eng Rovedar Journal of Veterinary Physiology and Pathology 2821-0328 2025-09-01 4 3 20 30 10.58803/jvpp.v4i3.60 62 Umar Aziz 0 https://orcid.org/0009-0009-6266-4340 Abdul Rehman 1 https://orcid.org/0009-0009-3221-2984 Xiaolong Xu 0 Junru Zhu 0 Yonglong He 0 Zhanhang Wang 0 Li Fu 0 Fasih Ur Rehman 2 Jiayuan Li 0 Xugan Wang 0 Hanbing Yan 0 Xiaopeng An 0 Department of Animal Breeding, Genetics and Reproduction, College of Animal Science and Technology, Northwest A&F University, Yangling, China Faculty of Animal Production and Technology, Cholistan University of Veterinary & Animal Sciences, Punjab, Pakistan Department of Parasitology, University of Veterinary and Animal Sciences, Lahore, Pakistan Genotyping by target sequencing (GBTS) liquid chip is a cutting-edge genomic tool that enables the efficient detection of genetic markers for economically important traits, including milk yield, fat content, and disease resistance, in milk goats. The present study aimed to review the development, validation, and application of the GBTS liquid chip in goat genomics, emphasizing its role in precision breeding. The methodology involved extracting DNA from different goat breeds, designing probes for specific gene markers, performing genotyping using the GBTS liquid chip, verifying detected single-nucleotide polymorphisms (SNPs) through whole-genome resequencing, and assessing chip repeatability across batches. Sequence alignment, variant calling, and genome-wide association studies were conducted using bioinformatics tools such as BWA, PLINK, and GATK to ensure accurate identification of SNP loci. Advanced statistical methods, including principal component analysis and phylogenetic tree construction, are employed to demonstrate the chip's effectiveness in distinguishing genetic diversity and relationships among breeds. Functional annotation through databases such as Ensembl and KEGG helped interpret the biological roles of identified markers, while genomic prediction models, including genomic best linear unbiased prediction and BayesC, estimate breeding values for targeted selection. This integrated strategy, combining high-throughput genomic technologies, microfluidic platforms, and computational analysis, demonstrated the potential of GBTS liquid chip technology to enhance goat breeding programs by improving productivity, conserving genetic diversity, and ensuring sustainability. https://jvpp.rovedar.com/index.php/JVPP/article/view/60 Breeding Genetic marker Genomic selection Genotyping by target sequencing Liquid chip Milk goat genomic Single-nucleotide polymorphism