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  • 1.
    Marina, Héctor
    et al.
    Swedish University of Agricultural Sciences, Uppsala.
    Ren, Keni
    Swedish University of Agricultural Sciences, Uppsala.
    Hansson, Ida
    Swedish University of Agricultural Sciences, Uppsala.
    Fikse, Freddy
    Swedish University of Agricultural Sciences, Uppsala.
    Nielsen, Per Peetz
    RISE Research Institute of Sweden; RISE Ideon, Lund.
    Rönnegård, Lars
    Högskolan Dalarna, Institutionen för information och teknik, Statistik. Swedish University of Agricultural Sciences, Uppsala.
    New insight into social relationships in dairy cows, and how time of birth, parity and relatedness affect spatial interactions later in life2024Ingår i: Journal of Dairy Science, ISSN 0022-0302, E-ISSN 1525-3198, Vol. 107, nr 2, s. 1110-1123Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Social interactions between cows play a fundamental role in the daily activities of dairy cattle. Real-time location systems provide on a continuous and automated basis information about the position of individual cows inside barns, offering a valuable opportunity to monitor dyadic social contacts. Understanding dyadic social interactions could be applied to enhance the stability of the social structure promoting animal welfare and to model disease transmission in dairy cattle. This study aimed to identify the impact of different cow characteristics on the likelihood of the formation and persistence of social contacts in dairy cattle. The individual position of the lactating cows was automatically collected once per second for 2 weeks, using an ultra-wideband system on a Swedish commercial farm consisting of nearly 200 dairy cows inside a free-stall barn. Social networks were constructed using the position data of 149 cows with available information on all characteristics during the study period. Social contacts were considered as a binary variable indicating whether a cow pair was within 2.5 m of each other for at least 10 min per day. The role of cow characteristics in social networks was studied by applying separable temporal exponential random graph models. Our results revealed that cows of the same parity interacted more consistently, as well as those born within 7 d of each other or are closely related by pedigree. The repeatability of the topological parameters indicated a consistent short-term stability of the individual animal roles within the social network structure. Additional research is required to elucidate the underlying mechanisms governing the long-term evolution of social contacts among dairy cattle and to investigate the relationship between these networks and the transmission of diseases in the dairy cattle population.

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  • 2.
    Hansson, I
    et al.
    Swedish University of Agricultural Sciences, Uppsala.
    Silvera, A
    Swedish University of Agricultural Sciences, Uppsala.
    Ren, K
    Swedish University of Agricultural Sciences, Uppsala.
    Woudstra, S
    University of Copenhagen, Frederiksberg, Denmark.
    Skarin, A
    Swedish University of Agricultural Sciences, Uppsala.
    Fikse, W F
    Swedish University of Agricultural Sciences, Uppsala.
    Nielsen, P P
    RISE Research Institute of Sweden, Lund.
    Rönnegård, Lars
    Högskolan Dalarna, Institutionen för information och teknik, Statistik. Swedish University of Agricultural Sciences, Uppsala.
    Cow characteristics associated with the variation in number of contacts between dairy cows2023Ingår i: Journal of Dairy Science, ISSN 0022-0302, E-ISSN 1525-3198, Vol. 106, nr 4, s. 2685-2699Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    In modern freestall barns where large groups of cows are housed together, the behavior displayed by herd mates can influence the welfare and production of other individuals. Therefore, understanding social interactions in groups of dairy cows is important to enhance herd management and optimize the outcomes of both animal health and welfare in the future. Many factors can affect the number of social contacts in a group. This study aimed to identify which characteristics of a cow are associated with the number of contacts it has with other group members in 2 different functional areas (feeding and resting area) to increase our understanding of the social behavior of dairy cows. Inside 2 herds housed in freestall barns with around 200 lactating cows each, cow positions were recorded with an ultra-wideband real-time location system collecting all cows' positions every second over 2 wk. Using the positioning data of the cows, we quantified the number of contacts between them, assuming that cows spending time in proximity to one another (within a distance of 2.5 m for at least 10 min per day) were interacting socially. We documented in which barn areas these interactions occurred and used linear mixed models to investigate if lactation stage, parity, breed, pregnancy status, estrus, udder health, and claw health affect the number of contacts. We found variation in the number of contacts a cow had between individuals in both functional areas. Cows in later lactation had more contacts in the feeding area than cows in early lactation. Furthermore, in one herd, higher parity cows had fewer contacts in the feeding area than first parity cows, and in the other herd, cows in third parity or higher had more contacts in the resting area. This study indicates that cow characteristics such as parity and days in milk are associated with the number of contacts a cow has daily to its herd mates and provides useful information for further research on social interactions of dairy cows.

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  • 3. Marjanovic, J.
    et al.
    Mulder, H. A.
    Rönnegård, Lars
    Högskolan Dalarna, Institutionen för information och teknik, Statistik. Swedish University of Agricultural Sciences, Uppsala.
    de Koning, D. -J
    Bijma, P.
    Capturing indirect genetic effects on phenotypic variability: Competition meets canalization2022Ingår i: Evolutionary Applications, E-ISSN 1752-4571, Vol. 15, nr 4, s. 694-705Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Phenotypic variability of a genotype is relevant both in natural and domestic populations. In the past two decades, variability has been studied as a heritable quantitative genetic trait in its own right, often referred to as inherited variability or environmental canalization. So far, studies on inherited variability have only considered genetic effects of the focal individual, that is, direct genetic effects on inherited variability. Observations from aquaculture populations and some plants, however, suggest that an additional source of genetic variation in inherited variability may be generated through competition. Social interactions, such as competition, are often a source of Indirect Genetic Effects (IGE). An IGE is a heritable effect of an individual on the trait value of another individual. IGEs may substantially affect heritable variation underlying the trait, and the direction and magnitude of response to selection. To understand the contribution of IGEs to evolution of environmental canalization in natural populations, and to exploit such inherited variability in animal and plant breeding, we need statistical models to capture this effect. To our knowledge, it is unknown to what extent the current statistical models commonly used for IGE and inherited variability capture the effect of competition on inherited variability. Here, we investigate the potential of current statistical models for inherited variability and trait values, to capture the direct and indirect genetic effects of competition on variability. Our results show that a direct model of inherited variability almost entirely captures the genetic sensitivity of individuals to competition, whereas an indirect model of inherited variability captures the cooperative genetic effects of individuals on their partners. Models for trait levels, however, capture only a small part of the genetic effects of competition. The estimation of direct and indirect genetic effects of competition, therefore, is possible with models for inherited variability but may require a two-step analysis. © 2022 The Authors. Evolutionary Applications published by John Wiley & Sons Ltd.

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  • 4. Chozas, A.
    et al.
    Mahjani, B.
    Rönnegård, Lars
    Högskolan Dalarna, Institutionen för information och teknik, Statistik. Swedish University of Agricultural Sciences, Uppsala.
    Family history of breast cancer is associated with elevated risk of prostate cancer: evidence for shared genetic risks2022Ingår i: Human Heredity, ISSN 0001-5652, E-ISSN 1423-0062, Vol. 87, s. 12-19Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Introduction: Although breast and prostate cancers arise in different organs and are more frequent in the opposite sex, multiple studies have reported an association between their family history. Analysis of single nucleotide polymorphism data, based on distant relatives, has revealed a small positive genetic correlation between these cancers explained by common variants. The estimate of genetic correlation based on close relatives reveals the extent to which shared genetic risks are explained by both common and rare variants. This estimate is unknown for breast and prostate cancer. Method: We estimated the relative risks, heritability, and genetic correlation of breast cancer and prostate cancer, based on the Minnesota Breast and Prostate Cancer Study, a family study of 141 families ascertained for breast cancer. Results: Heritability of breast cancer was 0.34 (95% credible interval: 0.23-0.49) and 0.65 (95% credible interval: 0.36-0.97) for prostate cancer, and the genetic correlation was 0.23. In terms of odds ratios, these values correspond to a 1.3 times higher odds of breast cancer among probands, given that the brother has prostate cancer. Conclusion: This study shows the inherent relation between prostate cancer and breast cancer; an incident of one in a family increases the risk of developing the other. The large difference between estimates of genetic correlation from distant and close relatives, if replicated, suggests that rare variants contribute to the shared genetic risk of breast and prostate cancer. However, the difference could steam from genotype-by-family effects shared between the two types of cancers. ©; 2021 The Author(s).

