The Challenge
Synomics’ combination of a proprietary technology platform and deep industry experience offers unique potential to identify trait-associated, combinatorial and predictive SNPs that standard GWAS does not find and translate these SNPs to breeding models which out-perform current best-in-class.
In this study, we used key commercial traits in dairy cattle (lameness, pregnancy success to first insemination, mastitis and 305-day fat yield) across multiple SNP densities (from 50k to 59m) to investigate the additional, detailed insight our platform was able to discover. The study sought to quantify the impact this additional insight has when translated to a genomic prediction model and genomic selection.
Genotype and phenotype datasets were analysed in Synomics’ proprietary platform, identifying high-order combinations of SNPs (including epistatic interactions). These combinations capture the non-linearity of biological effects and the impact they have on phenotypes much better than existing methods based on single features (such as GWAS). These novel, biologically, and statistically relevant genetic variants were then incorporated into our next-generation genomic evaluation method.
The Results
Despite the comparatively small dataset, Synomics’ platform identified signals sufficient to detect 13 – 117 highly-predictive SNPs which mapped to between 6 – 31 genes, which are potential targets for intervention. We were able to find these SNPs despite small sample sizes and high SNP chip densities. Indeed, increasing SNP density (777k and 59 million low pass sequence) found more novel signals. Conversion of these unique SNP combinations into a standard genomic prediction model showed step-change improvement in key metrics as well as a materially wider EBV distribution compared with standard breeding models. This results in an increased genetic gain in dairy cattle breeding.
Synomics has licensed global use of this proprietary technology platform in bovine exclusively to Vytelle Holdings Inc.
