Karacabey_merino_50K_genotype_data

<b>Abstract</b>Sheep have demonstrated remarkable adaptability to diverse and unproductive pastures, making them highly advantageous in the context of sustainable farming practices in the globally warming world. Despite their adaptation skills, local sheep breeds generally exhibit low performance, highlighting the need to develop desired traits. Traditional Mixed Linear Model (MLM)-based single-locus Genome-Wide Association (GWA) studies may fall short in identifying multiple loci influencing traits due to their linear genome scanning approach, rendering them less effective for detecting polygenic effects. To address this, various multi-locus methods have been developed, including MrMLM, FastMrMLM, ISIS EM-BLASSO, FASTmrEMMA, pLARmEB, and pKWmEB. These methods utilize a two-stage process to detect associated markers, first screening with a single locus approach at a less strict significance threshold, followed by collective evaluation using multi-locus GWA models. In the present study, using five multi-locus approaches, 11 SNPs were detected with significant effects on the birth weight (BW) and seven SNPs on the weaning weight (WW) in Karacabey merino lambs. Gene annotation revealed most associated SNPs were within or very close to protein-coding genes, suggesting a functional role in trait influence. Due to their location within intron regions or within ±100 Kb proximity of associated SNPs, we propose the genes <i>GNAQ</i>, <i>CDKL4</i>, <i>PIP</i>, <i>SLC7A1</i>, <i>PBRM1</i>, <i>SORCS3</i>, and<i> NFATC1</i> as candidate genes for the BW, while the genes <i>BABAM2</i>, <i>LALBA</i>, <i>NOP14</i>, <i>FAM110B</i>, <i>SKAP1</i>, <i>SVIL</i>, and <i>ATXN1</i> for the WW. These insights contribute to a better understanding of the genetic makeup of the the BW and WW traits, supporting efforts to refine breeding programs for improved growth performance.<br>