Marker technology and genome selection

Genetic markers are short segments of DNA with a known location within the genome and which are inherited together with a certain characteristic (for example, a gene). Using molecular markers, these characteristics (genes) can be quickly and easily identified before they appear as a fully grown plant. As a result, fungal resistance can already be determined in seedlings. Molecular markers make plant breeding significantly more efficient.

Without this modern procedure, we would have to wait until the plant has grown to full maturity to be able to observe the desired characteristic attributes. For example: Breeders cross two parental lines with each other and then let the seed germinate. They then obtain a small leaf sample from each seedling and analyse the DNA. If this reveals the marker they are looking for, it means that the offspring has the desired characteristic. Thanks to molecular markers, we can find out within 48 hours whether a desired characteristic is present in the cultivated variety. This allows for preselection of the offspring and allows breeders to concentrate on the most promising plants.

The lab results are then tested in field trials with far fewer candidates than ever before, which increases efficiency.

Even faster with genome selection

Genome selection is a further development of the traditional marker technology (MAS) and leads to an even better and more reliable selection when choosing suitable crossing partners and future varieties. Because the cost of detecting genetic markers has significantly decreased, one plant can be analysed for various markers simultaneously.

Breeders do this by creating a marker profile with several thousand markers for each individual plant. Each plant has a specific marker profile, comparable to a fingerprint. With the high-throughput marker technologies already established at KWS, marker profiles can be created quickly and cost-effectively.

Thousands of marker profiles from one plant population are then linked to the measured field data. Based on this, statistical and mathematical models are developed that can be used to predict the breeding value of the plants and whether they are suitable for subsequent development of varieties, based on the marker profiles of seeds or young plants. Complex software then assumes the task of determining those plants that are most promising for crossing from the marker profiles of other individual plants that were not field-tested. Thanks to this preselection process, many field tests are no longer required, while breeding progress is maintained.

Close collaboration between genome and breeding research continuously increases breeding efficiency and accelerates breeding progress.