Biomedical subjects

Orjan Carlborg

Publications and source records attributed to Orjan Carlborg.

4 recordsLinked to original sources

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↗