| 1. |
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| 2. |
- Berglund, Britt, et al.
(author)
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Ny hedersdoktor vid SLU
- 2017
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In: Husdjur. - 0046-8339. ; , s. 30-30
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Journal article (pop. science, debate, etc.)
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| 3. |
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| 4. |
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| 5. |
- Forabosco, Flavio, et al.
(author)
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Evaluation of genetic variation in the international Brown Swiss population
- 2013
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In: Animal. - 1751-7311 .- 1751-732X. ; 7, s. 1060-1066
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Journal article (peer-reviewed)abstract
- The international Brown Swiss cattle population pedigree was studied to measure genetic variations and to identify the most influential animals. Twenty-two countries provided pedigree information on 71 497 Brown Swiss bulls used for artificial insemination (AI). The total number of animals with the pedigree is 181 094. The mean inbreeding coefficient for the pedigree population was 0.77%. There was, in most cases, an increase in the mean inbreeding coefficient, with the highest value at 2.89% during the last 5-year period (2000 to 2004). The mean average relatedness for the pedigree population was 1.1%. The effective population size in 2004 was 204. There was notable variation between average generation intervals for the four parental pathways. The longest average generation interval, at 8.73 years, was observed in the sire son pathway. The average generation interval for the whole population was 6.53 years. Most genetically influential individuals were sires. The highest contributing founder was a sire with a 3.22% contribution, and the highest contributing founder dam made a contribution of 1.75%. The effective number of founders and the effective number of ancestors were 141 and 88, respectively. The study showed that genetic variation within the pedigree population has been decreasing over recent years. Increasing the number of AI bulls with a low individual coefficient of inbreeding could help to maintain a good level of genetic variation in the Brown Swiss population.
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| 6. |
- Guo, Jiazhong, et al.
(author)
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A genome-wide association study using international breeding-evaluation data identifies major loci affecting production traits and stature in the Brown Swiss cattle breed.
- 2012
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In: BMC Genetics. - : Springer Science and Business Media LLC. - 1471-2156. ; 13
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Journal article (peer-reviewed)abstract
- BACKGROUND: The genome-wide association study (GWAS) is a useful approach to identify genes affecting economically important traits in dairy cattle. Here, we report the results from a GWAS based on high-density SNP genotype data and estimated breeding values for nine production, fertility, body conformation, udder health and workability traits in the Brown Swiss cattle population that is part of the international genomic evaluation program.RESULT: GWASs were performed using 50 k SNP chip data and deregressed estimated breeding values (DEBVs) for nine traits from between 2061 and 5043 bulls that were part of the international genomic evaluation program coordinated by Interbull Center. The nine traits were milk yield (MY), fat yield (FY), protein yield (PY), lactating cow's ability to recycle after calving (CRC), angularity (ANG), body depth (BDE), stature (STA), milk somatic cell score (SCS) and milk speed (MSP). Analyses were performed using a linear mixed model correcting for population confounding. A total of 74 SNPs were detected to be genome-wide significantly associated with one or several of the nine analyzed traits. The strongest signal was identified on chromosome 25 for milk production traits, stature and body depth. Other signals were on chromosome 11 for angularity, chromosome 24 for somatic cell score, and chromosome 6 for milking speed. Some signals overlapped with earlier reported QTL for similar traits in other cattle populations and were located close to interesting candidate genes worthy of further investigations.CONCLUSIONS: Our study shows that international genetic evaluation data is a useful resource for identifying genetic factors influencing complex traits in livestock. Several genome wide significant association signals could be identified in the Brown Swiss population, including a major signal on BTA25. Our findings report several associations and plausible candidate genes that deserve further exploration in other populations and molecular dissection to explore the potential economic impact and the genetic mechanisms underlying these production traits in cattle.