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  • 5.
    Ren, Keni
    et al.
    Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden.
    Alam, Moudud
    Högskolan Dalarna, Institutionen för information och teknik, Statistik.
    Nielsen, Per Peetz
    Department of Agriculture and Food, RISE Research Institutes of Sweden (RISE), Lund, Sweden.
    Gussmann, Maya
    Department of Veterinary and Animal Sciences, University of Copenhagen, Frederiksberg, Denmark.
    Rönnegård, Lars
    Högskolan Dalarna, Institutionen för information och teknik, Statistik. Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden.
    Interpolation Methods to Improve Data Quality of Indoor Positioning Data for Dairy Cattle2022Ingår i: Frontiers in Animal Science, E-ISSN 2673-6225, Vol. 3, artikel-id 896666Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    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.

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  • 6.
    Stingo-Hirmas, Diego
    et al.
    IFM-Biology, Linköping University, Linköping, Sweden.
    Cunha, Felipe
    IFM-Biology, Linköping University, Linköping, Sweden.
    Cardoso, Rita France
    IFM-Biology, Linköping University, Linköping, Sweden.
    Carra, Laura G
    IFM-Biology, Linköping University, Linköping, Sweden.
    Rönnegård, Lars
    Högskolan Dalarna, Institutionen för information och teknik, Statistik. Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden.
    Wright, Dominic
    IFM-Biology, Linköping University, Linköping, Sweden.
    Henriksen, Rie
    IFM-Biology, Linköping University, Linköping, Sweden.
    Proportional Cerebellum Size Predicts Fear Habituation in Chickens2022Ingår i: Frontiers in Physiology, E-ISSN 1664-042X, Vol. 13, artikel-id 826178Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The cerebellum has a highly conserved neural structure across species but varies widely in size. The wide variation in cerebellar size (both absolute and in proportion to the rest of the brain) among species and populations suggests that functional specialization is linked to its size. There is increasing recognition that the cerebellum contributes to cognitive processing and emotional control in addition to its role in motor coordination. However, to what extent cerebellum size reflects variation in these behavioral processes within species remains largely unknown. By using a unique intercross chicken population based on parental lines with high divergence in cerebellum size, we compared the behavior of individuals repeatedly exposed to the same fear test (emergence test) early in life and after sexual maturity (eight trials per age group) with proportional cerebellum size and cerebellum neural density. While proportional cerebellum size did not predict the initial fear response of the individuals (trial 1), it did increasingly predict adult individuals response as the trials progressed. Our results suggest that proportional cerebellum size does not necessarily predict an individual's fear response, but rather the habituation process to a fearful stimulus. Cerebellum neuronal density did not predict fear behavior in the individuals which suggests that these effects do not result from changes in neuronal density but due to other variables linked to proportional cerebellum size which might underlie fear habituation.

  • 7. Anglart, D
    et al.
    Emanuelson, U
    Rönnegård, Lars
    Högskolan Dalarna, Institutionen för information och teknik, Statistik.
    Sandgren, C Hallén
    Detecting and predicting changes in milk homogeneity using data from automatic milking systems.2021Ingår i: Journal of Dairy Science, ISSN 0022-0302, E-ISSN 1525-3198, Vol. 104, nr 10, s. 11009-11017Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    To ensure milk quality and detect cows with signs of mastitis, visual inspection of milk by prestripping quarters before milking is recommended in many countries. An objective method to find milk changed in homogeneity (i.e., with clots) is to use commercially available inline filters to inspect the milk. Due to the required manual labor, this method is not applicable in automatic milking systems (AMS). We investigated the possibility of detecting and predicting changes in milk homogeneity using data generated by AMS. In total, 21,335 quarter-level milk inspections were performed on 5,424 milkings of 624 unique cows on 4 farms by applying visual inspection of inline filters that assembled clots from the separate quarters during milking. Images of the filters with clots were scored for density, resulting in 892 observations with signs of clots for analysis (77% traces or mild cases, 15% moderate cases, and 8% heavy cases). The quarter density scores were combined into 1 score indicating the presence of clots during a single cow milking and into 2 scores summarizing the density scores in cow milkings during a 30-h sampling period. Data generated from the AMS, such as milk yield, milk flow, conductivity, and online somatic cell counts, were used as input to 4 multilayer perceptron models to detect or predict single milkings with clots and to detect milking periods with clots. All models resulted in high specificity (98-100%), showing that the models correctly classified cow milkings or cow milking periods with no clots observed. The ability to successfully classify cow milkings or cow periods with observed clots had a low sensitivity. The highest sensitivity (26%) was obtained by the model that detected clots in a single milking. The prevalence of clots in the data was low (2.4%), which was reflected in the results. The positive predictive value depends on the prevalence and was relatively high, with the highest positive predictive value (72%) reached in the model that detected clots during the 30-h sampling periods. The misclassification rate for cow milkings that included higher-density scores was lower, indicating that the models that detected or predicted clots in a single milking could better distinguish the heavier cases of clots. Using data from AMS to detect and predict changes in milk homogeneity seems to be possible, although the prediction performance for the definitions of clots used in this study was poor.

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  • 8. Hallén Sandgren, C
    et al.
    Anglart, D
    Klaas, I C
    Rönnegård, Lars
    Högskolan Dalarna, Institutionen för information och teknik, Statistik.
    Emanuelson, U
    Homogeneity density scores of quarter milk in automatic milking systems.2021Ingår i: Journal of Dairy Science, ISSN 0022-0302, E-ISSN 1525-3198, Vol. 104, nr 9, s. 10121-10130Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Milk quality and clinical mastitis in dairy cows are monitored by detecting visually abnormal milk. A standardized method to evaluate clots in milk and studies of the incidence and dynamics of clots in milk at the quarter level are lacking. We validated a method to score clot density in quarter milk samples and describe the prevalence and dynamics of the density scores between consecutive samplings and periods in 4 farms with automatic milking systems. Using in-line filters, we collected quarter milk samples at each milking during 3 periods of 30 h each in each farm. Clot density was scored based on coverage of the filter area as 0 (negative), 1 (trace), 2 (mild), 3 (moderate), 4 (heavy), and 5 (very heavy). The score for a specific quarter and milking is referred to as the quarter milking score (QMS). Three assessors independently scored 902 images of filter samples with a Fleiss kappa value of 0.72. In total, 21,202 quarter milk samples from 5,398 milkings of 621 cows were collected. Of the quarter filter samples, 2.4% had visible clots, distributed as mild (1.4%), moderate (0.6%), heavy (0.3%), and very heavy (<0.1%, n = 8). Cases with a cow period sum of QMS ≥ 4, corresponding to 9.4% of all periods, harbored 86% and 94% of all QMS of 2 to 5 and 3 to 5, respectively. Of these cases, cows sampled in all 3 periods and clots in only 1 period had a quarter period sum score ≥ 1 in 1.8 different quarters in average. Corresponding numbers for the cows with clots or traces in 2 or 3 periods were 2.2 and 2.5 different quarters, respectively. A QMS of 2 to 5 in the preceding milking increased the chance of a QMS >1 in the following milking, with an average chance of 38%. The probability of a QMS > 1 increased with increasing previous QMS, a higher sum of QMS during the milking period, longer milking interval, and higher lactation number, but decreased with increasing days in milk. Our study showed that the method of clot-density scoring is feasible to perform and reproducible for investigating the occurrence and dynamics of clots in milk. Elevated clot-density scores clustered within certain cows and cow periods and appeared in new quarters of the cows over time. The low recurrence of QMS of 1 and 2 within quarters indicated that QMS 3 could be a reasonable threshold for detecting quarters with abnormal milk that require further attention.

