1
|
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.
Collapse
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
| |
Collapse
|
2
|
Shao B, Sun H, Ahmad MJ, Ghanem N, Abdel-Shafy H, Du C, Deng T, Mansoor S, Zhou Y, Yang Y, Zhang S, Yang L, Hua G. Genetic Features of Reproductive Traits in Bovine and Buffalo: Lessons From Bovine to Buffalo. Front Genet 2021; 12:617128. [PMID: 33833774 PMCID: PMC8021858 DOI: 10.3389/fgene.2021.617128] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2020] [Accepted: 02/25/2021] [Indexed: 11/13/2022] Open
Abstract
Bovine and buffalo are important livestock species that have contributed to human lives for more than 1000 years. Improving fertility is very important to reduce the cost of production. In the current review, we classified reproductive traits into three categories: ovulation, breeding, and calving related traits. We systematically summarized the heritability estimates, molecular markers, and genomic selection (GS) for reproductive traits of bovine and buffalo. This review aimed to compile the heritability and genome-wide association studies (GWASs) related to reproductive traits in both bovine and buffalos and tried to highlight the possible disciplines which should benefit buffalo breeding. The estimates of heritability of reproductive traits ranged were from 0 to 0.57 and there were wide differences between the populations. For some specific traits, such as age of puberty (AOP) and calving difficulty (CD), the majority beef population presents relatively higher heritability than dairy cattle. Compared to bovine, genetic studies for buffalo reproductive traits are limited for age at first calving and calving interval traits. Several quantitative trait loci (QTLs), candidate genes, and SNPs associated with bovine reproductive traits were screened and identified by candidate gene methods and/or GWASs. The IGF1 and LEP pathways in addition to non-coding RNAs are highlighted due to their crucial relevance with reproductive traits. The distribution of QTLs related to various traits showed a great differences. Few GWAS have been performed so far on buffalo age at first calving, calving interval, and days open traits. In addition, we summarized the GS studies on bovine and buffalo reproductive traits and compared the accuracy between different reports. Taken together, GWAS and candidate gene approaches can help to understand the molecular genetic mechanisms of complex traits. Recently, GS has been used extensively and can be performed on multiple traits to improve the accuracy of prediction even for traits with low heritability, and can be combined with multi-omics for further analysis.
Collapse
Affiliation(s)
- Baoshun Shao
- Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, China
| | - Hui Sun
- Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, China
| | - Muhammad Jamil Ahmad
- Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, China
| | - Nasser Ghanem
- Department of Animal Production, Faculty of Agriculture, Cairo University, Giza, Egypt
| | - Hamdy Abdel-Shafy
- Department of Animal Production, Faculty of Agriculture, Cairo University, Giza, Egypt
| | - Chao Du
- Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, China
| | - Tingxian Deng
- Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, China
- Guangxi Provincial Key Laboratory of Buffalo Genetics, Breeding and Reproduction Technology, Buffalo Research Institute, Chinese Academy of Agricultural Sciences, Nanning, China
| | - Shahid Mansoor
- National Institute for Biotechnology and Genetic Engineering (NIBGE), Faisalabad, Pakistan
| | - Yang Zhou
- Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, China
- International Joint Research Centre for Animal Genetics, Breeding and Reproduction, Wuhan, China
- Hubei Province’s Engineering Research Center in Buffalo Breeding and Products, Wuhan, China
| | - Yifen Yang
- Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, China
- Department of Animal Production, Faculty of Agriculture, Cairo University, Giza, Egypt
| | - Shujun Zhang
- Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, China
- International Joint Research Centre for Animal Genetics, Breeding and Reproduction, Wuhan, China
- Hubei Province’s Engineering Research Center in Buffalo Breeding and Products, Wuhan, China
| | - Liguo Yang
- Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, China
- International Joint Research Centre for Animal Genetics, Breeding and Reproduction, Wuhan, China
- Hubei Province’s Engineering Research Center in Buffalo Breeding and Products, Wuhan, China
| | - Guohua Hua
- Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, China
- International Joint Research Centre for Animal Genetics, Breeding and Reproduction, Wuhan, China
- Hubei Province’s Engineering Research Center in Buffalo Breeding and Products, Wuhan, China
| |
Collapse
|
3
|
Brito LF, Oliveira HR, McConn BR, Schinckel AP, Arrazola A, Marchant-Forde JN, Johnson JS. Large-Scale Phenotyping of Livestock Welfare in Commercial Production Systems: A New Frontier in Animal Breeding. Front Genet 2020; 11:793. [PMID: 32849798 PMCID: PMC7411239 DOI: 10.3389/fgene.2020.00793] [Citation(s) in RCA: 47] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Accepted: 07/03/2020] [Indexed: 12/13/2022] Open