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| 7. |
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| 8. |
- Jorjani, Hossein
(author)
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A general genomics simulation program
- 2009
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In: Bulletin / International Bull Evaluation Service. - 1011-6079. ; 40, s. 202-206
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Conference paper (other academic/artistic)
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| 9. |
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| 10. |
- Jorjani, Hossein
(author)
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Effects of national genomic preselection on the international genetic evaluations
- 2013
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In: Journal of Dairy Science. - : American Dairy Science Association. - 0022-0302 .- 1525-3198. ; 96, s. 3272-3284
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Journal article (peer-reviewed)abstract
- Genomic preselection of young bulls is now widely implemented in dairy breeding schemes, especially in the Holstein breed. However, if this step is not accounted for in genetic evaluation models, the national breeding values of bulls retained by a genomic preselection and of their progeny are estimated with bias. It follows that countries participating in international genetic evaluations will provide a selected and possibly biased set of data to the Interbull Centre (Swedish University of Agricultural Sciences, Uppsala, Sweden). The objective of the study was to show evidence of bias at the international level due to a genomic preselection step in national breeding schemes. The consequence of a genomic preselection for the international evaluations (i.e., using selected and biased national estimated breeding values) was simulated using actual national estimated breeding values as a proxy for genomically enhanced breeding values. Data were provided for 3 countries with a large population of Holstein bulls. International breeding values from simulated scenarios were compared with international breeding values using all available data, assumed to be complete and unbiased. Bias was measured among young bulls retained by a genomic preselection and their contemporaries in other countries. The results were analyzed by traits measured within each country and by country of origin of the young bulls. It turned out that sending preselected data, though based on genomic information, created bias in international evaluations, penalizing young bulls from the country sending the incorrect data. It also had an effect on the young bulls from the other countries. Sending biased data further affected the quality of international evaluations. This study underlines the importance of accounting for genomic preselection at the national level first. Moreover, submitting all available data appeared essential to maintain the quality of the international genetic evaluations after implementation of a genomic preselection step.
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| 11. |
- Jorjani, Hossein, et al.
(author)
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Genetic correlations between similar traits in the Danish and Swedish Warmblood sport horse populations
- 2009
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In: Livestock Science. - : Elsevier BV. - 1871-1413 .- 1878-0490. ; 124, s. 15-20
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Journal article (peer-reviewed)abstract
- Genetic correlations between phenotypically similar or related traits tested at young horse performance tests for Danish Warmblood (DWB) and Swedish Warmblood (SWB) horses were calculated using Multi-trait Across Country Evaluation (MACE). Data comprised stallions with an estimated breeding value (EBV) from the national genetic evaluations (NGE) based on at least 10 progeny tested in performance tests, and the ancestors of those stallions in two generations. The DWB data included 349 stallions and the SWB data 426 stallions. Of these, 28 had EBVs in both DWB and SWB. Additionally 151 pedigree animals were common between DWB and SWB. The dependent variables used were NGE results of stallions born 1980 and later, which reduced the number of common stallions with EBVs to 23. The genetic correlations were very high for jumping traits (0.99) and dressage related traits (0.89-0.97). For conformation traits correlations varied between 0.10 and 0.98. Because of the high genetic correlations and frequent use of same or closely related foreign stallions, breeders of both DWB and SWB would benefit from using the NGEs for performance traits across countries, although the genetic correlations do not consider differences in genetic merit levels between the populations. It would be feasible to perform a joint genetic evaluation using MACE, which would improve the reliability of estimated breeding values, and enable ranking of all stallions according to the national scale of each country. (C) 2008 Elsevier B.V. All rights reserved.
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| 12. |
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| 13. |
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| 14. |
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| 15. |
- Jorjani, Hossein
(author)
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Invited review: A quarter of a century-International genetic evaluation of dairy sires using MACE methodology
- 2022
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In: Journal of Dairy Science. - : American Dairy Science Association. - 0022-0302 .- 1525-3198. ; 105, s. 3-21
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Research review (peer-reviewed)abstract
