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Lou W, Bonfatti V, Bovenhuis H, Shi R, van der Linden A, Mulder HA, Liu L, Wang Y, Ducro B. Prediction of likelihood of conception in dairy cows using milk mid-infrared spectra collected before the first insemination and machine learning algorithms. J Dairy Sci 2024:S0022-0302(24)00850-6. [PMID: 38825141 DOI: 10.3168/jds.2023-24621] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2023] [Accepted: 04/15/2024] [Indexed: 06/04/2024]
Abstract
Accurate and ex-ante prediction of cows' likelihood of conception (LC) based on milk composition information could improve reproduction management on dairy farms. Milk composition is already routinely measured by mid-infrared (MIR) spectra, which are known to change with advancing stages of pregnancy. For lactating cows, MIR spectra may also be used for predicting the LC. Our objectives were to classify the LC at first insemination using milk MIR spectra data collected from calving to first insemination and to identify the spectral regions that contribute the most to the prediction of LC at first insemination. After quality control, 4,866 MIR spectra, milk production, and reproduction records from 3,451 Holstein cows were used. The classification accuracy and area under the curve (AUC) of 6 models comprising different predictors and 3 machine learning methods were estimated and compared. The results showed that partial least square discriminant analysis (PLS-DA) and random forest had higher prediction accuracies than logistic regression. The classification accuracy of good and poor LC cows and AUC in herd-by-herd validation of the best model were 76.35 ± 10.60% and 0.77 ± 0.11, respectively. All wavenumbers with values of variable importance in the projection higher than 1.00 in PLS-DA belonged to 3 spectral regions, namely from 1,003 to 1,189, 1,794 to 2,260, and 2,300 to 2,660 cm-1. In conclusion, the model can predict LC in dairy cows from a high productive TMR system before insemination with a relatively good accuracy, allowing farmers to intervene in advance or adjust the insemination schedule for cows with a poor predicted LC.
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Affiliation(s)
- W Lou
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory of Animal Breeding, State Key Laboratory of Animal Biotech Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China; Wageningen University & Research, Animal Breeding and Genomics, P.O. Box 338, 6700 AH Wageningen, the Netherlands; Wageningen University & Research, Animal Production Systems, P.O. Box 338, 6700 AH Wageningen, the Netherlands
| | - V Bonfatti
- Department of Comparative Biomedicine and Food Science, University of Padova, Legnaro, 35020, Italy.
| | - H Bovenhuis
- Wageningen University & Research, Animal Breeding and Genomics, P.O. Box 338, 6700 AH Wageningen, the Netherlands
| | - R Shi
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory of Animal Breeding, State Key Laboratory of Animal Biotech Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China; Wageningen University & Research, Animal Breeding and Genomics, P.O. Box 338, 6700 AH Wageningen, the Netherlands; Wageningen University & Research, Animal Production Systems, P.O. Box 338, 6700 AH Wageningen, the Netherlands
| | - A van der Linden
- Wageningen University & Research, Animal Production Systems, P.O. Box 338, 6700 AH Wageningen, the Netherlands
| | - H A Mulder
- Wageningen University & Research, Animal Breeding and Genomics, P.O. Box 338, 6700 AH Wageningen, the Netherlands
| | - L Liu
- Beijing Dairy Cattle Center, Beijing, 100192, China
| | - Y Wang
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory of Animal Breeding, State Key Laboratory of Animal Biotech Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
| | - B Ducro
- Wageningen University & Research, Animal Breeding and Genomics, P.O. Box 338, 6700 AH Wageningen, the Netherlands
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Estrada-León RJ, Valladares-Rodas MA, Vázquez ACS, Monforte JGM, Correa JCS, Parra-Bracamonte GM. Genetic parameters for milk yield and reproductive traits in Honduran Holstein cattle. Trop Anim Health Prod 2024; 56:175. [PMID: 38789604 DOI: 10.1007/s11250-024-04028-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Accepted: 05/09/2024] [Indexed: 05/26/2024]
Abstract
The aim of this study was to estimate the (co)variance components and genetic parameters for milk yield adjusted to 305d (MY305), calving-to-conception interval (CCI), number of services per conception (NSC) and calving interval (CI) of Honduran Holstein cows, by fitting a bivariate animal model using Maximum Restricted Likelihood procedures. Model included the fixed effects of calving number, the contemporary calving group (farm-season-year of calving and the cow age as covariate). The estimated means and standard deviations for MY, CCI, NSC and CI were, 5098.60 ± 1564.32 kg, 168.27 ± 104.71 days, 2.46 ± 1.69 services, and 448.73 ± 109.16 days, respectively; and their estimated heritabilities were 0.21 ± 0.05, 0.03 ± 0.028, 0.02 ± 0.024 and 0.06 ± 0.04, respectively. The genetic correlations between MY305 and CCI, NSC and CI were positive and antagonist, with values of 0.64 ± 0.52, 0.99 ± 0.56, and 0.32 ± 0.24 respectively. Even though moderate to low heritability was estimated for MY305, systematic selection for milk yield, with a reduction in reproductive efficiency, if considered as the only selection criterion is important to be considered. By including reproductive traits and considering permanent environment effects into the breeding program, might yield a slow, but constant and permanent improvement over time.
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Affiliation(s)
- Raciel Javier Estrada-León
- Tecnológico Nacional de México, Instituto Tecnológico Superior de Calkini. C.A. Bioprocesos, Av. Ah Canul S/N por Carretera Federal. Calkiní, Campeche, Calkin?, C.P. 24900, México
| | | | - Angel Carmelo Sierra Vázquez
- División de Estudios de Posgrado e Investigación, Tecnológico Nacional de México, Instituto Tecnológico de Conkal, Cuerpo Académico ITCON-5. Avenida Tecnológico S/N, Conkal, Yucatán, México
| | | | | | - Gaspar Manuel Parra-Bracamonte
- Instituto Politécnico Nacional, Centro de Biotecnología Genómica, Boulevard del Maestro s/n, esquina Elías Piña, colonia Narciso Mendoza, Reynosa, Tamaulipas, C.P. 88710, México.
