| 1. |
- Agnvall, Beatrix, et al.
(författare)
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Heritability and Genetic Correlations of Fear-Related Behaviour in Red Jungelfowl -Possible Implications for Early Domestication
- 2012
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Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 7:4, s. e35162-
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Tidskriftsartikel (refereegranskat)abstract
- Domesticated species differ from their wild ancestors in a number of traits, generally referred to as the domesticated phenotype. Reduced fear of humans is assumed to have been an early prerequisite for the successful domestication of virtually all species. We hypothesized that fear of humans is linked to other domestication related traits. For three generations, we selected Red Junglefowl (ancestors of domestic chickens) solely on the reaction in a standardized Fear of Human-test. In this, the birds were exposed for a gradually approaching human, and their behaviour was continuously scored. This generated three groups of animals, high (H), low (L) and intermediate (I) fearful birds. The birds in each generation were additionally tested in a battery of behaviour tests, measuring aspects of fearfulness, exploration, and sociality. The results demonstrate that the variation in fear response of Red Junglefowl towards humans has a significant genetic component and is genetically correlated to behavioural responses in other contexts, of which some are associated with fearfulness and others with exploration. Hence, selection of Red Junglefowl on low fear for humans can be expected to lead to a correlated change of other behavioural traits over generations. It is therefore likely that domestication may have caused an initial suite of behavioural modifications, even without selection on anything besides tameness.
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| 2. |
- Franzén, Jessica, et al.
(författare)
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Genetic evaluation of mastitis liability and recovery through longitudinal analysis of transition probabilities
- 2012
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Ingår i: Genetics Selection Evolution. - : Springer Science and Business Media LLC. - 0999-193X .- 1297-9686. ; 44
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Tidskriftsartikel (refereegranskat)abstract
- Background: Many methods for the genetic analysis of mastitis use a cross-sectional approach, which omits information on, e.g., repeated mastitis cases during lactation, somatic cell count fluctuations, and recovery process. Acknowledging the dynamic behavior of mastitis during lactation and taking into account that there is more than one binary response variable to consider, can enhance the genetic evaluation of mastitis. Methods: Genetic evaluation of mastitis was carried out by modeling the dynamic nature of somatic cell count (SCC) within the lactation. The SCC patterns were captured by modeling transition probabilities between assumed states of mastitis and non-mastitis. A widely dispersed SCC pattern generates high transition probabilities between states and vice versa. This method can model transitions to and from states of infection simultaneously, i.e. both the mastitis liability and the recovery process are considered. A multilevel discrete time survival model was applied to estimate breeding values on simulated data with different dataset sizes, mastitis frequencies, and genetic correlations. Results: Correlations between estimated and simulated breeding values showed that the estimated accuracies for mastitis liability were similar to those from previously tested methods that used data of confirmed mastitis cases, while our results were based on SCC as an indicator of mastitis. In addition, unlike the other methods, our method also generates breeding values for the recovery process. Conclusions: The developed method provides an effective tool for the genetic evaluation of mastitis when considering the whole disease course and will contribute to improving the genetic evaluation of udder health.
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| 3. |
- Johansson, Anna Maria, et al.
(författare)
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Genetic differentiation between subpopulations of Swedish mountain (Fjäll and Fjällnära) cattle
- 2020
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Ingår i: Acta Agriculturae Scandinavica, Section A - Animal Science. - : Informa UK Limited. - 0906-4702 .- 1651-1972. ; 69, s. 39-46
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Tidskriftsartikel (refereegranskat)abstract
- The Swedish Mountain (Fjall) cattle and the subpopulation Fjallnara originates from northern Sweden. They are differentiated from both traditional and commercial cattle from southern Sweden. We analysed data from the GGP HD150k SNP array and investigated genetic diversity and differences between Fjall and Fjallnara, and between different groups of Fjallnara. We found that the Fjallnara can be divided into four groups, which are differentiated from each other and from the other Fjall cattle. We also compared allele frequencies between different groups of Fjall and Fjallnara for some of the functional SNPs included in the SNP array. Interestingly, the B allele of Beta lactoglobulin has a very high frequency (94%) in the Fjallnara cattle, which is significantly different from the frequency in the Fjall cattle (60%). Comparing older samples of Fjall cattle with more recent samples, we found a significant increase in the frequency of the B allele in Fjall cattle.
