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  • 1. Ahsan, Muhammad
    et al.
    Li, Xidan
    Lundberg, Andreas E
    Kierczak, Marcin
    Siegel, Paul B
    Carlborg, Örjan
    SLU.
    Marklund, Stefan
    Identification of candidate genes and mutations in QTL regions for chicken growth using bioinformatic analysis of NGS and SNP-chip data.2013In: Frontiers in Genetics, ISSN 1664-8021, E-ISSN 1664-8021, Vol. 4Article in journal (Refereed)
    Abstract [en]

    Mapping of chromosomal regions harboring genetic polymorphisms that regulate complex traits is usually followed by a search for the causative mutations underlying the observed effects. This is often a challenging task even after fine mapping, as millions of base pairs including many genes will typically need to be investigated. Thus to trace the causative mutation(s) there is a great need for efficient bioinformatic strategies. Here, we searched for genes and mutations regulating growth in the Virginia chicken lines - an experimental population comprising two lines that have been divergently selected for body weight at 56 days for more than 50 generations. Several quantitative trait loci (QTL) have been mapped in an F2 intercross between the lines, and the regions have subsequently been replicated and fine mapped using an Advanced Intercross Line. We have further analyzed the QTL regions where the largest genetic divergence between the High-Weight selected (HWS) and Low-Weight selected (LWS) lines was observed. Such regions, covering about 37% of the actual QTL regions, were identified by comparing the allele frequencies of the HWS and LWS lines using both individual 60K SNP chip genotyping of birds and analysis of read proportions from genome resequencing of DNA pools. Based on a combination of criteria including significance of the QTL, allele frequency difference of identified mutations between the selected lines, gene information on relevance for growth, and the predicted functional effects of identified mutations we propose here a subset of candidate mutations of highest priority for further evaluation in functional studies. The candidate mutations were identified within the GCG, IGFBP2, GRB14, CRIM1, FGF16, VEGFR-2, ALG11, EDN1, SNX6, and BIRC7 genes. We believe that the proposed method of combining different types of genomic information increases the probability that the genes underlying the observed QTL effects are represented among the candidate mutations identified.

  • 2. Albert, F. W.
    et al.
    Hodges, E.
    Jensen, J. D.
    Besnier, F.
    Xuan, Z.
    Rooks, M.
    Bhattacharjee, A.
    Brizuela, L.
    Good, J. M.
    Green, R. E.
    Burbano, H. A.
    Plyusnina, I. Z.
    Trut, L.
    Andersson, Leif
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology.
    Schoeneberg, T.
    Carlborg, Örjan
    Swedish University of Agricultural Sciences, Uppsala, Sweden.
    Hannon, G. J.
    Pääbo, Svante
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology.
    Targeted resequencing of a genomic region influencing tameness and aggression reveals multiple signals of positive selection2011In: Heredity, ISSN 0018-067X, E-ISSN 1365-2540, Vol. 107, no 3, p. 205-214Article in journal (Refereed)
    Abstract [en]

    The identification of the causative genetic variants in quantitative trait loci (QTL) influencing phenotypic traits is challenging, especially in crosses between outbred strains. We have previously identified several QTL influencing tameness and aggression in a cross between two lines of wild-derived, outbred rats (Rattus norvegicus) selected for their behavior towards humans. Here, we use targeted sequence capture and massively parallel sequencing of all genes in the strongest QTL in the founder animals of the cross. We identify many novel sequence variants, several of which are potentially functionally relevant. The QTL contains several regions where either the tame or the aggressive founders contain no sequence variation, and two regions where alternative haplotypes are fixed between the founders. A re-analysis of the QTL signal showed that the causative site is likely to be fixed among the tame founder animals, but that several causative alleles may segregate among the aggressive founder animals. Using a formal test for the detection of positive selection, we find 10 putative positively selected regions, some of which are close to genes known to influence behavior. Together, these results show that the QTL is probably not caused by a single selected site, but may instead represent the joint effects of several sites that were targets of polygenic selection.

  • 3. Albert, Frank W.
    et al.
    Carlborg, Örjan
    SLU.
    Plyusnina, Irina
    Besnier, Francois
    Hedwig, Daniela
    Lautenschläger, Susann
    Lorenz, Doreen
    McIntosh, Jenny
    Neumann, Christof
    Richter, Henning
    Zeising, Claudia
    Kozhemyakina, Rimma
    Shchepina, Olesya
    Kratzsch, Jürgen
    Trut, Lyudmila
    Teupser, Daniel
    Thiery, Joachim
    Schöneberg, Torsten
    Andersson, Leif
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology.
    Pääbo, Svante
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Genetics and Pathology.
    Genetic architecture of tameness in a rat model of animal domestication2009In: Genetics, ISSN 0016-6731, E-ISSN 1943-2631, Vol. 182, no 2, p. 541-554Article in journal (Refereed)
    Abstract [en]

    A common feature of domestic animals is tameness - i.e., they tolerate and are unafraid of human presence and handling. To gain insight into the genetic basis of tameness and aggression, we studied an intercross between two lines of rats (Rattus norvegicus) selected over >60 generations for increased tameness and increased aggression against humans, respectively. We measured 45 traits, including tameness and aggression, anxiety-related traits, organ weights, and levels of serum components in >700 rats from an intercross population. Using 201 genetic markers, we identified two significant quantitative trait loci (QTL) for tameness. These loci overlap with QTL for adrenal gland weight and for anxiety-related traits and are part of a five-locus epistatic network influencing tameness. An additional QTL influences the occurrence of white coat spots, but shows no significant effect on tameness. The loci described here are important starting points for finding the genes that cause tameness in these rats and potentially in domestic animals in general.

  • 4.
    Alexander, Michelle
    et al.
    Univ York, York YO10 5DD, N Yorkshire, England.;Univ Aberdeen, Sch Geosci, Dept Archaeol, Aberdeen AB24 3UF, Scotland..
    Ho, Simon Y. W.
    Univ Sydney, Sch Biol Sci, Sydney, NSW 2006, Australia..
    Molak, Martyna
    Polish Acad Sci, Museum & Inst Zool, PL-00679 Warsaw, Poland..
    Barnett, Ross
    Palaeogen & Bioarchaeol Res Network, Res Lab Archaeol, Oxford OX1 3QY, England..
    Carlborg, Örjan
    Swedish University of Agricultural Sciences, Uppsala, Sweden.
    Dorshorst, Ben
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. Virginia Tech, Dept Anim & Poultry Sci, Blacksburg, VA 24061 USA..
    Honaker, Christa
    Virginia Tech, Dept Anim & Poultry Sci, Blacksburg, VA 24061 USA..
    Besnier, Francois
    Inst Marine Res, Sect Populat Genet, N-5024 Bergen, Norway..
    Wahlberg, Per
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular Medicine.
    Dobney, Keith
    Univ Aberdeen, Sch Geosci, Dept Archaeol, Aberdeen AB24 3UF, Scotland..
    Siegel, Paul
    Virginia Tech, Dept Anim & Poultry Sci, Blacksburg, VA 24061 USA..
    Andersson, Leif
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. Swedish Univ Agr Sci, Dept Anim Breeding & Genet, S-75007 Uppsala, Sweden..
    Larson, Greger
    Palaeogen & Bioarchaeol Res Network, Res Lab Archaeol, Oxford OX1 3QY, England..
    Mitogenomic analysis of a 50-generation chicken pedigree reveals a rapid rate of mitochondrial evolution and evidence for paternal mtDNA inheritance2015In: Biology Letters, ISSN 1744-9561, E-ISSN 1744-957X, Vol. 11, no 10, article id 20150561Article in journal (Refereed)
    Abstract [en]

    Mitochondrial genomes represent a valuable source of data for evolutionary research, but studies of their short-term evolution have typically been limited to invertebrates, humans and laboratory organisms. Here we present a detailed study of 12 mitochondrial genomes that span a total of 385 transmissions in a well-documented 50-generation pedigree in which two lineages of chickens were selected for low and high juvenile body weight. These data allowed us to test the hypothesis of time-dependent evolutionary rates and the assumption of strict maternal mitochondrial transmission, and to investigate the role of mitochondrial mutations in determining phenotype. The identification of a non-synonymous mutation in ND4L and a synonymous mutation in CYTB, both novel mutations in Gallus, allowed us to estimate a molecular rate of 3.13 x 10(-7) mutations/site/year (95% confidence interval 3.75 x 10(-8)-1.12 x 10(-6)). This is substantially higher than avian rate estimates based upon fossil calibrations. Ascertaining which of the two novel mutations was present in an additional 49 individuals also revealed an instance of paternal inheritance of mtDNA. Lastly, an association analysis demonstrated that neither of the point mutations was strongly associated with the phenotypic differences between the two selection lines. Together, these observations reveal the highly dynamic nature of mitochondrial evolution over short time periods.

