Location: Sugarbeet and Bean ResearchTitle: Comparison of three PCR-based assays for SNP genotyping in sugar beet Author
|Broccanello, Chiara - Universita Di Padova|
|Chiodi, Claudia - Universita Di Padova|
|Funk, Andrew - Michigan State University|
|Mcgrath, J Mitchell - Mitch|
|Stevanato, Piergiorgio - Universita Di Padova|
Submitted to: Plant Methods
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/20/2018
Publication Date: 3/28/2018
Citation: Broccanello, C., Chiodi, C., Funk, A., McGrath, J.M., Panella, L.W., Stevanato, P. 2018. Comparison of three PCR-based assays for SNP genotyping in sugar beet. Plant Methods. 14:28. doi.org/10.1186/s13007-018-0295-6.
DOI: https://doi.org/10.1186/s13007-018-0295-6 Interpretive Summary: Genetic markers have broad applications in genetics and genomics. The use of fluorescence-tagged probes is the leading method for targeting single nucleotide difference markers, but assay costs and error rates could be improved. A new assay, rhAmp, attempts to reduce error rates while lowering costs compared to existing technologies. Before rhAmp can be widely adopted, more experimentation is required to validate its effectiveness versus established methods. The aim of this study was to compare the accuracy, sensitivity and costs of rhAmp with two other widely used genotyping methods in sugar beet (Beta vulgaris L.). The rhAmp assay produced slightly more interpretable results than either other method tested, higher signal to noise ratio, and the lowest cost.
Technical Abstract: Background: PCR allelic discrimination technologies have broad applications in the detection of single nucleotide polymorphisms (SNPs) in genetics and genomics. The use of fluorescence-tagged probes is the leading method for targeted SNP detection, but assay costs and error rates could be improved to increase genotyping efficiency. A new assay, rhAmp, based on RNase H2-dependent PCR (rhPCR) combined with a universal reporter system attempts to reduce error rates from primer/primer and primer/probe dimers while lowering costs compared to existing technologies. Before rhAmp can be widely adopted, more experimentation is required to validate its effectiveness versus established methods. Results: The aim of this study was to compare the accuracy, sensitivity and costs of TaqMan, KASP, and rhAmp SNP genotyping methods in sugar beet (Beta vulgaris L.). For each approach, assays were designed to genotype 33 SNPs in a set of 96 sugar beet individuals obtained from 12 parental lines. The assay sensitivity was tested using a series of dilutions from 100 to 0.1 ng per PCR reaction. PCR was carried out on the QuantStudio 12K Flex Real-Time PCR System (Thermo Fisher Scientific, USA). The call-rate, defined as the percentage of genotype calls relative to the possible number of calls, was 97.0%, 97.6%, and 98.1% for TaqMan, KASP, and rhAmp, respectively. For rhAmp SNP, 24 of the 33 SNPs demonstrated 100% concordance with other two technologies. The genotype concordance with either technologies for the other 9 targets was above 99% (99.34% - 99.89%). Conclusion: The sensitivity test demonstrated that TaqMan and rhAmp were able to successfully determine SNP genotypes using as little as 0.2 ng DNA per reaction, while the KASP was unable to ascertain SNP states below 0.9 ng of DNA per reaction. Comparative cost per reaction was also analyzed with rhAmp SNP offering the lowest cost per reaction. In conclusion, rhAmp produced slightly more calls than either TaqMan or KASP, higher signal to NTC data while offering the lowest cost per reaction.