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Zhu K, Li T, Liu D, Wang S, Wang S, Wang Q, Pan Y, Zan L, Ma P. Estimation of genetic parameters for fertility traits in Chinese Holstein of south China. Front Genet 2024; 14:1288375. [PMID: 38235000 PMCID: PMC10791758 DOI: 10.3389/fgene.2023.1288375] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Accepted: 11/28/2023] [Indexed: 01/19/2024] Open
Abstract
Introduction: Chinese Holstein in South China suffer heat stress for a long period, which leads to evolutionary differences from Chinese Holstein in North China. The aim of this study was to estimate the genetic parameters of fertility traits for Chinese Holstein in South China. Methods: A total of 167,840 Chinese Holstein heifers and cows from Guangming Animal Husbandry Co., LTD farms were used in this study. The fertility traits analyzed were calving interval (CI), days open (DO), age of first service (AFS), age of first calving (AFC), calving to first insemination (CTFS), first insemination to conception (FSTC), gestation length (GL), non-return rate to 56 days (NRR), and number of services (NS). Results: The descriptive statistics revealed that the same trait in heifers performed better than in cows, which was consistent with the other studies. The heritabilities of fertility traits in this study ranged from close to 0 (for NS of cows) to 0.2474 (for AFC of heifers). The genetic correlation of NRR between heifers and cows was 0.9993, which indicates that the NRR for heifers and cows could be treated as one trait in this population. Conclusion: The heritabilities of fertility traits in Chinese Holstein in south China were quite different from the heritabilities of fertility traits in North China. NRR56, NS, AFC, and CI were suggested to be included into the selection index to improve fertility performance of Chinsese Holstein of south China. The results of this study could provide genetic parameters for the animal breeding program of Chinese Holstein in the south of China.
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Affiliation(s)
- Kai Zhu
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China
- Bright Dairy & Food Co., Ltd., Shanghai, China
| | - Tuowu Li
- Shanghai Collaborative Innovation Center of Agri-Seeds, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, China
| | - Dengying Liu
- Shanghai Collaborative Innovation Center of Agri-Seeds, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, China
| | - Shiyi Wang
- Shanghai Collaborative Innovation Center of Agri-Seeds, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, China
| | - Sihu Wang
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China
| | - Qishan Wang
- Department of Animal Science, College of Animal Sciences, Zhejiang University, Hangzhou, China
| | - Yuchun Pan
- Department of Animal Science, College of Animal Sciences, Zhejiang University, Hangzhou, China
| | - Linsen Zan
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China
- National Beef Cattle Improvement Center, Northwest A&F University, Yangling, Shaanxi, China
| | - Peipei Ma
- Shanghai Collaborative Innovation Center of Agri-Seeds, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, China
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Zhang J, Han L, Zhang H, Hu H, Sheng H, Yang T, Zhang Y, Wen W, Ma L, Ma Y, Wang Y. Genetic parameters for health traits and their association with fertility and milk production in Chinese Holsteins. J Anim Breed Genet 2024; 141:52-64. [PMID: 37746924 DOI: 10.1111/jbg.12825] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Revised: 08/14/2023] [Accepted: 09/09/2023] [Indexed: 09/26/2023]
Abstract
Herd health is one of the key problems influencing the efficiency of the dairy industry. Genetic selection, with a focus on animal health, is important for herd improvement. This study aimed to estimate genetic parameters for health traits and their correlations with fertility and milk production traits in dairy cattle. Based on records from 58,549 lactating cows calved between 2015 and 2021, a total of 24 health traits (six composite health traits and 18 independent health traits), four fertility traits and five milk production traits were analysed. First, linear and threshold animal models were used to estimate the variance components and heritabilities of the health traits. Second, a bivariate linear animal model was used to estimate genetic correlations among all 24 health traits. Finally, a bivariate linear animal model based on records from the first lactation was used to estimate the correlations between health traits and fertility or milk production traits. The results showed that all health traits had low heritabilities, ranging from 0.002 (0.001) to 0.048 (0.004) in the linear model and from <0.001 (0.021) to 0.226 (0.035) in the threshold model. Genetic correlations between health traits across categories were generally low, whereas the relatively high genetic correlations were found between health traits within the same category. In this study, only a few significant and moderate genetic correlations were observed between health traits and fertility or milk production traits. Clinical mastitis showed relatively moderate correlations with fertility traits, ranging from 0.277 (0.113) (interval from first to last insemination) to 0.401 (0.104) (calving interval). Moreover, there were moderate genetic correlations between hoof health and milk production traits. The results from the current study will support balanced dairy breeding to genetically improve disease resistance in dairy cows.