  • 5.
    Alvarez-Castro, Jose M.
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, The Linnaeus Centre for Bioinformatics.
    Le Rouzic, Arnaud
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, The Linnaeus Centre for Bioinformatics.
    Carlborg, Örjan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, The Linnaeus Centre for Bioinformatics.
    How to perform meaningful estimates of genetic effects2008In: PLoS Genetics, ISSN 1553-7390, Vol. 4, no 5, p. e1000062-Article in journal (Refereed)
    Abstract [en]

    Although the genotype-phenotype map plays a central role both in Quantitative and Evolutionary Genetics, the formalization of a completely general and satisfactory model of genetic effects, particularly accounting for epistasis, remains a theoretical challenge. Here, we use a two-locus genetic system in simulated populations with epistasis to show the convenience of using a recently developed model, NOIA, to perform estimates of genetic effects and the decomposition of the genetic variance that are orthogonal even under deviations from the Hardy-Weinberg proportions. We develop the theory for how to use this model in interval mapping of quantitative trait loci using Halley-Knott regressions, and we analyze a real data set to illustrate the advantage of using this approach in practice. In this example, we show that departures from the Hardy-Weinberg proportions that are expected by sampling alone substantially alter the orthogonal estimates of genetic effects when other statistical models, like F-2 or G2A, are used instead of NOIA. Finally, for the first time from real data, we provide estimates of functional genetic effects as sets of effects of natural allele substitutions in a particular genotype, which enriches the debate on the interpretation of genetic effects as implemented both in functional and in statistical models. We also discuss further implementations leading to a completely general genotype-phenotype map.

  • 6. Alvarez-Castro, José M
    et al.
    Carlborg, Örjan
    SLU.
    Rönnegård, Lars
    Estimation and interpretation of genetic effects with epistasis using the NOIA model.2012In: Methods in Molecular Biology, ISSN 1064-3745, E-ISSN 1940-6029, Vol. 871Article in journal (Refereed)
    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.

  • 7. Alvarez-Castro, José M
    et al.
    Le Rouzic, Arnaud
    Andersson, Leif
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology.
    Siegel, Paul B
    Carlborg, Örjan
    Modelling of genetic interactions improves prediction of hybrid patterns: a case study in domestic fowl2012In: Genetical Research, ISSN 0016-6723, E-ISSN 1469-5073, Vol. 94, no 5, p. 255-266Article in journal (Refereed)
    Abstract [en]

    Summary A major challenge in complex trait genetics is to unravel how multiple loci and environmental factors together cause phenotypic diversity. Both first (F1) and second (F2) generation hybrids often display phenotypes that deviate from what is expected under intermediate inheritance. We have here studied two chicken F2 populations generated by crossing divergent chicken lines to assess how epistatic loci, identified in earlier quantitative trait locus (QTL) studies, contribute to hybrid deviations from the mid-parent phenotype. Empirical evidence suggests that the average phenotypes of the intercross birds tend to be lower than the midpoint between the parental means in both crosses. Our results confirm that epistatic interactions, despite a relatively small contribution to the phenotypic variance, play an important role in the deviation of hybrid phenotypes from the mid-parent values (i.e. multi-locus hybrid genotypes lead to lower rather than higher body weights). To a lesser extent, dominance also appears to contribute to the mid-parent deviation, at least in one of the crosses. This observation coincides with the hypothesis that hybridization tends to break up co-adapted gene complexes, i.e. generate Bateson-Dobzhansky-Muller incompatibilities.

  • 8.
    Besnier, Francois
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, The Linnaeus Centre for Bioinformatics.
    Carlborg, Örjan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, The Linnaeus Centre for Bioinformatics. Swedish University of Agricultural Sciences, Uppsala, Sweden.
    A general and efficient method for estimating continuous IBD functions for use in genome scans for QTL2007In: BMC Bioinformatics, ISSN 1471-2105, E-ISSN 1471-2105, Vol. 8, article id 440Article in journal (Refereed)
    Abstract [en]

    Background: Identity by descent (IBD) matrix estimation is a central component in mapping of Quantitative Trait Loci (QTL) using variance component models. A large number of algorithms have been developed for estimation of IBD between individuals in populations at discrete locations in the genome for use in genome scans to detect QTL affecting various traits of interest in experimental animal, human and agricultural pedigrees. Here, we propose a new approach to estimate IBD as continuous functions rather than as discrete values. Results: Estimation of IBD functions improved the computational efficiency and memory usage in genome scanning for QTL. We have explored two approaches to obtain continuous marker-bracket IBD-functions. By re-implementing an existing and fast deterministic IBD-estimation method, we show that this approach results in IBD functions that produces the exact same IBD as the original algorithm, but with a greater than 2-fold improvement of the computational efficiency and a considerably lower memory requirement for storing the resulting genome-wide IBD. By developing a general IBD function approximation algorithm, we show that it is possible to estimate marker-bracket IBD functions from IBD matrices estimated at marker locations by any existing IBD estimation algorithm. The general algorithm provides approximations that lead to QTL variance component estimates that even in worst-case scenarios are very similar to the true values. The approach of storing IBD as polynomial IBD-function was also shown to reduce the amount of memory required in genome scans for QTL. Conclusion: In addition to direct improvements in computational and memory efficiency, estimation of IBD-functions is a fundamental step needed to develop and implement new efficient optimization algorithms for high precision localization of QTL. Here, we discuss and test two approaches for estimating IBD functions based on existing IBD estimation algorithms. Our approaches provide immediately useful techniques for use in single QTL analyses in the variance component QTL mapping framework. They will, however, be particularly useful in genome scans for multiple interacting QTL, where the improvements in both computational and memory efficiency are the key for successful development of efficient optimization algorithms to allow widespread use of this methodology.

  • 9.
    Besnier, Francois
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, The Linnaeus Centre for Bioinformatics.
    Carlborg, Örjan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, The Linnaeus Centre for Bioinformatics.
    A genetic algorithm based method for stringent haplotyping of family data2009In: BMC Genetics, ISSN 1471-2156, E-ISSN 1471-2156, Vol. 10, article id 57Article in journal (Refereed)
    Abstract [en]

    Background: The linkage phase, or haplotype, is an extra level of information that in addition to genotype and pedigree can be useful for reconstructing the inheritance pattern of the alleles in a pedigree, and computing for example Identity By Descent probabilities. If a haplotype is provided, the precision of estimated IBD probabilities increases, as long as the haplotype is estimated without errors. It is therefore important to only use haplotypes that are strongly supported by the available data for IBD estimation, to avoid introducing new errors due to erroneous linkage phases.

    Results: We propose a genetic algorithm based method for haplotype estimation in family data that includes a stringency parameter. This allows the user to decide the error tolerance level when inferring parental origin of the alleles. This is a novel feature compared to existing methods for haplotype estimation. We show that using a high stringency produces haplotype data with few errors, whereas a low stringency provides haplotype estimates in most situations, but with an increased number of errors.

    Conclusion: By including a stringency criterion in our haplotyping method, the user is able to maintain the error rate at a suitable level for the particular study; one can select anything from haplotyped data with very small proportion of errors and a higher proportion of non-inferred haplotypes, to data with phase estimates for every marker, when haplotype errors are tolerable. Giving this choice makes the method more flexible and useful in a wide range of applications as it is able to fulfil different requirements regarding the tolerance for haplotype errors, or uncertain marker-phases.

  • 10.
    Besnier, Francois
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, The Linnaeus Centre for Bioinformatics.
    Wahlberg, Per
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology.
    Rönnegård, Lars
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, The Linnaeus Centre for Bioinformatics.
    Ek, Weronica
    Swedish University of Agricultural Sciences .
    Andersson, Leif
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology.
    Siegel, Paul
    virginia polytechnic institute and state university.
    Carlborg, Örjan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, The Linnaeus Centre for Bioinformatics.
    Fine mapping and replication of QTL in outbred chicken advanced intercross lines2011In: Genetics Selection Evolution, ISSN 0999-193X, E-ISSN 1297-9686, Vol. 43, p. 3-Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: Linkage mapping is used to identify genomic regions affecting the expression of complex traits. However, when experimental crosses such as F2 populations or backcrosses are used to map regions containing a Quantitative Trait Locus (QTL), the size of the regions identified remains quite large, i.e. 10 or more Mb. Thus, other experimental strategies are needed to refine the QTL locations. Advanced Intercross Lines (AIL) are produced by repeated intercrossing of F2 animals and successive generations, which decrease linkage disequilibrium in a controlled manner. Although this approach is seen as promising, both to replicate QTL analyses and fine-map QTL, only a few AIL datasets, all originating from inbred founders, have been reported in the literature.

    METHODS: We have produced a nine-generation AIL pedigree (n = 1529) from two outbred chicken lines divergently selected for body weight at eight weeks of age. All animals were weighed at eight weeks of age and genotyped for SNP located in nine genomic regions where significant or suggestive QTL had previously been detected in the F2 population. In parallel, we have developed a novel strategy to analyse the data that uses both genotype and pedigree information of all AIL individuals to replicate the detection of and fine-map QTL affecting juvenile body weight.

