A framework for identifying and prioritizing SNPs in genes of the hypothalamic- pituitary-gonadal axis in Guzerat cattle using amplicon-based NGS

The combined use of NGS technologies with bioinformatics tools has significantly advanced research by enabling comprehensive analyses of entire genomes, specific genomic regions of interest, and transcriptomes. Targeted NGS methods, which focus on smaller genome fractions, are widely used to study genetic diseases, epigenetic modifications, microbiomes, and environmental DNA, among other applications. This study aimed to develop a roadmap for detecting and selecting polymorphisms in candidate genes by integrating amplicon NGS-Target techniques with bioinformatics analyses. Sixty-eight genes associated with the hypothalamic-pituitary-gonadal (HPG) axis were selected to develop the amplicon NGS assay, comprising 730 regions that cover a total of 136,274 bp. This method was used to sequence 75 Guzerat cattle, a dual-purpose breed from Brazil, renowned for their high rusticity and adaptability. This Zebu cattle exhibit certain limitations, such as delayed puberty onset, which can reduce reproductive efficiency. Using the GATK protocol a total of 2,600 SNPs and 1,615 indels were detected. A series of consecutive filtering steps (maf, the detection of non-synonymous substitution, phylogenetic amino acid conservation, and biochemical properties) were used, resulting in a subset of 30 candidate SNPs. Then, these polymorphisms were analysed using bioinformatic tools (SIFT, PANTHER, PolyPhen2, and MutPred), identifying 5 SNPs with high effect on the protein. Their structure and stability were estimated using AlphaFold and DDMut. Finally, 3 candidate polymorphisms (IGF1R, LHCGR, TAC3R) with potentially significant effects on the protein remained to be validated through dynamic simulations or in vitro and in vivo experimental assays.