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  • 9. Patxot, Marion
    et al.
    Banos, Daniel Trejo
    Kousathanas, Athanasios
    Orliac, Etienne J.
    Ojavee, Sven E.
    Moser, Gerhard
    Holloway, Alexander
    Sidorenko, Julia
    Kutalik, Zoltan
    Magi, Reedik
    Visscher, Peter M.
    Rönnegård, Lars
    Högskolan Dalarna, Institutionen för information och teknik, Statistik. Swedish University of Agricultural Science.
    Robinson, Matthew R.
    Probabilistic inference of the genetic architecture underlying functional enrichment of complex traits2021Ingår i: Nature Communications, E-ISSN 2041-1723, Vol. 12, nr 1, artikel-id 6972Artikel i tidskrift (Refereegranskat)
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  • 10.
    Ren, Keni
    et al.
    Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden.
    Nielsen, Per Peetz
    Department of Agriculture and Food, RISE Research Institutes of Sweden, Lund, Sweden.
    Alam, Moudud
    Högskolan Dalarna, Institutionen för information och teknik, Statistik.
    Rönnegård, Lars
    Högskolan Dalarna, Institutionen för information och teknik, Statistik.
    Where do we find missing data in a commercial real-time location system? Evidence from 2 dairy farms2021Ingår i: JDS Communications, ISSN 2666-9102, Vol. 2, s. 345-350Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Real-time indoor positioning using ultra-wideband devices provides an opportunity for modern dairy farms to monitor the behavior of individual cows; however, missing data from these devices hinders reliable continuous monitoring and analysis of animal movement and social behavior. The objective of this study was to examine the data quality, in terms of missing data, in one commercially available ultra-wideband–based real-time location system for dairy cows. The focus was on detecting major obstacles, or sections, inside open freestall barns that resulted in increased levels of missing data. The study was conducted on 2 dairy farms with an existing commercial real-time location system. Position data were recorded for 6 full days from 69 cows on farm 1 and from 59 cows on farm 2. These data were used in subsequent analyses to determine the locations within the dairy barns where position data were missing for individual cows. The proportions of missing data were found to be evenly distributed within the 2 barns after fitting a linear mixed model with spatial smoothing to logit-transformed proportions (mean = 18% vs. 4% missing data for farm 1 and farm 2, respectively), with the exception of larger proportions of missing data along one of the walls on both farms. On farm 1, the variation between individual tags was large (range: 9–49%) compared with farm 2 (range: 12–38%). This greater individual variation of proportions of missing data indicates a potential problem with the individual tag, such as a battery malfunction or tag placement issue. Further research is needed to guide researchers in identifying problems relating to data capture problems in real-time monitoring systems on dairy farms. This is especially important when undertaking detailed analyses of animal movement and social interactions between animals.

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  • 11. Anglart, D.
    et al.
    Hallén-Sandgren, C.
    Emanuelson, U.
    Rönnegård, Lars
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik. SLU.
    Comparison of methods for predicting cow composite somatic cell counts2020Ingår i: Journal of Dairy Science, ISSN 0022-0302, E-ISSN 1525-3198, Vol. 103, nr 9, s. 8433-8442Artikel i tidskrift (Refereegranskat)
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  • 12.
    Saqlain, Murshid
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Mikrodataanalys.
    Alam, Moudud
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Rönnegård, Lars
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Westin, Jerker
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Investigating Stochastic Differential Equations Modelling for Levodopa Infusion in Patients with Parkinson's Disease2020Ingår i: European journal of drug metabolism and pharmacokinetics, ISSN 0378-7966, E-ISSN 2107-0180, Vol. 45, nr 1, s. 41-49Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    BACKGROUND AND OBJECTIVES: Levodopa concentration in patients with Parkinson's disease is frequently modelled with ordinary differential equations (ODEs). Here, we investigate a pharmacokinetic model of plasma levodopa concentration in patients with Parkinson's disease by introducing stochasticity to separate the intra-individual variability into measurement and system noise, and to account for auto-correlated errors. We also investigate whether the induced stochasticity provides a better fit than the ODE approach.

    METHODS: In this study, a system noise variable is added to the pharmacokinetic model for duodenal levodopa/carbidopa gel (LCIG) infusion described by three ODEs through a standard Wiener process, leading to a stochastic differential equations (SDE) model. The R package population stochastic modelling (PSM) was used for model fitting with data from previous studies for modelling plasma levodopa concentration and parameter estimation. First, the diffusion scale parameter (σw), measurement noise variance, and bioavailability are estimated with the SDE model. Second, σw is fixed to certain values from 0 to 1 and bioavailability is estimated. Cross-validation was performed to compare the average root mean square errors (RMSE) of predicted plasma levodopa concentration.

    RESULTS: Both the ODE and the SDE models estimated bioavailability to be approximately 75%. The SDE model converged at different values of σw that were significantly different from zero. The average RMSE for the ODE model was 0.313, and the lowest average RMSE for the SDE model was 0.297 when σw was fixed to 0.9, and these two values are significantly different.

    CONCLUSIONS: The SDE model provided a better fit for LCIG plasma levodopa concentration by approximately 5.5% in terms of mean percentage change of RMSE.

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  • 13.
    Mouresan, Elena Flavia
    et al.
    Swedish University of Agricultural Sciences.
    Selle, Maria
    Norwegian University of Science and Technology.
    Rönnegård, Lars
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Genomic Prediction Including SNP-Specific Variance Predictors2019Ingår i: G3: Genes, Genomes, Genetics, E-ISSN 2160-1836, Vol. 9, nr 10, s. 3333-3343Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The increasing amount of available biological information on the markers can be used to inform the models applied for genomic selection to improve predictions. The objective of this study was to propose a general model for genomic selection using a link function approach within the hierarchical generalized linear model framework (hglm) that can include external information on the markers. These models can be fitted using the well-established hglm package in R. We also present an R package (CodataGS) to fit these models, which is significantly faster than the hglm package. Simulated data was used to validate the proposed model. We tested categorical, continuous and combination models where the external information on the markers was related to 1) the location of the QTLs on the genome with varying degree of uncertainty, 2) the relationship of the markers with the QTLs calculated as the LD between them, and 3) a combination of both. The proposed models showed improved accuracies from 3.8% up to 23.2% compared to the SNP-BLUP method in a simulated population derived from a base population with 100 individuals. Moreover, the proposed categorical model was tested on a dairy cattle dataset for two traits (Milk Yield and Fat Percentage). These results also showed improved accuracy compared to SNP-BLUP, especially for the Fat% trait. The performance of the proposed models depended on the genetic architecture of the trait, as traits that deviate from the infinitesimal model benefited more from the external information. Also, the gain in accuracy depended on the degree of uncertainty of the external information provided to the model. The usefulness of these type of models is expected to increase with time as more accurate information on the markers becomes available.

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  • 14.
    Rönnegård, Lars
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik. Swedish University of Agricultural Sciences.
    The evolution of peer-reviewed papers.2019Ingår i: Journal of Animal Breeding and Genetics, ISSN 0931-2668, E-ISSN 1439-0388, Vol. 136, nr 2, s. 77-78Artikel i tidskrift (Övrigt vetenskapligt)
  • 15. Marjanovic, Jovana
    et al.
    Mulder, Han A
    Rönnegård, Lars
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik. SLU.
    Bijma, Piter
    Modelling the co-evolution of indirect genetic effects and inherited variability2018Ingår i: Heredity, ISSN 0018-067X, E-ISSN 1365-2540, Vol. 121, s. 631-647Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    When individuals interact, their phenotypes may be affected not only by their own genes but also by genes in their social partners. This phenomenon is known as Indirect Genetic Effects (IGEs). In aquaculture species and some plants, however, competition not only affects trait levels of individuals, but also inflates variability of trait values among individuals. In the field of quantitative genetics, the variability of trait values has been studied as a quantitative trait in itself, and is often referred to as inherited variability. Such studies, however, consider only the genetic effect of the focal individual on trait variability and do not make a connection to competition. Although the observed phenotypic relationship between competition and variability suggests an underlying genetic relationship, the current quantitative genetic models of IGE and inherited variability do not allow for such a relationship. The lack of quantitative genetic models that connect IGEs to inherited variability limits our understanding of the potential of variability to respond to selection, both in nature and agriculture. Models of trait levels, for example, show that IGEs may considerably change heritable variation in trait values. Currently, we lack the tools to investigate whether this result extends to variability of trait values. Here we present a model that integrates IGEs and inherited variability. In this model, the target phenotype, say growth rate, is a function of the genetic and environmental effects of the focal individual and of the difference in trait value between the social partner and the focal individual, multiplied by a regression coefficient. The regression coefficient is a genetic trait, which is a measure of cooperation; a negative value indicates competition, a positive value cooperation, and an increasing value due to selection indicates the evolution of cooperation. In contrast to the existing quantitative genetic models, our model allows for co-evolution of IGEs and variability, as the regression coefficient can respond to selection. Our simulations show that the model results in increased variability of body weight with increasing competition. When competition decreases, i.e., cooperation evolves, variability becomes significantly smaller. Hence, our model facilitates quantitative genetic studies on the relationship between IGEs and inherited variability. Moreover, our findings suggest that we may have been overlooking an entire level of genetic variation in variability, the one due to IGEs.

