| 1. |
- LeBlanc, Neil, et al.
(author)
-
A novel combination of TaqMan RT-PCR and a suspension microarray assay for the detection and species identification of pestiviruses
- 2010
-
In: Veterinary Microbiology. - : Elsevier BV. - 0378-1135 .- 1873-2542. ; 142:1-2, s. 81-86
-
Journal article (peer-reviewed)abstract
- The genus pestivirus contains four recognized species: classical swine fever virus, border disease virus, bovine viral diarrhoea virus types 1 and 2. All are economically important and globally distributed but classical swine fever is the most serious, concerning losses and control measures. It affects both domestic pigs and wild boars. Outbreaks of this disease in domestic pigs call for the most serious measures of disease control, including a stamping out policy in Europe. Since all the members of the pestivirus genus can infect swine, differential diagnosis using traditional methods poses some problems. Antibody tests may lack specificity due to cross-reactions, antigen capture ELISAs may have low sensitivity, and virus isolation may take several days or even longer time to complete. PCR-based tests overcome these problems for the most part, but in general lack the multiplexing capability to detect and differentiate all the pestiviruses simultaneously. The assay platform described here addresses all of these issues by combining the advantages of real-time PCR with the multiplexing capability of microarray technology. The platform includes a TaqMan real-time PCR designed for the universal detection of pestiviruses and a microarray assay that can use the amplicons produced in the real-time PCR to identify the specific pestivirus.
|
|
| 2. |
- Rönnegård, Lars, et al.
(author)
-
Genetic heterogeneity of residual variance - estimation of variance components using double hierarchical generalized linear models
- 2010
-
In: Genetics Selection Evolution. - : Springer Science and Business Media LLC. - 0999-193X .- 1297-9686. ; 42
-
Journal article (peer-reviewed)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.
|
|
| 3. |
|
|
| 4. |
- Besnier, Francois, et al.
(author)
-
Fine mapping and replication of QTL in outbred chicken advanced intercross lines
- 2011
-
In: Genetics Selection Evolution. - Paris : Springer Science and Business Media LLC. - 0999-193X .- 1297-9686. ; 43, s. 3-
-
Journal article (peer-reviewed)abstract
- BACKGROUND: Linkage mapping is used to identify genomic regions affecting the expression of complex traits. However, when experimental crosses such as F2 populations or backcrosses are used to map regions containing a Quantitative Trait Locus (QTL), the size of the regions identified remains quite large, i.e. 10 or more Mb. Thus, other experimental strategies are needed to refine the QTL locations. Advanced Intercross Lines (AIL) are produced by repeated intercrossing of F2 animals and successive generations, which decrease linkage disequilibrium in a controlled manner. Although this approach is seen as promising, both to replicate QTL analyses and fine-map QTL, only a few AIL datasets, all originating from inbred founders, have been reported in the literature.METHODS: We have produced a nine-generation AIL pedigree (n = 1529) from two outbred chicken lines divergently selected for body weight at eight weeks of age. All animals were weighed at eight weeks of age and genotyped for SNP located in nine genomic regions where significant or suggestive QTL had previously been detected in the F2 population. In parallel, we have developed a novel strategy to analyse the data that uses both genotype and pedigree information of all AIL individuals to replicate the detection of and fine-map QTL affecting juvenile body weight.RESULTS: Five of the nine QTL detected with the original F2 population were confirmed and fine-mapped with the AIL, while for the remaining four, only suggestive evidence of their existence was obtained. All original QTL were confirmed as a single locus, except for one, which split into two linked QTL.CONCLUSIONS: Our results indicate that many of the QTL, which are genome-wide significant or suggestive in the analyses of large intercross populations, are true effects that can be replicated and fine-mapped using AIL. Key factors for success are the use of large populations and powerful statistical tools. Moreover, we believe that the statistical methods we have developed to efficiently study outbred AIL populations will increase the number of organisms for which in-depth complex traits can be analyzed.
|
|
| 5. |
- Nelson, Ronald, et al.
(author)
-
qtl.outbred: Interfacing outbred line cross data with the R/qtl mapping software
- 2011
-
In: BMC Research Notes. - : BioMed Central. - 1756-0500. ; 4:154
-
Journal article (peer-reviewed)abstract
- Backgroundqtl.outbred is an extendible interface in the statistical environment, R, for combining quantitative trait loci (QTL) mapping tools. It is built as an umbrella package that enables outbred genotype probabilities to be calculated and/or imported into the software package R/qtl.FindingsUsing qtl.outbred, the genotype probabilities from outbred line cross data can be calculated by interfacing with a new and efficient algorithm developed for analyzing arbitrarily large datasets (included in the package) or imported from other sources such as the web-based tool, GridQTL.Conclusionqtl.outbred will improve the speed for calculating probabilities and the ability to analyse large future datasets. This package enables the user to analyse outbred line cross data accurately, but with similar effort than inbred line cross data.
|
|
| 6. |
- Ren, Keni, 1983-, et al.
