The overall aim of this project is to unravel the genetic architecture underlying equine body conformation and locomotion to complement traditional subjective breeding evaluations with objective, genomics-informed tools. Horse conformation is directly relevant to locomotor function, performance, and injury risk, and has been shaped by both natural adaptation and selective breeding. However, the link between genetic background and body shape remains poorly quantified, largely due to the lack of precise, scalable phenotyping methods. This project, NextGen Horse, integrates Whole Genome Sequencing (WGS) with an innovative 3D digital phenotyping pipeline (VAREN), to generate a unique dataset combining deep genomic and morphological data. We will sequence blood-derived DNA from horses across multiple breeds selected to maximise phenotypic diversity, and combine this with 3D body scans and markerless motion capture data from a partially overlapping cohort of horses. The specific objectives are to: - Process and quality-control WGS data through a variant-calling bioinformatics pipeline (SNVs, indels, structural variants); - Generate objective 3D morphological and locomotor phenotypes from digital scanning and motion capture; - Apply quantitative genetics approaches (GWAS, ridge regression) and explore novel methods to associate genomic variants with conformation and motion traits; Evaluate genomic and machine learning frameworks to integrate genomic embeddings with 3D phenotypic data, exploring the feasibility of predicting body shape directly from sequence data. By combining state-of-the-art sequencing with unprecedented phenotypic resolution, NextGen Horse aims to identify novel genomic regions associated with conformation and locomotion, deepen understanding of genotype-phenotype relationships shaped by domestication, and ultimately provide new tools for informed, sustainable breeding selection in horses.