Development of a high-throughput pipeline to identify causal variants and its demonstration in pig muscle

This project will increase the effectiveness of commercial livestock breeding programmes by developing an "Allele-Testing" framework to identify causal genomic variants that control economically important traits, using pig muscling as an exemplar trait. The framework will act as a multi-stage filter to identify causal variants by integrating information from different sources. As the stages proceed, a reducing number of variants emerge with an increasing probability of being causal and beneficial for the trait. In the project we propose to develop the framework and integrate and test four stages including genome-editing in vitro. In the future, the framework can be expanded to include new sources of information as they come available. The project will develop an "Allele Testing" framework for breeding programmes by integrating: - Sequence data and phenotypes on 375,000 pigs from a recently concluded project of ours; - Functional genomic and expression data that is publicly available, or which we have generated in a Roslin funded Pump Priming Project or will collect in this proposed project; - Data from gene-editing of cultured muscle cells to be collected in the proposed project. The project has three objectives, as follows: 1. Develop a genomics pipeline that integrates; GWAS, expression quantitative trait loci (eQTL) and functional annotation into a ranked list of putative causal variants, using a suite of statistical and bioinformatic methods. 2. Use gene editing to introduce putative causal genomic variants into a pig in vitro cell system for detection of a cell phenotype. 3. Validate the "Allele Testing" framework by predicting genomic breeding values for a set of validation pigs, with and without the information on these putative causal genomic variants discovered by the "Allele Testing" framework, followed by comparing the accuracy of both sets of genomic breeding values by correlating them to progeny test records test records.