- For the past few decades, the international exchange of genetic materials has accelerated. This acceleration has been more substantial for dairy cattle compared with other species. The industry faced the need to put international genetic evaluation (IGE) systems in place. The Interbull Centre has been conducting IGE for various dairy cattle breeds and traits. This study reviews the past and the current status of IGE for dairy cattle, emphasizing the most prominent and well established method of IGE, namely multiple across country evaluation (MACE), and the challenges that should be addressed in the future of IGE. The first IGE methods were simple conversion equations. Only a limited number of common bulls between pairs of countries were considered. These bulls were a biased sample of highly selected animals, with their daughters under preferential treatment in the importing countries. Genetic relationships among animals were not considered either. The MACE method was the first IGE method based on mixed-model theory that could handle genotype by environment interaction (G x E) between countries. The G x E between countries is handled by treating the same trait in different countries as different traits, with genetic correlations less than unity between the traits. The G x E between countries is not solely due to different genetic expressions in different environments (countries), but is also attributable to different units or ways of measuring the trait, data editing, and statistical approaches and models used in different countries. The MACE method also considers different genetic means, genetic groups for unknown parents, heterogeneous genetic and residual variances among countries, and heterogeneous residual variances (precision weights for observations) within countries. Other IGE methods that came after MACE are rooted in MACE. The genomic revolution of the industry created new needs and opportunities. However, an unwanted aspect of it was genomic preselection bias. Genomic preselection causes directional information loss from pre-culled animals (bias) in statistical models for genetic and genomic evaluations, and preselected progeny of a mating are no longer a random sample of possible progeny from that mating. National genetic evaluations without genotypes are input to MACE, and biases in national evaluations are propagated interna-tionally through MACE. Genomic preselection for the Holstein breed is a source of concern for introducing bias to MACE, especially when genomic preselection is practiced intensively in the population. However, MACE continues to be useful for other breeds, among other species, or for non-IGE purposes. Future methods will need to make optimum use of genomic information and be free of genomic preselection bias
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| 16. |
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| 17. |
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| 18. |
- Jorjani, Hossein
(author)
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Multiple-breed genomic evaluation by principal component analysis in small size populations
- 2015
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In: Animal. - 1751-7311 .- 1751-732X. ; 9, s. 738-749
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Journal article (peer-reviewed)abstract
- In this study, the effects of breed composition and predictor dimensionality on the accuracy of direct genomic values (DGV) in a multiple breed (MB) cattle population were investigated. A total of 3559 bulls of three breeds were genotyped at 54 001 single nucleotide polymorphisms: 2093 Holstein (H), 749 Brown Swiss (B) and 717 Simmental (S). DGV were calculated using a principal component (PC) approach for either single (SB) or MB scenarios. Moreover, DGV were computed using all SNP genotypes simultaneously with SNPBLUP model as comparison. A total of seven data sets were used: three with a SB each, three with different pairs of breeds (HB, HS and BS), and one with all the three breeds together (HBS), respectively. Editing was performed separately for each scenario. Reference populations differed in breed composition, whereas the validation bulls were the same for all scenarios. The number of SNPs retained after data editing ranged from 36 521 to 41 360. PCs were extracted from actual genotypes. The total number of retained PCs ranged from 4029 to 7284 in Brown Swiss and HBS respectively, reducing the number of predictors by about 85% (from 82% to 89%). In all, three traits were considered: milk, fat and protein yield. Correlations between deregressed proofs and DGV were used to assess prediction accuracy in validation animals. In the SB scenarios, average DGV accuracy did not substantially change when either SNPBLUP or PC were used. Improvement of DGV accuracy were observed for some traits in Brown Swiss, only when MB reference populations and PC approach were used instead of SB-SNPBLUP (+10% HBS, +16%HB for milk yield and +3% HBS and +7% HB for protein yield, respectively). With the exclusion of the abovementioned cases, similar accuracies were observed using MB reference population, under the PC or SNPBLUP models. Random variation owing to sampling effect or size and composition of the reference population may explain the difficulty in finding a defined pattern in the results.
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| 19. |
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| 20. |
- Jorjani, Hossein
(author)
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SNPchiMp v.3: integrating and standardizing single nucleotide polymorphism data for livestock species
- 2015
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In: BMC Genomics. - : Springer Science and Business Media LLC. - 1471-2164. ; 16
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Journal article (peer-reviewed)abstract
- Background: In recent years, the use of genomic information in livestock species for genetic improvement, association studies and many other fields has become routine. In order to accommodate different market requirements in terms of genotyping cost, manufacturers of single nucleotide polymorphism (SNP) arrays, private companies and international consortia have developed a large number of arrays with different content and different SNP density. The number of currently available SNP arrays differs among species: ranging from one for goats to more than ten for cattle, and the number of arrays available is increasing rapidly. However, there is limited or no effort to standardize and integrate array- specific (e.g. SNP IDs, allele coding) and species-specific (i.e. past and current assemblies) SNP information. Results: Here we present SNPchiMp v.3, a solution to these issues for the six major livestock species (cow, pig, horse, sheep, goat and chicken). Original data was collected directly from SNP array producers and specific international genome consortia, and stored in a MySQL database. The database was then linked to an open-access web tool and to public databases. SNPchiMp v.3 ensures fast access to the database (retrieving within/across SNP array data) and the possibility of annotating SNP array data in a user-friendly fashion. Conclusions: This platform allows easy integration and standardization, and it is aimed at both industry and research. It also enables users to easily link the information available from the array producer with data in public databases, without the need of additional bioinformatics tools or pipelines. In recognition of the open-access use of Ensembl resources, SNPchiMp v.3 was officially credited as an Ensembl E!mpowered tool. Availability at http://bioinformatics.tecnoparco.org/ SNPchimp.