    RESULTS: Five of the nine QTL detected with the original F2 population were confirmed and fine-mapped with the AIL, while for the remaining four, only suggestive evidence of their existence was obtained. All original QTL were confirmed as a single locus, except for one, which split into two linked QTL.

    CONCLUSIONS: Our results indicate that many of the QTL, which are genome-wide significant or suggestive in the analyses of large intercross populations, are true effects that can be replicated and fine-mapped using AIL. Key factors for success are the use of large populations and powerful statistical tools. Moreover, we believe that the statistical methods we have developed to efficiently study outbred AIL populations will increase the number of organisms for which in-depth complex traits can be analyzed.

     

  • 11. Brady, Siobhan M
    et al.
    Burow, Meike
    Busch, Wolfgang
    Carlborg, Örjan
    SLU.
    Denby, Katherine J
    Glazebrook, Jane
    Hamilton, Eric S
    Harmer, Stacey L
    Haswell, Elizabeth S
    Maloof, Julin N
    Springer, Nathan M
    Kliebenstein, Daniel J
    Reassess the t Test: Interact with All Your Data via ANOVA.2015In: The Plant Cell, ISSN 1040-4651, E-ISSN 1532-298X, Vol. 27, no 8Article in journal (Refereed)
    Abstract [en]

    Plant biology is rapidly entering an era where we have the ability to conduct intricate studies that investigate how a plant interacts with the entirety of its environment. This requires complex, large studies to measure how plant genotypes simultaneously interact with a diverse array of environmental stimuli. Successful interpretation of the results from these studies requires us to transition away from the traditional standard of conducting an array of pairwise t tests toward more general linear modeling structures, such as those provided by the extendable ANOVA framework. In this Perspective, we present arguments for making this transition and illustrate how it will help to avoid incorrect conclusions in factorial interaction studies (genotype × genotype, genotype × treatment, and treatment × treatment, or higher levels of interaction) that are becoming more prevalent in this new era of plant biology.

  • 12.
    Brandt, Monika
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences.
    Ahsan, Muhammad
    Swedish Univ Agr Sci, Div Computat Genet, Dept Clin Sci, S-75007 Uppsala, Sweden.
    Honaker, Christa F.
    Virginia Polytech Inst & State Univ, Dept Anim & Poultry Sci, Blacksburg, VA 24061 USA.
    Siegel, Paul B.
    Virginia Polytech Inst & State Univ, Dept Anim & Poultry Sci, Blacksburg, VA 24061 USA.
    Carlborg, Örjan
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology.
    Imputation-Based Fine-Mapping Suggests That Most QTL in an Outbred Chicken Advanced Intercross Body Weight Line Are Due to Multiple, Linked Loci2017In: G3: Genes, Genomes, Genetics, ISSN 2160-1836, E-ISSN 2160-1836, Vol. 7, no 1, p. 119-128Article in journal (Refereed)
    Abstract [en]

    The Virginia chicken lines have been divergently selected for juvenile body weight for more than 50 generations. Today, the high- and low-weight lines show a >12-fold difference for the selected trait, 56-d body weight. These lines provide unique opportunities to study the genetic architecture of long-term, single-trait selection. Previously, several quantitative trait loci (QTL) contributing to weight differences between the lines were mapped in an F2-cross between them, and these were later replicated and fine-mapped in a nine-generation advanced intercross of them. Here, we explore the possibility to further increase the fine-mapping resolution of these QTL via a pedigree-based imputation strategy that aims to better capture the genetic diversity in the divergently selected, but outbred, founder lines. The founders of the intercross were high-density genotyped, and then pedigree-based imputation was used to assign genotypes throughout the pedigree. Imputation increased the marker density 20-fold in the selected QTL, providing 6911 markers for the subsequent analysis. Both single-marker association and multi-marker backward-elimination analyses were used to explore regions associated with 56-d body weight. The approach revealed several statistically and population structure independent associations and increased the mapping resolution. Further, most QTL were also found to contain multiple independent associations to markers that were not fixed in the founder populations, implying a complex underlying architecture due to the combined effects of multiple, linked loci perhaps located on independent haplotypes that still segregate in the selected lines.

  • 13.
    Carlborg, Orjan
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, The Linnaeus Centre for Bioinformatics.
    Haley, Chris S
    Epistasis: too often neglected in complex trait studies?2004In: Nat Rev Genet, ISSN 1471-0056, Vol. 5, no 8, p. 618-25Article in journal (Other academic)
  • 14.
    Carlborg, Örjan
    et al.
    SLU.
    Andersson, L
    Kinghorn, B
    The use of a genetic algorithm for simultaneous mapping of multiple interacting quantitative trait loci.2000In: Genetics, ISSN 0016-6731, E-ISSN 1943-2631, Vol. 155, no 4Article in journal (Refereed)
    Abstract [en]

    Here we describe a general method for improving computational efficiency in simultaneous mapping of multiple interacting quantitative trait loci (QTL). The method uses a genetic algorithm to search for QTL in the genome instead of an exhaustive enumerative ("step-by-step") search. It can be used together with any method of QTL mapping based on a genomic search, since it only provides a more efficient way to search the genome for QTL. The computational demand decreases by a factor of approximately 130 when using genetic algorithm-based mapping instead of an exhaustive enumerative search for two QTL in a genome size of 2000 cM using a resolution of 1 cM. The advantage of using a genetic algorithm increases further for larger genomes, higher resolutions, and searches for more QTL. We show that a genetic algorithm-based search has efficiency higher than or equal to a search method conditioned on previously identified QTL for all epistatic models tested and that this efficiency is comparable to that of an exhaustive search for multiple QTL. The genetic algorithm is thus a powerful and computationally tractable alternative to the exhaustive enumerative search for simultaneous mapping of multiple interacting QTL. The use of genetic algorithms for simultaneous mapping of more than two QTL and for determining empirical significance thresholds using permutation tests is also discussed.

  • 15.
    Carlborg, Örjan
    et al.
    SLU.
    Andersson, Leif
    Use of randomization testing to detect multiple epistatic QTLs.2002In: Genetical research, Vol. 79, no 2Article in journal (Refereed)
    Abstract [en]

    Here, we describe a randomization testing strategy for mapping interacting quantitative trait loci (QTLs). In a forward selection strategy, non-interacting QTLs and simultaneously mapped interacting QTL pairs are added to a total genetic model. Simultaneous mapping of epistatic QTLs increases the power of the mapping strategy by allowing detection of interacting QTL pairs where none of the QTL can be detected by their marginal additive and dominance effects. Randomization testing is used to derive empirical significance thresholds for every model selection step in the procedure. A simulation study was used to evaluate the statistical properties of the proposed randomization tests and for which types of epistasis simultaneous mapping of epistatic QTLs adds power. Least squares regression was used for QTL parameter estimation but any other QTL mapping method can be used. A genetic algorithm was used to search for interacting QTL pairs, which makes the proposed strategy feasible for single processor computers. We believe that this method will facilitate the evaluation of the importance at epistatic interaction among QTLs controlling multifactorial traits and disorders.

  • 16.
    Carlborg, Örjan
    et al.
    SLU.
    Andersson-Eklund, L
    Andersson, L
    Parallel computing in interval mapping of quantitative trait loci.2002In: Journal of Heredity, ISSN 0022-1503, E-ISSN 1465-7333, Vol. 92, no 5Article in journal (Refereed)
    Abstract [en]

    Linear regression analysis is considered the least computationally demanding method for mapping quantitative trait loci (QTL). However, simultaneous search for multiple QTL, the use of permutations to obtain empirical significance thresholds, and larger experimental studies significantly increase the computational demand. This report describes an easily implemented parallel algorithm, which significantly reduces the computing time in both QTL mapping and permutation testing. In the example provided, the analysis time was decreased to less than 15% of a single processor system by the use of 18 processors. We indicate how the efficiency of the analysis could be improved by distributing the computations more evenly to the processors and how other ways of distributing the data facilitate the use of more processors. The use of parallel computing in QTL mapping makes it possible to routinely use permutations to obtain empirical significance thresholds for multiple traits and multiple QTL models. It could also be of use to improve the computational efficiency of the more computationally demanding QTL analysis methods.

  • 17.
    Carlborg, Örjan
    et al.
    Roslin Institute.
    Brockmann, Gudrun A
    Haley, Chris S
    Simultaneous mapping of epistatic QTL in DU6i x DBA/2 mice.2005In: Mammalian Genome, ISSN 0938-8990, E-ISSN 1432-1777, Vol. 16, no 7Article in journal (Refereed)
    Abstract [en]

    We have mapped epistatic quantitative trait loci (QTL) in an F2 cross between DU6i x DBA/2 mice. By including these epistatic QTL and their interaction parameters in the genetic model, we were able to increase the genetic variance explained substantially (8.8%-128.3%) for several growth and body composition traits. We used an analysis method based on a simultaneous search for epistatic QTL pairs without assuming that the QTL had any effect individually. We were able to detect several QTL that could not be detected in a search for marginal QTL effects because the epistasis cancelled out the individual effects of the QTL. In total, 23 genomic regions were found to contain QTL affecting one or several of the traits and eight of these QTL did not have significant individual effects. We identified 44 QTL pairs with significant effects on the traits, and, for 28 of the pairs, an epistatic QTL model fit the data significantly better than a model without interactions. The epistatic pairs were classified by the significance of the epistatic parameters in the genetic model, and visual inspection of the two-locus genotype means identified six types of related genotype-phenotype patterns among the pairs. Five of these patterns resembled previously published patterns of QTL interactions.

