Abstract:
Poultry are highly variable phenotypically as a result of natural selection and domestication. This leaves behind signatures of selection which may be used for genetic improvement of poultry through selective breeding. The aim of this study was to perform analysis of signatures of selection at candidate genes for egg production and growth. Genes selected for egg production were prolactin, vasoactive intestinal peptide1 and vasoactive intestinal peptide receptor 1. Genes selected for growth were growth hormone, growth hormone receptor, insulin-like growth factor 1, and insulin-like growth factor 1 receptor. A reciprocal BLASTp using BLOSUM62 substitution matrix was performed to identify the homologs. Orthologs with an expectation value greater than 1e-10 were selected for further analysis. Thereafter, multiple sequence alignment was performed using MUSCLE which is based on an iterative algorithm. Phylogeny construction was then done using Distance-based FastME followed by analysis using codon-based models in PAML. Likelihood ratio test was used to detect positive selection followed by posterior probability using Bayes Empirical Bayes Analysis to identify the sites under selection. Web-based servers: Raptor X and DeepAlign were used to predict 3D structures and compare the structures, respectively. This led to identification of purifying selection in all lineages in vasoactive intestinal peptide receptor 1, while in prolactin, there was positive selection in poultry. Additionally,purifying selection was detected in poultry lineages for Growth Hormone and Growth Hormone Receptor genes. Insulin-like growth factor 1 receptor (IGF1R) had positive selection on amino acid Isoleucine at position 460 on Receptor L domain.
The positive selection on IGF1R may be used as a molecular marker in improving growth of poultry through molecular breeding. The computational approach is fast and accurate and may be used as an additional tool in genetic improvement of poultry.