From Data to Wisdom: How in silico Lead Discovery can Bridge the Gap. An Application to Abiotic Stress

Already for several years, the need for bioinformatics solutions in plant breeding is growing in order to support the crucial process of transforming the wealth of data to information, knowledge and the application of that knowledge (i.e. wisdom). It is also clear that the true limitation in this trajectory is not the attention that bioinformatics receives nor the number of available tools but mainly the practical implementation and adoption of those tools by experts from different domains. These limitations can be counteracted by bioinformatics solutions that have low user thresholds, high transparency and focus, but that are also complete: tools and insights from different bioinformatics disciplines are integrated.

This presentation shows an in silico lead discovery framework for molecular plant breeding that supports structuring, visualization and mining of heterogeneous data (sequences, genetic maps, QTLs, variances and gene expression networks) in a logical context. Within this framework it is possible to easily combine forward and reverse genetics as well as to link quantitative gene expression analysis to the underlying genome and genes. Moreover, a specific example is shown where in silico lead discovery resulted in candidate genes that were proven to increase tolerance to drought stress.