Studying the nature of inheritance of avenin components in F2 hybrids from crossing oat varieties of Siberian selection

The purpose of this work is to study the nature of inheritance of avenin components and description of new blocks of components in oat varieties cultivated in the Tyumen region for further use in marker breeding. Methods. We analyzed the grains of F2 hybrids from crosses of oat varieties ♀Tyumenskiy golozernyy × ♂Megion, ♀Tyumenskiy golozernyy × ♂Otrada, ♀Otrada × ♂Tyumenskiy golozernyy, ♀Megion × ♂Otrada. Native electrophoresis was performed in 13.2 % PAGE for 4.0–4.5 h at a constant voltage of 500 V. Results. In the course of research, it was found that the analyzed components of avenin make up blocks. The frequency distribution of phenotypic classes for each locus in each of the studied hybrid combinations corresponds to the assumption that each of the blocks is inherited as a single codominant mendelian unit. The synthesis of blocks of avenin components is controlled by three independent avenin-coding loci. Analysis of the inheritance of individual components of avenin in F2 hybrids made it possible to describe three new blocks of components, the synthesis of which is controlled by the Avn A locus – A9, A10, and A11; one block controlled by the Avn B locus – B7 and one block controlled by the Avn C locus – C8. On the basis of the results obtained, complete protein formulas were drawn up for the studied varieties of sowing oats: Tyumenskiy golozernyy – Avn 2.7.3; Megion – Avn 2 + 9.7.5; Otrada – Avn 10 + 11.4.8. It was found that the use of a spectrum of only one type as a standard is insufficient and leads to errors in the identification of component blocks. For more accurate identification, several varieties should be used simultaneously to obtain a complex spectrum-standard that combines several blocks of components for each locus. Scientific novelty. Described 5 new blocks of avenin components. These blocks can be used to assess the intrapopulation genetic diversity of oat varieties, as well as to search for adaptively significant and economically valuable traits linked to them.