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| 21. |
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| 22. |
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| 23. |
- Loberg, Anne, et al.
(author)
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Estimates of genetic variance and variance of predicted genetic merits using pedigree or genomic relationship matrices in six Brown Swiss cattle populations for different traits
- 2015
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In: Journal of Animal Breeding and Genetics. - : Wiley. - 0931-2668 .- 1439-0388. ; 132, s. 376-385
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Journal article (peer-reviewed)abstract
- The amount of variance captured in genetic estimations may depend on whether a pedigree-based or genomic relationship matrix is used. The purpose of this study was to investigate the genetic variance as well as the variance of predicted genetic merits (PGM) using pedigree-based or genomic relationship matrices in Brown Swiss cattle. We examined a range of traits in six populations amounting to 173 population-trait combinations. A main aim was to determine how using different relationship matrices affect variance estimation. We calculated ratios between different types of estimates and analysed the impact of trait heritability and population size. The genetic variances estimated by REML using a genomic relationship matrix were always smaller than the variances that were similarly estimated using a pedigree-based relationship matrix. The variances from the genomic relationship matrix became closer to estimates from a pedigree relationship matrix as heritability and population size increased. In contrast, variances of predicted genetic merits obtained using a genomic relationship matrix were mostly larger than variances of genetic merit predicted using pedigree-based relationship matrix. The ratio of the genomic to pedigree-based PGM variances decreased as heritability and population size rose. The increased variance among predicted genetic merits is important for animal breeding because this is one of the factors influencing genetic progress.
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| 24. |
- Loberg, Anne, et al.
(author)
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Genomic conversion equations
- 2009
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In: Bulletin / International Bull Evaluation Service. - 1011-6079. ; 40, s. 151-154
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Conference paper (other academic/artistic)
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| 25. |
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| 26. |
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| 27. |
- Nilforooshan, Mohammad A., et al.
(author)
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Application of a multiple-trait, multiple-country genetic evaluation model for female fertility traits
- 2010
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In: Journal of Dairy Science. - : American Dairy Science Association. - 0022-0302 .- 1525-3198. ; 93, s. 5977-5986
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Journal article (peer-reviewed)abstract
- The need to implement a method that can handle multiple traits per country in international genetic evaluations is evident. Today, many countries have implemented multiple-trait national genetic evaluations and they may expect to have their traits simultaneously analyzed in international genetic evaluations. Traits from the same country are residually correlated and the method currently in use, single-trait multiple across-country evaluation (ST-MACE), cannot handle nonzero residual correlations. Therefore, multiple-trait, multiple across-country evaluation (MT-MACE) was proposed to handle several traits from the same country simultaneously. To test the robustness of MT-MACE on real data, female fertility was chosen as a complex trait with low heritability. Data from 7 Holstein populations, 3 with 2 traits and 4 with 1 trait, were used. The differences in the estimated genetic correlations by MT-MACE and the single ST-MACE analysis (average absolute deviation of 0.064) were due to the bias of considering several traits from the same country in the ST-MACE analysis. However, the differences between the estimated genetic correlations by MT-MACE and multiple ST-MACE analyses avoiding more than one trait per country in each analysis (average absolute deviation of 0.066) were due to the lack of analysis of the correlated traits from the same country together and using the reported within-country genetic correlations. Applying MT-MACE resulted in reliability gain in international genetic evaluations, which was different from trait to trait and from bull to bull. The average reliability gain by MT-MACE over ST-MACE was 3.0 points for domestic bulls and 6.3 points for foreign bulls. Even countries with 1 trait benefited from the joint analysis of traits from the 2-trait countries. Another superiority of MT-MACE over ST-MACE is that the bulls that do not have national genetic evaluation for some traits from multiple trait countries will receive international genetic evaluations for those traits. Rank correlations were high between ST-MACE and MT-MACE when considering all bulls. However, the situation was different for the top 100 bulls. Simultaneous analysis of traits from the same country affected bull ranks, especially for top 100 bulls. Multi-trait MACE is a recommendable and robust method for international genetic evaluations and is appropriate for handling multiple traits per country, which can increase the reliability of international genetic evaluations.
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| 28. |
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| 29. |
- Nilforooshan, Mohammad A., et al.
