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Scientists discover genetic markers for predicting seed oil quality

Scientists discover genetic markers for predicting seed oil quality
Figure 1. Tocopherol biosynthesis scheme with corresponding phenotype classes. Names of the metabolites are indicated in bold: 2-methyl-6-phytyl-1,4-benzoquinone - MPBQ; 3,2-dimethyl-6-phytyl-1,4-benzoquinone - DMPBQ. Gray arrows correspond to the reactions catalyzed by the enzymes indicated in the gray squares: MPBQ methyltransferase - MPBQ-MT; tocopherol cyclase - TC; γ-tocopherol methyltransferase - γ-TMT. Red arrows indicate enzymes encoded by Tph1 and Tph2. The biosynthesis pathway scheme was adapted from (Lushchak and Semchuk 2012). Credit: DOI: 10.1093/g3journal/jkac036

Researchers from Skoltech and Pustovoit All-Russian Research Institute of Oil Crops (VNIIMK) performed a genetic analysis of Russian sunflower lines and identified genetic markers that can help to predict the composition of tocopherols, one of the key attributes of oil quality. The research was published in G3: Genes, Genomes, Genetics.

Tocopherols are a class of chemical compounds, many of which have Vitamin E activity. There are four types of tocopherols: alpha, beta, gamma, and delta. Vitamin E activity decreases, whereas antioxidant characteristics increase from alpha to delta. Dressing oils are produced using varieties with a high content of alpha- and beta-tocopherols that increase Vitamin E intake. By contrast, oils used for frying, baking and roasting require a higher content of gamma (and delta) tocopherols that reduce the form of thermal oxidation products during cooking.

Marker-assisted breeding that helps create new varieties based on is widely applied across the world. Researchers use DNA sequencing and large-scale genotyping to obtain genetic profiles of cultivated plants. Analyzing and comparing genetic profiles to field data can help to find genetic markers of traits useful for farming and use them to predict a plant's properties and value based on its genetic profile alone.

"We analyzed valuable breeding lines obtained by our colleagues from VNIIMK. To do this, we used high-throughput progeny genotyping for sunflower lines contrasting in tocopherol composition. In our , we tried to find out which parts of the plant's genome are related to tocopherol composition and discovered four genetic markers that allow predicting the composition of tocopherols in sunflower," Skoltech Ph.D. student Rim Gubaev, first author and co-founder of the OilGene startup, explains.

The identified will help predict the composition of tocopherols for future sunflower lines and facilitate faster breeding of new varieties suitable for dressing and cooking oils production.

"The reason we chose sunflower is that it is a key source of vegetable oil, and Russia is the world's leading supplier of sunflower oil. The OilGene startup founded by Skoltech will use the markers to develop new testing tools," Skoltech researcher Stepan Boldrev, co-author and co-founder of OilGene, comments.

"Thanks to this project, we have gained valuable insights and built a team of like-minded people keen on helping breeders to introduce genetics in their work in order to create new commercial varieties. Our OilGene startup will focus on practical tasks and provide a genomic breeding service," Alina Chernova, Skoltech Ph.D. graduate and co-founder of OilGene, adds.

More information: Rim Gubaev et al, Genetic mapping of loci involved in oil tocopherol composition control in Russian sunflower (Helianthus annuus L.) lines, G3 Genes|Genomes|Genetics (2022).

Citation: Scientists discover genetic markers for predicting seed oil quality (2022, March 1) retrieved 9 May 2025 from /news/2022-03-scientists-genetic-markers-seed-oil.html
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Genetic analysis to help predict sunflower oil properties

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