I first met Dr. Pengyin Chen and Dr. Caio Canella Vieira in July 2020. Dr. Chen is a faculty member at the University of Missouri in the Plant Science Division, College of Agriculture, Food and Natural Resources, and holds the D.M. Haggard Endowed Professorship in Soybean Breeding and Genetics. Dr. Canella is a Post-doctoral Fellow working with Dr. Chen. Little did I realize that these initial meetings would quickly develop into a rewarding collaborative relationship between the University of Missouri and NRGene.
Dr. Chen leads a large, public soybean breeding program for the University of Missouri. The primary objective of the program is to release finished lines that offer superior yield, specific traits, and improved disease resistances compared to existing cultivars available to growers. Currently, Dr. Chen’s program is almost entirely conventional, which means that breeding decisions are largely driven by the performance of new lines in the field without the use of molecular marker data or knowledge of the genetic factors that underlie performance.
Dr. Chen would like to improve his program by adopting advanced breeding methods like genomic selection. The cost and complexity of implementing genotyping at scale, however, is a real barrier.
This is a common problem. Recognizing the need, NRGene developed innovative, customized solutions to reduce financial barriers facing breeders who aspire to adopt the latest, cutting-edge molecular breeding methods. Yet, after fruitful discussions with Dr. Chen and Dr. Canella, it became apparent that NRGene’s customized solutions, while highly desirable and offering many benefits in other contexts, could be improved. Further reductions in cost could be achieved by a generic solution. The resources needed to develop this solution were readily available, and this solution would be broadly applicable to all soy breeding programs in North and South America. It was out of these insights that Soy SNProTM was conceived.
Many molecular breeding applications in soy utilize genotypic data for 6,000 SNP loci collected from a very large number of samples. NRGene sought to deliver data for the 6,000 SNP loci by directly genotyping only 500 loci and imputing data for the remaining 5,500. Soy SNProTM comprises two essential elements: (1) a low-density genotyping plex that enables 500 SNP loci to be genotyped in the lab, and (2) a computational pipeline that imputes accurate data for 6,000 SNP loci from the 500 SNP loci directly genotyped by the plex.
How does Soy SNProTM reduce genotyping costs? Genotyping costs typically scale dramatically with the number of samples genotyped and the number of SNP loci genotyped in each sample. Imputation, however, does not. Hence, the goal is to minimize the number of loci genotyped and maximize the number of loci imputed. NRGene scientists optimized the genotyping plex and the imputation algorithms together to deliver accurate data for 6,000 loci and yet minimize lab costs by genotyping only 500 loci. Imputation works due to the high levels of linkage disequilibrium that exists in structured breeding populations.
In addition to reducing cost, the complexity of large-scale genotyping is reduced for the breeder through NRGene’s continuing support. The breeder only needs to collect and submit tissue samples for the lines to be genotyped, while NRGene manages the genotyping process, data quality control, and imputation pipeline, and – ultimately – delivers complete, high-quality data to the breeder.
Overall, the collaboration between the University of Missouri and NRGene is an outstanding example of how NRGene strives to meet the requirements of a breeding program and enables the program to deliver value to downstream producers and consumers. This collaboration enabled the University of Missouri to acquire genotypic data for its current breeding populations as it proceeds to implement advanced molecular breeding methods in its program. The collaboration has also enabled NRGene to develop and validate a low-cost genotyping solution that can be offered to other soy breeding programs with the promise of similar benefits. Finally, the University of Missouri may continue to reap the benefits of participating in the development of a cost-effective genotyping solution.
To add a personal note, I find successful partnerships like this both rewarding and gratifying. What was initially a potential customer interaction with Dr. Chen and Dr. Canella has transformed into a collaboration. I am proud to be a member of the NRGene team and of what it has accomplished.
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