Investigation of genes associated with egg weight in chickens with different growth curve models

The aim of this study is to analyze genes associated with egg weight in chickens with different growth curve models. In the study, genomic analysis of the associated of time-based (first egg weight, 28, 36, 56, 66, 72 and 80 weeks) egg weights collected from 1063 chickens with 294705 SNPs with different growth curves was performed. For the first time in the study, the genomic regions responsible for egg weight were investigated by testing growth curves such as exponential, Güç, legendre polynomials with different covariance structures (auto-regressive, ARMA, CS, heterogeneous factor analytical, factor analytics, Toeplitz, SAD). Güç growth curve and heterogeneous factor analytical covariance structure were selected as the best model as a result of the analysis. In this study, LMM (Linear Mixed Model) and multiple comparison tests were applied to prevent experimental errors via GEMMA program, without making both genomic association matrix and genomic association matrix using layers (inbreeding coefficient 0.1 for 1063 chickens 294702 SNP; 1063 chickens 294699 SNP for inbreeding coefficient 0.2; 1063 chickens 294705 SNP for inbreeding coefficient 0.3; 1063 chickens 294700 SNP for inbreeding coefficient 0.4; 1063 chickens 294697 SNP for inbreeding coefficient 0.5 for 0.6 1063 chicken 294692) selected according to inbreeding. As a result of the analysis, the best genomic signals were obtained from the egg weight data of 36-week-old chickens on chromosome 1, close to the DLEU7 gene. The findings in this thesis can make a significant contribution to the future production of ideal egg weight in marker assisted selection studies. KEYWORDS: Egg weight, Genomic Association Study, Genomic Selection, Growth Curve