Annogen’s FACE™ screen
Developing the next generation of crops
An ever-growing global population demands a more productive and resilient agricultural system to ensure food security and environmental sustainability, especially considering our changing environment. Unlocking the full potential of agricultural crops hinges on a deep understanding of their genetic blueprint. At Annogen, we partner with leading academics and agricultural biotech companies to help develop the next generation of crops. In these collaborations we focus on what we know best: how to most effectively tailor gene expression.
Functional Analysis of non-coding sequence variants for Crop Engineering
An adaptation of our SuRE™ technology, the Functional Analysis for Crop Engineering (FACE™) assay empowers crop engineers to efficiently assess the impact of thousands of non-coding variants on gene expression in vitro. This enables researchers to for example prioritize the most promising edits for in vivo follow up.
Screen for promoter edits than can upregulate (or downregulate) your gene
If you want to change the expression level of a certain gene, one approach is to edit the promoter sequence. But how do you know which edits to make?
One approach to quickly identify important regulatory sequences and the functional impact of potential edits, is to perform a saturation mutagenesis of this promoter and analyze it in protoplasts (or in the living plant using agrobacterium).
This is shown in the adjacent plots for all possible mutations in the 35S promoter for tomato (top) and maize (bottom), with fold-activity on the y-axis.
Another example application is testing the impact of many specific variants in parallel, e.g. deletions close to PAM sites. The volcano plot below is an example of such an analysis.
Learn more about SuRE™ →
Additional examples of FACE™ applications
- Test 10,000 variants associated to drought resistance by a GWAS study to identify those that effect gene regulation
- Screen variants identified in EMS seedbanks to identify those that affect expression of relevant genes
- Generate large databases containing millions of measurements on the relation between genotype and transcriptional phenotype to train (AI) models to predict the impact of potential variants.
We have previously supported leading agriculture companies including Bayer, BASF and Syngenta and would gladly support your work as well. Contact us today to discuss your project with us.
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