  • 18.
    Carlborg, Örjan
    et al.
    Roslin Institute.
    De Koning, D J
    Manly, K F
    Chesler, E
    Williams, R W
    Haley, C S
    Methodological aspects of the genetic dissection of gene expression.2005In: Bioinformatics, ISSN 1367-4803, E-ISSN 1367-4811, Vol. 21, no 10Article in journal (Refereed)
    Abstract [en]

    MOTIVATION: Dissection of the genetics underlying gene expression utilizes techniques from microarray analyses as well as quantitative trait loci (QTL) mapping. Available QLT mapping methods are not tailored for the highly automated analyses required to deal with the thousand of gene transcripts encountered in the mapping of QTL affecting gene expression (sometimes referred to as eQTL). This report focuses on the adaptation of QTL mapping methodology to perform automated mapping of QTL affecting gene expression.

    RESULTS: The analyses of expression data on > 12,000 gene transcripts in BXD recombinant inbred mice found, on average, 629 QTL exceeding the genome-wide 5% threshold. Using additional information on trait repeatabilities and QTL location, 168 of these were classified as 'high confidence' QTL. Current sample sizes of genetical genomics studies make it possible to detect a reasonable number of QTL using simple genetic models, but considerably larger studies are needed to evaluate more complex genetic models. After extensive analyses of real data and additional simulated data (altogether > 300,000 genome scans) we make the following recommendations for detection of QTL for gene expression: (1) For populations with an unbalanced number of replicates on each genotype, weighted least squares should be preferred above ordinary least squares. Weights can be based on repeatability of the trait and the number of replicates. (2) A genome scan based on multiple marker information but analysing only at marker locations is a good approximation to a full interval mapping procedure. (3) Significance testing should be based on empirical genome-wide significance thresholds that are derived for each trait separately. (4) The significant QTL can be separated into high and low confidence QTL using a false discovery rate that incorporates prior information such as transcript repeatabilities and co-localization of gene-transcripts and QTL. (5) Including observations on the founder lines in the QTL analysis should be avoided as it inflates the test statistic and increases the Type I error. (6) To increase the computational efficiency of the study, use of parallel computing is advised. These recommendations are summarized in a possible strategy for mapping of QTL in a least squares framework.

    AVAILABILITY: The software used for this study is available on request from the authors.

  • 19.
    Carlborg, Örjan
    et al.
    Roslin Institute.
    Hocking, Paul M
    Burt, Dave W
    Haley, Chris S
    Simultaneous mapping of epistatic QTL in chickens reveals clusters of QTL pairs with similar genetic effects on growth.2004In: Genetical research, Vol. 83, no 3Article in journal (Refereed)
    Abstract [en]

    We used simultaneous mapping of interacting quantitative trait locus (QTL) pairs to study various growth traits in a chicken F2 intercross. The method was shown to increase the number of detected QTLs by 30 % compared with a traditional method detecting QTLs by their marginal genetic effects. Epistasis was shown to be an important contributor to the genetic variance of growth, with the largest impact on early growth (before 6 weeks of age). There is also evidence for a discrete set of interacting loci involved in early growth, supporting the previous findings of different genetic regulation of early and late growth in chicken. The genotype-phenotype relationship was evaluated for all interacting QTL pairs and 17 of the 21 evaluated QTL pairs could be assigned to one of four clusters in which the pairs in a cluster have very similar genetic effects on growth. The genetic effects of the pairs indicate commonly occurring dominance-by-dominance, heterosis and multiplicative interactions. The results from this study clearly illustrate the increase in power obtained by using this novel method for simultaneous detection of epistatic QTL, and also how visualization of genotype-phenotype relationships for epistatic QTL pairs provides new insights to biological mechanisms underlying complex traits.

  • 20.
    Carlborg, Örjan
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, The Linnaeus Centre for Bioinformatics.
    Jacobsson, Lina
    Ahgren, Per
    Siegel, Paul
    Andersson, Leif
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology.
    Epistasis and the release of genetic variation during long-term selection.2006In: Nat Genet, ISSN 1061-4036, Vol. 38, no 4, p. 418-20Article in journal (Refereed)
  • 21.
    Carlborg, Örjan
    et al.
    Swedish University of Agricultural Sciences, Uppsala, Sweden.
    Kerje, Susanne
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology.
    Schutz, K
    Jacobsson, L
    Jensen, P
    Andersson, Leif
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology.
    A global search reveals epistatic interaction between QTL for early growthin the chicken2003In: Genome Research, ISSN 1088-9051, E-ISSN 1549-5469, Vol. 13, p. 413-421Article in journal (Refereed)
  • 22.
    Carlborg, Örjan
    et al.
    SLU.
    Kerje, Susanne
    Schütz, Karin
    Jacobsson, Lina
    Jensen, Per
    Andersson, Leif
    A global search reveals epistatic interaction between QTL for early growth in the chicken.2003In: Genome Research, ISSN 1088-9051, E-ISSN 1549-5469, Vol. 13, no 3Article in journal (Refereed)
    Abstract [en]

    We have identified quantitative trait loci (QTL) explaining a large proportion of the variation in body weights at different ages and growth between chronological ages in an F(2) intercross between red junglefowl and White Leghorn chickens. QTL were mapped using forward selection for loci with significant marginal genetic effects and with a simultaneous search for epistatic QTL pairs. We found 22 significant loci contributing to these traits, nine of these were only found by the simultaneous two-dimensional search, which demonstrates the power of this approach for detecting loci affecting complex traits. We have also estimated the relative contribution of additive, dominance, and epistasis effects to growth and the contribution of epistasis was more pronounced prior to 46 days of age, whereas additive genetic effects explained the major portion of the genetic variance later in life. Several of the detected loci affected either early or late growth but not both. Very few loci affected the entire growth process, which points out that early and late growth, at least to some extent, have different genetic regulation.

  • 23.
    Carlborg, Örjan
    et al.
    SLU.
    Kerje, Susanne
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology.
    Schütz, Karin
    Jacobsson, Lina
    Jensen, Per
    Andersson, Leif
    A Global Search Reveals Epistatic Interaction Between QTL for Early Growth in the Chicken2003In: Genome Research, no 13, p. 413-421Article in journal (Refereed)
  • 24.
    Crooks, Lucy
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology.
    Carlborg, Örjan
    Swedish University of Agricultural Sciences, Uppsala, Sweden.
    Marklund, Stefan
    Johansson, Anna M.
    Identification of Null Alleles and Deletions from SNP Genotypes for an Intercross Between Domestic and Wild Chickens2013In: G3: Genes, Genomes, Genetics, ISSN 2160-1836, E-ISSN 2160-1836, Vol. 3, no 8, p. 1253-1260Article in journal (Refereed)
    Abstract [en]

    We analyzed genotypes from similar to 10K single-nucleotide polymorphisms (SNPs) in two families of an F-2 intercross between Red Junglefowl and White Leghorn chickens. Possible null alleles were found by patterns of incompatible and missing genotypes. We estimated that 2.6% of SNPs had null alleles compared with 2.3% with genotyping errors and that 40% of SNPs in which a parent and offspring were genotyped as different homozygotes had null alleles. Putative deletions were identified by null alleles at adjacent markers. We found two candidate deletions that were supported by fluorescence intensity data from a 60K SNP chip. One of the candidate deletions was from the Red Junglefowl, and one was present in both the Red Junglefowl and White Leghorn. Both candidate deletions spanned protein-coding regions and were close to a previously detected quantitative trait locus affecting body weight in this population. This study demonstrates that the similar to 50K SNP genotyping arrays now available for several agricultural species can be used to identify null alleles and deletions in data from large families. We suggest that our approach could be a useful complement to linkage analysis in experimental crosses.