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  • 16.
    Saqlain, Murshid
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Mikrodataanalys.
    Alam, Moudud
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Brandt, Daniel
    Högskolan Dalarna, Akademin Industri och samhälle, Kulturgeografi.
    Rönnegård, Lars
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Westin, Jerker
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Stochastic differential equations modelling of levodopa concentration in patients with Parkinson's disease2018Konferensbidrag (Övrigt vetenskapligt)
    Abstract [en]

    The purpose of this study is to investigate a pharmacokinetic model of levodopa concentration in patients with Parkinson's disease by introducing stochasticity so that inter-individual variability may be separated into measurement and system noise. It also aims to investigate whether the stochastic differential equations (SDE) model provide better fits than its ordinary differential equations (ODE) counterpart, by using a real data set. Westin et al. developed a pharmacokinetic-pharmacodynamic model for duodenal levodopa infusion described by four ODEs, the first three of which define the pharmacokinetic model. In this study, system noise variables are added to the aforementioned first three equations through a standard Wiener process, also known as Brownian motion. The R package PSM for mixed-effects models is used on data from previous studies for modelling levodopa concentration and parameter estimation. First, the diffusion scale parameter, σ, and bioavailability are estimated with the SDE model. Second, σ is fixed to integer values between 1 and 5, and bioavailability is estimated. Cross-validation is performed to determine whether the SDE based model explains the observed data better or not by comparingthe average root mean squared errors (RMSE) of predicted levodopa concentration. Both ODE and SDE models estimated bioavailability to be about 88%. The SDE model converged at different values of σ that were signicantly different from zero while estimating bioavailability to be about 88%. The average RMSE for the ODE model wasfound to be 0.2980, and the lowest average RMSE for the SDE model was 0.2748 when σ was xed to 4. Both models estimated similar values for bioavailability, and the non-zero σ estimate implies that the inter-individual variability may be separated. However, the improvement in the predictive performance of the SDE model turned out to be rather small, compared to the ODE model.

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  • 17. Bring, Johan
    et al.
    Rönnegård, Lars
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Åldersbedömningar - en statistisk utmaning2018Ingår i: Folkvett, ISSN 0283-0795, nr 1, s. 7-13Artikel i tidskrift (Övrig (populärvetenskap, debatt, mm))
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  • 18. Zan, Yanjun
    et al.
    Sheng, Zheya
    Lillie, Mette
    Rönnegård, Lars
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik. SLU.
    Honaker, Christa F
    Siegel, Paul B
    Carlborg, Örjan
    Artificial selection response due to polygenic adaptation from a multilocus, multiallelic genetic architecture2017Ingår i: Molecular biology and evolution, ISSN 0737-4038, E-ISSN 1537-1719, Vol. 34, nr 10, s. 2678-2689Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The ability of a population to adapt to changes in their living conditions, whether in nature or captivity, often depends on polymorphisms in multiple genes across the genome. In-depth studies of such polygenic adaptations are difficult in natural populations, but can be approached using the resources provided by artificial selection experiments. Here, we dissect the genetic mechanisms involved in long-term selection responses of the Virginia chicken lines, populations that after 40 generations of divergent selection for 56-day body weight display a 9-fold difference in the selected trait. In the F15 generation of an intercross between the divergent lines, 20 loci explained >60% of the additive genetic variance for the selected trait. We focused particularly on fine-mapping seven major QTL that replicated in this population and found that only two fine-mapped to single, bi-allelic loci; the other five contained linked loci, multiple alleles or were epistatic. This detailed dissection of the polygenic adaptations in the Virginia lines provides a deeper understanding of the range of different genome-wide mechanisms that have been involved in these long-term selection responses. The results illustrate that the genetic architecture of a highly polygenic trait can involve a broad range of genetic mechanisms, and that this can be the case even in a small population bred from founders with limited genetic diversity.

  • 19. Lee, Youngjo
    et al.
    Rönnegård, Lars
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Noh, Maengseok
    Data Analysis Using Hierarchical Generalized Linear Models with R2017Bok (Övrigt vetenskapligt)
  • 20. Nelson, Ronald M
    et al.
    Temnykh, Svetlana V
    Johnson, Jennifer L
    Kharlamova, Anastasiya V
    Vladimirova, Anastasiya V
    Shepeleva, Darya V
    Rönnegård, Lars
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Trut, Lyudmila N
    Carlborg, Örjan
    Kukekova, Anna V
    Genetics of interactive behavior in silver foxes (Vulpes vulpes)2017Ingår i: Behavior Genetics, ISSN 0001-8244, E-ISSN 1573-3297, Vol. 47, nr 1, s. 88-101Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Individuals involved in a social interaction exhibit different behavioral traits that, in combination, form the individual's behavioral responses. Selectively bred strains of silver foxes (Vulpes vulpes) demonstrate markedly different behaviors in their response to humans. To identify the genetic basis of these behavioral differences we constructed a large F2 population including 537 individuals by cross-breeding tame and aggressive fox strains. 98 fox behavioral traits were recorded during social interaction with a human experimenter in a standard four-step test. Patterns of fox behaviors during the test were evaluated using principal component (PC) analysis. Genetic mapping identified eight unique significant and suggestive QTL. Mapping results for the PC phenotypes from different test steps showed little overlap suggesting that different QTL are involved in regulation of behaviors exhibited in different behavioral contexts. Many individual behavioral traits mapped to the same genomic regions as PC phenotypes. This provides additional information about specific behaviors regulated by these loci. Further, three pairs of epistatic loci were also identified for PC phenotypes suggesting more complex genetic architecture of the behavioral differences between the two strains than what has previously been observed.

  • 21. Silva, C. N. S
    et al.
    McFarlane, S. E
    Hagen, I. J
    Rönnegård, Lars
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik. Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala.
    Billing, A. M
    Kvalnes, T
    Kemppainen, P
    Rønning, B
    Ringsby, T. H
    Husby, A
    Insights into the genetic architecture of morphological traits in two passerine bird species2017Ingår i: Heredity, ISSN 0018-067X, E-ISSN 1365-2540, Vol. 119, nr 3, s. 197-205Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Knowledge about the underlying genetic architecture of phenotypic traits is needed to understand and predict evolutionary dynamics. The number of causal loci, magnitude of the effects and location in the genome are, however, still largely unknown. Here, we use genome-wide single-nucleotide polymorphism (SNP) data from two large-scale data sets on house sparrows and collared flycatchers to examine the genetic architecture of different morphological traits (tarsus length, wing length, body mass, bill depth, bill length, total and visible badge size and white wing patches). Genomic heritabilities were estimated using relatedness calculated from SNPs. The proportion of variance captured by the SNPs (SNP-based heritability) was lower in house sparrows compared with collared flycatchers, as expected given marker density (6348 SNPs in house sparrows versus 38 689 SNPs in collared flycatchers). Indeed, after downsampling to similar SNP density and sample size, this estimate was no longer markedly different between species. Chromosome-partitioning analyses demonstrated that the proportion of variance explained by each chromosome was significantly positively related to the chromosome size for some traits and, generally, that larger chromosomes tended to explain proportionally more variation than smaller chromosomes. Finally, we found two genome-wide significant associations with very small-effect sizes. One SNP on chromosome 20 was associated with bill length in house sparrows and explained 1.2% of phenotypic variation (VP), and one SNP on chromosome 4 was associated with tarsus length in collared flycatchers (3% of VP). Although we cannot exclude the possibility of undetected large-effect loci, our results indicate a polygenic basis for morphological traits.

  • 22.
    Svenson, Kristin
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Li, Yujiao
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Macuchova, Zuzana
    Högskolan Dalarna, Akademin Industri och samhälle, Kulturgeografi.
    Rönnegård, Lars
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Evaluating needs of road maintenance in Sweden with the mixed proportional hazards model2016Ingår i: Transportation Research Record, ISSN 0361-1981, E-ISSN 2169-4052, nr 2589, s. 51-58Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    National road databases often lack important information for long-term maintenance planning of paved roads. In the Swedish case, latent variables of which there are no recordings in the pavement management systems database are, for example, underlying road construction, subsoil conditions, and amount of heavy traffic measured by the equivalent single-axle load. The mixed proportional hazards model with random effects was used to capture the effect of these latent variables on a road's risk of needing maintenance. Estimation of random effects makes it possible to identify sections that have shorter or longer lifetimes than could be expected from the observed explanatory variables (traffic load, pavement type, road type, climate zone, road width, speed limit, and bearing capacity restrictions). The results indicate that the mixed proportional hazards model is useful for maintenance planning because the weakest and strongest sections in a road network can be identified. The effect of the latent variables was visualized by,plotting the random effect of each section in a map of the road network. In addition, the spatial correlation between road sections was evaluated by fitting the random effects in an intrinsic conditional autoregressive model. The spatial correlation was estimated to explain 17% of the variation in lifetimes of roads that occur because of the latent variables. The Swedish example shows that the mixed proportional hazards and intrinsic conditional autoregressive models are suitable for analyzing the effect of latent variables in national road databases.