(author)
-
Interpolation methods to improve data quality of indoor positioning data for dairy cattle
- 2022
-
In: Frontiers in Animal Science. - : Frontiers Media S.A.. - 2673-6225. ; 3
-
Journal article (peer-reviewed)abstract
- Position data from real-time indoor positioning systems are increasingly used for studying individual cow behavior and social behavior in dairy herds. However, missing data challenges achieving reliable continuous activity monitoring and behavior studies. This study investigates the pattern of missing data and alternative interpolation methods in ultra-wideband based real-time indoor positioning systems in a free-stall barn. We collected 3 months of position data from a Swedish farm with around 200 cows. Data sampled for 6 days from 69 cows were used in subsequent analyzes to determine the location and duration of missing data. Data from 20 cows with the most reliable tags were selected to compare the effects of four different interpolation methods (previous, linear interpolation, cubic spline data interpolation and modified Akima interpolation). By comparing the observed data with the interpolations of the simulated missing data, the mean error distance varied from around 55 cm, using the previously last observed position, to around 17 cm for modified Akima. Modified Akima interpolation has the lowest error distance for all investigated activities (rest, walking, standing, feeding). Larger error distances were found in areas where the cows walk and turn, such as the corner between feeding and cubicles. Modified Akima interpolation is expected to be useful in the subsequent analyses of data gathered using real-time indoor positioning systems.
|
|
| 7. |
- Rönnegård, Lars, et al.
(author)
-
Hglm: A package for fitting hierarchical generalized linear models
- 2010
-
In: The R Journal. - 2073-4859. ; 2:2, s. 20-28
-
Journal article (peer-reviewed)abstract
- We present the hglm package for fitting hierarchical generalized linear models. It can be used for linear mixed models and generalized linear mixed models with random effects for a variety of links and a variety of distributions for both the outcomes and the random effects. Fixed effects can also be fitted in the dispersion part of the model.
|
|
| 8. |
- Rönnegård, Lars, et al.
(author)
-
How to deal with genotype uncertainty in variance component quantitative trait loci analyses
- 2011
-
In: Genetics Research. - : Cambridge University Press. - 0016-6723 .- 1469-5073. ; 93, s. 333-342
-
Journal article (peer-reviewed)abstract
- Dealing with genotype uncertainty is an ongoing issue in genetic analyses of complex traits. Here we consider genotype uncertainty in quantitative trait loci (QTL) analyses for large crosses in variance component models, where the genetic information is included in identity-by-descent (IBD) matrices. An IBD matrix is one realization from a distribution of potential IBD matrices given available marker information. In QTL analyses, its expectation is normally used resulting in potentially reduced accuracy and loss of power. Previously, IBD distributions have been included in models for small human full-sib families. We develop an Expectation-Maximization (EM) algorithm for estimating a full model based on Monte Carlo imputation for applications in large animal pedigrees. Our simulations show that the bias of variance component estimates using traditional expected IBD matrix can be adjusted by accounting for the distribution and that the calculations are computationally feasible for large pedigrees.
|
|
| 9. |
- Rönnegård, Lars, et al.
(author)
-
Modelling dominance in a flexible intercross analysis
- 2009
-
In: BMC Genetics. - : Springer Science and Business Media LLC. - 1471-2156. ; 10
-
Journal article (peer-reviewed)abstract
- Conclusion: We have extended FIA to include QTL dominance effects. The power of FIA was superior, or similar, to standard regression methods for QTL effects with dominance. The difference in power for FIA with or without dominance is expected to be small as long as the QTL effects are not overdominant. We suggest that FIA with only additive effects should be the standard model to be used, especially since it is more computationally efficient.
|
|
| 10. |
- Rönnegård, Lars, et al.
(author)
-
Non-iterative variance component estimation in QTL analysis
- 2009
-
In: Journal of Animal Breeding and Genetics. - : Wiley. - 0931-2668 .- 1439-0388. ; 126:2, s. 110-116
-
Journal article (peer-reviewed)abstract
- In variance component quantitative trait loci (QTL) analysis, a mixed model is used to detect the most likely chromosome position of a QTL. The putative QTL is included as a random effect and a method is needed to estimate the QTL variance. The standard estimation method used is an iterative method based on the restricted maximum likelihood (REML). In this paper, we present a novel non-iterative variance component estimation method. This method is based on Henderson's method 3, but relaxes the condition of unbiasedness. Two similar estimators were compared, which were developed from two different partitions of the sum of squares in Henderson's method 3. The approach was compared with REML on data from a European wild boar x domestic pig intercross. A meat quality trait was studied on chromosome 6 where a functional gene was known to be located. Both partitions resulted in estimated QTL variances close to the REML estimates. From the non-iterative estimates, we could also compute good approximations of the likelihood ratio curve on the studied chromosome.
|
|
