Most traits of economic and biomedical importance are influenced by multiple genetic and environmental factors. Using techniques that allow for inclusion of epistasis and sex-specificity in a QTL model enables a better understanding of the genetic regulatory mechanisms that underlie body composition. Chicken breast muscle is comprised of two distinct muscle groups: the P. major and the P. minor. A significant main- effect QTL for BMY was detected on GGA7; yet analysis of each breast muscle indicates that P. major was the only trait contributing to BMY on GGA7. The location of the P. major QTL is similar to that reported for BMY [9, 22]. The QTL region for P. major yield contains several genes [the interferon induced with helicase C domain 1 (IFIH1), glucagon (GCG), ring finger protein 25 (RNF25) and BAX inhibitor motif containing 1 (TMBIM1)]. We identified three novel QTL for P. minor weight on GGA3, 4 and 17; however after adjustment with BW at 9 wk, the QTL on GGA4 and 17 met the level of significance. The P. minor yield QTL on GGA17 explained approximately 6% of the phenotypic variation. The pre-B-cell leukemia transcription factor 3 (PBX3), a homeobox gene is located within this QTL region. Most studies evaluate breast meat as a single trait [8, 23, 24]. The current study suggests that these traits should be treated independently since they are influenced by different QTL. We also identified a QTL for TDW and TDY at the same location (0 cM) on GGA27. The 0 cM region of GGA27 harbors the mitogenic activated protein kinase kinase 14 (MAP3K14), defender against cell death 1 (DAD1) and MYST histone acetyltransferase 2 (MYST2) genes.
Intensive genetic selection of meat-type chicken during the the last 50 years has led to rapid somatic (muscle) growth and a concomitant increase in ABFY . Abdominal fatness is a complex trait affected both by genes, environmental factors (nutrition, appetite, behavior, etc), and their interactions. In the present study, we found QTL for ABFW on GGA1, 2, 5, 7, 14, 15 and 18. The QTL for ABFW on GGA1, 5, 15 and 18 were similar to the location reported for these traits in other chicken populations [4, 6, 22]. When ABFW was corrected for BW at 9 wk, ABFY QTL were confirmed on GGA1 and GGA5, and novel ones were identified on GGA3, 9, 12 and 27. The ABFY QTL on GGA27 co-localized with the TDY QTL, while the position of the ABFY QTL on GGA3 is similar to a suggested fatness QTL (10% chromosome-wide significance) by Lagarrigue et al. . The ABFY QTL on GGA1 harbors thyroid hormone responsive protein (THRSP) which is a nuclear protein expressed in lipogenic tissues (liver, fat and lactating mammary glands), and is involved in the transduction of hormonal and dietary signals for increased lipid metabolism . The THRSP gene is differentially expressed in the high and low lines; and mutants of THRSPα are associated with ABF in chickens . The THRSP gene also modulates tumorigenesis in human breast cancer . Positional candidate genes that underlie the GGA3 ABFY QTL include inhibitor of growth, family member 1 (ING1), Rho guanine nucleotide exchange factor 7 (ARHGEF7) and ankyrin repeat domain 10 (ANKRD10). The ABFY QTL on GGA5 harbors the insulin gene and insulin-like growth factor 2 (IGF2) gene. A biallelic marker in the chicken IGF2 gene appears to be associated with growth and carcass traits .
Several studies in other species point to sex-bias, sex specificity or sex antagonism in QTL analysis [30–32]. The approach allows us to test for interactions between QTL and sex. A QTL by sex interaction with a Bayes Factor (2LogBF) ≥ 2.1 was considered as sex specific (QTL influencing a trait in only one sex) or sex antagonistic (QTL with allelic effects going in opposite directions between the sexes). A sex antagonistic fatness QTL has been reported in chickens divergently selected for abdominal fatness . Sex-antagonistic QTL for ABFY were found on GGA2, 4, 6, 12, 14 and 19. Male-specific QTL for ABFY on GGA2 and GGA4 were similar to those reported by Jennen et al.  and McElroy et al. , respectively. However, the ABFY QTL on GGA6, 12, 14 and 19 (Additional file 1) are unique to the HG × LG cross. There were several female-specific QTL affecting P. major yield, and contrarily several sex-antagonistic QTL affecting P. minor yield. Some fatness QTL were also found to be sex-antagonistic in the current study. The male-specific QTL for ABFW was within the confidence interval of the sex-antagonistic QTL for abdominal fatness reported by Abasht et al. . Sex-specific QTL and their genetic inter-relationships have been reported for human obesity and lipid levels . The mechanisms underlying sex-specific, sex influenced or sex-antagonistic effects are unknown although the influence of sex hormones on the regulation of the genes that underlie these QTL is the first evident hypothesis. Other parameters showing sex-dimorphism (such as food intake, plasma nutrient levels etc.) may exert further additional controls on their own. The fine mapping strategies utilized to identify major genes that underlie QTL would depend on whether QTL effect is additive, epistatic, sex-specific or sex-antagonistic.
Epistatic QTL effects
By definition, a complex trait is affected by many genes, each with a small effect, the environment and gene by environment interactions. However, in most instances the summation of the additive effects of each single-locus cannot explain all the phenotypic variation of a particular trait. The dependency of one locus upon another, referred to as epistasis, also contributes towards the phenotypic variation. The inclusion of epistatic effects through interactions of different QTL regions (same or different chromosomes) in QTL mapping allows for the detection of novel loci. Epistatic QTL explained between 3 to 25% of the phenotypic variation. Epistasis QTL involving positions on GGA 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 17 and 27 were associated with body composition traits in the current study. An earlier study utilizing a White Leghorn × Red Jungle fowl cross identified many epistatic pairs that affected both early and late growth . They argued that, the degree of divergence between their populations could be the reason for the measured epistasis. Gene interactions may be the norm rather than the exception. Limited studies on epistasis QTL are due principally to the lack of statistical methods with sufficient power to detect them, rather than their lack of existence. Other studies have described the effect of epistasis on fatness in mice [11, 17, 18, 33, 34]. Genes that underlie interacting QTL may interact biologically or may code for enzymes involved in common pathways . Several positional candidate genes at the GGA2 284-286.1 cM region [Yamaguchi sarcoma viral oncogene homolog 1 (YES1), GATA-6-transcription factor (GATA-6), retinoblastoma binding protein 8 (RBBP8), Rho-associated, coiled-coil containing protein kinase 1 (ROCK1)] could be interacting with other genes on GGA6 and 27 to affect abdominal fatness in meat-type chickens. It appears that some of the candidate genes that underlie QTL for ABFY are also associated with breast cancer in humans . Therefore candidate genes within the QTL regions identified in this study should be investigated for their biologically significance to body composition in chickens and to obesity and cancers in humans.