Abstract
Genomic breeding programs have been paramount in improving the rates of genetic progress of productive efficiency traits in livestock. Such improvement has been accompanied by the intensification of production systems, use of a wider range of precision technologies in routine management practices, and high-throughput phenotyping. Simultaneously, a greater public awareness of animal welfare has influenced livestock producers to place more emphasis on welfare relative to production traits. Therefore, management practices and breeding technologies in livestock have been developed in recent years to enhance animal welfare. In particular, genomic selection can be used to improve livestock social behavior, resilience to disease and other stress factors, and ease habituation to production system changes. The main requirements for including novel behavioral and welfare traits in genomic breeding schemes are: (1) to identify traits that represent the biological mechanisms of the industry breeding goals; (2) the availability of individual phenotypic records measured on a large number of animals (ideally with genomic information); (3) the derived traits are heritable, biologically meaningful, repeatable, and (ideally) not highly correlated with other traits already included in the selection indexes; and (4) genomic information is available for a large number of individuals (or genetically close individuals) with phenotypic records. In this review, we (1) describe a potential route for development of novel welfare indicator traits (using ideal phenotypes) for both genetic and genomic selection schemes; (2) summarize key indicator variables of livestock behavior and welfare, including a detailed assessment of thermal stress in livestock; (3) describe the primary statistical and bioinformatic methods available for large-scale data analyses of animal welfare; and (4) identify major advancements, challenges, and opportunities to generate high-throughput and large-scale datasets to enable genetic and genomic selection for improved welfare in livestock. A wide variety of novel welfare indicator traits can be derived from information captured by modern technology such as sensors, automatic feeding systems, milking robots, activity monitors, video cameras, and indirect biomarkers at the cellular and physiological levels. The development of novel traits coupled with genomic selection schemes for improved welfare in livestock can be feasible and optimized based on recently developed (or developing) technologies. Efficient implementation of genetic and genomic selection for improved animal welfare also requires the integration of a multitude of scientific fields such as cell and molecular biology, neuroscience, immunology, stress physiology, computer science, engineering, quantitative genomics, and bioinformatics.
Collapse
Affiliation(s)
- Luiz F. Brito
- Department of Animal Sciences, Purdue University, West Lafayette, IN, United States
| | - Hinayah R. Oliveira
- Department of Animal Sciences, Purdue University, West Lafayette, IN, United States
- Department of Animal Biosciences, University of Guelph, Guelph, ON, Canada
| | - Betty R. McConn
- Oak Ridge Institute for Science and Education, Oak Ridge, TN, United States
| | - Allan P. Schinckel
- Department of Animal Sciences, Purdue University, West Lafayette, IN, United States
| | - Aitor Arrazola
- Department of Comparative Pathobiology, Purdue University, West Lafayette, IN, United States
| | | | - Jay S. Johnson
- USDA-ARS Livestock Behavior Research Unit, West Lafayette, IN, United States
| |
Collapse
|
4
|
Grayaa M, Vanderick S, Rekik B, Ben Gara A, Hanzen C, Grayaa S, Reis Mota R, Hammami H, Gengler N. Linking first lactation survival to milk yield and components and lactation persistency in Tunisian Holstein cows. Arch Anim Breed 2019; 62:153-160. [PMID: 31807625 PMCID: PMC6853000 DOI: 10.5194/aab-62-153-2019] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2018] [Accepted: 03/01/2019] [Indexed: 11/22/2022] Open
Abstract
Genetic parameters were estimated for first lactation
survival defined as a binary trait (alive or dead to second calving) and the curve
shape traits of milk yield, fat and protein percentages using information
from 25 981 primiparous Tunisian Holsteins. For each trait, shape curves
(i.e. peak lactation, persistency), level of production adjusted to 305 days in
milk (DIMs) for total milk yield (TMY), and average fat (TF %) and protein (TP %)
percentages were defined. Variance components were estimated with a
linear random regression model under three bivariate animal models.
Production traits were modelled by fixed herd × test-day (TD)
interaction effects, fixed classes of 25 DIMs × age of
calving × season of calving interaction effects, fixed classes of
pregnancy, random environment effects and random additive genetic effects.
Survival was modelled by fixed herd × year of calving interaction
effects and age of calving × season of calving interaction effects,
random permanent environment effects, and random additive genetic effects.
