Data compression can discriminate broilers by selection line, detect haplotypes, and estimate genetic potential for complex phenotypes.

摘要: Accurately establishing the relationships among individuals lays foundation for genetic analyses such as genome-wide association studies and identification of selection signatures. Of particular interest to poultry industry are estimates merit based on molecular data. These can be commercially exploited in marker-assisted breeding programs accelerate improvement. Here, we test utility a new method have recently developed estimate animal relatedness applied it parameter estimation commercial broilers. Our approach is concept data compression from information theory. Using real-world compressor gzip normalized distance (NCD) built compression-based relationship matrices (CRM) 988 chickens 4 broiler lines-2 male 2 female lines. For all pairs individuals, found strong neg-ative between commonly used genomic matrix (GRM) NCD. This reflects fact that "similarity" inverse "distance." The CRM explained more variation than corresponding GRM 3 phenotypes, with improvements accuracy genomic-enabled predictions value. A sliding-window version analysis highlighted haplotype regions genome apparently under line-specific manner. In lines, retrieved high population-specific scores IGF-1 cognate receptor, INSR. detected an extreme score region containing reproductive hormone receptor (GNRHR). We conclude our valid established identify selective pressure lines chickens.