Mapping main, epistatic and sex-specific QTL for body composition in a chicken population divergently selected for low or high growth rate

Abstract

Background: Delineating the genetic basis of body composition is important to agriculture and medicine. In addition, the incorporation of gene-gene interactions in the statistical model provides further insight into the genetic factors that underlie body composition traits. We used Bayesian model selection to comprehensively map main, epistatic and sex-specific QTL in an F2 reciprocal intercross between two chicken lines divergently selected for high or low growth rate.

Results: We identified 17 QTL with main effects across 13 chromosomes and several sex-specific and sex-antagonistic QTL for breast meat yield, thigh + drumstick yield and abdominal fatness. Different sets of QTL were found for both breast muscles [Pectoralis (P) major and P. minor], which suggests that they could be controlled by different regulatory mechanisms. Significant interactions of QTL by sex allowed detection of sex-specific and sex-antagonistic QTL for body composition and abdominal fat. We found several female-specific P. major QTL and sex-antagonistic P. minor and abdominal fatness QTL. Also, several QTL on different chromosomes interact with each other to affect body composition and abdominal fatness.

Conclusions: The detection of main effects, epistasis and sex-dimorphic QTL suggest complex genetic regulation of somatic growth. An understanding of such regulatory mechanisms is key to mapping specific genes that underlie QTL controlling somatic growth in an avian model.

Figure 1

One-dimensional profiles of Bayes factors rescaled as 2log_e BF for main (solid lines), epistatic effects (dotted lines) and sex-specific effects (dashed lines). A: Breast meat yield B: Pectoralis (P) major C. P. minor yield. The horizontal lines represent the significance threshold of 2log_eBF = 2.1.

Figure 2

Two-dimensional profiles of Bayes factors (rescaled as 2logeBF) for fat yield (Figure 2A) and fat weight (Figure 2B) for selected chromosomes. The upper diagonal shows the Bayes factor for the epistatic model, the lower diagonal shows the Bayes factor for the full model with epistasis compared with no QTL.