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Affiliation(s)
- Junxing Zhang
- Key Laboratory of Ruminant Molecular and Cellular Breeding, College of Animal Science and Technology, Ningxia University, Yinchuan, China
| | - Liyun Han
- Key Laboratory of Ruminant Molecular and Cellular Breeding, College of Animal Science and Technology, Ningxia University, Yinchuan, China
- Key Laboratory of Animal Genetics, Breeding and Reproduction, MARA, National Engineering Laboratory of Animal Breeding, State Key Laboratory of Farm Animal Biotech Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
- Ningxia Nongken Dairy Industry Co., Ltd, Yinchuan, China
| | - Hailiang Zhang
- Key Laboratory of Animal Genetics, Breeding and Reproduction, MARA, National Engineering Laboratory of Animal Breeding, State Key Laboratory of Farm Animal Biotech Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Honghong Hu
- Key Laboratory of Ruminant Molecular and Cellular Breeding, College of Animal Science and Technology, Ningxia University, Yinchuan, China
| | - Hui Sheng
- Key Laboratory of Ruminant Molecular and Cellular Breeding, College of Animal Science and Technology, Ningxia University, Yinchuan, China
| | - Tongtong Yang
- Key Laboratory of Animal Genetics, Breeding and Reproduction, MARA, National Engineering Laboratory of Animal Breeding, State Key Laboratory of Farm Animal Biotech Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Yi Zhang
- Key Laboratory of Animal Genetics, Breeding and Reproduction, MARA, National Engineering Laboratory of Animal Breeding, State Key Laboratory of Farm Animal Biotech Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Wan Wen
- The Ningxia Hui Autonomous Region Animal Husbandry Station, Yinchuan, China
| | - Liqin Ma
- The Ningxia Hui Autonomous Region Animal Husbandry Station, Yinchuan, China
| | - Yun Ma
- Key Laboratory of Ruminant Molecular and Cellular Breeding, College of Animal Science and Technology, Ningxia University, Yinchuan, China
| | - Yachun Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction, MARA, National Engineering Laboratory of Animal Breeding, State Key Laboratory of Farm Animal Biotech Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
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Sahoo S, Alex R, Vohra V, Mukherjee S, Gowane GR. Estimation of genetic parameters and genetic change of first parity reproductive traits in Alpine × Beetal goats. Reprod Domest Anim 2023; 58:1188-1198. [PMID: 37405572 DOI: 10.1111/rda.14418] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2023] [Revised: 06/15/2023] [Accepted: 06/26/2023] [Indexed: 07/06/2023]
Abstract
The study of reproductive traits is crucial for improving genetic potential of goats because of their significant utility in meat production. Hence, genetic analysis was conducted for reproductive traits on Alpine × Beetal goats using animal model for first parity data. Information on 1462 reproductive records were collected over five decades from ICAR-National Dairy Research Institute, Karnal, Haryana (1971-2021). Single-trait and multi-trait animal models were used for genetic analysis. Estimates of (co)variance components and genetic parameters were obtained using Gibbs Sampler for Animal Model due to non-normal distribution of data. Six single-trait animal models (including or excluding maternal and environmental effects) were fitted and best models were determined based on Deviance Convergence Criterion values. The prolificacy for the A × B goats for first parity data was 32%, having 68% single births, 31% twins and 1% triplets/quadruplets. The least squares mean for age at first service (AFS), age at first kidding (AFK), service period (SP), dry period (DP), gestation length (GL), kidding interval (KI), litter weight (LW), number of kids born (NKB) and number of females kids born (NFKB) in first parity were 546.15 ± 4.10 days, 679.05 ± 4.07 days, 226.51 ± 4.02 days, 67.96 ± 2.76 days, 150.74 ± 0.13 days, 362.53 ± 3.35 days, 3.99 ± 0.04 kg, 1.32 ± 0.02 and 0.64 ± 0.02, respectively. The heritability estimates obtained from best model for AFS, AFK, GL, KI, SP, and DP were 0.12 ± 0.00, 0.10 ± 0.00, 0.09 ± 0.01, 0.03 ± 0.00, 0.04 ± 0.00, and 0.05 ± 0.00, respectively. For NKB, NFKB and LW, heritability estimates were 0.16 ± 0.01, 0.03 ± 0.03, and 0.04 ± 0.00, respectively. These results imply lower heritability estimates for reproductive traits, and hence meagre scope for selection for further improvement. Maternal effects contributed significantly for traits such as GL, NKB and NFKB. Genetic correlation for number of female kids born was negative with SP and DP which is favourable. Furthermore, genetic correlation was negative for dry period and litter weight which is favourable as number of kids born and litter weight are traits of direct economic importance. Results reveal high genetic potential of this breed for meat industry owing to high prolificacy, provided consistent efforts are made for the genetic improvement of this germplasm.
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Affiliation(s)
- Shweta Sahoo
- Division of Animal Genetics and Breeding, ICAR-National Dairy Research Institute, Karnal, Haryana, India
| | - Rani Alex
- Division of Animal Genetics and Breeding, ICAR-National Dairy Research Institute, Karnal, Haryana, India
| | - Vikas Vohra
- Division of Animal Genetics and Breeding, ICAR-National Dairy Research Institute, Karnal, Haryana, India
| | - Sabyasachi Mukherjee
- Division of Animal Genetics and Breeding, ICAR-National Dairy Research Institute, Karnal, Haryana, India
| | - G R Gowane
- Division of Animal Genetics and Breeding, ICAR-National Dairy Research Institute, Karnal, Haryana, India
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Wang A, Brito LF, Zhang H, Shi R, Zhu L, Liu D, Guo G, Wang Y. Exploring milk loss and variability during environmental perturbations across lactation stages as resilience indicators in Holstein cattle. Front Genet 2022; 13:1031557. [PMID: 36531242 PMCID: PMC9757536 DOI: 10.3389/fgene.2022.1031557] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Accepted: 11/14/2022] [Indexed: 09/12/2023] Open
Abstract
Genetic selection for resilience is essential to improve the long-term sustainability of the dairy cattle industry, especially the ability of cows to maintain their level of production when exposed to environmental disturbances. Recording of daily milk yield provides an opportunity to develop resilience indicators based on milk losses and fluctuations in daily milk yield caused by environmental disturbances. In this context, our study aimed to explore milk loss traits and measures of variability in daily milk yield, including log-transformed standard deviation of milk deviations (Lnsd), lag-1 autocorrelation (Ra), and skewness of the deviations (Ske), as indicators of general resilience in dairy cows. The unperturbed dynamics of milk yield as well as milk loss were predicted using an iterative procedure of lactation curve modeling. Milk fluctuations were defined as a period of at least 10 successive days of negative deviations in which milk yield dropped at least once below 90% of the expected values. Genetic parameters of these indicators and their genetic correlation with economically important traits were estimated using single-trait and bivariate animal models and 8,935 lactations (after quality control) from 6,816 Chinese Holstein cows. In general, cows experienced an average of 3.73 environmental disturbances with a milk loss of 267 kg of milk per lactation. Each fluctuation lasted for 19.80 ± 11.46 days. Milk loss traits are heritable with heritability estimates ranging from 0.004 to 0.061. The heritabilities differed between Lnsd (0.135-0.250), Ra (0.008-0.058), and Ske (0.001-0.075), with the highest heritability estimate of 0.250 ± 0.020 for Lnsd when removing the first and last 10 days in milk in a lactation (Lnsd2). Based on moderate to high genetic correlations, lower Lnsd2 is associated with less milk losses, better reproductive performance, and lower disease incidence. These findings indicate that among the variables evaluated, Lnsd2 is the most promising indicator for breeding for improved resilience in Holstein cattle.