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| 4. |
- Mulder, Han A., et al.
(författare)
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Estimation of genetic variance for macro- and micro-environmental sensitivity using double hierarchical generalized linear models
- 2013
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Ingår i: Genetics Selection Evolution. - : BioMed Central. - 0999-193X .- 1297-9686. ; 45
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Tidskriftsartikel (refereegranskat)abstract
- Background: Genetic variation for environmental sensitivity indicates that animals are genetically different in their response to environmental factors. Environmental factors are either identifiable (e.g. temperature) and called macro-environmental or unknown and called micro-environmental. The objectives of this study were to develop a statistical method to estimate genetic parameters for macro- and micro-environmental sensitivities simultaneously, to investigate bias and precision of resulting estimates of genetic parameters and to develop and evaluate use of Akaike’s information criterion using h-likelihood to select the best fitting model.Methods: We assumed that genetic variation in macro- and micro-environmental sensitivities is expressed as genetic variance in the slope of a linear reaction norm and environmental variance, respectively. A reaction norm model to estimate genetic variance for macro-environmental sensitivity was combined with a structural model for residual variance to estimate genetic variance for micro-environmental sensitivity using a double hierarchical generalized linear model in ASReml. Akaike’s information criterion was constructed as model selection criterion using approximated h-likelihood. Populations of sires with large half-sib offspring groups were simulated to investigate bias and precision of estimated genetic parameters.Results: Designs with 100 sires, each with at least 100 offspring, are required to have standard deviations of estimated variances lower than 50% of the true value. When the number of offspring increased, standard deviations of estimates across replicates decreased substantially, especially for genetic variances of macro- and micro-environmental sensitivities. Standard deviations of estimated genetic correlations across replicates were quite large (between 0.1 and 0.4), especially when sires had few offspring. Practically, no bias was observed for estimates of any of the parameters. Using Akaike’s information criterion the true genetic model was selected as the best statistical model in at least 90% of 100 replicates when the number of offspring per sire was 100. Application of the model to lactation milk yield in dairy cattle showed that genetic variance for micro- and macro-environmental sensitivities existed.Conclusion: The algorithm and model selection criterion presented here can contribute to better understand genetic control of macro- and micro-environmental sensitivities. Designs or datasets should have at least 100 sires each with 100 offspring.
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| 5. |
- Rönnegård, Lars, et al.
(författare)
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Genetic heterogeneity of residual variance - estimation of variance components using double hierarchical generalized linear models
- 2010
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Ingår i: Genetics Selection Evolution. - : Springer Science and Business Media LLC. - 0999-193X .- 1297-9686. ; 42
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Tidskriftsartikel (refereegranskat)abstract
- Background: The sensitivity to microenvironmental changes varies among animals and may be under genetic control. It is essential to take this element into account when aiming at breeding robust farm animals. Here, linear mixed models with genetic effects in the residual variance part of the model can be used. Such models have previously been fitted using EM and MCMC algorithms.Results: We propose the use of double hierarchical generalized linear models (DHGLM), where the squared residuals are assumed to be gamma distributed and the residual variance is fitted using a generalized linear model. The algorithm iterates between two sets of mixed model equations, one on the level of observations and one on the level of variances. The method was validated using simulations and also by re-analyzing a data set on pig litter size that was previously analyzed using a Bayesian approach. The pig litter size data contained 10,060 records from 4,149 sows. The DHGLM was implemented using the ASReml software and the algorithm converged within three minutes on a Linux server. The estimates were similar to those previously obtained using Bayesian methodology, especially the variance components in the residual variance part of the model.Conclusions: We have shown that variance components in the residual variance part of a linear mixed model can be estimated using a DHGLM approach. The method enables analyses of animal models with large numbers of observations. An important future development of the DHGLM methodology is to include the genetic correlation between the random effects in the mean and residual variance parts of the model as a parameter of the DHGLM.