  • 25.
    Crooks, Lucy
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology.
    Nettelblad, Carl
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Carlborg, Örjan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology.
    An improved method for estimating chromosomal line origin in QTL analysis of crosses between outbred lines2011In: G3: Genes, Genomes, Genetics, ISSN 2160-1836, E-ISSN 2160-1836, Vol. 1, p. 57-64Article in journal (Refereed)
  • 26. Crooks, Lucy
    et al.
    Sahana, Goutam
    de Koning, Dirk-Jan
    Lund, Mogens Sandø
    Carlborg, Örjan
    SLU.
    Comparison of analyses of the QTLMAS XII common dataset. II: genome-wide association and fine mapping.2009In: BMC Proceedings, ISSN 1753-6561, E-ISSN 1753-6561, Vol. 3 Suppl 1Article in journal (Refereed)
    Abstract [en]

    As part of the QTLMAS XII workshop, a simulated dataset was distributed and participants were invited to submit analyses of the data based on genome-wide association, fine mapping and genomic selection. We have evaluated the findings from the groups that reported fine mapping and genome-wide association (GWA) efforts to map quantitative trait loci (QTL). Generally the power to detect QTL was high and the Type 1 error was low. Estimates of QTL locations were generally very accurate. Some methods were much better than others at estimating QTL effects, and with some the accuracy depended on simulated effect size or minor allele frequency. There were also indications of bias in the effect estimates. No epistasis was simulated, but the two studies that included searches for epistasis reported several interacting loci, indicating a problem with controlling the Type I error rate in these analyses. Although this study is based on a single dataset, it indicates that there is a need to improve fine mapping and GWA methods with respect to estimation of genetic effects, appropriate choice of significance thresholds and analysis of epistasis.

  • 27. de Koning, Dirk-Jan
    et al.
    Carlborg, Örjan
    Roslin Institute.
    Haley, Chris S
    The genetic dissection of immune response using gene-expression studies and genome mapping.2005In: Veterinary Immunology and Immunopathology, ISSN 0165-2427, E-ISSN 1873-2534, Vol. 105, no 3-4Article in journal (Refereed)
    Abstract [en]

    Functional genomics has been applied to the genetic dissection of immune response in different ways: (1) experimental crosses between lines that differ in their (non-) specific immune response have been used to detect quantitative trait loci (QTL) underlying these differences. (2) The measurement of gene expression levels for thousands of genes using microarrays or oligonucleotide chips to identify differential expression with regard to antigen challenge: (a) before and after infection, (b) resistant versus susceptible lines, or (c) combinations of both. Interpretation of QTL results is hampered by the fact that confidence regions of the QTL are large and can contain hundreds of potential candidate genes for the QTL. At the same time, the microarray experiments tend to show large numbers of differentially expressed genes without identifying the relationships between these genes. In the recently proposed 'genetical genomics' framework, members of a segregating population are characterised for genome-wide molecular markers and for gene expression levels. This facilitates the mapping of expression-QTL (eQTL): loci in the genome that control the expression of genes. Initial applications of this approach are critically reviewed and potential applications of this approach with regard to immune response are presented.

  • 28. Ek, Weronica
    et al.
    Marklund, Stefan
    Ragavendran, Ashok
    Siegel, Paul
    Muir, William
    Carlborg, Örjan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology. Swedish University of Agricultural Sciences, Uppsala, Sweden.
    Generation of a multi-locus chicken introgression line to study the effects of genetic interactions on metabolic phenotypes in chickens.2012In: Frontiers in Genetics, ISSN 1664-8021, E-ISSN 1664-8021, Vol. 3Article in journal (Refereed)
    Abstract [en]

    Most biological traits are regulated by a complex interplay between genetic and environmental factors. By intercrossing divergent lines, it is possible to identify individual and interacting QTL involved in the genetic architecture of these traits. When the loci have been mapped, alternative strategies are needed for fine-mapping and studying the individual and interactive effects of the QTL in detail. We have previously identified, replicated, and fine mapped a four-locus QTL network that determines nearly half of the eightfold difference in body weight at 56 days of age between two divergently selected chicken lines. Here, we describe, to our knowledge, the first generation of a three-locus QTL introgression line in chickens. Recurrent marker-assisted backcrossing was used to simultaneously transfer QTL alleles from the low-weight selected line into the high-weight selected line. Three generations of backcrossing and one generation of intercrossing resulted in an introgression line where all three introgressed QTL and several unlinked and linked control-loci were segregating at nearly expected allele frequencies. We show how intensive selection can be applied using artificial insemination to rapidly generate a multi-locus introgression line and provide recommendations for future breeding of introgression lines. This confirmed introgression line will facilitate later detailed studies of the effects of genetic interactions on complex traits in this population, including growth, and body-composition traits.

  • 29. Ek, Weronica
    et al.
    Sahlqvist, Anna-Stina
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Autoimmunity.
    Crooks, Lucy
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology.
    Sgonc, Roswitha
    Dietrich, Hermann
    Wick, Georg
    Ekwall, Olov
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Autoimmunity.
    Andersson, Leif
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology.
    Carlborg, Örjan
    Swedish University of Agricultural Sciences, Uppsala, Sweden.
    Kämpe, Olle
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Autoimmunity.
    Kerje, Susanne
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology.
    Mapping QTL affecting a systemic sclerosis-like disorder in a cross between UCD-200 and red jungle fowl chickens2012In: Developmental and Comparative Immunology, ISSN 0145-305X, E-ISSN 1879-0089, Vol. 38, no 2, p. 352-359Article in journal (Refereed)
    Abstract [en]

    Systemic sclerosis (SSc) or scleroderma is a rare, autoimmune, multi-factorial disease characterized by early microvascular alterations, inflammation, and fibrosis. Chickens from the UCD-200 line develop a hereditary SSc-like disease, showing all the hallmarks of the human disorder, which makes this line a promising model to study genetic factors underlying the disease. A backcross was generated between UCD-200 chickens and its wild ancestor - the red jungle fowl and a genome-scan was performed to identify loci affecting early (21days of age) and late (175days of age) ischemic lesions of the comb. A significant difference in frequency of disease was observed between sexes in the BC population, where the homogametic males were more affected than females, and there was evidence for a protective W chromosome effect. Three suggestive disease predisposing loci were mapped to chromosomes 2, 12 and 14. Three orthologues of genes implicated in human SSc are located in the QTL region on chromosome 2, TGFRB1, EXOC2-IRF4 and COL1A2, as well as CCR8, which is more generally related to immune function. IGFBP3 is also located within the QTL on chromosome 2 and earlier studies have showed increased IGFBP3 serum levels in SSc patients. To our knowledge, this study is the first to reveal a potential genetic association between IGFBP3 and SSc. Another gene with an immunological function, SOCS1, is located in the QTL region on chromosome 14. These results illustrate the usefulness of the UCD-200 chicken as a model of human SSc and motivate further in-depth functional studies of the implicated candidate genes.

  • 30. Ek, Weronica
    et al.
    Strömstedt, Lina
    Wahlberg, Per
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology.
    Siegel, Paul
    Andersson, Leif
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology.
    Carlborg, Örjan
    SLU.
    Genetic analysis of metabolic traits in an intercross between body weight-selected chicken lines2010In: Physiological Genomics, ISSN 1094-8341, E-ISSN 1531-2267, Vol. 42, no 1, p. 20-22Article in journal (Refereed)
    Abstract [en]

    A network of four interacting loci has been reported previously to influence growth in two lines of chickens divergently selected for body weight at 56 days of age. Located on chromosomes 3 (Growth4), 4 (Growth6), 7 (Growth9), and 20 (Growth12), they explained nearly half of the difference in body weight at selection age between the two lines. The original study reported effects on body weight and fat deposition, but no attempts were made to explore the effects of the network on other phenotypes measured in the F(2) population. In this study we conducted further analyses to evaluate the specific effects of the four-locus network on other metabolic traits as well as refining results from the original study by including a larger number of genetic markers in the quantitative trait locus (QTL) regions. We confirm the previously described effect of the epistatic network on body weight and show that the network increases the total amount of muscle and fat as well as the weight of the internal organs. The network as a whole did not change the relative content of any studied organs or tissues in the body. There was, however, a significant interaction between the loci on chromosomes 3 and 7 that changed the relative proportion of abdominal fat and breast muscle in the chicken by increasing abdominal fat weight without a corresponding increase in muscle mass.

  • 31. Forsberg, Simon K G
    et al.
    Andreatta, Matthew E
    Huang, Xin-Yuan
    Danku, John
    Salt, David E
    Carlborg, Örjan
    SLU.
    The Multi-allelic Genetic Architecture of a Variance-Heterogeneity Locus for Molybdenum Concentration in Leaves Acts as a Source of Unexplained Additive Genetic Variance.2015In: PLoS Genetics, ISSN 1553-7390, E-ISSN 1553-7404, Vol. 11, no 11Article in journal (Refereed)
    Abstract [en]

    Genome-wide association (GWA) analyses have generally been used to detect individual loci contributing to the phenotypic diversity in a population by the effects of these loci on the trait mean. More rarely, loci have also been detected based on variance differences between genotypes. Several hypotheses have been proposed to explain the possible genetic mechanisms leading to such variance signals. However, little is known about what causes these signals, or whether this genetic variance-heterogeneity reflects mechanisms of importance in natural populations. Previously, we identified a variance-heterogeneity GWA (vGWA) signal for leaf molybdenum concentrations in Arabidopsis thaliana. Here, fine-mapping of this association reveals that the vGWA emerges from the effects of three independent genetic polymorphisms that all are in strong LD with the markers displaying the genetic variance-heterogeneity. By revealing the genetic architecture underlying this vGWA signal, we uncovered the molecular source of a significant amount of hidden additive genetic variation or "missing heritability". Two of the three polymorphisms underlying the genetic variance-heterogeneity are promoter variants for Molybdate transporter 1 (MOT1), and the third a variant located ~25 kb downstream of this gene. A fourth independent association was also detected ~600 kb upstream of MOT1. Use of a T-DNA knockout allele highlights Copper Transporter 6; COPT6 (AT2G26975) as a strong candidate gene for this association. Our results show that an extended LD across a complex locus including multiple functional alleles can lead to a variance-heterogeneity between genotypes in natural populations. Further, they provide novel insights into the genetic regulation of ion homeostasis in A. thaliana, and empirically confirm that variance-heterogeneity based GWA methods are a valuable tool to detect novel associations of biological importance in natural populations.

