, Bay E, Stoll J, Gengler N. Accessing genotype by environment interaction using within- and across-country test-day random regression sire models. J Anim Breed Genet 2009; 126:366-77. [DOI: 10.1111/j.1439-0388.2008.00794.x] [Citation(s) in RCA: 14] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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43
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Abstract
The milk fatty acid (FA) profile is far from the optimal fat composition in regards to human health. The natural sources of variation, such as feeding or genetics, could be used to increase the concentrations of unsaturated fatty acids. The impact of feeding is well described. However, genetic effects on the milk FA composition begin to be extensively studied. This paper summarizes the available information about the genetic variability of FAs. The greatest breed differences in FA composition are observed between Holstein and Jersey milk. Milk fat of the latter breed contains higher concentrations of saturated FAs, especially short-chain FAs. The variation of the delta-9 desaturase activity estimated from specific FA ratios could explain partly these breed differences. The choice of a specific breed seems to be a possibility to improve the nutritional quality of milk fat. Generally, the proportions of FAs in milk are more heritable than the proportions of these same FAs in fat. Heritability estimates range from 0.00 to 0.54. The presence of some single nucleotide polymorphisms could explain partly the observed individual genetic variability. The polymorphisms detected on SCD1 and DGAT1 genes influence the milk FA composition. The SCD1 V allele increases the unsaturation of C16 and C18. The DGAT1 A allele is related to the unsaturation of C18. So, a combination of the molecular and quantitative approaches should be used to develop tools helping farmers in the selection of their animals to improve the nutritional quality of the produced milk fat.
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Affiliation(s)
- V M-R Arnould
- Gembloux Agricultural University, Animal Science Unit, Passage des Déportés,2, 5030 Gembloux, Belgium.
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Loker S, Miglior F, Bohmanova J, Schaeffer LR, Jamrozik J, Kistemaker G. Short communication: effect of preadjusting test-day yields for stage of pregnancy on variance component estimation in Canadian Ayrshires. J Dairy Sci 2009; 92:2270-5. [PMID: 19389986 DOI: 10.3168/jds.2008-1806] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
Preadjustment of phenotypic records is an alternative to accounting for the effect of pregnancy within the genetic evaluation model. Variance components used in the Canadian Test-Day Model may need to be re-estimated after preadjusting for pregnancy. The objective of this study was to assess the effect of preadjusting test-day yields on variance components and estimated breeding values using a random regression test-day model in a random sample of Ayrshire cows. A random sample of 981 Canadian Ayrshire cows from 18 complete herds (average of 54.5 cows/herd) was analyzed. Two data sets were created using the same animals, one with unadjusted milk, fat, and protein yields, and one data set with test-day records adjusted for pregnancy effects. Pregnancy effect estimates from a previous study were used for additive preadjustment of records. Variance components were estimated using both data sets. Results were very similar between the 2 data sets for all estimated genetic parameters (heritabilities, genetic, and permanent environmental correlations). The relative squared differences were very small: 0.05% for heritabilities, 0.20% for genetic correlations, and 0.18% for permanent environmental correlations. Furthermore, paired Student's t-tests showed that the differences between the genetic parameters of data sets adjusted and unadjusted for pregnancy effect were not significantly different from 0. Results from this study show that preadjusting data for pregnancy did not yield changes in covariance component estimates, thus suggesting that preadjusting test-day records could be a feasible solution to account for pregnancy in the Canadian Test-Day Model without changing the current model. Estimated breeding values (EBV) were calculated for both data sets to observe the impact of preadjusting for pregnancy. Overall, the largest changes in EBV seen when preadjusting for pregnancy (compared with unadjusted records) occurred for nonpregnant elite cows, whose EBV declined. Preadjusting for pregnancy before genetic evaluations improves the estimation of breeding values by adding the negative impact of pregnancy back onto pregnant cow test-day records, causing an increase in their production EBV.
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Affiliation(s)
- S Loker
- Centre for Genetic Improvement of Livestock, University of Guelph, Guelph, Ontario, Canada, N1G 2W1
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Samoré AB, Groen AF, Boettcher PJ, Jamrozik J, Canavesi F, Bagnato A. Genetic correlation patterns between somatic cell score and protein yield in the Italian Holstein-Friesian population. J Dairy Sci 2009; 91:4013-21. [PMID: 18832227 DOI: 10.3168/jds.2007-0718] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
Genetic parameters for somatic cell score (SCS) in the Italian Holstein-Friesian population were estimated addressing the pattern of genetic correlation with protein yield in different parities (first, second, and third) and on different days in milk within each parity. Three approaches for parameter estimation were applied using random samples of herds from the national database of the Italian Holstein Association. Genetic correlations for lactation measures (305-d protein yield and lactation SCS) were positive in the first parity (0.31) and close to zero in the second (0.01) and third (0.09) parities. These results indicated that larger values of SCS were genetically associated with increased production. The second and third sets of estimates were based on random regression test-day models, modeling the shape of lactation curve with the Wilmink function and fourth-order Legendre polynomials, respectively. Genetic correlations from both random regression models showed a specific pattern associated with days in milk within and across parities. Estimates varied from positive to negative in the first and second parity, and from null to negative in the third parity. Patterns were similar for both random regression models. The average overall correlation between SCS and protein yield was zero or slightly positive in the first lactation and ranged from zero to negative in later lactations. Correlation estimates differed by parity and stage of lactation. They also demonstrated the dubiousness of applying a single genetic correlation measure between SCS and protein in setting selection strategies. Differences in magnitude and the sign of genetic correlations between SCS and yields across and within parities should be accounted for in selection schemes.