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| 6. |
- Rönnegård, Lars, et al.
(författare)
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Variance component and breeding value estimation for genetic heterogeneity of residual variance in Swedish Holstein dairy cattle
- 2013
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Ingår i: Journal of Dairy Science. - : Elsevier. - 0022-0302 .- 1525-3198. ; 96:4, s. 2627-2636
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Tidskriftsartikel (refereegranskat)abstract
- Trait uniformity, or micro-environmental sensitivity, may be studied through individual differences in residual variance. These differences appear to be heritable, and the need exists, therefore, to fit models to predict breeding values explaining differences in residual variance. The aim of this paper is to estimate breeding values for micro-environmental sensitivity (vEBV) in milk yield and somatic cell score, and their associated variance components, on a large dairy cattle data set having more than 1.6 million records. Estimation of variance components, ordinary breeding values, and vEBV was performed using standard variance component estimation software (ASReml), applying the methodology for double hierarchical generalized linear models. Estimation using ASReml took less than 7 d on a Linux server. The genetic standard deviations for residual variance were 0.21 and 0.22 for somatic cell score and milk yield, respectively, which indicate moderate genetic variance for residual variance and imply that a standard deviation change in vEBV for one of these traits would alter the residual variance by 20%. This study shows that estimation of variance components, estimated breeding values and vEBV, is feasible for large dairy cattle data sets using standard variance component estimation software. The possibility to select for uniformity in Holstein dairy cattle based on these estimates is discussed.
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| 7. |
- Strandberg, Erling
(författare)
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Genetic dissection of complex behaviour traits in German Shepherd dogs
- 2019
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Ingår i: Heredity. - : Springer Science and Business Media LLC. - 0018-067X .- 1365-2540. ; 123, s. 746-758
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Tidskriftsartikel (refereegranskat)abstract
- A favourable genetic structure and diversity of behavioural features highlights the potential of dogs for studying the genetic architecture of behaviour traits. However, behaviours are complex traits, which have been shown to be influenced by numerous genetic and non-genetic factors, complicating their analysis. In this study, the genetic contribution to behaviour variation in German Shepherd dogs (GSDs) was analysed using genomic approaches. GSDs were phenotyped for behaviour traits using the established Canine Behavioural Assessment and Research Questionnaire (C-BARQ). Genome-wide association study (GWAS) and regional heritability mapping (RHM) approaches were employed to identify associations between behaviour traits and genetic variants, while accounting for relevant non-genetic factors. By combining these complementary methods we endeavoured to increase the power to detect loci with small effects. Several behavioural traits exhibited moderate heritabilities, with the highest identified for Human-directed playfulness, a trait characterised by positive interactions with humans. We identified several genomic regions associated with one or more of the analysed behaviour traits. Some candidate genes located in these regions were previously linked to behavioural disorders in humans, suggesting a new context for their influence on behaviour characteristics. Overall, the results support dogs as a valuable resource to dissect the genetic architecture of behaviour traits and also highlight the value of focusing on a single breed in order to control for background genetic effects and thus avoid limitations of between-breed analyses.
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| 8. |
- Strandberg, Erling, et al.
(författare)
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Statistical tools to select for robustness and milk quality
- 2013
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Ingår i: Advances in Animal Biosciences. - : Cambridge University Press. - 2040-4700 .- 2040-4719. ; 4:3, s. 606-611
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Tidskriftsartikel (refereegranskat)abstract
- This work was part of the EU RobustMilk project. In this work package, we have focused on two aspects of robustness, micro- and macro-environmental sensitivity and applied these to somatic cell count (SCC), one aspect of milk quality. We showed that it is possible to combine both categorical and continuous descriptions of the environment in one analysis of genotype by environment interaction. We also developed a method to estimate genetic variation in residual variance and applied it to both simulated and a large field data set of dairy cattle. We showed that it is possible to estimate genetic variation in both micro- and macro-environmental sensitivity in the same data, but that there is a need for good data structure. In a dairy cattle example, this would mean at least 100 bulls with at least 100 daughters each. We also developed methods for improved genetic evaluation of SCC. We estimated genetic variance for some alternative SCC traits, both in an experimental herd data and in field data. Most of them were highly correlated with subclinical mastitis (>0.9) and clinical mastitis (0.7 to 0.8), and were also highly correlated with each other. We studied whether the fact that animals in different herds are differentially exposed to mastitis pathogens could be a reason for the low heritabilities for mastitis, but did not find strong evidence for that. We also created a new model to estimate breeding values not only for the probability of getting mastitis but also for recovering from it. In a progeny-testing situation, this approach resulted in accuracies of 0.75 and 0.4 for these two traits, respectively, which means that it is possible to also select for cows that recover more quickly if they get mastitis.