  • 23.
    Rönnegård, Lars
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    McFarlane, S. Eryn
    Uppsala universitet.
    Husby, Arlid
    University of Helsinki; Norwegian University of Science and Technology.
    Kawakami, Takeshi
    Uppsala universitet.
    Ellegren, Hans
    Uppsala universitet.
    Qvarnström, Anna
    Uppsala universitet.
    Increasing the power of genome wide association studies in natural populations using repeated measures: evaluation and implementation2016Ingår i: Methods in Ecology and Evolution, E-ISSN 2041-210X, Vol. 7, nr 7, s. 792-799Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    1. Genomewide association studies (GWAS) enable detailed dissections of the genetic basis for organisms' ability to adapt to a changing environment. In long-term studies of natural populations, individuals are often marked at one point in their life and then repeatedly recaptured. It is therefore essential that a method for GWAS includes the process of repeated sampling. In a GWAS, the effects of thousands of single-nucleotide polymorphisms (SNPs) need to be fitted and any model development is constrained by the computational requirements. A method is therefore required that can fit a highly hierarchical model and at the same time is computationally fast enough to be useful.

    2. Our method fits fixed SNP effects in a linear mixed model that can include both random polygenic effects and permanent environmental effects. In this way, the model can correct for population structure and model repeated measures. The covariance structure of the linear mixed model is first estimated and subsequently used in a generalized least squares setting to fit the SNP effects. The method was evaluated in a simulation study based on observed genotypes from a long-term study of collared flycatchers in Sweden.

    3. The method we present here was successful in estimating permanent environmental effects from simulated repeated measures data. Additionally, we found that especially for variable phenotypes having large variation between years, the repeated measurements model has a substantial increase in power compared to a model using average phenotypes as a response.

    4. The method is available in the R package RepeatABEL. It increases the power in GWAS having repeated measures, especially for long-term studies of natural populations, and the R implementation is expected to facilitate modelling of longitudinal data for studies of both animal and human populations.

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  • 24. Sivertsen, Therese R.
    et al.
    Åhman, Birgitta
    Steyaert, Sam M. J. G.
    Rönnegård, Lars
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Frank, Jens
    Segerström, Peter
    Støen, Ole-Gunnar
    Skarin, Anna
    Reindeer habitat selection under the risk of brown bear predation during calving season2016Ingår i: Ecosphere, ISSN 2150-8925, E-ISSN 2150-8925, Vol. 7, nr 11, artikel-id e01583Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The depredation of semi-domesticated reindeer by large carnivores reflects an important human-wildlife conflict in Fennoscandia. Recent studies have revealed that brown bears (Ursus arctos) may kill substantial numbers of reindeer calves (Rangifer tarandus tarandus) in forest areas in Sweden. Several authors have suggested that predation risk is an important driver of habitat selection in wild Rangifer populations where predation is a limiting factor, but little is known about these mechanisms in semi-domesticated populations. We examined the habitat selection of female reindeer in relation to spatial and temporal variations in brown bear predation risk on the reindeer calving grounds and evaluated the simultaneous responses of brown bears and reindeer to landscape characteristics. We used GPS data from 110 reindeer years (97 individuals) and 29 brown bear years (19 individuals), from two reindeer herding districts in the forest area of northern Sweden. Our results did not indicate that reindeer alter their behavior in response to spatiotemporal variation in brown bear predation risk, on the scale of the calving range. Instead, we suggest that spatiotemporal behavioral adjustments by brown bears were the main driver of prey-predator interactions in our study system. Contrasting responses by brown bears and reindeer to clear-cuts and young forest indicate that forestry can influence species interactions and possibly yield negative consequences for the reindeer herd. Even if clear-cuts may be beneficial in terms of calf survival, logging activity will eventually cause greater abundance of young regenerating forest, reducing available reindeer habitats and increasing habitat preferred by brown bears. Domestication may have made semi-domesticated reindeer in Fennoscandia less adapted to cope with predators. Areal restrictions, limiting the opportunity for dispersion and escape, possibly make the calves more susceptible to predation. Also, a generally higher population density in semi-domesticated herds compared to wild populations can make dispersion a less efficient strategy and the reindeer calves easier prey. Overall, the lack of ability of the reindeer females to reduce brown bear encounter risk on the scale of the calving range is probably an important reason for the high brown bear predation rates on reindeer calves documented in our study areas. 

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  • 25.
    Youngjo, Lee
    et al.
    Seoul National University.
    Alam, Moudud
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Noh, Maengseok
    Pukyong National University, Korea.
    Rönnegård, Lars
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Skarin, Anna
    Swedish University of Agricultural Science, Uppsala.
    Spatial modeling of data with excessive zeros applied to reindeer pellet-group counts2016Ingår i: Ecology and Evolution, E-ISSN 2045-7758, Vol. 6, nr 19, s. 7047-7056Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    We analyze a real data set pertaining to reindeer fecal pellet-group counts obtained from a survey conducted in a forest area in northern Sweden. In the data set, over 70% of counts are zeros, and there is high spatial correlation. We use conditionally autoregressive random effects for modeling of spatial correlation in a Poisson generalized linear mixed model (GLMM), quasi-Poisson hierarchical generalized linear model (HGLM), zero-inflated Poisson (ZIP), and hurdle models. The quasi-Poisson HGLM allows for both under- and overdispersion with excessive zeros, while the ZIP and hurdle models allow only for overdispersion. In analyzing the real data set, we see that the quasi-Poisson HGLMs can perform better than the other commonly used models, for example, ordinary Poisson HGLMs, spatial ZIP, and spatial hurdle models, and that the underdispersed Poisson HGLMs with spatial correlation fit the reindeer data best. We develop R codes for fitting these models using a unified algorithm for the HGLMs. Spatial count response with an extremely high proportion of zeros, and underdispersion can be successfully modeled using the quasi-Poisson HGLM with spatial random effects.

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  • 26.
    Han, Mengjie
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik. HUI Research.
    Håkansson, Johan
    Högskolan Dalarna, Akademin Industri och samhälle, Informatik. Högskolan Dalarna, Akademin Industri och samhälle, Kulturgeografi. HUI Research, Stockholm.
    Rönnegård, Lars
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik. HUI Research, Stockholm.
    To what extent do neighbouring populations affect local population growth over time?2016Ingår i: Population, Space and Place, ISSN 1544-8444, E-ISSN 1544-8452, Vol. 22, nr 1, s. 68-83Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This study covers a period when society changed from a pre-industrial agricultural society to a post-industrial service-producing society. Parallel with this social transformation, major population changes took place. In this study, we analyse to what extent local population change is affected by neighbouring populations. To do this, we focused on the last 190 years of local population change that redistributed population in Sweden. We used literature to identify several different processes in the population redistribution. The different processes implied different spatial dependencies between local population change and the surrounding populations. The analysis is based on an unchanged historical parish division, and we used an index of local spatial correlation to describe different types of spatial dependencies that influenced the redistribution of the population. To control inherent time dependencies, we introduced a non-separable spatial-temporal correlation model into the analysis of population redistribution. Hereby, several different spatial dependencies could be simultaneously observed over time. The main conclusions are that while local population changes have been highly dependent on neighbouring populations in the 19th century, this spatial dependence became insignificant already when two parishes are separated by 5 km in the late 20th century. It is argued that the only process that significantly redistributed the population at the end of the 20th century is the immigration to Sweden.

  • 27.
    Alam, Moudud
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Rönnegård, Lars
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Shen, Xia
    Karolinska Institutet.
    Fitting conditional and simultaneous autoregressive spatial models in hglm2015Ingår i: The R Journal, E-ISSN 2073-4859, Vol. 7, nr 2, s. 5-18Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    We present a new version (> 2.0) of the hglm package for fitting hierarchical generalized linear models (HGLMs) with spatially correlated random effects. CAR() and SAR() families for conditional and simultaneous autoregressive random effects were implemented. Eigen decomposition of the matrix describing the spatial structure (e.g., the neighborhood matrix) was used to transform the CAR/SAR random effects into an independent, but eteroscedastic, Gaussian random effect. A linear predictor is fitted for the random effect variance to estimate the parameters in the CAR and SAR models. This gives a computationally efficient algorithm for moderately sized problems.

