The Enterprise Breeding System (EBS), developed by CGIAR, is transforming how rice breeders utilize molecular data to enhance varieties. For years, EBS has been the trusted platform for managing breeding information, germplasm, and trial data. Today, it takes a step further: through QTL profiling, the system can now turn complex genotyping data into clear, actionable insights—faster and at scale.
From Manual Processing to Instant Results
Traditionally, analyzing molecular data was a slow and painstaking task. Breeders often spent days—or even weeks—cleaning datasets and interpreting results. With the new Molecular Data Analytics (MDA) module in EBS, this process is streamlined into just three steps: request, upload, and analyze. In a few minutes, breeders receive precise gene profiles, freeing them to focus on strategic breeding decisions.
Precision That Drives Breeding Progress
QTL profiling enables breeders to pinpoint which genes and traits are present—or missing—in their breeding material. This is critical for selecting traits such as disease resistance, stress tolerance, and yield stability. Currently, EBS generates profiles for approximately 90 key rice genes and QTLs, with more being added as research advances. By keeping the platform updated with the latest scientific discoveries, breeders gain direct access to information that bridges innovation and practical application.
The development of this QTL profiling functionality has been made possible through the work of Marinell Quintana, Jared Muñoz, Alaine Gulles, Argem Flores, and Marko Karkainnen from the EBS team, with technical guidance from Dr. Damien Platten and testing support from Janine Vitto. Their combined expertise ensures the tool is both scientifically robust and practically useful for breeding programs worldwide.
Standardized and Scalable Across Programs
Unlike fragmented tools of the past, EBS offers globally standardized pipelines that deliver consistent, high-quality results across breeding programs. With this approach, breeders can:
- Rapidly generate high-throughput genetic fingerprints of their materials
- Monitor gene frequencies across populations to identify gaps
- Select superior parents and progeny with greater confidence
This unified system ensures greater accuracy, efficiency, and speed in breeding cycles—helping programs deliver improved rice varieties to farmers more quickly.
Future-Ready Performance
Working with huge datasets may sometimes slow loading times—for instance, when selecting thousands of samples and markers. However, this is also an opportunity for growth. Upcoming improvements will deliver faster processing, smarter optimization, and greater responsiveness, keeping EBS scalable, reliable, and ready for tomorrow’s demands.
Breeding Made Smarter
By embedding genetic fingerprinting into EBS, breeders gain a powerful yet user-friendly tool that simplifies complex analytics. With reliable insights available in just a few clicks, rice breeding is becoming faster, smarter, and more effective. This innovation strengthens CGIAR’s commitment to supporting global breeding programs with cutting-edge tools that accelerate genetic gains and contribute to food security worldwide.