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.

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.

Two growth-selected lines in chickens have been developed from a single founder population by divergent selection for body weight at 56 days of age. After more than 40 generations of selection they show a nine-fold difference in body weight at selection age and large differences in growth rate, appetite, fat deposition and metabolic characteristics. We have generated a large intercross between these lines comprising more than 800 F2 birds. QTL mapping revealed 13 loci affecting growth. The most striking observation was that the allele in the high weight line in all cases was associated with enhanced growth, but each locus explained only a small proportion of the phenotypic variance using a standard QTL model (1.3-3.1%). This result is in sharp contrast to our previous study where we reported that the two-fold difference in adult body size between the red junglefowl and White Leghorn domestic chickens is explained by a small number of QTLs with large additive effects. Furthermore, no QTLs for anorexia or antibody response were detected despite large differences for these traits between the founder lines. The result is an excellent example where a large phenotypic difference between populations occurs in the apparent absence of any single locus with large phenotypic effects. The study underscores the need for powerful experimental designs in genetic studies of multifactorial traits. No QTL at all would have reached genome-wide significance using a less powerful design (e.g. approx. 200 F2 individuals) regardless of the nine-fold phenotypic difference between the founder lines for the selected trait.

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.

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.

The high- and low-growth lines of chickens have been developed from a single founder population by divergent selection for body weight at 56 days of age for more than 40 generations. The two lines show a ninefold difference in body weight at selection age and several interesting correlated selection responses such as altered body composition and metabolic differences. We have generated a reciprocal intercross comprising >800 F2 birds. In a previous study, we reported the detection of 13 quantitative trait loci (QTLs) affecting growth. Here we report QTLs for body composition (fat deposition, muscle development), weight of internal organs, and metabolic traits (plasma concentrations of glucose, insulin, cholesterol, glucagon, triglycerides, and IGF-I). Most of the QTLs with convincing statistical support mapped in the vicinity of growth QTLs. One of the most interesting observations was that the type of reciprocal cross had highly significant effects on body weight at hatch and on plasma concentrations of glucose, cholesterol, insulin, and IGF-I, but it had no significant effect on body weight at 56 days of age. The reciprocal cross explained between 15 and 35% of the phenotypic variance for weight at hatch and for plasma concentrations of glucose and insulin. The observed pattern indicated that these effects were caused by maternal effects or by genetic differences in mitochondrial DNA.

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.

A large mapping population, with 874 F2 individuals, was generated by reciprocally intercrossing 2 chicken lines. A genetic map of 2,426.6 cM comprising 25 linkage groups was established based on 145 microsatellite markers. Chromosome locations were assigned for 14 previously unmapped markers. The marker ADL0132 was previously mapped to chromosome 9; however, here close linkage to the MCW0091 marker on chromosome 4 was found. With this exception, the derived linkage map was in excellent agreement with the chicken consensus map. A comparison with the chicken genome assembly (http://genome.ucsc.edu; February 2004) suggested a few minor errors in the assembly. A PCR-RFLP test was used to genotype a single nucleotide polymorphism in the melanocortin receptor 3 (MC3R) gene in the intercross, and pyrosequencing was used to map the genes for Hemopoetic Cell Kinase (HCK) and Bone Morphogenic Protein 7 (BMP7). The HCK and BMP7 genes on linkage group E32 showed significant linkage to MC3R on the distal end of linkage group E47W24, consequently joining the 2 linkage groups. A comparison between the linkage data in the current study and the physical location of markers as revealed in the chicken genome sequence assembly (February 2004) showed a 3-fold higher recombination rate on microchromosomes than on macrochromosomes.