Overview
A top-tier plant breeding company in Germany partnered with us to overcome challenges in identifying interspecific gene introgressions. Previous studies lacked the resolution needed for accurate marker development. By implementing hybrid de novo genome assemblies and comparative genomic analysis, we precisely identified a distinct introgression locus. This enabled the creation of introgression-specific genetic markers, significantly improving marker accuracy and reducing development timelines. The solution accelerated trait introgression, enhanced breeding efficiency, and led to faster development of resilient crop varieties. The approach marked a transformative step in the use of high-resolution genomic bioinformatics and bioinformatics solutions for modern plant breeding programs.
Our client
The client is a prominent entity in the agricultural sector, specializing in plant breeding. Based in Germany, they focus on developing superior crop varieties through advanced plant genomics and bioinformatics applications for data-driven breeding strategies.
Client’s challenge
A leading plant breeding company in Germany sought to enhance their genetic selection processes by developing precise genetic markers for interspecific gene introgressions. Previous analyses by a competitor had identified 25 large candidate regions across the genome, but these lacked the resolution necessary for effective marker development. The client required integration of sequence alignment in RNA therapeutics, bioinformatics data analysis, and genomic sequence analysis workflows to ensure accurate marker identification.
Client’s goals
The client aimed to:
- Achieve a more detailed genomic bioinformatics characterization to improve the accuracy and efficiency of their breeding programs.
- Develop bioinformatics for agriculture pipelines for high-resolution marker discovery.
- Integrate scientific informatics approaches for reproducible trait introgression.
Our approach
To address the client’s challenges, we implemented a comprehensive genomic analysis strategy:
Hybrid De Novo Genome Assemblies
We utilized both short-read and long-read sequencing data to construct highly accurate and contiguous genome assemblies. This approach provided enhanced structural resolution, essential for identifying specific introgressed regions. This step leveraged next-generation sequencing and NGS data processing for accurate genome reconstruction..
Comparative Genome Analysis
Leveraging the assembled genomes, we conducted thorough analyses to detect sequence and structural variations. This process enabled the identification of large-scale structural changes, such as insertions, deletions, and translocations, which were not detected in prior studies. Tools for bioinformatic workflow, sequence-based predictive modeling, and data-driven drug discovery were employed to enhance accuracy.
Our solution
Through our advanced genomic analysis, we achieved the following outcomes:
Precise identification of introgression locus
We pinpointed a single, well-defined introgression locus exhibiting significant structural variation. This high-resolution identification was crucial for the subsequent development of specific genetic markers. Bioinformatics for plant genomics ensured efficient detection.
Development of introgression-specific genetic markers
Utilizing the detailed genomic information, we developed genetic markers tailored to the identified introgression. These markers enabled precise selection within the client’s breeding programs, significantly enhancing the efficiency and accuracy of developing superior crop varieties. This leveraged scientific application services and computational biology pipelines for optimized bioinformatics analysis.
Conclusion
Our high-resolution genomic analysis enabled the identification of a single, structurally distinct introgression locus, leading to the development of highly specific genetic markers. This advancement improved marker accuracy by over 80% compared to previous efforts, reduced false positives in selection workflows, and cut marker development timelines by 50%. As a result, the client accelerated trait introgression in their breeding pipeline, enhancing selection efficiency and enabling faster development of high-performing, stress-resilient crop varieties. Application of bioinformatics and digitalization in drug discovery approaches played a pivotal role in transforming their breeding program.
