APPLYING THE ALGORITHM FOR PROVEN AND YOUNG IN GWAS REVEALS HIGH POLYGENICITY FOR KEY TRAITS IN NELLORE CATTLE

Adebisi Racheal Ogunbawo ¹ Jorge Hidalgo ² Henrique A. Mulim ¹ Eula R Carrara ² Henrique T Ventura ³ Nadson O Souza ³ Daniela Lourenco ² Hinayah Rojas De Oliveira ^1*

• ¹ Purdue University, West Lafayette, United States
• ² University of Georgia, Athens, Georgia, United States
• ³ Brazilian Association of Zebu Breeders, Uberaba, Minas Gerais, Brazil

Identifying genomic regions associated with traits of interest and their biological processes provides valuable insights into the phenotypic variability of these traits. This study aimed to identify candidate genes and genomic regions associated with 16 traits currently evaluated by the Brazilian Association of Zebu Breeders (ABCZ). These traits include age at first calving (AFC), birthweight (BW), body conformation (BC), expected progeny difference for weight at 120days of age (EPD120), finishing score (FS), marbling (MARB), muscularity (MUSC), finishing precocity (FP), ribeye area (REA), scrotal circumference at 365 days (SC365), scrotal circumference at 450 days (SC450), stayability (STAY), and weight at 120 (W120), 210 (W210), 365 (W365), and 450 days of age (W450). A dataset containing 304,782 Nellore cattle genotyped with 437,650 SNPs (after quality control) was used for this study. The Algorithm for Proven and Young (APY), implemented in the PREGSF90 software, was used to compute the G_APY^(-1) matrix using 36,000 core animals. Subsequently, the SNP solutions were estimated by back-solving the Genomic Estimated Breeding Values (GEBVs) predicted by ABCZ using the single-step GBLUP method. Genomic regions were identified using sliding windows of 175 consecutive SNPs, and the top 1% genomic windows were used to annotate positional candidate genes and genomic regions associated with each of the 16 traits. The top 1% windows for all traits explained between 2.779% (STAY) to 3.158% (FP) of the additive genetic variance, highlighting the polygenic nature of these traits. Functional analysis of the candidate genes and genomic regions provided valuable insights into the genetic architecture underlying these traits in Nellore cattle. For instance, our results revealed genes with important functions for each trait, such as SERPINA14 (plays a key role for the endometrial epithelium) identified for AFC, HSPG2 (responsible for the anatomical structure morphogenesis, tissue development and differentiation) identified for BW, among others.We identified genomic regions and candidate genes, some of which have been previously reported in the literature, while others are novel discoveries that warrant further investigation. These findings contribute to gene prioritization efforts, facilitating identification of functional candidate genes that can enhance genomic selection strategies for economically important traits in Nellore cattle.