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  • 28. Husby, Arild
    et al.
    Kawakami, Takeshi
    Rönnegård, Lars
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik. SLU.
    Smeds, Linnéa
    Ellegren, Hans
    Qvarnström, Anna
    Genome-wide association mapping in a wild avian population identifies a link between genetic and phenotypic variation in a life-history trait2015Ingår i: Proceedings of the Royal Society of London. Biological Sciences, ISSN 0962-8452, E-ISSN 1471-2954, Vol. 282, nr 1806Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Understanding the genetic basis of traits involved in adaptation is a major challenge in evolutionary biology but remains poorly understood. Here, we use genome-wide association mapping using a custom 50 k single nucleotide polymorphism (SNP) array in a natural population of collared flycatchers to examine the genetic basis of clutch size, an important life-history trait in many animal species. We found evidence for an association on chromosome 18 where one SNP significant at the genome-wide level explained 3.9% of the phenotypic variance. We also detected two suggestive quantitative trait loci (QTLs) on chromosomes 9 and 26. Fitness differences among genotypes were generally weak and not significant, although there was some indication of a sex-by-genotype interaction for lifetime reproductive success at the suggestive QTL on chromosome 26. This implies that sexual antagonism may play a role in maintaining genetic variation at this QTL. Our findings provide candidate regions for a classic avian life-history trait that will be useful for future studies examining the molecular and cellular function of, as well as evolutionary mechanisms operating at, these loci.

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  • 29. Casals, M.
    et al.
    Langohr, K.
    Carrasco, J. L.
    Rönnegård, Lars
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Parameter estimation of Poisson generalized linear mixed models based on three different statistical principles: a simulation study2015Ingår i: SORT - Statistics and Operations Research Transactions, ISSN 1696-2281, E-ISSN 2013-8830, Vol. 39, nr 2, s. 281-308Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Generalized linear mixed models are flexible tools for modeling non-normal data and are useful for accommodating overdispersion in Poisson regression models with random effects. Their main difficulty resides in the parameter estimation because there is no analytic solution for the maximization of the marginal likelihood. Many methods have been proposed for this purpose and many of them are implemented in software packages. The purpose of this study is to compare the performance of three different statistical principles - marginal likelihood, extended likelihood, Bayesian analysis-via simulation studies. Real data on contact wrestling are used for illustration.

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  • 30.
    Skarin, Anna
    et al.
    Swedish Univ Agr Sci, Dept Anim Nutr & Management, Uppsala.
    Nellemann, Christian
    GRID Arendal, United Nations Environm Programme, Lillehammer, Norway..
    Rönnegård, Lars
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Sandstrom, Per
    Swedish Univ Agr Sci, Dept Forest Resource Management, Umea, Sweden.
    Lundqvist, Henrik
    Swedish Univ Agr Sci, Dept Anim Nutr & Management, Uppsala, Sweden.
    Wind farm construction impacts reindeer migration and movement corridors2015Ingår i: Landscape Ecology, ISSN 0921-2973, E-ISSN 1572-9761, Vol. 30, nr 8, s. 1527-1540Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Over the last decade, we have seen a massive increase in the construction of wind farms in northern Fennoscandia. Wind farms comprising hundreds of wind turbines are being built, with little knowledge of the possible cumulative adverse effects on the habitat use and migration of semi-domesticated free-ranging reindeer. We assessed how reindeer responded to wind farm construction in an already fragmented landscape, with specific reference to the effects on use of movement corridors and reindeer habitat selection. We used GPS-data from reindeer during calving and post-calving in the MalAyen reindeer herding community in Sweden. We analysed data from the pre-development years compared to the construction years of two relatively small wind farms. During construction of the wind farms, use of original migration routes and movement corridors within 2 km of development declined by 76 %. This decline in use corresponded to an increase in activity of the reindeer measured by increased step lengths within 0-5 km. The step length was highest nearest the development and declining with distance, as animals moved towards migration corridors and turned around or were observed in holding patterns while not crossing. During construction, reindeer avoided the wind farms at both regional and landscape scale of selection. The combined construction activities associated with even a few wind turbines combined with power lines and roads in or close to central movement corridors caused a reduction in the use of such corridors and grazing habitat and increased the fragmentation of the reindeer calving ranges.

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  • 31. Shen, Xia
    et al.
    Li, Ying
    Rönnegård, Lars
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Uden, Peter
    Carlborg, Orjan
    Application of a genomic model for high-dimensional chemometric analysis2014Ingår i: Journal of Chemometrics, ISSN 0886-9383, E-ISSN 1099-128X, Vol. 28, nr 7, s. 548-557Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The rapid development of newtechnologies for large-scale analysis of genetic variation in the genomes of individuals and populations has presented statistical geneticists with a grand challenge to develop efficient methods for identifying the small proportion of all identified genetic polymorphisms that have effects on traits of interest. To address such a "large p small n" problem, we have developed a heteroscedastic effects model (HEM) that has been shown to be powerful in high-throughput genetic analyses. Here, we describe how this whole-genome model can also be utilized in chemometric analysis. As a proof of concept, we use HEM to predict analyte concentrations in silage using Fourier transform infrared spectroscopy signals. The results show that HEM often outperforms the classic methods and in addition to this presents a substantial computational advantage in the analyses of such high-dimensional data. The results thus show the value of taking an interdisciplinary approach to chemometric analysis and indicate that large-scale genomic models can be a promising new approach for chemometric analysis that deserve to be evaluated more by experts in the field. The software used for our analyses is freely available as an R package at http://cran.r-project.org/web/packages/bigRR/. Copyright (C) 2014 JohnWiley & Sons, Ltd.

  • 32.
    Alam, Moudud
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Rönnegård, Lars
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Shen, Xia
    Swedish University of Agricultural Sciences, Uppsala.
    Fitting spatial models in the R package: hglm2014Rapport (Övrigt vetenskapligt)
    Abstract [en]

    We present a new version of the hglm package for fittinghierarchical generalized linear models (HGLM) with spatially correlated random effects. A CAR family for conditional autoregressive random effects was implemented. Eigen decomposition of the matrix describing the spatial structure (e.g. the neighborhood matrix) was used to transform the CAR random effectsinto an independent, but heteroscedastic, gaussian random effect. A linear predictor is fitted for the random effect variance to estimate the parameters in the CAR model.This gives a computationally efficient algorithm for moderately sized problems (e.g. n<5000).

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  • 33. Ahman, Birgitta
    et al.
    Svensson, Kristin
    Rönnegård, Lars
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    High female mortality resulting in herd collapse in free-ranging domesticated reindeer (Rangifer tarandus tarandus) in Sweden2014Ingår i: PLOS ONE, E-ISSN 1932-6203, Vol. 9, nr 10, artikel-id e111509Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Reindeer herding in Sweden is a form of pastoralism practised by the indigenous Sami population. The economy is mainly based on meat production. Herd size is generally regulated by harvest in order not to overuse grazing ranges and keep a productive herd. Nonetheless, herd growth and room for harvest is currently small in many areas. Negative herd growth and low harvest rate were observed in one of two herds in a reindeer herding community in Central Sweden. The herds (A and B) used the same ranges from April until the autumn gathering in October-December, but were separated on different ranges over winter. Analyses of capture-recapture for 723 adult female reindeer over five years (2007-2012) revealed high annual losses (7.1% and 18.4%, for herd A and B respectively). A continuing decline in the total reindeer number in herd B demonstrated an inability to maintain the herd size in spite of a very small harvest. An estimated breakpoint for when herd size cannot be kept stable confirmed that the observed female mortality rate in herd B represented a state of herd collapse. Lower calving success in herd B compared to A indicated differences in winter foraging conditions. However, we found only minor differences in animal body condition between the herds in autumn. We found no evidence that a lower autumn body mass generally increased the risk for a female of dying from one autumn to the next. We conclude that the prime driver of the on-going collapse of herd B is not high animal density or poor body condition. Accidents or disease seem unlikely as major causes of mortality. Predation, primarily by lynx and wolverine, appears to be the most plausible reason for the high female mortality and state of collapse in the studied reindeer herding community.