(author)
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MT-MACE for female fertility and milk yield
- 2009
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In: Bulletin / International Bull Evaluation Service. - 1011-6079. ; 40, s. 68-71
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Conference paper (other academic/artistic)
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| 30. |
- Nilforooshan, Mohammad A., et al.
(author)
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Multiple-trait multiple-country genetic evaluation of Holstein bulls for female fertility and milk production traits
- 2014
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In: Animal. - 1751-7311 .- 1751-732X. ; 8, s. 887-894
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Journal article (peer-reviewed)abstract
- The aim of this study was to investigate the effect of including milk yield data in the international genetic evaluation of female fertility traits to reduce or eliminate a possible bias because of across-country selection for milk yield. Data included two female fertility traits from Great Britain, Italy and the Netherlands, together with milk yield data from the same countries and from the United States, because the genetic trends in other countries may be influenced by selection decisions on bulls in the United States. Potentially, female fertility data had been corrected nationally for within-country selection and management biases for milk yield. Using a multiple-trait multiple across-country evaluation (MT-MACE) for the analysis of female fertility traits with milk yield, acrosscountry selection patterns both for female fertility and milk yield can be considered simultaneously. Four analyses were performed; one single-trait multiple across-country evaluation analysis including only milk yield data, one MT-MACE analysis including only female fertility traits, and one MT-MACE analysis including both female fertility and milk yield traits. An additional MT-MACE analysis was performed including both female fertility and milk yield traits, but excluding the United States. By including milk yield traits to the analysis, female fertility reliabilities increased, but not for all bulls in all the countries by trait combinations. The presence of milk yield traits in the analysis did not considerably change the genetic correlations, genetic trends or bull rankings of female fertility traits. Even though the predicted genetic merits of female fertility traits hardly changed by including milk yield traits to the analysis, the change was not equally distributed to the whole data. The number of bulls in common between the two sets of Top 100 bulls for each trait in the two analyses of female fertility traits, with and without the four milk yield traits and their rank correlations were low, not necessarily because of the absence of the US milk yield data. The joint international genetic evaluation of female fertility traits with milk yield is recommended to make use of information on several female fertility traits from different countries simultaneously, to consider selection decisions for milk yield in the genetic evaluation of female fertility traits for obtaining more accurate estimating breeding values (EBV) and to acquire female fertility EBV for bulls evaluated for milk yield, but not for female fertility.
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| 31. |
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| 33. |
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| 34. |
- Palucci, Valentina, et al.
(author)
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Overview of the Mendelian Sampling Variance Test Pilot Study
- 2014
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In: Interbull bulletin. - 2001-340X. ; 48, s. 58-62
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Conference paper (other academic/artistic)abstract
- A software for calculating the Mendelian sampling variance has been developed by MTT for Interbull service users. In 2013 the software and its methodology was approved by the Interbull Technical Committee to be tested in a pilot study with real countries data. Countries were asked to test the software on two different group of traits: a group of traits with medium-high heritability (protein, stature and somatic cells score) including results for both males and females; two traits of their choice with heritability lower than 0.1 with results restricted only to males. A total of 21 countries participated in the pilot study. Data received were mostly related to the Holstein breed, and for low heritable traits countries chose most commonly direct longevity and fertility related traits. Overall, 50 (26%) country-breed-trait combinations failed the test. Some more investigations will be needed to better understand the reasons behind their failure. The following paper presents an overview of the data received by countries and of the trend test results.
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| 35. |
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| 36. |
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| 37. |
- Splittorff, Haifa, et al.
(author)
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SNPMace – A meta-analysis to estimate SNP effects by combining results from multiple countries
- 2018
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In: Interbull bulletin. - 2001-340X. ; , s. 1-6
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Conference paper (other academic/artistic)abstract
- Selection of bulls and cows is increasingly made on genomic estimated breeding values (GEBVs) calculated from their SNP genotypes and the estimated effects of each SNP. To obtain the most accurate GEBVs a large training population of animals with phenotypes and genotypes is needed. For some traits, some breeds and some countries such a large training population is not available. In these cases it would increase the accuracy of GEBVs if information from multiple countries and breeds were combined. This paper describes a meta-analysis to combine SNP effects from multiple countries. A project to test this procedure is under way and, if successful, may result in a new Interbull service.
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| 38. |
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| 39. |
- Zumbach, Birgit, et al.
(author)
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Brown Swiss Genomic Evaluation
- 2010
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In: Interbull bulletin. - 2001-340X. ; 42, s. 44-51
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Conference paper (other academic/artistic)
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| 40. |
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