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Orjan Carlborg

Publications and source records attributed to Orjan Carlborg.

14 recordsLinked to original sources
PubMed2007

Separation of base allele and sampling term effects gives new insights in variance component QTL analysis.

BACKGROUND: Variance component (VC) models are commonly used for Quantitative Trait Loci (QTL) mapping in outbred populations. Here, the QTL effect is given as a random effect and a critical part of the model is the relationship between the phenotypic values and the random effect. In the traditional VC model, each individual has a unique QTL effect and the relationship between these random effects is given as a covariance structure (known as the identity-by-descent (IBD) matrix). RESULTS: We present an alternative notation of the variance component model, where the elements of the random effect are independent base generation allele effects and sampling term effects. The relationship between the phenotypic vales and the random effect is given by an incidence matrix, which results in a novel, but statistically equivalent, version of the traditional VC model. A general algorithm to estimate this incidence matrix is presented. Since the model is given in terms of base generation allele effects and sampling term effects, these effects can be estimated separately using best linear unbiased prediction (BLUP). From simulated data, we showed that biallelic QTL effects could be accurately clustered using the BLUP obtained from our model notation when markers are fully informative, and that the accuracy increased with the size of the QTL effect. We also developed a measure indicating whether a base generation marker homozygote is a QTL heterozygote or not, by comparing the variances of the sampling term BLUP and the base generation allele BLUP. A ratio greater than one gives strong support for a QTL heterozygote. CONCLUSION: We developed a simple presentation of the VC QTL model for identification of base generation allele effects in QTL linkage analysis. The base generation allele effects and sampling term effects were separated in our model notation. This clarifies the assumptions of the model and should also enhance the development of genome scan methods.

Alleles↗
PubMed2006

Statistical epistasis is a generic feature of gene regulatory networks.

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.

Epistasis, Genetic↗
PubMed2006

Epistatic regulation of behavioural and morphological traits in the zebrafish (Danio rerio).

There is currently a lack of studies examining epistasis in general, and specifically for behavioural traits of evolutionary significance. The advent of more efficient analytical methods for exploring epistasis in QTL studies removes the computational restraint on this type of analysis and suggests that performing further analyses of existing datasets may reveal a more complete picture of the genetic architecture of the traits. Here we report the results from an epistatic QTL analysis of an F2 cross between a wild population and a standard laboratory strain of zebrafish. This further analysis was performed using a simultaneous search to identify epistatically interacting QTL affecting behavioural and morphological traits and uncovered several novel epistatic interactions that reached either genome-wide or suggestive significance levels as determined by a randomisation testing approach. These results provide novel insight into the genetic architecture of the regulation of behavioural as well as morphological phenotypes and call for more studies of epistasis for this group of traits.

Animals↗
PubMed2006

Epistasis and the release of genetic variation during long-term selection.

It is an enigma how long-term selection in model organisms and agricultural species can lead to marked phenotypic changes without exhausting genetic variation for the selected trait. Here, we show that the genetic architecture of an apparently major locus for growth in chicken dissects into a genetic network of four interacting loci. The interactions in this radial network mediate a considerably larger selection response than predicted by a single-locus model.

Animals↗
PubMed2005

The genetic dissection of immune response using gene-expression studies and genome mapping.

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.

Animals↗
PubMed2005

Simultaneous mapping of epistatic QTL in DU6i x DBA/2 mice.

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.

Animals↗
PubMed2004

Chicken genomics: feather-pecking and victim pigmentation.

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.

Aggression↗
PubMed2004

Simultaneous mapping of epistatic QTL in chickens reveals clusters of QTL pairs with similar genetic effects on growth.

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.

Algorithms↗
PubMed2004

Major growth QTLs in fowl are related to fearful behavior: possible genetic links between fear responses and production traits in a red junglefowl x white leghorn intercross.

