Agrigenomics - Novel workflow for SNP genotyping in sugar beet

Dr. Piergiorgio Stevanato, University of Padova, Italy - Sugar beet is one of the world’s most important crops, currently supplying around 20% of the sugar consumed worldwide. The development of varieties that require less technical inputs for cultivation is one of the main research goals in sugar beet. To achieve this, sugar beet breeding is focusing on genetic improvement programs assisted by SNP (single nucleotide polymorphisms) molecular markers. Several methods are available for SNP genotyping at University of Padova (Italy), with Applied Biosystems™ instruments that include Quantitative Real-Time PCR (qPCR), High Resolution Melting (HRM) and Digital PCR (dPCR) technologies. qPCR with TaqMan™ probes specific for each SNP allele is commonly used for SNP genotyping. The QuantStudio™ 12K Flex system coupled with TaqMan OpenArray™ technology constitutes a platform endowed with all the key elements required for high-throughput SNP genotyping, thus allowing rapid genotyping of large numbers of SNPs in many individuals in a relatively short time. HRM is generally used to identify SNP genotypes with unlabeled probes. QuantStudio 12K is the only real-time quantitative PCR system that combines 384-well plate compatibility with HRM analysis. An advantage of HRM over qPCR is that non-targeted mutations can also be revealed by HRM in the amplicon. Digital PCR is an emerging qPCR approach for detection of SNP polymorphisms in a diluted target sample. It is based on the partitioning of a standard PCR reaction mix in aliquots, thus allowing thousands of parallel PCR reactions. QuantStudio 3D Digital PCR System is able to identify SNP variants at about 1% allele frequency. dPCR is used for the SNP genotyping of DNA bulks, where plant DNA is pooled by group and genotyping is performed on the bulk rather than on individual plants. This option reduces the cost of SNP screening for removal of off-type plants. SNP genotyping approaches developed at University of Padova are making selection procedures in sugar beet more rapid, accurate and less expensive with relevant impact on breeding program decisions.