Variation in sexual dimorphism (SD) is particularly marked in meat-type chickens. This paper investigates the genetic basis of SD in an important economic trait, i.e. body weight (BW) at 35 days of age, in broilers by applying quantitative genetic analysis. A large dataset comprising 203,323 BW records of a commercial line of broiler chicken was used. First, a bivariate approach was employed treating BW as a sex-specific trait. During this approach, seven bivariate models were applied and variances due to direct additive genetic, maternal genetic and maternal environmental effects were estimated via the restricted maximum likelihood method. The best-fitting model included direct additive genetic, maternal genetic and maternal environmental effects with a direct-maternal genetic covariance. Differences between male and female direct heritabilities were non-significant (0.28 vs. 0.29 for males and females, respectively), implying no need for sex-specific selection strategies. The direct-maternal genetic correlation was more strongly negative in males than in females (-0.72 vs. -0.56), implying a more profound antagonism between direct additive and maternal genetic effects in this particular gender. The direct genetic correlation of BW between the two sexes was as high as 0.91, i.e. only slightly lower than unity. Second, variance components and genetic parameters of two measures of SD, i.e. the weight difference (Δ) and the weight ratio (R), between the genders were estimated. Direct heritabilities for both measures were significantly different to 0 but of low magnitude (0.04). Apart from the additive-maternal covariance, no other random effects were found to be of importance for Δ and R. The results of the present study suggest that only minimal selection responses due to the selection of Δ and/or R and a small capacity for amplifying or reducing the BW differences between the sexes are to be expected in this specific population. Furthermore, selection pressure on BW is expected to amplify SD.

Aim of the present study was to investigate whether body weight (BW) in broilers is associated with functional modular genes. To this end, first a GWAS for BW was conducted using 6,598 broilers and the high density SNP array. The next step was to search for positional candidate genes and QTLs within strong LD genomic regions around the significant SNPs. Using all positional candidate genes, a network was then constructed and community structure analysis was performed. Finally, functional enrichment analysis was applied to infer the functional relevance of modular genes. A total number of 645 positional candidate genes were identified in strong LD genomic regions around 11 genome-wide significant markers. 428 of the positional candidate genes were located within growth related QTLs. Community structure analysis detected 5 modules while functional enrichment analysis showed that 52 modular genes participated in developmental processes such as skeletal system development. An additional number of 14 modular genes ( GABRG1, NGF, APOBEC2, STAT5B, STAT3, SMAD4, MED1, CACNB1, SLAIN2, LEMD2, ZC3H18, TMEM132D, FRYL and SGCB ) were also identified as related to body weight. Taken together, current results suggested a total number of 66 genes as most plausible functional candidates for the trait examined.

Maniatis, G., Demiris, N., Kranis, A., Banos, G. and Kominakis, A. 2013. Model comparison and estimation of genetic parameters for body weight in commercial broilers. Can. J. Anim. Sci. 93: 67–77. The availability of powerful computing and advances in algorithmic efficiency allow for the consideration of increasingly complex models. Consequently, the development and application of appropriate statistical procedures for model evaluation is becoming increasingly important. This paper is concerned with the application of an alternative model determination criterion (conditional Akaike Information Criterion, cAIC) in a large dataset comprising 203 323 body weights of broilers, pertaining to 7 (BW7) and 35 (BW35) days of age. Seven univariate and seven bivariate models were applied. Direct genetic, maternal genetic and maternal environmental (c2) effects were estimated via REML. The model evaluation criteria included conditional Akaike Information Criterion (cAIC), Bayesian Information Criterion (BIC) and the standard Akaike Information Criterion (henceforth marginal; mAIC). According to cAIC the best-fitting model included direct genetic, maternal genetic and c2 effects. Maternal heritabilities were low (0.10 and 0.03) compared to the direct heritabilities (0.17 and 0.21), while c2 was 0.05 and 0.04 for BW7 and BW35, respectively. BIC and mAIC favoured a model that additionally included a direct-maternal genetic covariance, resulting in highly negative direct-maternal genetic correlations (−0.47 and −0.64 for BW7 and BW35, respectively) and higher direct heritabilities (0.25 and 0.28 for BW7 and BW35, respectively). Results suggest that cAIC can select different animal models than mAIC and BIC with different biological properties.

Background: Aim of the present study was first to identify genetic variants associated with egg number (EN) in female broilers, second to describe the mode of their gene action (additive and/or dominant) and third to provide a list with implicated candidate genes for the trait. A number of 2586 female broilers genotyped with the high density (~600 k) SNP array and with records on EN (mean = 132.4 eggs, SD = 29.8 eggs) were used. Data were analyzed with application of additive and dominant multi-locus mixed models. Results: A number of 7 additive, 4 dominant and 6 additive plus dominant marker-trait significant associations were detected. A total number of 57 positional candidate genes were detected within 50 kb downstream and upstream flanking regions of the 17 significant markers. Functional enrichment analysis pinpointed two genes (BHLHE40 and CRTC1) to be involved in the 'entrainment of circadian clock by photoperiod' biological process. Gene prioritization analysis of the positional candidate genes identified 10 top ranked genes (GDF15, BHLHE40, JUND, GDF3, COMP, ITPR1, ELF3, ELL, CRLF1 and IFI30). Seven prioritized genes (GDF15, BHLHE40, JUND, GDF3, COMP, ELF3, CRTC1) have documented functional relevance to reproduction, while two more prioritized genes (ITPR1 and ELL) are reported to be related to egg quality in chickens. Conclusions: Present results have shown that detailed exploration of phenotype-marker associations can disclose the mode of action of genetic variants and help in identifying causative genes associated with reproductive traits in the species.

Abstract. REML (restricted maximum likelihood) has become the standard method of variance component estimation in animal breeding. Inference in Bayesian animal models is typically based upon Markov chain Monte Carlo (MCMC) methods, which are generally flexible but time-consuming. Recently, a new Bayesian computational method, integrated nested Laplace approximation (INLA), has been introduced for making fast non-sampling-based Bayesian inference for hierarchical latent Gaussian models. This paper is concerned with the comparison of estimates provided by three representative programs (ASReml, WinBUGS and the R package AnimalINLA) of the corresponding methods (REML, MCMC and INLA), with a view to their applicability for the typical animal breeder. Gaussian and binary as well as simulated data were used to assess the relative efficiency of the methods. Analysis of 2319 records of body weight at 35 days of age from a broiler line suggested a purely additive animal model, in which the heritability estimates ranged from 0.31 to 0.34 for the Gaussian trait and from 0.19 to 0.36 for the binary trait, depending on the estimation method. Although in need of further development, AnimalINLA seems a fast program for Bayesian modeling, particularly suitable for the inference of Gaussian traits, while WinBUGS appeared to successfully accommodate a complicated structure between the random effects. However, ASReml remains the best practical choice for the serious animal breeder.