  • 32.
    Forsberg, Simon K. G.
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology.
    Bloom, Joshua S.
    Univ Calif Los Angeles, Dept Human Genet, Los Angeles, CA USA.; Univ Calif Los Angeles, Howard Hughes Med Inst, Los Angeles, CA 90024 USA.; Univ Calif Los Angeles, Dept Biol Chem, Los Angeles, CA 90024 USA..
    Sadhu, Meru J.
    Univ Calif Los Angeles, Dept Human Genet, Los Angeles, CA USA.; Univ Calif Los Angeles, Howard Hughes Med Inst, Los Angeles, CA 90024 USA.; Univ Calif Los Angeles, Dept Biol Chem, Los Angeles, CA 90024 USA..
    Kruglyak, Leonid
    Univ Calif Los Angeles, Dept Human Genet, Los Angeles, CA USA.; Univ Calif Los Angeles, Howard Hughes Med Inst, Los Angeles, CA 90024 USA.; Univ Calif Los Angeles, Dept Biol Chem, Los Angeles, CA 90024 USA..
    Carlborg, Örjan
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology.
    Accounting for genetic interactions improves modeling of individual quantitative trait phenotypes in yeast2017In: Nature Genetics, ISSN 1061-4036, E-ISSN 1546-1718, Vol. 49, no 4, p. 497-503Article in journal (Refereed)
    Abstract [en]

    Experiments in model organisms report abundant genetic interactions underlying biologically important traits, whereas quantitative genetics theory predicts, and data support, the notion that most genetic variance in populations is additive. Here we describe networks of capacitating genetic interactions that contribute to quantitative trait variation in a large yeast intercross population. The additive variance explained by individual loci in a network is highly dependent on the allele frequencies of the interacting loci. Modeling of phenotypes for multilocus genotype classes in the epistatic networks is often improved by accounting for the interactions. We discuss the implications of these results for attempts to dissect genetic architectures and to predict individual phenotypes and long-term responses to selection.

  • 33.
    Forsberg, Simon K. G.
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology.
    Carlborg, Örjan
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology.
    On the relationship between epistasis and genetic variance heterogeneity.2017In: Journal of Experimental Botany, ISSN 0022-0957, E-ISSN 1460-2431, Vol. 68, no 20, p. 5431-5438Article in journal (Refereed)
    Abstract [en]

    Epistasis and genetic variance heterogeneity are two non-additive genetic inheritance patterns that are often, but not always, related. Here we use theoretical examples and empirical results from earlier analyses of experimental data to illustrate the connection between the two. This includes an introduction to the relationship between epistatic gene action, statistical epistasis, and genetic variance heterogeneity, and a brief discussion about how genetic processes other than epistasis can also give rise to genetic variance heterogeneity.

  • 34. Forsberg, Simon K. G.
    et al.
    Kierczak, Marcin
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology.
    Ljungvall, Ingrid
    Merveille, Anne-Christine
    Gouni, Vassiliki
    Wiberg, Maria
    Willesen, Jakob Lundgren
    Hanas, Sofia
    Lequarre, Anne-Sophie
    Sorensen, Louise Mejer
    Tiret, Laurent
    McEntee, Kathleen
    Seppala, Eija
    Koch, Jorgen
    Battaille, Geraldine
    Lohi, Hannes
    Fredholm, Merete
    Chetboul, Valerie
    Haggstrom, Jens
    Carlborg, Örjan
    Swedish University of Agricultural Sciences, Uppsala, Sweden.
    Lindblad-Toh, Kerstin
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Hoglund, Katja
    The Shepherds' Tale: A Genome-Wide Study across 9 Dog Breeds Implicates Two Loci in the Regulation of Fructosamine Serum Concentration in Belgian Shepherds2015In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 10, no 5, article id e0123173Article in journal (Refereed)
    Abstract [en]

    Diabetes mellitus is a serious health problem in both dogs and humans. Certain dog breeds show high prevalence of the disease, whereas other breeds are at low risk. Fructosamine and glycated haemoglobin (HbA1c) are two major biomarkers of glycaemia, where serum concentrations reflect glucose turnover over the past few weeks to months. In this study, we searched for genetic factors influencing variation in serum fructosamine concentration in healthy dogs using data from nine dog breeds. Considering all breeds together, we did not find any genome-wide significant associations to fructosamine serum concentration. However, by performing breed-specific analyses we revealed an association on chromosome 3 (rho(corrected) approximate to 1:68 x 10(-6)) in Belgian shepherd dogs of the Malinois subtype. The associated region and its close neighbourhood harbours interesting candidate genes such as LETM1 and GAPDH that are important in glucose metabolism and have previously been implicated in the aetiology of diabetes mellitus. To further explore the genetics of this breed specificity, we screened the genome for reduced heterozygosity stretches private to the Belgian shepherd breed. This revealed a region with reduced heterozygosity that shows a statistically significant interaction (rho = 0.025) with the association region on chromosome 3. This region also harbours some interesting candidate genes and regulatory regions but the exact mechanisms underlying the interaction are still unknown. Nevertheless, this finding provides a plausible explanation for breed-specific genetic effects for complex traits in dogs. Shepherd breeds are at low risk of developing diabetes mellitus. The findings in Belgian shepherds could be connected to a protective mechanism against the disease. Further insight into the regulation of glucose metabolism could improve diagnostic and therapeutic methods for diabetes mellitus.

  • 35. Giuffra, E
    et al.
    Kijas, J M
    Amarger, V
    Carlborg, Örjan
    SLU.
    Jeon, J T
    Andersson, L
    The origin of the domestic pig: independent domestication and subsequent introgression.2000In: Genetics, ISSN 0016-6731, E-ISSN 1943-2631, Vol. 154, no 4Article in journal (Refereed)
    Abstract [en]

    The domestic pig originates from the Eurasian wild boar (Sus scrofa). We have sequenced mitochondrial DNA and nuclear genes from wild and domestic pigs from Asia and Europe. Clear evidence was obtained for domestication to have occurred independently from wild boar subspecies in Europe and Asia. The time since divergence of the ancestral forms was estimated at approximately 500,000 years, well before domestication approximately 9,000 years ago. Historical records indicate that Asian pigs were introduced into Europe during the 18th and early 19th centuries. We found molecular evidence for this introgression and the data indicated a hybrid origin of some major "European" pig breeds. The study is an advance in pig genetics and has important implications for the maintenance and utilization of genetic diversity in this livestock species.

  • 36. Gjuvsland, Arne B.
    et al.
    Hayes, Ben J.
    Omholt, Stig W.
    Carlborg, Örjan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, The Linnaeus Centre for Bioinformatics.
    Statistical epistasis is a generic feature of gene regulatory networks2007In: Genetics, ISSN 0016-6731, E-ISSN 1943-2631, Vol. 175, no 1, p. 411-420Article in journal (Refereed)
    Abstract [en]

    Functional dependencies between genes are a defining characteristic of gene networks underlying quantitative traits. However, recent studies show that the proportion of the genetic variation that can be attributed to statistical epistasis varies from almost zero to very high. It is thus of fundamental as well as instrumental importance to better understand whether different functional dependency patterns among polymorphic genes give rise to distinct statistical interaction patterns or not. Here we address this issue by combining a quantitative genetic model approach with genotype-phenotype models capable of translating allelic variation and regulatory principles into phenotypic variation at the level of gene expression. We show that gene regulatory networks with and without feedback motifs can exhibit a wide range of possible statistical genetic architectures with regard to both type of effect explaining phenotypic variance and number of apparent loci underlying the observed phenotypic effect. Although all motifs are capable of harboring significant interactions, positive feedback gives rise to higher amounts and more types of statistical epistasis. The results also suggest that the inclusion of statistical interaction terms in genetic models will increase the chance to detect additional QTL as well as functional dependencies between genetic loci over a broad range of regulatory regimes. This article illustrates how statistical genetic methods can fruitfully be combined with nonlinear systems dynamics to elucidate biological issues beyond reach of each methodology in isolation.