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  • 34.
    Shen, Xia
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Alam, Moudud
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Fikse, Freddy
    Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala.
    Rönnegård, Lars
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    A novel generalized ridge regression method for quantitative genetics2013Ingår i: Genetics, ISSN 0016-6731, E-ISSN 1943-2631, Vol. 193, nr 4, s. 1255-1268Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    As the molecular marker density grows, there is a strong need in both genome-wide association studies and genomic selection to fit models with a large number of parameters. Here we present a computationally efficient generalized ridge regression (RR) algorithmfor situations where the number of parameters largely exceeds the number of observations. The computationally demanding parts of the method depend mainly on the number ofobservations and not the number of parameters. The algorithm was implemented in the R package bigRR based on the previously developed package hglm. Using such an approach, a heteroscedastic effects model (HEM) was also developed, implemented and tested. Theefficiency for different data sizes were evaluated via simulation. The method was tested for a bacteria-hypersensitive trait in a publicly available Arabidopsis dataset including 84 inbred lines and 216 130 SNPs. The computation of all the SNP effects required less than10 seconds using a single 2.7 GHz core. The advantage in run-time makes permutationtest feasible for such a whole-genome model, so that a genome-wide significance threshold can be obtained. HEM was found to be more robust than ordinary RR (a.k.a. SNPBLUP) in terms of QTL mapping, because SNP specific shrinkage was applied instead of acommon shrinkage. The proposed algorithm was also assessed for genomic evaluation and was shown to give better predictions than ordinary RR.

  • 35. Lee, Youngjo
    et al.
    Alam, Moudud
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Noh, M
    Rönnegård, Lars
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Skarin, Anna
    Analyzing spatially correlated counts with excessive zeros: a case of modeling the changes of reindeer distribution2013Rapport (Övrigt vetenskapligt)
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    WP_2013
  • 36. Mulder, Han A.
    et al.
    Rönnegård, Lars
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Fikse, W Freddy
    Veerkamp, R F
    Strandberg, E
    Estimation of genetic variance for macro- and micro-environmental sensitivity using double hierarchical generalized linear models2013Ingår i: Genetics Selection Evolution, ISSN 0999-193X, E-ISSN 1297-9686, Vol. 45, artikel-id 23Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    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.

    Ladda ner fulltext (pdf)
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  • 37.
    Rönnegård, Lars
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik. Swedish University of Agricultural Sciences, Uppsala, Sweden.
    Lee, Y
    Seoul National University, Seoul, Korea.
    Exploring the potential of hierarchical generalized linear models in animal breeding and genetics2013Ingår i: Journal of Animal Breeding and Genetics, ISSN 0931-2668, E-ISSN 1439-0388, Vol. 130, nr 6, s. 415-416Artikel i tidskrift (Refereegranskat)
  • 38. Shukur, Ghazi
    et al.
    Rönnegård, Lars
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Framtida utmaningar för forskarutbildningen i statistik2013Ingår i: Qvintensen, ISSN 2000-1819, nr 4, s. 21-21Artikel i tidskrift (Övrig (populärvetenskap, debatt, mm))
  • 39. Sonesson, Anna K
    et al.
    Odegård, Jørgen
    Rönnegård, Lars
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Genetic heterogeneity of within-family variance of body weight in Atlantic salmon (Salmo salar)2013Ingår i: Genetics Selection Evolution, ISSN 0999-193X, E-ISSN 1297-9686, Vol. 45, artikel-id 41Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    BACKGROUND: Canalization is defined as the stability of a genotype against minor variations in both environment and genetics. Genetic variation in degree of canalization causes heterogeneity of within-family variance. The aims of this study are twofold: (1) quantify genetic heterogeneity of (within-family) residual variance in Atlantic salmon and (2) test whether the observed heterogeneity of (within-family) residual variance can be explained by simple scaling effects.

    RESULTS: Analysis of body weight in Atlantic salmon using a double hierarchical generalized linear model (DHGLM) revealed substantial heterogeneity of within-family variance. The 95% prediction interval for within-family variance ranged from ~0.4 to 1.2 kg2, implying that the within-family variance of the most extreme high families is expected to be approximately three times larger than the extreme low families. For cross-sectional data, DHGLM with an animal mean sub-model resulted in severe bias, while a corresponding sire-dam model was appropriate. Heterogeneity of variance was not sensitive to Box-Cox transformations of phenotypes, which implies that heterogeneity of variance exists beyond what would be expected from simple scaling effects.

    CONCLUSIONS: Substantial heterogeneity of within-family variance was found for body weight in Atlantic salmon. A tendency towards higher variance with higher means (scaling effects) was observed, but heterogeneity of within-family variance existed beyond what could be explained by simple scaling effects. For cross-sectional data, using the animal mean sub-model in the DHGLM resulted in biased estimates of variance components, which differed substantially both from a standard linear mean animal model and a sire-dam DHGLM model. Although genetic differences in canalization were observed, selection for increased canalization is difficult, because there is limited individual information for the variance sub-model, especially when based on cross-sectional data. Furthermore, potential macro-environmental changes (diet, climatic region, etc.) may make genetic heterogeneity of variance a less stable trait over time and space.

    Ladda ner fulltext (pdf)
    fulltext
  • 40.
    Han, Mengjie
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Håkansson, Johan
    Högskolan Dalarna, Akademin Industri och samhälle, Kulturgeografi.
    Rönnegård, Lars
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    How do neighbouring populations affect local population change over time?2013Rapport (Övrigt vetenskapligt)
    Abstract [en]

    This study covers a period when society changed from a pre-industrial agricultural society to a post-industrial service-producing society. Parallel with this social transformation, major population changes took place. In this study, we analyse how local population changes are affected by neighbouring populations. To do so we use the last 200 years of local population change that redistributed population in Sweden. We use literature to identify several different processes and spatial dependencies in the redistribution between a parish and its surrounding parishes. The analysis is based on a unique unchanged historical parish division, and we use an index of local spatial correlation to describe different kinds of spatial dependencies that have influenced the redistribution of the population. To control inherent time dependencies, we introduce a non-separable spatial temporal correlation model into the analysis of population redistribution. Hereby, several different spatial dependencies can be observed simultaneously over time. The main conclusions are that while local population changes have been highly dependent on the neighbouring populations in the 19th century, this spatial dependence have become insignificant already when two parishes is separated by 5 kilometres in the late 20th century. Another conclusion is that the time dependency in the population change is higher when the population redistribution is weak, as it currently is and as it was during the 19th century until the start of industrial revolution.

    Ladda ner fulltext (pdf)
    fulltext
  • 41.
    Shen, Xia
    et al.
    SLUDivision of Computational Genetics, Department of Clinical Sciences, Swedish University of Agricultural Sciences, Uppsala.
    Rönnegård, Lars
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik. Division of Quantitative Genetics, Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala.
    Issues with data transformation in genome-wide association studies for phenotypic variability2013Ingår i: F1000Research, ISSN 2046-1402, Vol. 2, nr 200Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The purpose of this correspondence is to discuss and clarify a few points about data transformation used in genome-wide association studies, especially for phenotypic variability. By commenting on the recent publication by Sun et al. in the American Journal of Human Genetics, we emphasize the importance of statistical power in detecting functional loci and the real meaning of the scale of the phenotype in practice.

  • 42.
    Nelson, Ronald Michael
    et al.
    Swedish University of Agricultural Sciences.
    Nettelblad, Carl
    Uppsala University.
    Pettersson, Mats E
    Swedish University of Agricultural Sciences.
    Shen, Xia
    Swedish University of Agricultural Sciences; Uppsala University;.
    Crooks, Lucy
    Swedish University of Agricultural Sciences.
    Besnier, Francois
    Swedish University of Agricultural Sciences.
    Alvarez-Castro, José
    Swedish University of Agricultural Sciences.
    Rönnegård, Lars
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Ek, Weronica
    Swedish University of Agricultural Sciences.
    Carlborg, Örjan
    Swedish University of Agricultural Sciences.
    MAPfastR: quantitative trait loci mapping in outbred line crosses2013Ingår i: G3: Genes, Genomes, Genetics, E-ISSN 2160-1836, Vol. 12, nr 3, s. 2147-2149Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    MAPfastR is a software package developed to analyze QTL data from inbred and outbred line-crosses. The package includes a number of modules for fast and accurate QTL analyses. It has been developed in the R language for fast and comprehensive analyses of large datasets. MAPfastR is freely available at: http://www.computationalgenetics.se/?page_id=7.

    Ladda ner fulltext (pdf)
    fulltext
  • 43. Skarin, Anna
    et al.
    Helleman, Christian
    Sandström, Per
    Rönnegård, Lars
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Lundquist, Henrik
    Renar och vindkraft: Studie från anläggningen av två vindkraftparker i Malå sameby2013Rapport (Övrigt vetenskapligt)
    Abstract [sv]

    Studien undersöker hur renar påverkas under konstruktionsfasen när vindkraftverk byggs. Studien följer uppförandet av två nya vindparker i Malå kommun i Västerbotten. Sammanlagt byggdes 18 vindkraftverk i Malå samebys kalvnings- och försommarland. Inventering av renspillning samt positioner från renar med GPS-halsband visar att konstruktionen av vindkraftsparkerna har påverkat renarnas användning av området. Analysen visar att renarna under tiden för byggnationen har sökt sig bort från området. Spillningsinventeringen och GPS-data visar också att renarna undviker kraftledningar och större vägar när de ska beta.

