Identification of Target Chicken Populations by Machine Learning Models Using the Minimum Number of SNPs.

ABSTRACT: A marker combination capable of classifying a specific chicken population could improve commercial value by increasing consumer confidence with respect to the origin of the population. This would facilitate the protection of native genetic resources in the market of each country. In this study, a total of 283 samples from 20 lines, which consisted of Korean native chickens, commercial native chickens, and commercial broilers with a layer population, were analyzed to determine the optimal marker combination comprising the minimum number of markers, using a 600 k high-density single nucleotide polymorphism (SNP) array. Machine learning algorithms, a genome-wide association study (GWAS), linkage disequilibrium (LD) analysis, and principal component analysis (PCA) were used to distinguish a ta

SUBMITTER: Seo D 

PROVIDER: S-EPMC7835996 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature