Phenotypic comparisons of HG and LG lines
The HG and LG lines were divergently selected for body weight (BW) at 8 and 36 weeks of age for more than 20 generations , resulting in a large difference in growth rate . These founder lines and the F2 population from their intercross were used to assess effects of divergent selection on several meat quality traits and their genetic control.
For the present analysis of meat quality traits and muscle characteristics, 109 males (56 and 53 issued from HG and LG lines, respectively) were reared under standard management conditions and slaughtered at 9 weeks of age. Live body weight (BW), abdominal fat percentage and breast yield were measured in addition to meat pH at 15 min post-slaughter (pH15), ultimate pH (pHu), objective meat color at 24 h post-slaughter, and drip loss after 2 days of storage at 4°C, as described by Le Bihan-Duval et al.  (Hunterlab, Reston, VA 20190). The breast meat color (BCo) was measured using a Miniscan spectrocolorimeter with the CIE L*a*b* system, where L* is for the lightness (BCo-L), a* for the redness (BCo-R) and b* for the yellowness (BCo-Y). Higher L*, a* and b* values correspond to paler, redder and more yellow meat, respectively. The activity of the birds while on the pre-slaughter shackle line was also estimated by different measurements: straightening up (SU) of the body (head over the legs) was recorded during the period from the hanging to the electrical stunning and noted as a binary variable equal to 0 when the bird did not try to straighten up (absence) and to 1 otherwise (presence of straightening up). The total duration of wing flapping (TDWF) was recorded from hanging to electrical stunning. The breast muscle glycogen content at death was estimated on eight additional birds by line from measurement of the glycolytic potential  according to Berri et al.
Phenotypic traits, genetic markers and F2 population
The F1 and F2 populations were issued from crossing of the HG and LG lines. Five F1 males (three F1 males issued from the cross of HG males by LG females, and two from LG males by HG females) were mated to 10 unrelated F1 dams each. A total of 698 F2 individuals originating from 50 full-sib families were produced in four successive hatches. At 9 weeks of age, body weight, abdominal fat percentage and breast muscle yield and meat traits [pH15, pHu, lightness (BCo-L), redness (BCo-R), yellowness (BCo-L) and DL] were measured on F2 birds as described earlier .
Genomic DNA was extracted from whole blood by phenol chloroform extraction. A total of 108 microsatellite markers covering 21 chromosomes, with an average distance of 23 cM between markers, were selected according to accessibility of the markers in the first genetic consensus map  and heterozygosity of the F1 parents. Fluorescently labeled microsatellite markers were analyzed on an ABI 3700 DNA sequencer (Applied Biosystems, Foster City, CA USA), and genotypes were determined using GeneScan Analysis 3.7 and Genotyper Analysis 3.7 software (Applied Biosystems, Foster City, CA USA). The GEMMA database was used to manage the informativity tests . All F0, F1 and F2 (both males and females) animals were genotyped for all markers.
QTL analysis software
Prior to QTL detection, the data were corrected for sex and hatch effects as estimated using PEST software . QTL detection was performed first by using the QTLMAP software [12, 13], based on interval mapping . A maximum likelihood technique was applied to the mixture of full and half sib families, with no hypothesis concerning fixation of the QTL alleles in the founder lines. The QTL substitution effects (e.g. half the difference between QQ and qq genotypes) were estimated within each F1 family. The F1 haplotype probabilities were calculated from the marker information within the pedigree. Following assumptions of Mangin et al. , only the most probable sire genotype was considered and retained to compute the likelihood, whereas all dam genotypes with probability higher than 10% were considered. In practice, the likelihood could be linearized within sire families to improve computing efficiency.
F2 analyses using QTLExpress software were also performed . Interval mapping was conducted using regression methods, in which alleles were assumed to be fixed in the founder lines. The founder line contrast was considered as identical in all the families. Haplotype transmission probabilities were computed with respect to approximations described by Haley and Knott .
Three significance levels including chromosome-wide, genome-wide and suggestive were considered in this study. First, the chromosome-wide thresholds were derived empirically. When using QTLMAP, 2000 simulations under the null hypothesis of no QTL were performed  for each trait × linkage analysis group. When using QTLExpress, chromosome-wide thresholds were estimated from 2000 permutations, as suggested by Churchill and Doerge . According to Lander and Kruglyak , the suggestive levels, for which one false positive is expected per genome analysis, were obtained for a specific chromosome as the contribution of that chromosome to the total genome length. The genome-wide thresholds were derived from chromosome-wide significance levels, using an approximate Bonferroni correction: PGenome-wide= 1 - (1 - PChromosome-wide)1/rin which r was obtained by dividing the length of a specific chromosome by the length of the genome considered for QTL detection (2527 cM).
Confidence interval and significance of the substitution effect in sire families
Following Lander and Botstein , 95% confidence intervals were set for QTL locations using the one-LOD drop-off method.
To test the significance of the sire effects estimated with QTLMAP, we modified the Lynch and Walsh equation , which describes the sample size (n) required to detect a completely additive QTL, located at the marker position and which explains a VF fraction of the total F2 phenotypic variance: where α is the risk of false positive detections and 1-β the power of QTL detection; for a given α and β, Z can be retrieved from statistical tables of standard normal distribution. In the present experiment, n = 140 in each sire family so, for a given α and β (in the present study α = 5% and β = 10%), we can infer a threshold value for VF, and test the significance of the substitution QTL effect estimated for each sire. Adjustments were applied to the equation, first to test only the sire allele effect (because QTLMAP makes no assumption about the number of QTL alleles and F1 dams can not be assumed to be heterozygous), and second to take into account the distance between marker and QTL (see appendix). Following this approach the critical value for the proportion of the family variance explained by the QTL (VF), ranged from 3.7% to 13.2%, depending on the distance between marker and QTL. As a consequence, only sires with a sufficient proportion of the family variance explained by the QTL were considered as heterozygous and included in the calculation of the average QTL substitution effect.