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Genetic Analysis Could Help Predict Sunflower Properties

A team of researchers from Skolkovo Institute of Science and Technology and from the University of Southern California has identified the genetic markers that could help predict the composition of sunflower oil using genetic analysis. The researchers used bioinformatics analysis to study 601 lines of cultivated sunflower from two major Russian gene banks and Agroplasma's collection.

A team of researchers from Skolkovo Institute of Science and Technology and from the University of Southern California has identified the genetic markers that could help predict the composition of sunflower oil using genetic analysis.

 

The researchers used bioinformatics analysis to study 601 lines of cultivated sunflower from two major Russian gene banks and Agroplasma's collection. They used the results of the analysis to check the genetic diversity of the sunflower to compare with the global collection. The results revealed the genetic markers that are essential in the fatty acid oil composition of the sunflower which is not present in the international collection.

 

The study provides valuable information for breeders to develop sunflower varieties that can produce oils with different properties suitable for food and industrial uses. The data could also be used in producing sunflower varieties that can grow under different environmental stress.

 

For more details, read the article in Skoltech and the journal article in BMC Genomics.

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