The creation of a public–private research partnership between plant breeding industry and academia can be beneficial for all parties involved. Academic partners benefit from the material contributions by industry and a practically relevant research focus, while industry benefits from increased insights and methodology tailored to a relevant set of data. However, plant breeding industry is highly competitive and there are obvious limits to the data and material partners are willing and able to share. This will usually include current and historic released cultivated materials, but will very often not include the elite germplasm used in-house to create new cultivars. Especially for crops where hybrid cultivars dominate the market, parental lines of hybrid cultivars are considered core assets that are never provided to outside parties. However, this limitation often does not apply to DNA or genetic fingerprints of these parental lines. We developed a procedure to take advantage of elite breeding materials for the creation of new promising research populations, through indirect selection of parents. The procedure starts with the identification of a number of traits for further study based on the presence of marker-trait associations and a priori knowledge within the participating companies about promising traits for quality improvement. Next, regression-based multi-QTL models are fitted to hybrid cultivar data to identify QTLs. Fingerprint data of parental lines of a limited number of specific hybrids are then used to predict parental phenotypes using the multi-QTL model fitted on hybrid data. The specific hybrids spanned the whole of the sensory space adequately. Finally, a choice of parental lines is made based on the QTL model predictions and new promising line combinations are identified. Breeding industry is then asked to create and provide progeny of these line combinations for further research. This approach will be illustrated with a case study in tomato.
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