  • 37. Guo, Jiazhong
    et al.
    Jorjani, Hossein
    Carlborg, Örjan
    SLU.
    A genome-wide association study using international breeding-evaluation data identifies major loci affecting production traits and stature in the Brown Swiss cattle breed.2012In: BMC Genetics, ISSN 1471-2156, E-ISSN 1471-2156, Vol. 13Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: The genome-wide association study (GWAS) is a useful approach to identify genes affecting economically important traits in dairy cattle. Here, we report the results from a GWAS based on high-density SNP genotype data and estimated breeding values for nine production, fertility, body conformation, udder health and workability traits in the Brown Swiss cattle population that is part of the international genomic evaluation program.

    RESULT: GWASs were performed using 50 k SNP chip data and deregressed estimated breeding values (DEBVs) for nine traits from between 2061 and 5043 bulls that were part of the international genomic evaluation program coordinated by Interbull Center. The nine traits were milk yield (MY), fat yield (FY), protein yield (PY), lactating cow's ability to recycle after calving (CRC), angularity (ANG), body depth (BDE), stature (STA), milk somatic cell score (SCS) and milk speed (MSP). Analyses were performed using a linear mixed model correcting for population confounding. A total of 74 SNPs were detected to be genome-wide significantly associated with one or several of the nine analyzed traits. The strongest signal was identified on chromosome 25 for milk production traits, stature and body depth. Other signals were on chromosome 11 for angularity, chromosome 24 for somatic cell score, and chromosome 6 for milking speed. Some signals overlapped with earlier reported QTL for similar traits in other cattle populations and were located close to interesting candidate genes worthy of further investigations.

    CONCLUSIONS: Our study shows that international genetic evaluation data is a useful resource for identifying genetic factors influencing complex traits in livestock. Several genome wide significant association signals could be identified in the Brown Swiss population, including a major signal on BTA25. Our findings report several associations and plausible candidate genes that deserve further exploration in other populations and molecular dissection to explore the potential economic impact and the genetic mechanisms underlying these production traits in cattle.

  • 38. Guo, Ying
    et al.
    Gu, Xiaorong
    Sheng, Zheya
    Wang, Yanqiang
    Luo, Chenglong
    Liu, Ranran
    Qu, Hao
    Shu, Dingming
    Wen, Jie
    Crooijmans, Richard P M A
    Carlborg, Örjan
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology.
    Zhao, Yiqiang
    Hu, Xiaoxiang
    Li, Ning
    A Complex Structural Variation on Chromosome 27 Leads to the Ectopic Expression of HOXB8 and the Muffs and Beard Phenotype in Chickens2016In: PLoS Genetics, ISSN 1553-7390, E-ISSN 1553-7404, Vol. 12, no 6, article id e1006071Article in journal (Refereed)
    Abstract [en]

    Muffs and beard (Mb) is a phenotype in chickens where groups of elongated feathers gather from both sides of the face (muffs) and below the beak (beard). It is an autosomal, incomplete dominant phenotype encoded by the Muffs and beard (Mb) locus. Here we use genome-wide association (GWA) analysis, linkage analysis, Identity-by-Descent (IBD) mapping, array-CGH, genome re-sequencing and expression analysis to show that the Mb allele causing the Mb phenotype is a derived allele where a complex structural variation (SV) on GGA27 leads to an altered expression of the gene HOXB8. This Mb allele was shown to be completely associated with the Mb phenotype in nine other independent Mb chicken breeds. The Mb allele differs from the wild-type mb allele by three duplications, one in tandem and two that are translocated to that of the tandem repeat around 1.70 Mb on GGA27. The duplications contain total seven annotated genes and their expression was tested during distinct stages of Mb morphogenesis. A continuous high ectopic expression of HOXB8 was found in the facial skin of Mb chickens, strongly suggesting that HOXB8 directs this regional feather-development. In conclusion, our results provide an interesting example of how genomic structural rearrangements alter the regulation of genes leading to novel phenotypes. Further, it again illustrates the value of utilizing derived phenotypes in domestic animals to dissect the genetic basis of developmental traits, herein providing novel insights into the likely role of HOXB8 in feather development and differentiation.

  • 39. Heyne, Henrike O
    et al.
    Lautenschläger, Susann
    Nelson, Ronald
    Besnier, François
    Rotival, Maxime
    Cagan, Alexander
    Kozhemyakina, Rimma
    Plyusnina, Irina Z
    Trut, Lyudmila
    Carlborg, Örjan
    SLU.
    Petretto, Enrico
    Kruglyak, Leonid
    Pääbo, Svante
    Schöneberg, Torsten
    Albert, Frank W
    Genetic influences on brain gene expression in rats selected for tameness and aggression.2014In: Genetics, ISSN 0016-6731, E-ISSN 1943-2631, Vol. 198, no 3Article in journal (Refereed)
    Abstract [en]

    Interindividual differences in many behaviors are partly due to genetic differences, but the identification of the genes and variants that influence behavior remains challenging. Here, we studied an F2 intercross of two outbred lines of rats selected for tame and aggressive behavior toward humans for >64 generations. By using a mapping approach that is able to identify genetic loci segregating within the lines, we identified four times more loci influencing tameness and aggression than by an approach that assumes fixation of causative alleles, suggesting that many causative loci were not driven to fixation by the selection. We used RNA sequencing in 150 F2 animals to identify hundreds of loci that influence brain gene expression. Several of these loci colocalize with tameness loci and may reflect the same genetic variants. Through analyses of correlations between allele effects on behavior and gene expression, differential expression between the tame and aggressive rat selection lines, and correlations between gene expression and tameness in F2 animals, we identify the genes Gltscr2, Lgi4, Zfp40, and Slc17a7 as candidate contributors to the strikingly different behavior of the tame and aggressive animals.

  • 40. Jeon, J T
    et al.
    Carlborg, Örjan
    SLU.
    Törnsten, A
    Giuffra, E
    Amarger, V
    Chardon, P
    Andersson-Eklund, L
    Andersson, K
    Hansson, I
    Lundström, K
    Andersson, L
    A paternally expressed QTL affecting skeletal and cardiac muscle mass in pigs maps to the IGF2 locus.1999In: Nature Genetics, ISSN 1061-4036, E-ISSN 1546-1718, Vol. 21, no 2Article in journal (Refereed)
  • 41. Johansson, Anna M.
    et al.
    Pettersson, Mats E.
    Siegel, Paul B.
    Carlborg, Örjan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, The Linnaeus Centre for Bioinformatics.
    Genome-Wide Effects of Long-Term Divergent Selection2010In: PLoS Genetics, ISSN 1553-7390, Vol. 6, no 11, p. e1001188-Article in journal (Refereed)
    Abstract [en]

    To understand the genetic mechanisms leading to phenotypic differentiation, it is important to identify genomic regions under selection. We scanned the genome of two chicken lines from a single trait selection experiment, where 50 generations of selection have resulted in a 9-fold difference in body weight. Analyses of nearly 60,000 SNP markers showed that the effects of selection on the genome are dramatic. The lines were fixed for alternative alleles in more than 50 regions as a result of selection. Another 10 regions displayed strong evidence for ongoing differentiation during the last 10 generations. Many more regions across the genome showed large differences in allele frequency between the lines, indicating that the phenotypic evolution in the lines in 50 generations is the result of an exploitation of standing genetic variation at 100s of loci across the genome.

  • 42. Keeling, L
    et al.
    Andersson, L
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology.
    Schütz, EK
    Kerje, S
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology.
    Fredriksson, R
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Neuroscience. Farmakologi 3.
    Carlborg, Örjan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, The Linnaeus Centre for Bioinformatics.
    Cornwallis, CK
    Pizzari, T
    Jensen, P
    Chicken genomics: Feather-pecking and victim pigmentation2004In: Nature, Vol. 431, p. 645-6Article in journal (Refereed)
  • 43. Keeling, Linda
    et al.
    Andersson, Leif
    Schütz, Karin E
    Kerje, Susanne
    Fredriksson, Robert
    Carlborg, Örjan
    SLU.
    Cornwallis, Charles K
    Pizzari, Tommaso
    Jensen, Per
    Chicken genomics: feather-pecking and victim pigmentation.2004In: Nature, ISSN 0028-0836, E-ISSN 1476-4687, Vol. 431, no 7009Article in journal (Refereed)
    Abstract [en]

    Feather-pecking in domestic birds is associated with cannibalism and severe welfare problems. It is a dramatic example of a spiteful behaviour in which the victim's fitness is reduced for no immediate direct benefit to the perpetrator and its evolution is unexplained. Here we show that the plumage pigmentation of a chicken may predispose it to become a victim: birds suffer more drastic feather-pecking when the colour of their plumage is due to the expression of a wild recessive allele at PMEL17, a gene that controls plumage melanization, and when these birds are relatively common in a flock. These findings, obtained using an intercross between a domestic fowl and its wild ancestor, have implications for the welfare of domestic species and offer insight into the genetic changes associated with the evolution of feather-pecking during the early stages of domestication.

