The genomic characteristics affect phenotypic diversity from the perspective of genetic improvement of economic traits.

The genetic improvement of economic traits suggests that chicken is an excellent model for exploring the genetic changes and molecular mechanisms underlying phenotypic diversity and artificial selection. Here, the sequencing data including 477 samples from 25 breeds worldwide were used to reveal the genomic patterns of chicken domestication. We analyzed 7.4 Tb clean data with 14.8× per individual to identify 23,504,766 SNPs, 3,289,782 InDels, and 27,027 SVs. The diversity analysis indicates that high-intensity artificial selection would accelerate population differentiation. We also found that the human-driven traits are controlled by polygenes and major genes, such as the primary candidates SOX5 and IGF1 for body size, and NEDD4 for sperm storage capacity. Our findings provide an important reference for understanding how genomic patterns shape phenotypes in livestock.

Species and Phenotypic Distribution Models Reveal Population Differentiation in Ethiopian Indigenous Chickens.

Smallholder poultry production dominated by indigenous chickens is an important source of livelihoods for most rural households in Ethiopia. The long history of domestication and the presence of diverse agroecologies in Ethiopia create unique opportunities to study the effect of environmental selective pressures. Species distribution models (SDMs) and Phenotypic distribution models (PDMs) can be applied to investigate the relationship between environmental variation and phenotypic differentiation in wild animals and domestic populations. In the present study we used SDMs and PDMs to detect environmental variables related with habitat suitability and phenotypic differentiation among nondescript Ethiopian indigenous chicken populations. 34 environmental variables (climatic, soil, and vegetation) and 19 quantitative traits were analyzed for 513 adult chickens from 26 populations. To have high variation in the dataset for phenotypic and ecological parameters, animals were sampled from four spatial gradients (each represented by six to seven populations), located in different climatic zones and geographies. Three different ecotypes are proposed based on correlation test between habitat suitability maps and phenotypic clustering of sample populations. These specific ecotypes show phenotypic differentiation, likely in response to environmental selective pressures. Nine environmental variables with the highest contribution to habitat suitability are identified. The relationship between quantitative traits and a few of the environmental variables associated with habitat suitability is non-linear. Our results highlight the benefits of integrating species and phenotypic distribution modeling approaches in characterization of livestock populations, delineation of suitable habitats for specific breeds, and understanding of the relationship between ecological variables and quantitative traits, and underlying evolutionary processes.