The Challenge
Whilst Cassava (Manihot esculenta) is one of the most important starchy root crops in the tropics, its genome biology is rarely studied using advanced tools for detecting phenotype impacting Single Nucleotide Polymorphisms (SNPs), genes and molecular pathways.
Synomics applied a combination of a proprietary technology platform and deep industry experience to identify predictive SNPs for Cassava Mosaic Disease (CMD) resistance. The aim was to understand whether our platform could identify novel insight that could improve disease resistance and help support food security in developing and under-developed parts of the world where the crop is a staple part of their diet.
Our Solution
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).
for 3-month CMD
for 1-month CMD
The Results
Synomics’ platform was able to identify novel genetic variants and produce biologically relevant results, for example identifying 285 and 136 unique candidate genes for CMD, not reported before in the literature, related to 3-month and 1-month disease cases, respectively. Furthermore, we were able to identify key biological mechanisms underlying CMD through the novel technique of using well-researched ortholog genes as replacements for poorly annotated species, such as cassava, to find enriched pathways. These results show the value the Synomics’ platform has in discovering novel targets. The 67 QTNs identified as either disease resistance or susceptibility loci for CMD will pave the way for further functional validation and for potential use as gene introgression or editing targets.
