When a paper and pulp company designs its next planetary forest, it must plan for the long term. To ensure forest trees can survive, adapt and evolve under changing environmental conditions, it is vital to cope with threats such as pests and diseases in a long harvest cycles that averages between 5-7 years. Without an advanced genomic understanding, planting massive acres across the globe with the wrong tree genetics is a multi-million-dollar investment risk.
This real challenge was posed to NRGene, the Israel-based industry leader in big data genomic analysis, with an objective to create the optimal breeding and deployment strategies.
“The company approached us to discover the genetic traits responsible for pest resistance of an organism with a very complex genome,” says Guy Kol, SVP of Products & Strategic Alliances. “The goal was to breed trees that grow fast, are resilient and easy to process. Our challenge, increased by the extremely long growing cycle and the fact that backcrossing of an undomesticated tree is impossible, was to solve this complicated scenario by building the genomic data from scratch, as a first step.”
After the creation of a full genomic data, company’s highly-skilled team used its unique TraitMAGIC product to discover the desired traits in order to prevent a potential multi-million dollar damage, through the use of computational genomics.
Deliver Desired Traits
“We established NRGene with an intent to increase the breeding efficiency and outcome of plant breeding programs for companies of all types and sizes”, says Kol. “We achieve this by accurately sequencing the genome, then applying our advanced analytical tools to predict which genetic crossings will deliver the desired traits. Speed and accuracy equally reduce investment.”
“We have been able to help many companies make informed breeding decisions based on scientific data through the understanding of the genetic basis for specific traits,” says Kol.
Smarter Breeding
Using our technology, companies are able to quickly discover the phenotype-genotype correlations in any organism. “We are able to determine exact regions in the genome that contribute to specific traits”, says Kol.
“Our proprietary algorithms combine the assembly technology with skim-sequencing data to allow high accuracy genotyping as the basis of the QTL analysis, thus allowing to work in a large scale with many samples and many phenotypes simultaneously.”
Whether solving complex genomics-based breeding challenges or simply discovering a specific trait – NRGene provides the cutting-edge advanced genomic solutions to get there. To date, the company has mapped more than 400 genomes from maize, soybeans, cotton, wheat and rye to fruits, trees, cannabis and more.
“To obtain the most updated and accurate genomic understanding big investments are required. Companies that strive to make the most efficient and cost-effective decisions, approach us to help them achieve their goals,” says Kol.