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Affiliation(s)
- Ao Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Luiz F. Brito
- Department of Animal Sciences, Purdue University, West Lafayette, IN, United States
| | - Hailiang Zhang
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Rui Shi
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Lei Zhu
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Dengke Liu
- Hebei Sunlon Modern Agricultural Technology Co., Ltd., Dingzhou, China
| | - Gang Guo
- Beijing Sunlon Livestock Development Co., Ltd., Beijing, China
| | - Yachun Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
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Kgari RD, Muller C, Dzama K, Makgahlela ML. Estimation of Genetic Parameters for Heifer and Cow Fertility Traits Derived from On-Farm AI Service Records of South African Holstein Cattle. Animals (Basel) 2022; 12:ani12162023. [PMID: 36009614 PMCID: PMC9404416 DOI: 10.3390/ani12162023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Revised: 07/30/2022] [Accepted: 08/03/2022] [Indexed: 11/16/2022] Open
Abstract
This study aimed to derive additional fertility traits from service data and estimate their genetic parameters for their possible inclusion in the South African Holstein cattle breeding programs. Service records (n = 64,464) were collected from 18 South African Holstein herds using on-farm automated milk recording systems. Using a multivariate model, the data were used to estimate heritabilities and correlations among several fertility traits. The pedigree data consisted of information on 18,592 animals born between 1981 and 2013. Heritability estimates observed were low to moderate (0.02 ± 0.00 to 0.24 ± 0.00), indicating that there is some genetic basis for the explored fertility traits to warrant selection. The genetic correlations observed between fertility traits were generally favorable, with some high correlations between age at first service (AFS) and services per conception for heifers (SPCh) (0.73 ± 0.00) and between days from calving to first service (CFS) and services per conception for cows (SPC) (0.90 ± 0.01). Positive genetic correlations indicate that improvement in one trait is coupled with a correlated genetic increase in another trait. The studied fertility traits could be used in addition to AFC and CI to serve as a basis for the selection of reproduction in dairy cattle to minimize selection bias.
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Affiliation(s)
- Ramadimetje Delight Kgari
- Agricultural Research Council, Department of Animal Breeding and Genetics, Private Bag X2, Irene 0062, South Africa
- Department of Animal Sciences, University of Stellenbosch, Stellenbosch 7600, South Africa
- Correspondence:
| | - Carel Muller
- Department of Animal Sciences, University of Stellenbosch, Stellenbosch 7600, South Africa
| | - Kennedy Dzama
- Department of Animal Sciences, University of Stellenbosch, Stellenbosch 7600, South Africa
| | - Mahlako Linah Makgahlela
- Agricultural Research Council, Department of Animal Breeding and Genetics, Private Bag X2, Irene 0062, South Africa
- Department of Animal, Wildlife and Grassland Sciences, University of the Free State, Bloemfontein 9301, South Africa
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Sammad A, Zhang H, Shi R, Dong Y, Luo H, Chen Z, Liu L, Guo G, Liu A, Wang Y. A Post-GWAS Functional Analysis Confirming Effects of Three BTA13 Genes CACNB2, SLC39A12, and ZEB1 on Dairy Cattle Reproduction. Front Genet 2022; 13:882951. [PMID: 35754833 PMCID: PMC9216173 DOI: 10.3389/fgene.2022.882951] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Accepted: 05/18/2022] [Indexed: 11/26/2022] Open
Abstract
In our previous GWAS of Chinese and Nordic dairy cattle, genes CACNB2, SLC39A12, and ZEB1 locating on BTA 13 were suggested as candidate genes for reproduction. In this study, validation of these associations was performed in an independent population with records of nine reproductive traits. More importantly, functions of these genes in the reproductive process were verified by employing the expression data of ovarian follicles. The potential variants within the three genes were firstly detected in 68 Chinese Holstein bulls, and then screened in 1,588 Chinese Holstein cows using the KASP (Kompetitive allele-specific PCR) method. There were nine variants with polymorphisms in CACNB2, five in SLC39A12, and four in ZEB1, respectively, of which one SNP was in the upstream regulatory region, two in exon region, four in downstream regulatory region, and 11 SNPs in intronic regions. Amongst the 18 variants, g.33267056T/G in CACNB2 explained the largest phenotypic variance for age at first calving (0.011%), interval from first to last insemination (0.004%), and calving ease (0.002%), while g.32751518G/A in SLC39A12 contributed the most to stillbirth in heifers (0.038%). Two haplotype blocks were constructed for CACNB2 while one each for SLC39A12 and ZEB1, which were significantly associated with five reproductive traits, including age at the first service, age at the first calving, calving ease in heifers and cows, and the interval from calving to the first insemination. We then studied the profile of gene expression in granulosa cells isolated from four developmental stages of ovarian follicles from eight dairy cows. All three genes were differentially expressed between ovarian follicles with different sizes (p < 0.05), indicating their potential roles in the reproductive process of dairy cows. This study successfully demonstrated the associations of three BTA 13 genes CACNB2, SLC39A12, and ZEB1 with reproduction and further examined their expression levels in ovarian follicles directly. These findings can be beneficial for the ongoing genomic selection program for reproductive traits which have long been considered as traits that are difficult to achieve genetic improvement due to the lack of efficient genetic markers.