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Affiliation(s)
- A B Samoré
- Department of Veterinary Sciences and Technologies for Food Safety, University of Milan, Milano, Italy.
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Soyeurt H, Dardenne P, Dehareng F, Bastin C, Gengler N. Genetic Parameters of Saturated and Monounsaturated Fatty Acid Content and the Ratio of Saturated to Unsaturated Fatty Acids in Bovine Milk. J Dairy Sci 2008; 91:3611-26. [DOI: 10.3168/jds.2007-0971] [Citation(s) in RCA: 50] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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47
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Detection of QTL for milk protein percentage in Italian Friesian cattle by AFLP markers and selective genotyping. J DAIRY RES 2008; 75:430-8. [PMID: 18700999 DOI: 10.1017/s0022029908003415] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
We targeted quantitative trait loci (QTL) for milk protein percentage (P%) in two Italian Holstein granddaughter design families using selective genotyping in combination with high throughput amplified fragment length polymorphism (AFLP) markers. A total of 64 extreme high and low sires in respect to estimated breeding value (EBV) for P% (EBVP%) were genotyped with 25 AFLP primer combinations that revealed 305 and 291 polymorphisms in the two families. Association between markers and EBVP% was investigated by a linear model only on bands having paternal origin (105 and 96 AFLP bands in family D and S, respectively). Although no marker was significantly associated with the target trait after correction for multiple comparisons, 17 AFLP markers, significant without correction for multiple tests, were considered suggestive of the presence of a QTL. Eleven of these were successfully located on six Bos taurus (BTA) chromosomes by radiation hybrid or in-silico mapping. Ten of these mapped in the immediate neighbourhood (less than 10 cM) of already described QTL for P%. Suggestive association was verified in four regions by microsatellites analysis: one on BTA 10; one on BTA 28; and two on BTA 18. Microsatellites identified significant effects by single marker and interval mapping analyses on BTA 10 and BTA 28, while they were only suggestive of the presence of QTL on BTA 18. In summary, our results firstly indicate that AFLP markers may be used to seek QTL exploiting a selective genotyping approach in GDD, a wide used experimental design in cattle; secondly, propose two approaches for AFLP mapping, namely in-silico mapping exploiting most updated release from the bovine whole genome sequencing project, and physical mapping exploiting a panel of Bovine/Hamster Radiation Hybrids; and thirdly, provide new information on QTLs for an economic important trait in a never investigated Holstein cattle population. AFLP in combination with selective genotyping can be a useful strategy for QTL searching in minor livestock species, sometimes having large economic impact in marginal areas, where more informative markers are still poorly developed.
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Macciotta N, Mele M, Conte G, Serra A, Cassandro M, Dal Zotto R, Cappio Borlino A, Pagnacco G, Secchiari P. Association Between a Polymorphism at the Stearoyl CoA Desaturase Locus and Milk Production Traits in Italian Holsteins. J Dairy Sci 2008; 91:3184-9. [DOI: 10.3168/jds.2007-0947] [Citation(s) in RCA: 55] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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49
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Hammami H, Rekik B, Soyeurt H, Ben Gara A, Gengler N. Genetic Parameters for Tunisian Holsteins Using a Test-Day Random Regression Model. J Dairy Sci 2008; 91:2118-26. [DOI: 10.3168/jds.2007-0382] [Citation(s) in RCA: 34] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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50
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Canavesi F, Biffani S, Banos G. The accuracy of test day model evaluation for the Italian Holstein. ITALIAN JOURNAL OF ANIMAL SCIENCE 2007. [DOI: 10.4081/ijas.2007.1s.57] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Affiliation(s)
- F. Canavesi
- Associazione Nazionale Allevatori Frisona Italiana, Cremona, Italy
| | - S. Biffani
- Associazione Nazionale Allevatori Frisona Italiana, Cremona, Italy
| | - G. Banos
- Aristotele University, Thessaloniki, Greece
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