Stats PD: Causal variant: discovery, application and implementation

Date: Tue, 11 November 2025, 10:00-11:00 AM (Adelaide)

Location: Hybrid – Zoom meeting & SET WT Waite Building 204 Meeting Room

Contact: biometryhub@adelaide.edu.au

Presenter: Dr Ruidong Xiang, Computational Biology, Agriculture Victoria Research, Department of Energy, Environment and Climate Action (DEECA)  | School of Applied Systems Biology, La Trobe University

 Causal variant: discovery, application and implementation

Most genomic research in agriculture relies on genotyping panels, or SNP chips. However, SNP chips are designed to include genetic markers, instead of causal mutations. Causal mutations are those variants that directly impact the expression of phenotypic traits. In agricultural species, at least in animals, causal mutations are difficult to identify due to their high correlation (linkage disequilibrium or LD) with non-causal SNP markers. In this talk, I will discuss years of research by us in trying to discover causal variants using statistical analysis, applying them in genomic prediction and the implementation of these findings in the breeding industry. I will also discuss some future insights into validating and using causal variants with new technologies.

Email the Biometry Hub to get the zoom link!