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Affiliation(s)
- Abdul Sammad
- Key Laboratory of Animal Genetics, Breeding and Reproduction, MARA, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Hailiang Zhang
- Key Laboratory of Animal Genetics, Breeding and Reproduction, MARA, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Rui Shi
- Key Laboratory of Animal Genetics, Breeding and Reproduction, MARA, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Yixin Dong
- Key Laboratory of Animal Genetics, Breeding and Reproduction, MARA, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Hanpeng Luo
- Key Laboratory of Animal Genetics, Breeding and Reproduction, MARA, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Ziwei Chen
- Key Laboratory of Animal Genetics, Breeding and Reproduction, MARA, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Lin Liu
- Beijing Dairy Cattle Center, Beijing, China
| | - Gang Guo
- Beijing Sunlon Livestock Development Co. Ltd., Beijing, China
| | - Aoxing Liu
- Key Laboratory of Animal Genetics, Breeding and Reproduction, MARA, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China.,Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus, Denmark
| | - Yachun Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction, MARA, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
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Otwinowska-Mindur A, Ptak E, Jagusiak W, Zarnecki A. Estimation of Genetic Parameters for Female Fertility Traits in the Polish Holstein-Friesian Population. Animals (Basel) 2022; 12:ani12121485. [PMID: 35739822 PMCID: PMC9219430 DOI: 10.3390/ani12121485] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Revised: 05/26/2022] [Accepted: 06/06/2022] [Indexed: 11/16/2022] Open
Abstract
Simple Summary Female fertility is an important functional trait in dairy cattle. The aim of this study was to estimate genetic parameters for some fertility traits of Polish Holstein-Friesian cows. The results indicate that a few analyzed traits could be of use in genetic evaluation of Polish Holstein-Friesian cows. Abstract The objective of this study was to estimate genetic parameters for the analyzed fertility traits of Polish Holstein-Friesian primiparous and multiparous cows, as a step toward the incorporation of new traits into routine genetic evaluation. Lactation records of 116,836 Polish Holstein-Friesian cows were studied. The records cover the first three lactations of all cows. The cows, daughters of 2884 sires, were calved from 2006 to 2020. The conception rate for heifers (CRh) and for cows in the second (CR2) and third parity (CR3), the interval from first calving to first insemination (CTFI), the days open (DO), and the interval from first to successful insemination for heifers (FSh) and for cows in second (FS2) and third (FS3) parity were analyzed. The BLUPf90 package and a Bayesian method via Gibbs sampling were used to estimate (co)variance components. In general, all heritabilities were low and ranged from 0.013 (CTFI) to 0.038 (FS2). The heritability of conception rate and interval from first to successful insemination was slightly lower for heifers than for cows. Genetic correlations were moderate to high with two exceptions: correlation of CTFI with CRh (0.033) and with FSh (−0.051). The results indicate that a few analyzed traits could be used in genetic evaluation of Polish Holstein-Friesian cows. It is suggested to complement the selection index with traits for both heifers and cows, such as the interval from first to successful insemination (i.e., FSh, FS2 and FS3), in order to enable effective improvement of female fertility scores in the Polish Holstein-Friesian population.
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Affiliation(s)
- Agnieszka Otwinowska-Mindur
- Department of Genetics, Animal Breeding and Ethology, University of Agriculture in Krakow, al. Mickiewicza 24/28, 30-059 Krakow, Poland
| | - Ewa Ptak
- Department of Genetics, Animal Breeding and Ethology, University of Agriculture in Krakow, al. Mickiewicza 24/28, 30-059 Krakow, Poland
| | - Wojciech Jagusiak
- Department of Genetics, Animal Breeding and Ethology, University of Agriculture in Krakow, al. Mickiewicza 24/28, 30-059 Krakow, Poland
| | - Andrzej Zarnecki
- National Research Institute of Animal Production, ul. Krakowska 1, 32-083 Balice, Poland
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Lou W, Zhang H, Luo H, Chen Z, Shi R, Guo X, Zou Y, Liu L, Brito LF, Guo G, Wang Y. Genetic analyses of blood β-hydroxybutyrate predicted from milk infrared spectra and its association with longevity and female reproductive traits in Holstein cattle. J Dairy Sci 2022; 105:3269-3281. [PMID: 35094854 DOI: 10.3168/jds.2021-20389] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Accepted: 11/16/2021] [Indexed: 11/19/2022]
Abstract
Ketosis is one of the most prevalent and complex metabolic disorders in high-producing dairy cows and usually detected through analyses of β-hydroxybutyrate (BHB) concentration in blood. Our main objectives were to evaluate genetic parameters for blood BHB predicted based on Fourier-transform mid-infrared spectra from 5 to 305 d in milk, and estimate the genetic relationships of blood BHB with 7 reproduction traits and 6 longevity traits in Holstein cattle. Predicted blood BHB records of 11,609 Holstein cows (after quality control) were collected from 2016 to 2019 and used to derive 4 traits based on parity number, including predicted blood BHB in all parities (BHBp), parity 1 (BHB1), parity 2 (BHB2), and parity 3+ (BHB3). Single- and multitrait repeatability models were used for estimating genetic parameters for the 4 BHB traits. Random regression test-day models implemented via Bayesian inference were used to evaluate the daily genetic feature of BHB variability. In addition, genetic correlations were calculated for the 4 BHB traits with reproduction and longevity traits. The heritability estimates of BHBp, BHB1, BHB2, and BHB3 ranged from 0.100 ± 0.026 (± standard error) to 0.131 ± 0.023. The BHB in parities 1 to 3+ were highly genetically correlated and ranged from 0.788 (BHB1 and BHB2) to 0.911 (BHB1 and BHB3). The daily heritability of BHBp ranged from 0.069 to 0.195, higher for the early and lower for the later lactation periods. A similar trend was observed for BHB1, BHB2, and BHB3. There are low direct genetic correlations between BHBp and selected reproductive performance and longevity traits, which ranged from -0.168 ± 0.019 (BHBp and production life) to 0.157 ± 0.019 (BHBp and age at first calving) for the early lactation stage (5 to 65 d). These direct genetic correlations indicate that cows with higher BHBp (greater likelihood of having ketosis) in blood usually have shorter production life (-0.168 ± 0.019). Cows with higher fertility and postpartum recovery, such as younger age at first calving (0.157 ± 0.019) and shorter interval from calving to first insemination in heifer (0.111 ± 0.006), usually have lower BHB concentration in the blood. Furthermore, the direct genetic correlations change across parity and lactation stage. In general, our results suggest that selection for lower predicted BHB in early lactation could be an efficient strategy for reducing the incidence of ketosis as well as indirectly improving reproductive and longevity performance in Holstein cattle.
