What agrigenomics covers

Agrigenomics brings genomic information into breeding decisions. By combining genotype data with phenotype observations, breeding programmes can identify appropriate markers earlier, improve selection accuracy and increase the rate of genetic gain.

Plant genomics plays a central role in modern crop breeding, helping breeders associate genetic markers with economically important traits and make selection decisions. Applications include marker-assisted selection, marker-assisted backcrossing, genomic selection, parentage testing, germplasm characterisation, variety identification, seed purity assessment and GMO testing. These approaches are now widely integrated into modern crop and livestock improvement programmes.

Choosing a genotyping method for your throughput

The best genotyping technology depends on the number of samples being processed, the number of markers under investigation and the objectives of the breeding programme.

For breeding programmes screening a defined set of markers across large populations, PCR-based genotyping frequently offers the most efficient balance of throughput, turnaround time and cost per data point. Sequencing approaches are often selected for marker discovery, genome characterisation and high-density genomic analysis.

Working from crude plant extracts

For many breeding programmes, the goal is not simply to generate more data. It is to generate enough high-quality data to improve selection decisions without increasing programme costs.

In high-throughput breeding programmes, DNA purification can become a significant bottleneck, increasing labour requirements, consumable costs and sample turnaround times. As a result, many crop breeding organisations use crude extraction workflows based on leaf punch samples to increase throughput and simplify sample handling.

However, plant tissues often contain compounds that can inhibit downstream reactions. Successful workflows therefore depend on extraction and genotyping chemistries that maintain reliable performance despite these challenges. When implemented effectively, crude extraction can significantly improve throughput and reduce the cost per data point.

Plant breeding: trait screening and marker-assisted selection

Marker-assisted selection helps breeders identify favourable genotypes before target traits are fully expressed in the field. This allows selection decisions to be made earlier in the breeding cycle and can reduce the resources required for phenotype-based screening.

Applications include screening for disease resistance, abiotic stress tolerance, quality attributes and yield-related traits. Marker-assisted backcrossing can further support the efficient transfer of valuable traits into elite germplasm through the assessment of foreground markers for trait introgression and background markers for recovery of the recurrent parent genome. As breeding populations expand, scalable SNP genotyping workflows help breeders evaluate more material while maintaining confidence in selection decisions.

Animal and livestock breeding: parentage, traits and genomic selection

Livestock breeding programmes increasingly rely on genomic data to support parentage verification, trait screening and genomic selection.

Reliable genotyping data helps confirm pedigree records, supports breeding value predictions and enables more informed selection decisions. Across cattle, poultry, swine, sheep and aquaculture programmes, genomic tools are helping breeders improve productivity, health and long-term genetic progress.

Scaling agrigenomics from hundreds to hundreds of thousands of samples

Agrigenomics operates at a scale that differs significantly from many other genomics applications. Breeding organisations routinely process large populations, making throughput, automation and operational efficiency critical considerations. 

When programmes scale, every step influences overall economics, including sample collection, DNA extraction, assay design, automation, data analysis and reporting. Small improvements in workflow efficiency can have a substantial impact when applied across tens or hundreds of thousands of samples. 

For large breeding programmes, technology selection is often driven as much by throughput and cost per data point as by analytical performance. Aligning extraction, genotyping and automation strategies with programme goals can help maximise efficiency while maintaining confidence in selection decisions.