The genetic material of plants can be altered by crossing, natural mutations, targeted induction of mutations by radiation or chemicals, and biotechnological methods. The aim of our work is to detect such changes in the DNA of the plant. For this purpose, we analyze sequence data of different plant lines and cultivars using bioinformatic methods. Furthermore, we compare the observed changes of different breeding methods.

The genetic material of every cell in an organism is largely identical. Nevertheless, specialized cells, tissues or organs perform very different tasks. These functional differences are enabled by (complex) regulatory mechanisms that cause genes to become active only when they are needed. Special regulators bind to DNA or its working copy, the RNA, and can for example switch genes on or off. To gain a better understanding of regulatory mechanisms, we predict binding sites. To do this, we use bioinformatics to compare patterns in sequence data of similarly regulated genes.

As sequencing technology advances, more and more plant genomes are being decoded. In addition, there are partially decoded genomes of multiple lines or varieties of a plant species. In addition, the location of the genes is of particular interest to researchers and breeders. However, the prediction of yet unknown genes is a laborious, complicated and error-prone process. Nevertheless, it is possible to consider known genes in related plant species to detect similar genes in unknown genomes. We use such comparisons to improve gene prediction. For this purpose, we developed the software package GeMoMa, which has already been successfully used for many genomes and is applied worldwide. GeMoMa is under continuous development.

Literature reviews summarize available scientific data on a specific topic. With the rapidly growing amount of published literature, this is becoming increasingly urgent and challenging. A special approach (systematic reviews) aims to make the data collection and evaluation process as reliable and comprehensible as possible. This involves a significant investment of time and person power. We provide computer-based tools to efficiently support review authors in their work. These include the online tool CADIMA, which is freely available to the public and is continuously being further developed.

The Institute SB also coordinates the bioinformatics exchange among colleagues on current topics and issues across the JKI.