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Affiliation(s)
- W Lou
- National Engineering Laboratory of Animal Breeding; Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs (MARA); College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - H Zhang
- National Engineering Laboratory of Animal Breeding; Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs (MARA); College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - H Luo
- National Engineering Laboratory of Animal Breeding; Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs (MARA); College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Z Chen
- National Engineering Laboratory of Animal Breeding; Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs (MARA); College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - R Shi
- National Engineering Laboratory of Animal Breeding; Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs (MARA); College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China; Animal Breeding and Genomics Group, Wageningen University & Research, PO Box 338, 6700 AH Wageningen, the Netherlands
| | - X Guo
- Center of Quantitative Genetics and Genomics, Aarhus University, Tjele, 8830, Denmark
| | - Y Zou
- Beijing Dairy Cattle Center, Beijing, 100192, China
| | - L Liu
- Beijing Dairy Cattle Center, Beijing, 100192, China
| | - L F Brito
- Department of Animal Science, Purdue University, West Lafayette, IN 47907
| | - G Guo
- Beijing Sunlon Livestock Development Company Limited, Beijing, 10029, China
| | - Y Wang
- National Engineering Laboratory of Animal Breeding; Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs (MARA); College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
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Chen Z, Brito LF, Luo H, Shi R, Chang Y, Liu L, Guo G, Wang Y. Genetic and Genomic Analyses of Service Sire Effect on Female Reproductive Traits in Holstein Cattle. Front Genet 2021; 12:713575. [PMID: 34539741 PMCID: PMC8446201 DOI: 10.3389/fgene.2021.713575] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2021] [Accepted: 08/03/2021] [Indexed: 12/19/2022] Open
Abstract
Fertility and reproductive performance are key drivers of dairy farm profitability. Hence, reproduction traits have been included in a large majority of worldwide dairy cattle selection indexes. The reproductive traits are lowly heritable but can be improved through direct genetic selection. However, most scientific studies and dairy cattle breeding programs have focused solely on the genetic effects of the dam (GED) on reproductive performance and, therefore, ignored the contribution of the service sire in the phenotypic outcomes. This study aimed to investigate the service sire effects on female reproductive traits in Holstein cattle from a genomic perspective. Genetic parameter estimation and genome-wide association studies (GWAS) were performed for the genetic effect of service sire (GESS) on conception rate (CR), 56-day non-return rate (NRR56), calving ease (CE), stillbirth (SB), and gestation length (GL). Our findings indicate that the additive genetic effects of both sire and dam contribute to the phenotypic variance of reproductive traits measured in females (0.0196 vs. 0.0109, 0.0237 vs. 0.0133, 0.0040 vs. 0.0289, 0.0782 vs. 0.0083, and 0.1024 vs. 0.1020 for GESS and GED heritability estimates for CR, NRR56, CE, SB, and GL, respectively), and these two genetic effects are positively correlated for SB (0.1394) and GL (0.7871). Interestingly, the breeding values for GESS on insemination success traits (CR and NRR56) are unfavorably and significantly correlated with some production, health, and type breeding values (ranging from -0.449 to 0.274), while the GESS values on calving traits (CE, SB, and GL) are usually favorably associated with those traits (ranging from -0.493 to 0.313). One hundred sixty-two significant single-nucleotide polymorphisms (SNPs) and their surrounding protein-coding genes were identified as significantly associated with GESS and GED, respectively. Six genes overlapped between GESS and GED for calving traits and 10 genes overlapped between GESS for success traits and calving traits. Our findings indicate the importance of considering the GESS when genetically evaluating the female reproductive traits in Holstein cattle.
