Visualization of Runs of Homozygosity and Classification Using Convolutional Neural Networks.

ABSTRACT: Runs of homozygosity (ROH) are key elements of the genetic structure of populations, reflecting inbreeding levels, selection history, and potential associations with phenotypic traits. This study proposes a novel approach to ROH analysis through visualization and classification using convolutional neural networks (CNNs). Genetic data from Large White (n = 568) and Duroc (n = 600) pigs were used to construct ROH maps, where each homozygous segment was classified by length and visualized as a color-coded image. The analysis was conducted in two stages: (1) classification of animals by breed based on ROH maps and (2) identification of the presence or absence of a phenotypic trait (limb defects). Genotyping was performed using the GeneSeek^® GGP SNP80x1_XT chip (Illumina Inc., San Di

SUBMITTER: Bakoev S 

PROVIDER: S-EPMC12025119 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature