Project Inspiration
In 2020, the SUNY Oneonta iGEM team elected to use synthetic biology to create a field-deployable genetic testing system. The specific purpose of this detection system was to differentiate between two alleles of the bovine beta-casein gene, A1 and A2, which differ by a Single Nucleotide Polymorphism (SNP) (1). Cattle that are homozygous for this gene produce A2 milk, which has been reported to have health benefits over the more common A1 milk (2-4). More importantly, this A2 milk commands higher prices at market, which allows farmers to earn more for their product. Our genetic system could be used by farmers at their own farms to make selective breeding choices to convert their dairy herds to A2.
The system we conceptualized last year involves the use of a 5’ Flap Endonuclease (Flappase). This enzyme cleaves multi-DNA stranded structures called Holiday junctions. In our system, we create a Holiday junction by annealing DNA oligos to gene fragments created by using Recombinase Polymerase Amplification (RPA) (Figure 1). This Holiday junction is recognized and cleaved by the Flappase enzyme, which dequenches a fluorophore on the 5’ end of the cleaved oligo, yielding a detectable signal.
Figure 1: Conceptual workflow for how genetic polymorphisms can be detected using Flappase. DNA samples are collected and extracted, followed by amplification of the target DNA by use of RPA. The samples are then run through the Flappase Assay for variant detection.
For this year's competition, we asked why stop at A2 milk? This is only one trait that a farmer might want to breed cattle to select for. Conversely, there are also genetic traits that are undesirable, and therefore should be selected against when engaged in selective breeding. This inspired us to expand the scope of the project, which we rechristened SNflaPs. The goal of SNflaPs is to adapt our genetic testing system to enable farmers to test for a panel of genetic traits in their dairy cows. Use of this system will enable farms to determine the genetic profiles of their animals, allowing them to selectively breed them to increase the frequency of desirable traits in their herds, while making decisions about breeding out undesirable genetic traits.
Figure 2: The goal of SNflaPs is to make genetic testing more available to small operation farmers, which we hope will help level the playing field, and make small farms more profitable through better breeding.
Key features of this system are that it must be affordable, user friendly, and cost effective to permit farmers to perform genetic testing themselves. This would increase accessibility to the use of genetic testing to inform breeding choices, as well as increase the speed of results and reduce cost for the end user. Access to such technology would help level the playing field for small-scale, family operated farms which lack resources and access to breeding technologies employed by factory farms.
Figure 3: Methodology behind project inspiration. Genetic experts in the field directed us to look for new target genes of interest which we then analyzed for viability in the Flappase assay.
To accomplish this goal, we reached out to experts in dairy cattle genetics and breeding for information about what types of genetic traits are considered advantageous and deleterious in the dairy industry. Using information from these experts, we identified genes responsible for these traits and polymorphisms associated with these. Thanks to our conversations with the experts, it became clear that our system would need to detect many types of genetic polymorphisms, and not just single SNPs. We therefore selected representative genes with different types of polymorphisms (e.g., deletions, insertions, multiple SNPs) for use in the testing and development of our Flappase-based detection system.
References
- Kamiński, S., Cieslińska, A., & Kostyra, E. (2007). Polymorphism of bovine beta-casein and its potential effect on human health. Journal of applied genetics, 48(3), 189–198. https://doi.org/10.1007/BF03195213
- Nguyen, D. D., Johnson, S. K., Busetti, F., & Solah, V. A. (2014). Formation and Degradation of Beta-casomorphins in Dairy Processing. Critical Reviews in Food Science and Nutrition,55(14), 1955-1967. doi:10.1080/10408398.2012.740102
- Jianqin, S., Leiming, X., Lu, X., Yelland, G. W., Ni, J., & Clarke, A. J. (2015). Effects of milk containing only A2 beta casein versus milk containing both A1 and A2 beta casein proteins on gastrointestinal physiology, symptoms of discomfort, and cognitive behavior of people with self-reported intolerance to traditional cows’ milk. Nutrition Journal,15(1). doi:10.1186/s12937-016-0147-z
- Pal, S., Woodford, K., Kukuljan, S., & Ho, S. (2015). Milk Intolerance, Beta-Casein and Lactose. Nutrients,7(9), 7285-7297. doi:10.3390/nu7095339