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Affiliation(s)
- Ziwei Chen
- Key Laboratory of Animal Genetics, Breeding and Reproduction, MARA, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Luiz F. Brito
- Department of Animal Sciences, Purdue University, West Lafayette, IN, United States
| | - Hanpeng Luo
- Key Laboratory of Animal Genetics, Breeding and Reproduction, MARA, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Rui Shi
- Key Laboratory of Animal Genetics, Breeding and Reproduction, MARA, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Yao Chang
- Key Laboratory of Animal Genetics, Breeding and Reproduction, MARA, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Lin Liu
- Beijing Dairy Cattle Center, Beijing, China
| | - Gang Guo
- Beijing Sunlon Livestock Development Company Limited, Beijing, China
| | - Yachun Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction, MARA, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
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Amin AMS, Abo-Ismail MK, Salem MMI. Genetic parameters and genetic trends for reproductive traits in Egyptian buffalo. Anim Reprod Sci 2021; 231:106800. [PMID: 34246040 DOI: 10.1016/j.anireprosci.2021.106800] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Revised: 07/02/2021] [Accepted: 07/02/2021] [Indexed: 11/28/2022]
Abstract
Reproductive traits are important for farm profitability because failure to reproduce is the primary reason for culling animals. Study objectives were to estimate genetic parameters and evaluate the trends for reproductive traits. Age at first calving (AFC), gestation length (GL), postpartum interval to pregnancy (PPIP), calving interval (CI) and calving ease score (CE) were recorded. A total of 38,906 records were available from 2426 buffalo cows. There was evaluation of genetic parameters using three models. The first model was applied to the first three parities fitting animal as a random effect. There was also a repeatability model utilized where data from all parities were evaluated to estimate heritability and repeatability. There was also a bivariate model to estimate genetic correlations between reproductive traits. Heritability estimates ranged from 0.0001 to 0.12 for PPIP and CE, respectively. Repeatability estimates were low to moderate ranging from 0.13 to 0.38 for PPIP and GL, respectively. There were close genetic correlations of 0.99 and - 0.93 between PPIP-CI and GL-CE, respectively. Genetic correlations between the other reproductive traits were low to moderate. Genetic trends for all reproductive traits were negative with and of a small magnitude, and regression coefficients were significant only for AFC and PPIP. The results from the current study supported the urgent need, not only for genetic or genomic selection improvement programs, but also for improving the farm management practices for reproductive traits in Egyptian buffalo.
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Affiliation(s)
- Amin M S Amin
- Animal Production Research Institute (APRI), Agricultural Research Center, Ministry of Agriculture and Land Reclamation, Dooki, Giza, 12618, Egypt.
| | - Mohammed K Abo-Ismail
- Animal Science Department, College of Agriculture, Food and Environmental Sciences, California Polytechnic State University, San Luis Obispo, CA, 93407, USA
| | - Mohamed M I Salem
- Department of Animal and Fish Production, Faculty of Agriculture, University of Alexandria, Alexandria, 21545, Egypt
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Luo H, Brito LF, Li X, Su G, Dou J, Xu W, Yan X, Zhang H, Guo G, Liu L, Wang Y. Genetic parameters for rectal temperature, respiration rate, and drooling score in Holstein cattle and their relationships with various fertility, production, body conformation, and health traits. J Dairy Sci 2021; 104:4390-4403. [PMID: 33685707 DOI: 10.3168/jds.2020-19192] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Accepted: 11/03/2020] [Indexed: 12/12/2022]
Abstract
Genetic selection for improved climatic resilience is paramount to increase the long-term sustainability of high-producing dairy cattle, especially in face of climate change. Various physiological indicators, such as rectal temperature (RT), respiration rate score (RR), and drooling score (DS), can be used to genetically identify animals with more effective coping mechanisms in response to heat stress events. In this study, we investigated genetic parameters for RT, RR (score from 1-3), and DS (score from 1-3). Furthermore, we assessed the genetic relationship among these indicators and other economically important traits for the dairy cattle industry. After data editing, 59,265 (RT), 30,290 (RR), and 30,421 (DS) records from 13,592 lactating Holstein cows were used for the analyses. Variance components were estimated based on a multiple-trait repeatability animal model. The heritability ± standard error estimate for RT, RR, and DS was 0.06 ± 0.01, 0.04 ± 0.01, and 0.02 ± 0.01, respectively, whereas their repeatability was 0.19, 0.14, and 0.14, respectively. Moderate genetic correlations of RR with RT and DS (0.26 ± 0.11 and 0.25 ± 0.16) and nonsignificant correlation between RT and DS (-0.11 ± 0.14) were observed. Furthermore, the approximate genetic correlations between RT, RR, and DS with 12 production, 29 conformation, 5 fertility and reproduction, 5 health, and 9 longevity-indicator traits were assessed. In general, the approximate genetic correlations calculated were low to moderate. In summary, 3 physiological indicators of heat stress response were measured in a large number of animals and shown to be lowly heritable. There is a value in developing a selection index including all the 3 indicators to improve heat tolerance in dairy cattle. All the unfavorable genetic relationships observed between heat tolerance and other economically important traits can be accounted for in a selection index to enable improved climatic resilience while also maintaining or increasing productivity in Holstein cattle.
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Affiliation(s)
- H Luo
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, 100193, Beijing, China
| | - Luiz F Brito
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907
| | - X Li
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, 100193, Beijing, China
| | - G Su
- Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, Tjele 8830, Denmark
| | - J Dou
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, 100193, Beijing, China
| | - W Xu
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, 100193, Beijing, China
| | - X Yan
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, 100193, Beijing, China
| | - H Zhang
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, 100193, Beijing, China
| | - G Guo
- Beijing Sunlon Livestock Development Co. Ltd., 100029, Beijing, China
| | - L Liu
- Beijing Dairy Cattle Center, 100192, Beijing, China
| | - Y Wang
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, 100193, Beijing, China.
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Setiaji A, Oikawa T. Genetics of heifer reproductive traits in Japanese Black cattle. ASIAN-AUSTRALASIAN JOURNAL OF ANIMAL SCIENCES 2019; 33:197-202. [PMID: 31208175 PMCID: PMC6946956 DOI: 10.5713/ajas.19.0118] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 02/08/2019] [Accepted: 05/07/2019] [Indexed: 11/27/2022]
Abstract
Objective The objective of this study was to identify environmental factors strongly associated with and to estimate genetic parameters of reproductive traits in Japanese Black heifers. Methods Data included reproduction records of Japanese Black heifers born between 2004 and 2014. First service non-return rate (NRR) to 56 days from first to successful insemination (FS), number of services per conception (IN), age at first calving (AFC) and gestation length were analyzed with the use of the general linear model. Genetic parameters were estimated with the use of the univariate animal model of the residual maximum likelihood. Results Averages of reproductive traits over eleven years were assessed, and the effects of farm, year, month, artificial insemination technician and interaction of farm×year on the traits were determined. Estimated heritability of FS was very low and that of AFC was higher than that of the other traits. A close genetic relation was observed among NRR, IN, and FS; however, their heritabilities were very low. AFC shows favorable genetic correlation with IN and FS. Conclusion Low heritabilities of most reproductive traits in Japanese Black heifers are strongly influenced by farm management practices, and that large residual variances make genetic evaluation difficult. Among the reproductive traits, AFC is potentially more useful for genetic improvement of heifer reproductive traits because it has high heritability and favorable genetic correlations with IN and FS.