  • 44.
    Kerje, S
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology.
    Carlborg, Örjan
    Swedish University of Agricultural Sciences, Uppsala, Sweden.
    Jacobsson, L
    Schutz, K
    Hartmann, C
    Jensen, P
    Andersson, L
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology.
    The twofold difference in adult size between the red junglefowl and WhiteLeghorn chickens is largely explained by a limited number of QTLs2003In: Animal Genetics, ISSN 0268-9146, E-ISSN 1365-2052, Vol. 34, no 4, p. 264-274Article in journal (Refereed)
    Abstract [en]

    A large intercross between the domestic White Leghorn chicken and the wild ancestor, the red junglefowl, has been used in a Quantitative Trait Loci (QTL) study of growth and egg production. The linkage map based on 105 marker loci was in good agreement with the chicken consensus map. The growth of the 851 F2 individuals was lower than both parental lines prior to 46 days of age and intermediate to the two parental lines thereafter. The QTL analysis of growth traits revealed 13 loci that showed genome-wide significance. The four major growth QTLs explained 50 and 80% of the difference in adult body weight between the founder populations for females and males, respectively. A major QTL for growth, located on chromosome 1 appears to have pleiotropic effects on feed consumption, egg production and behaviour. There was a strong positive correlation between adult body weight and average egg weight. However, three QTLs affecting average egg weight but not body weight were identified. An interesting observation was that the estimated effects for the four major growth QTLs all indicated a codominant inheritance.

  • 45. Kerje, S
    et al.
    Carlborg, Örjan
    SLU.
    Jacobsson, L
    Schütz, K
    Hartmann, C
    Jensen, P
    Andersson, L
    The twofold difference in adult size between the red junglefowl and White Leghorn chickens is largely explained by a limited number of QTLs.2003In: Animal Genetics, ISSN 0268-9146, E-ISSN 1365-2052, Vol. 34, no 4Article in journal (Refereed)
    Abstract [en]

    A large intercross between the domestic White Leghorn chicken and the wild ancestor, the red junglefowl, has been used in a Quantitative Trait Loci (QTL) study of growth and egg production. The linkage map based on 105 marker loci was in good agreement with the chicken consensus map. The growth of the 851 F2 individuals was lower than both parental lines prior to 46 days of age and intermediate to the two parental lines thereafter. The QTL analysis of growth traits revealed 13 loci that showed genome-wide significance. The four major growth QTLs explained 50 and 80% of the difference in adult body weight between the founder populations for females and males, respectively. A major QTL for growth, located on chromosome 1 appears to have pleiotropic effects on feed consumption, egg production and behaviour. There was a strong positive correlation between adult body weight and average egg weight. However, three QTLs affecting average egg weight but not body weight were identified. An interesting observation was that the estimated effects for the four major growth QTLs all indicated a codominant inheritance.

  • 46.
    Kerje, Susanne
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology.
    Carlborg, Örjan
    SLU.
    Jacobsson, Lina
    Schütz, Karin
    Hartmann, Camilla
    Jensen, Per
    Andersson, Leif
    The twofold difference in adult size between the red junglefowl and White Leghorn chickens is largely explained by a limited number of QTLs2003In: Animal Genetics, no 34, p. 264-274Article in journal (Refereed)
  • 47.
    Kierczak, Marcin
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Jablonska, Jagoda
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology.
    Forsberg, S. K.
    Bianchi, Matteo
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Tengvall, Katarina
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Pettersson, Mats
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Scholz, Veronica
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Meadows, Jennifer R.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Jern, Patric
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Carlborg, Örjan
    Swedish University of Agricultural Sciences, Uppsala, Sweden.
    Lindblad-Toh, Kerstin
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    cgmisc: Enhanced Genome-wide Association Analyses and Visualisation2015In: Bioinformatics, ISSN 1367-4803, E-ISSN 1367-4811, Vol. 31, no 23, p. 3830-3831Article in journal (Refereed)
    Abstract [en]

    SUMMARY:

    High-throughput genotyping and sequencing technologies facilitate studies of complex genetic traits and provide new research opportunities. The increasing popularity of genome-wide association studies (GWAS) leads to the discovery of new associated loci and a better understanding of the genetic architecture underlying not only diseases, but also other monogenic and complex phenotypes. Several softwares are available for performing GWAS analyses, R environment being one of them.

    RESULTS: We present cgmisc, an R package that enables enhanced data analysis and visualisation of results from GWAS. The package contains several utilities and modules that complement and enhance the functionality of the existing software. It also provides several tools for advanced visualisation of genomic data and utilises the power of the R language to aid in preparation of publication-quality figures. Some of the package functions are specific for the domestic dog (Canis familiaris) data.

    AVAILABILITY: The package is operating system-independent and is available from: https://github.com/cgmisc-team/cgmisc CONTACT: cgmisc@imbim.uu.se.

  • 48. Lachowiec, Jennifer
    et al.
    Shen, Xia
    Queitsch, Christine
    Carlborg, Örjan
    SLU.
    A Genome-Wide Association Analysis Reveals Epistatic Cancellation of Additive Genetic Variance for Root Length in Arabidopsis thaliana.2015In: PLoS Genetics, ISSN 1553-7390, E-ISSN 1553-7404, Vol. 11, no 9Article in journal (Refereed)
    Abstract [en]

    Efforts to identify loci underlying complex traits generally assume that most genetic variance is additive. Here, we examined the genetics of Arabidopsis thaliana root length and found that the genomic narrow-sense heritability for this trait in the examined population was statistically zero. The low amount of additive genetic variance that could be captured by the genome-wide genotypes likely explains why no associations to root length could be found using standard additive-model-based genome-wide association (GWA) approaches. However, as the broad-sense heritability for root length was significantly larger, and primarily due to epistasis, we also performed an epistatic GWA analysis to map loci contributing to the epistatic genetic variance. Four interacting pairs of loci were revealed, involving seven chromosomal loci that passed a standard multiple-testing corrected significance threshold. The genotype-phenotype maps for these pairs revealed epistasis that cancelled out the additive genetic variance, explaining why these loci were not detected in the additive GWA analysis. Small population sizes, such as in our experiment, increase the risk of identifying false epistatic interactions due to testing for associations with very large numbers of multi-marker genotypes in few phenotyped individuals. Therefore, we estimated the false-positive risk using a new statistical approach that suggested half of the associated pairs to be true positive associations. Our experimental evaluation of candidate genes within the seven associated loci suggests that this estimate is conservative; we identified functional candidate genes that affected root development in four loci that were part of three of the pairs. The statistical epistatic analyses were thus indispensable for confirming known, and identifying new, candidate genes for root length in this population of wild-collected A. thaliana accessions. We also illustrate how epistatic cancellation of the additive genetic variance explains the insignificant narrow-sense and significant broad-sense heritability by using a combination of careful statistical epistatic analyses and functional genetic experiments.

  • 49.
    Le Rouzic, Arnaud
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, The Linnaeus Centre for Bioinformatics.
    Alvarez-Castro, Jose M.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, The Linnaeus Centre for Bioinformatics.
    Carlborg, Örjan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, The Linnaeus Centre for Bioinformatics.
    Dissection of the genetic architecture of body weight in chicken reveals the impact of epistasis on domestication traits2008In: Genetics, ISSN 0016-6731, E-ISSN 1943-2631, Vol. 179, no 3, p. 1591-1599Article in journal (Refereed)
    Abstract [en]

    In this contribution, we study the genetic mechanisms leading to differences in the observed growth patterns of domesticated White Leghorn chickens and their wild ancestor the red jungle fowl. An epistatic QTL analysis for several body-weight measures from hatch to adulthood confirms earlier findings that polymorphisms at > , 15 loci contribute to body-weight determination in an F-2 intercross between these populations and that many loci are involved in complex genetic interactions. Here, we use a new genetic model to decompose the genetic effects of this multilocus epistatic genetic network. The results show how the functional modeling of genetic effects provides new insights into how genetic interactions in a large set of loci jointly contribute to phenotypic expression. By exploring the functional effects of QTL allels, we show that some alleles can display temporal shifts in the expression of genetic effects due to their dependencies on the genetic background. Our results demonstrate that the effects of many genes are dependent on genetic interactions with other loci and how their involvement in the domestication process relies on these interactions.

  • 50.
    Le Rouzic, Arnaud
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, The Linnaeus Centre for Bioinformatics.
    Carlborg, Örjan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, The Linnaeus Centre for Bioinformatics.
    Evolutionary potential of hidden genetic variation2008In: Trends in Ecology & Evolution, ISSN 0169-5347, E-ISSN 1872-8383, Vol. 23, no 1, p. 33-37Article, review/survey (Refereed)
    Abstract [en]

    The ability of a population to respond to natural or artificial selection pressures is determined by the genetic architecture of the selected trait. It is now widely acknowledged that a substantial part of genetic variability can be buffered or released as the result of complex genetic interactions. However, the impact of hidden genetic diversity on phenotypic evolution is still not clear. Here, we argue that a common term to describe the impact of hidden genetic variation on phenotypic change is needed and will help to provide new insights into the contribution of different components of genetic architectures to the evolvability of a character. We introduce the 'genetic charge' concept, to describe how the architecture of a trait can be 'charged' with potential for evolutionary change that can later be 'discharged' in response to selection.

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