Heritability (h2) estimates were 0.03 (±0.01) for survival and
0.23 (±0.01), 0.31 (±0.01) and 0.31 (±0.01) for TMY,
TF % and TP %, respectively. Genetic correlations between survival and
TMY, TF % and TP % were 0.26 (±0.08), -0.24 (±0.06) and
-0.13 (±0.06), respectively. Genetic correlations between survival
and persistency for fat and protein percentages were -0.35 (±0.09)
and -0.19 (±0.09), respectively. Cows that had higher persistencies
for fat and protein percentages were more likely not to survive.
Collapse
Affiliation(s)
- Marwa Grayaa
- Institut National Agronomique de Tunisie, Tunis, 1082, Tunisia.,TERRA Teaching and Research Centre, Gembloux Agro-Bio Tech, University of Liège, Gembloux, 5030, Belgium
| | - Sylvie Vanderick
- TERRA Teaching and Research Centre, Gembloux Agro-Bio Tech, University of Liège, Gembloux, 5030, Belgium
| | - Boulbaba Rekik
- Département des Productions Animales, Ecole supérieure d'Agriculture de Mateur, Mateur, 7030, Tunisia
| | - Abderrahman Ben Gara
- Département des Productions Animales, Ecole supérieure d'Agriculture de Mateur, Mateur, 7030, Tunisia
| | - Christian Hanzen
- Clinical Department of Production Animals, Faculty of Veterinary Medicine, University of Liège, Liège, 4000, Belgium
| | - Siwar Grayaa
- Institut National Agronomique de Tunisie, Tunis, 1082, Tunisia
| | - Rodrigo Reis Mota
- TERRA Teaching and Research Centre, Gembloux Agro-Bio Tech, University of Liège, Gembloux, 5030, Belgium
| | - Hedi Hammami
- TERRA Teaching and Research Centre, Gembloux Agro-Bio Tech, University of Liège, Gembloux, 5030, Belgium
| | - Nicolas Gengler
- TERRA Teaching and Research Centre, Gembloux Agro-Bio Tech, University of Liège, Gembloux, 5030, Belgium
| |
Collapse
|
5
|
Ling A, Hay EH, Aggrey SE, Rekaya R. A Bayesian approach for analysis of ordered categorical responses subject to misclassification. PLoS One 2018; 13:e0208433. [PMID: 30543662 PMCID: PMC6292639 DOI: 10.1371/journal.pone.0208433] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2018] [Accepted: 11/10/2018] [Indexed: 11/18/2022] Open
Abstract
Ordinal categorical responses are frequently collected in survey studies, human medicine, and animal and plant improvement programs, just to mention a few. Errors in this type of data are neither rare nor easy to detect. These errors tend to bias the inference, reduce the statistical power and ultimately the efficiency of the decision-making process. Contrarily to the binary situation where misclassification occurs between two response classes, noise in ordinal categorical data is more complex due to the increased number of categories, diversity and asymmetry of errors. Although several approaches have been presented for dealing with misclassification in binary data, only limited practical methods have been proposed to analyze noisy categorical responses. A latent variable model implemented within a Bayesian framework was proposed to analyze ordinal categorical data subject to misclassification using simulated and real datasets. The simulated scenario consisted of a discrete response with three categories and a symmetric error rate of 5% between any two classes. The real data consisted of calving ease records of beef cows. Using real and simulated data, ignoring misclassification resulted in substantial bias in the estimation of genetic parameters and reduction of the accuracy of predicted breeding values. Using our proposed approach, a significant reduction in bias and increase in accuracy ranging from 11% to 17% was observed. Furthermore, most of the misclassified observations (in the simulated data) were identified with a substantially higher probability. Similar results were observed for a scenario with asymmetric misclassification. While the extension to traits with more categories between adjacent classes is straightforward, it could be computationally costly. For traits with high heritability, the performance of the methodology would be expected to improve.