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Affiliation(s)
- Asep Setiaji
- United Graduate School of Agricultural Sciences, Kagoshima University, Korimoto, Kagoshima 890-0065, Japan.,Faculty of Agriculture, University of the Ryukyus, Nishihara, Okinawa 903-0213 Japan.,Department of Animal Science, Faculty of Animal and Agricultural Sciences, Diponegoro University, Semarang, 50275 Central Java, Indonesia
| | - Takuro Oikawa
- United Graduate School of Agricultural Sciences, Kagoshima University, Korimoto, Kagoshima 890-0065, Japan.,Faculty of Agriculture, University of the Ryukyus, Nishihara, Okinawa 903-0213 Japan
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Liu A, Lund MS, Wang Y, Guo G, Dong G, Madsen P, Su G. Variance components and correlations of female fertility traits in Chinese Holstein population. J Anim Sci Biotechnol 2017; 8:56. [PMID: 28680590 PMCID: PMC5493847 DOI: 10.1186/s40104-017-0189-x] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2016] [Accepted: 06/08/2017] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The objective of the present study was to estimate (co)variance components of female fertility traits in Chinese Holsteins, considering fertility traits in different parities as different traits. Data on 88,647 females with 215,632 records (parities) were collected during 2000 to 2014 from 32 herds in the Sanyuan Lvhe Dairy Cattle Center, Beijing, China. The analyzed female fertility traits included interval from calving to first insemination, interval from first to last insemination, days open, conception rate at first insemination, number of inseminations per conception and non-return rates within 56 days after first insemination. RESULTS The descriptive statistics showed that the average fertility of heifers was superior to that of cows. Moreover, the genetic correlations between the performances of a trait in heifers and in cows were all moderate to high but far from one, which suggested that the performances of a trait in heifers and cows should be considered as different but genetically correlated traits in genetic evaluations. On the other hand, genetic correlations between performances of a trait in different parities of cows were greater than 0.87, with only a few exceptions, but variances were not homogeneous across parities for some traits. The estimated heritabilities of female fertility traits were low; all were below 0.049 (except for interval from calving to first insemination). Additionally, the heritabilities of the heifer interval traits were lower than those of the corresponding cow interval traits. Moreover, the heritabilities of the interval traits were higher than those of the threshold traits when measuring similar fertility functions. In general, estimated genetic correlations between traits were highly consistent with the biological categories of the female fertility traits. CONCLUSIONS Interval from calving to first insemination, interval from first to last insemination and non-return rates within 56 days after first insemination are recommended to be included in the selection index of the Chinese Holstein population. The parameters estimated in the present study will facilitate the development of a genetic evaluation system for female fertility traits to improve the reproduction efficiency of Chinese Holsteins.
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Affiliation(s)
- Aoxing Liu
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193 China.,Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, 8830 Tjele, Denmark
| | - Mogens Sandø Lund
- Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, 8830 Tjele, Denmark
| | - Yachun Wang
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193 China
| | - Gang Guo
- Beijing Sunlon Livestock Development Co., Ltd, Beijing, 100176 China
| | - Ganghui Dong
- Beijing Sunlon Livestock Development Co., Ltd, Beijing, 100176 China
| | - Per Madsen
- Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, 8830 Tjele, Denmark
| | - Guosheng Su
- Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, 8830 Tjele, Denmark
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Study on reproductive performance of Holstein x Lai Sind crossbred dairy heifers and cows at smallholdings in Ho Chi Minh City, Vietnam. Trop Anim Health Prod 2017; 49:483-489. [DOI: 10.1007/s11250-016-1217-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2016] [Accepted: 12/27/2016] [Indexed: 11/26/2022]
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17
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Guo G, Hou Y, Zhang Y, Su G. Comparison of models for genetic evaluation of number of inseminations to conception in Danish Holstein cows. Anim Sci J 2016; 88:567-574. [DOI: 10.1111/asj.12406] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2013] [Accepted: 01/28/2015] [Indexed: 11/27/2022]
Affiliation(s)
- Gang Guo
- Beijing Sanyuan Breeding Technology Co., Ltd.; Beijing China
- National Center for Molecular Genetics and Breeding of Animal, Institute of Animal Sciences; Chinese academy of Agricultural Sciences; Beijing China
| | - Yali Hou
- Department of Molecular Biology and Genetics; Aarhus University; Tjele Denmark
- Laboratory of Disease Genomics and Individualized Medicine, Beijing Institute of Genomics; Chinese Academy of Sciences; Beijing China
| | - Yuan Zhang
- College of Animal Science and Technology; China Agricultural University; Beijing China
| | - Guosheng Su
- Department of Molecular Biology and Genetics; Aarhus University; Tjele Denmark
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Buaban S, Duangjinda M, Suzuki M, Masuda Y, Sanpote J, Kuchida K. Short communication: Genetic analysis for fertility traits of heifers and cows from smallholder dairy farms in a tropical environment. J Dairy Sci 2015; 98:4990-8. [DOI: 10.3168/jds.2014-8866] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2014] [Accepted: 03/27/2015] [Indexed: 11/19/2022]
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