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| 9. |
- Strandberg, Erling
(författare)
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Unravelling selection signatures in a single dog breed suggests recent selection for morphological and behavioral traits
- 2020
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Ingår i: Advanced Genetics. - : Wiley. - 2641-6573. ; 2
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Tidskriftsartikel (refereegranskat)abstract
- Strong selection has resulted in substantial morphological and behavioral diversity across modern dog breeds, which makes dogs interesting model animals to study the underlying genetic architecture of these traits. However, results from between-breed analyses may confound selection signatures for behavior and morphological features that were coselected during breed development. In this study, we assess population genetic differences in a unique resource of dogs of the same breed but with systematic behavioral selection in only one population. We exploit these different breeding backgrounds to identify signatures of recent selection. Selection signatures within populations were found on chromosomes 4 and 19, with the strongest signals in behavior-related genes. Regions showing strong signals of divergent selection were located on chromosomes 1, 24, and 32, and include candidate genes for both physical features and behavior. Some of the selection signatures appear to be driven by loci associated with coat color (Chr 24; ASIP) and length (Chr 32; FGF5), while others showed evidence of association with behavior. Our findings suggest that signatures of selection within dog breeds have been driven by selection for morphology and behavior. Furthermore, we demonstrate that combining selection scans with association analyses is effective for dissecting the traits under selection.
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| 10. |
- Upadhyay, Maulik, et al.
(författare)
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Genomic relatedness and diversity of Swedish native cattle breeds
- 2019
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Ingår i: Genetics Selection Evolution. - : Springer Science and Business Media LLC. - 0999-193X .- 1297-9686. ; 51
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Tidskriftsartikel (refereegranskat)abstract
- Background: Native cattle breeds are important genetic resources given their adaptation to the local environment in which they are bred. However, the widespread use of commercial cattle breeds has resulted in a marked reduction in population size of several native cattle breeds worldwide. Therefore, conservation management of native cattle breeds requires urgent attention to avoid their extinction. To this end, we genotyped nine Swedish native cattle breeds with genome-wide 150 K single nucleotide polymorphisms (SNPs) to investigate the level of genetic diversity and relatedness between these breeds.Results: We used various SNP-based approaches on this dataset to connect the demographic history with the genetic diversity and population structure of these Swedish cattle breeds. Our results suggest that the Vane and Ringamala breeds originating from southern Sweden have experienced population isolation and have a low genetic diversity, whereas the Fjall breed has a large founder population and a relatively high genetic diversity. Based on the shared ancestry and the constructed phylogenetic trees, we identified two major clusters in Swedish native cattle. In the first cluster, which includes Swedish mountain cattle breeds, there was little differentiation among the Fjall, Fjallnara, Swedish Polled, and Bohus Polled breeds. The second cluster consists of breeds from southern Sweden: Vane, Ringamala and Swedish Red. Interestingly, we also identified sub-structuring in the Fjallnara breed, which indicates different breeding practices on the farms that maintain this breed.Conclusions: This study represents the first comprehensive genome-wide analysis of the genetic relatedness and diversity in Swedish native cattle breeds. Our results show that different demographic patterns such as genetic isolation and cross-breeding have shaped the genomic diversity of Swedish native cattle breeds and that the Swedish mountain breeds have retained their authentic distinct gene pool without significant contribution from any of the other European cattle breeds that were included in this study.
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