Collapse
Affiliation(s)
- Ashley Ling
- Department of Anismal and Dairy Science, University of Georgia, Athens, Georgia, United States of America
- * E-mail:
| | - El Hamidi Hay
- USDA Agricultural Research Service, Fort Keogh Livestock and Range Research Laboratory, Miles City, Montana, United States of America
| | - Samuel E. Aggrey
- Institute of Bioinformatics, University of Georgia, Athens, Georgia, United States of America
- Department of Poultry Science, University of Georgia, Athens, Georgia, United States of America
| | - Romdhane Rekaya
- Department of Anismal and Dairy Science, University of Georgia, Athens, Georgia, United States of America
- Institute of Bioinformatics, University of Georgia, Athens, Georgia, United States of America
- Department of Statistics, University of Georgia, Athens, Georgia, United States of America
| |
Collapse
|
6
|
Silvestre A, Martins Â, Santos V, Colaço J. Genetic parameters of calving ease in dairy cattle using threshold and linear models. ITALIAN JOURNAL OF ANIMAL SCIENCE 2018. [DOI: 10.1080/1828051x.2018.1482801] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
Affiliation(s)
- António Silvestre
- Animal Science Department, School of Agrarian and Veterinary Sciences, University of Trás-os-Montes and Alto Douro, 5000-801 Vila Real, Portugal
| | - Ângela Martins
- CECAV, Animal and Veterinary research Centre, University of Trás-os-Montes and Alto Douro, 5000-801 Vila Real, Portugal
| | - Virgínia Santos
- CECAV, Animal and Veterinary research Centre, University of Trás-os-Montes and Alto Douro, 5000-801 Vila Real, Portugal
| | - Jorge Colaço
- CECAV, Animal and Veterinary research Centre, University of Trás-os-Montes and Alto Douro, 5000-801 Vila Real, Portugal
| |
Collapse
|
7
|
Hossein-Zadeh NG, Salimi MH, Shadparvar AA. Bayesian estimates of genetic relationship between calving difficulty and productive and reproductive performance in Holstein cows. ANIMAL PRODUCTION SCIENCE 2018. [DOI: 10.1071/an16186] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
The objective of present study was to estimate genetic correlations between calving difficulty and productive and reproductive traits in Iranian Holsteins. Calving records from the Animal Breeding Center of Iran, collected from 1991 to 2011 and comprising 183 203 first-calving events of Holstein cows from 1470 herds were included in the dataset. Threshold animal models included direct genetic effect (Model 1) or direct and maternal genetic effects with covariance between them (Model 2) were fitted for the genetic analysis of calving difficulty. Also, linear animal models including direct genetic effect were fitted for the genetic analysis of productive and reproductive performance traits. A set of linear-threshold bivariate models was used for obtaining genetic correlation between calving difficulty and other traits. All analyses were implemented by Bayesian approach via Gibbs sampling methodology. A single Gibbs sampling chain with 300 000 rounds was generated by the TM program. Posterior mean estimates of direct heritabilities for calving difficulty were 0.056 and 0.066, obtained from different models. Also, posterior mean estimate of maternal heritability for this trait was 0.018. Estimate of correlation between direct and maternal genetic effects for calving difficulty was negative (–0.44). Posterior mean estimates of direct heritabilities for milk yield, fat yield, protein yield, days from calving to first service, days open and first calving interval were 0.257, 0.188, 0.235, 0.034, 0.042 and 0.050 respectively. The posterior means of direct genetic correlation between calving difficulty and milk yield, fat yield, protein yield, days from calving to first service, days open and first calving interval were low and equal to –0.135, 0.030, –0.067, –0.010, –0.075 and –0.074 respectively. The results of the current study indicated that exploitable genetic variation in calving difficulty, productive and reproductive traits could be applied in designing future genetic selection plans for Iranian Holsteins.
Collapse
|
8
|
Mota RR, Mayeres P, Bastin C, Glorieux G, Bertozzi C, Vanderick S, Hammami H, Colinet FG, Gengler N. Genetic evaluation for birth and conformation traits in dual-purpose Belgian Blue cattle using a mixed inheritance model. J Anim Sci 2017; 95:4288-4299. [PMID: 29108034 DOI: 10.2527/jas2017.1748] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
The segregation of the causal mutation () in the muscular hypertrophy gene in dual-purpose Belgian Blue (dpBB) cattle is considered to result in greater calving difficulty (dystocia). Establishing adapted genetic evaluations might overcome this situation through efficient selection. However, the heterogeneity of dpBB populations at the locus implies separating the major gene and other polygenic effects in complex modeling. The use of mixed inheritance models may be an interesting option because they simultaneously assume both influences. A genetic evaluation in dpBB based on a mixed inheritance model was developed for birth and conformation traits: gestation length (GL), calving difficulty (CD), birth weight (BiW), and body conformation score (BC). A total of 27,362 animals having records were used for analyses. The total number of animals in the pedigree used to build the numerator relationship matrix was 62,617. Genotypes at the locus were available for 2,671 animals. Missing records at this locus were replaced with genotype probabilities. A total of 13,221 (48.3%) were registered as dpBB, 1,287 (4.7%) as beef Belgian Blue, and 12,854 (47.0%) were unknown. From those 13,221 dpBB animals, 650, 849, and 534 had double or single copies or no copy, respectively, of the causal mutation () in the muscular hypertrophy gene, whereas 11,188 had missing genotypes. This heterogeneity at the locus may be the reason for high variability in the studied traits, that is, high heritability estimates of 0.33, 0.30, 0.38, and 0.43 for GL, CD, BiW, and BC, respectively. In general, additive ( < 0.05) and dominance ( < 0.001) allele substitution for calves and dams had significant impact for all traits. The moderate coefficient of genetic variation (27.80%) and high direct heritability (0.28) for CD suggested genetic variability in dpBB and possible genetic improvement through selection. This variability has allowed dpBB breeders to successfully apply mass selection in the past. Genetic trend means from 1988 to 2016 showed that sire selection for CD within genotype was progressively applied by breeders. The selection intensity was more important for CD in double-muscled lines than in segregated lines. Our study illustrated the possible confusion caused by the use of major genes in selection and the importance of fitting appropriate models such as mixed inheritance models that combine polygenic and gene content information.