    Rapport från kunskapsprogrammet Vindval.

  • 44.
    Strandberg, E
    et al.
    SLU.
    Felleki, Majbritt
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Fikse, W F
    SLU.
    Franzén, J
    Stockholms Universitet.
    Mulder, H A
    Rönnegård, Lars
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Urioste, J I
    Windig, J J
    Statistical tools to select for robustness and milk quality2013Ingår i: Advances in Animal Biosciences, ISSN 2040-4719, Vol. 4, nr 3, s. 606-611Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    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.

  • 45.
    Rönnegård, Lars
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik. Swedish Univ Agr Sci, Dept Anim Breeding & Genet, S-75007 Uppsala, Sweden.
    Felleki, Majbritt
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik. Swedish Univ Agr Sci, Dept Anim Breeding & Genet, S-75007 Uppsala, Sweden.
    Fikse, W. F.
    Mulder, H. A.
    Strandberg, E.
    Variance component and breeding value estimation for genetic heterogeneity of residual variance in Swedish Holstein dairy cattle2013Ingår i: Journal of Dairy Science, ISSN 0022-0302, E-ISSN 1525-3198, Vol. 96, nr 4, s. 2627-2636Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    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.

  • 46. Alvarez-Castro, J.M.
    et al.
    Carlborg, Ö.
    Rönnegård, Lars
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Estimation and interpretation of genetic effects with epistasis using the NOIA model2012Ingår i: Quantitative trait loci (QTL): Methods and Protocols / [ed] Scott A. Rifkin, Humana Press, 2012, s. 191-204Kapitel i bok, del av antologi (Övrigt vetenskapligt)
    Abstract [en]

    We introduce this communication with a brief outline of the historical landmarks in genetic modeling, especially concerning epistasis. Then, we present methods for the use of genetic modeling in QTL analyses. In particular, we summarize the essential expressions of the natural and orthogonal interactions (NOIA) model of genetic effects. Our motivation for reviewing that theory here is twofold. First, this review presents a digest of the expressions for the application of the NOIA model, which are often mixed with intermediate and additional formulae in the original articles. Second, we make the required theory handy for the reader to relate the genetic concepts to the particular mathematical expressions underlying them. We illustrate those relations by providing graphical interpretations and a diagram summarizing the key features for applying genetic modeling with epistasis in comprehensive QTL analyses. Finally, we briefly review some examples of the application of NOIA to real data and the way it improves the interpretability of the results.

  • 47.
    Felleki, Majbritt
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Lee, Dongwhan
    Department of Statistics, Seoul National University, Seoul 151-747, Korea .
    Lee, Youngjo
    Department of Statistics, Seoul National University, Seoul 151-747, Korea .
    Gilmour, Arthur R.
    School of Mathematics and Applied Statistics, Faculty of Informatics, University of Wollongong, Wollongong, NSW 2522, Australia.
    Rönnegård, Lars
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Estimation of breeding values for mean and dispersion, their variance and correlation using double hierarchical generalized linear models2012Ingår i: Genetics Research, ISSN 0016-6723, Vol. 94, nr 6, s. 307-317Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The possibility of breeding for uniform individuals by selecting animals expressing a small response to environment has been studied extensively in animal breeding. Bayesian methods for fitting models with genetic components in the residual variance have been developed for this purpose, but have limitations due to the computational demands. We use the hierarchical (h)-likelihood from the theory of double hierarchical generalized linear models (DHGLM) to derive an estimation algorithm that is computationally feasible for large datasets. Random effects for both the mean and residual variance parts of the model are estimated together with their variance/covariance components. An important feature of the algorithm is that it can fit a correlation between the random effects for mean and variance. An h-likelihood estimator is implemented in the R software and an iterative reweighted least square (IRWLS) approximation of the h-likelihood is implemented using ASReml. The difference in variance component estimates between the two implementations is investigated, as well as the potential bias of the methods, using simulations. IRWLS gives the same results as h-likelihood in simple cases with no severe indication of bias. For more complex cases, only IRWLS could be used, and bias did appear. The IRWLS is applied on the pig litter size data previously analysed by Sorensen & Waagepetersen (2003) using Bayesian methodology. The estimates we obtained by using IRWLS are similar to theirs, with the estimated correlation between the random genetic effects being −0·52 for IRWLS and −0·62 in Sorensen & Waagepetersen (2003).

  • 48.
    Shen, Xia
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Pettersson, Mats
    Rönnegård, Lars
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Carlborg, Örjan
    Inheritance beyond plain heritability: variance-controlling genes in Arabidopsis thaliana2012Ingår i: PLOS Genetics, ISSN 1553-7390, E-ISSN 1553-7404, Vol. 8, nr 8, artikel-id e1002839Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The phenotypic effect of a gene is normally described by the mean-difference between alternative genotypes. A gene may, however, also influence the phenotype by causing a difference in variance between genotypes. Here, we reanalyze a publicly available Arabidopsis thaliana dataset [1] and show that genetic variance heterogeneity appears to be as common as normal additive effects on a genomewide scale. The study also develops theory to estimate the contributions of variance differences between genotypes to the phenotypic variance, and this is used to show that individual loci can explain more than 20% of the phenotypic variance. Two well-studied systems, cellular control of molybdenum level by the ion-transporter MOT1 and flowering-time regulation by the FRI-FLC expression network, and a novel association for Leaf serration are used to illustrate the contribution of major individual loci, expression pathways, and gene-by-environment interactions to the genetic variance heterogeneity.

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    fulltext
  • 49.
    Rönnegård, Lars
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Valdar, William
    Recent developments in statistical methods for detecting genetic loci affecting phenotypic variability2012Ingår i: BMC Genetics, E-ISSN 1471-2156, Vol. 13, artikel-id 63Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    A number of recent works have introduced statistical methods for detecting genetic loci that affect phenotypic variability, which we refer to as variability-controlling quantitative trait loci (vQTL). These are genetic variants whose allelic state predicts how much phenotype values will vary about their expected means. Such loci are of great potential interest in both human and non-human genetic studies, one reason being that a detected vQTL could represent a previously undetected interaction with other genes or environmental factors. The simultaneous publication of these new methods in different journals has in many cases precluded opportunity for comparison. We survey some of these methods, the respective trade-offs they imply, and the connections between them. The methods fall into three main groups: classical non-parametric, fully parametric, and semi-parametric two-stage approximations. Choosing between alternatives involves balancing the need for robustness, flexibility, and speed. For each method, we identify important assumptions and limitations, including those of practical importance, such as their scope for including covariates and random effects. We show in simulations that both parametric methods and their semi-parametric approximations can give elevated false positive rates when they ignore mean-variance relationships intrinsic to the data generation process. We conclude that choice of method depends on the trait distribution, the need to include non-genetic covariates, and the population size and structure, coupled with a critical evaluation of how these fit with the assumptions of the statistical model.

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  • 50.
    Rönnegård, Lars
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Statistik.
    Fikse, Freddy
    Mulder, Herman
    Strandberg, E
    Breeding Value Estimation for Environmental Sensitivity on a Large Dairy Cattle Data Set2011Ingår i: Interbull Meeting, Stavanger, Norway, 2011Konferensbidrag (Övrigt vetenskapligt)
    Abstract [en]

    Animal robustness, or environmental sensitivity, may be studied through individual differences in re-sidual variance. These differences appear to be heritable, and there is therefore a need to fit models having breeding values explaining differences in residual variance. The aim of this report is to study whether breeding value estimation for environmental sensitivity (vEBV) can be performed on a large dairy cattle data set having around 1.6 million records. Two traits were analyzed separately, somatic cell score and milk yield. Estimation of variance components, ordinary breeding values and vEBVs was performed using standard variance component estimation software (ASReml), applying the me-thodology for double hierarchical generalized linear models. Converged estimates were obtained by running ASReml iteratively 20 times, which took less than 10 days on a Linux server. The genetic coefficients of variation for environmental variance were 0.45 and 0.52, for somatic cell score and milk yield, respectively, which indicate a substantial genetic variance for environmental variance. This study shows that estimation of variance components, EBVs and vEBVs, is feasible for large dairy cattle data sets using standard variance component estimation software.

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