The aim of this work was to study fear responses and their relation to production traits in red junglefowl ( Gallus gallus spp.), White Leghorn ( Gallus domesticus ), and their F2-progeny. Quantitative trait locus (QTL) analyses were performed for behavioral traits to gain information about possible genetic links between fear-related behaviors and production. Four behavioral tests were performed that induce different levels of acute fear (open field [OF], exposure to a novel object, tonic immobility, and restraint). Production traits, that is, egg production, sexual maturity (in females), food intake, and growth, were measured individually. A genome scan using 105 microsatellite markers was carried out to identify QTLs controlling the traits studied. In the OF and novel object tests (NO), Leghorns showed less fear behavior than junglefowl, whereas junglefowl behaved less fearfully in the tonic immobility test (TI) and were more active in the restraint test. In the F2 progeny, only weak phenotypic associations were found between production traits and fear behavior. A significant QTL for TI duration was found on chromosome 1 that coincided with a QTL for egg weight and growth in the same animals. Another QTL for NO in males coincided with another major growth QTL. These two known growth QTLs affected a wide range of reactions in different tests. Several other significant and suggestive QTLs for behavioral traits related to fear were found. These QTLs did not coincide with QTLs for production traits, indicating that these fear variables may not be genetically linked to the production traits we measured here. The results show that loci affecting important production traits are located in the same chromosomal region as loci affecting different fear-related behaviors.

Animals↗
PubMed2003

A global search reveals epistatic interaction between QTL for early growth in the chicken.

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.

Aging↗
PubMed2002

Use of randomization testing to detect multiple epistatic QTLs.

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.

Algorithms↗
PubMed2002

QTL analysis of a red junglefowl x White Leghorn intercross reveals trade-off in resource allocation between behavior and production traits.

Behaviors with high energetic costs may decrease in frequency in domestic animals as a response to selection for increased production. The aim of this study was to quantify production traits, foraging behavior, and social motivation in F2 progeny from a White Leghorn x red junglefowl intercross (n = 751-1046) and to perform QTL analyses on the behavioral traits. A foraging-social maze was used for behavioral testing, which consisted of four identical arms and a central box. In two arms there was ad libitum access to the birds' usual food, and in the other two there was novel food (sunflower seeds) mixed with cat litter. In one arm with each of the two food sources, social stimuli were simulated by the presence of a mirror. Each bird could therefore feed on novel or well known food either alone or in the perceived company of a conspecific. Egg production, sexual maturity (females), food intake, and growth were measured individually, and residual food intake and metabolic body weight were estimated using standard methods. A genome scan using 104 microsatellite markers was carried out to identify QTLs affecting behavioral traits. Phenotypic growth rates at different ages showed weak associations in both sexes. Sexual maturity and egg weight were not strongly correlated to growth, indicating that these traits are not genetically linked. Time spent in each arm and in the central part of the maze was analyzed using principal component analyses. Four principal components (PC) were extracted, each reflecting a pattern of behavior in the maze. Females with early onset of sexual maturity scored higher on the PC1 reflecting preference for free food without social stimuli, and females with higher egg production scored higher on the PC2 reflecting exploration. Males with an overall higher growth rate and higher residual food intake scored higher on the PC3, which possibly reflected fear of the test situation, and tended to score higher on the PC4 reflecting low contrafreeloading. Significant QTLs were found for PC1 and PC4 scores on chromosomes 27 and 7, respectively. The location of the QTLs coincided with known QTLs for growth rate and body weight. The results suggest a trade-off between energy-demanding behavior and high production and that some of this may be caused by genetic linkage or pleiotropic gene effects.

Animals↗
PubMed2002

Efficient algorithms for quantitative trait loci mapping problems.

Rapid advances in molecular genetics push the need for efficient data analysis. Advanced algorithms are necessary for extracting all possible information from large experimental data sets. We present a general linear algebra framework for quantitative trait loci (QTL) mapping, using both linear regression and maximum likelihood estimation. The formulation simplifies future comparisons between and theoretical analyses of the methods. We show how the common structure of QTL analysis models can be used to improve the kernel algorithms, drastically reducing the computational effort while retaining the original analysis results. We have evaluated our new algorithms on data sets originating from two large F(2) populations of domestic animals. Using an updating approach, we show that 1-3 orders of magnitude reduction in computational demand can be achieved for matrix factorizations. For interval-mapping/composite-interval-mapping settings using a maximum likelihood model, we also show how to use the original EM algorithm instead of the ECM approximation, significantly improving the convergence and further reducing the computational time. The algorithmic improvements makes it feasible to perform analyses which have previously been deemed impractical or even impossible. For example, using the new algorithms, it is reasonable to perform permutation testing using exhaustive search on populations of 200 individuals using an epistatic two-QTL model.

Algorithms↗