Collapse
|
9
|
Vanderick S, Gillon A, Glorieux G, Mayeres P, Mota R, Gengler N. Usefulness of multi-breed models in genetic evaluation of direct and maternal calving ease in Holstein and Belgian Blue Walloon purebreds and crossbreds. Livest Sci 2017. [DOI: 10.1016/j.livsci.2017.02.019] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
|
10
|
Mokhtari M, Moradi Shahrbabak M, Nejati Javaremi A, Rosa G. Relationship between calving difficulty and fertility traits in first-parity Iranian Holsteins under standard and recursive models. J Anim Breed Genet 2016; 133:513-522. [DOI: 10.1111/jbg.12212] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2015] [Accepted: 02/19/2016] [Indexed: 11/29/2022]
Affiliation(s)
- M.S. Mokhtari
- Department of Animal Science; University College of Agriculture and Natural Resources; University of Tehran; Karaj Iran
| | - M. Moradi Shahrbabak
- Department of Animal Science; University College of Agriculture and Natural Resources; University of Tehran; Karaj Iran
| | - A. Nejati Javaremi
- Department of Animal Science; University College of Agriculture and Natural Resources; University of Tehran; Karaj Iran
| | - G.J.M. Rosa
- Department of Animal Sciences; University of Wisconsin - Madison; Madison WI USA
| |
Collapse
|
11
|
Le TH, Madsen P, Lundeheim N, Nilsson K, Norberg E. Genetic association between leg conformation in young pigs and sow longevity. J Anim Breed Genet 2015; 133:283-90. [PMID: 26578175 DOI: 10.1111/jbg.12193] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2015] [Accepted: 10/06/2015] [Indexed: 12/01/2022]
Abstract
Longevity is important in pig production with respect to both economic and ethical aspects. Direct selection for longevity might be ineffective because 'true' longevity can only be recorded when a sow has been culled or died. Thus, indirect selection for longevity using information from other traits that can be recorded early in life and are genetically correlated with longevity might be an alternative. Leg conformation has been included in many breeding schemes for a number of years. However, proving that leg conformation traits are good early indicators for longevity still remains. Our aim was to study genetic associations between leg conformation traits of young (5 months; 100 kg) Swedish Yorkshire pigs in nucleus herds and longevity traits of sows in nucleus and multiplier herds. Data included 97 533 animals with information on conformation (Movement and Overall score) recorded at performance testing and 26 962 sows with information on longevity. The longevity traits were as follows: stayability from 1st to 2nd parity, lifetime number of litters and lifetime number of born alive piglets. Genetic analyses were performed with both linear models using REML and linear-threshold models using Bayesian methods. Heritabilities estimated using the Bayesian method were higher than those estimated using REML, ranging from 0.10 to 0.24 and 0.07 to 0.20, respectively. All estimated genetic correlations between conformation and longevity traits were significant and favourable. Heritabilities and genetic correlations between conformation and longevity indicate that selection on leg conformation should improve sow longevity.
Collapse
Affiliation(s)
- T H Le
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden.,Department of Molecular Biology and Genetics, Aarhus University, Tjele, Denmark
| | - P Madsen
- Department of Molecular Biology and Genetics, Aarhus University, Tjele, Denmark
| | - N Lundeheim
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - K Nilsson
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - E Norberg
- Department of Molecular Biology and Genetics, Aarhus University, Tjele, Denmark
| |
Collapse
|
12
|
Pérez-Cabal M, Charfeddine N. Models for genetic evaluations of claw health traits in Spanish dairy cattle. J Dairy Sci 2015; 98:8186-94. [DOI: 10.3168/jds.2015-9562] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2015] [Accepted: 07/21/2015] [Indexed: 11/19/2022]
|