Accepted_test

Identification of subpopulation in Russian soybean germplasm collection using advanced genetic methods
by Yawar Habib | Alexey Zamalutdinov | Stepan Boldyrev | Albert Schegokolkov | Cecile Ben | Laurent Gentzbittel | Skolkovo Institute of Science and Technology, Moscow, Russia | Skolkovo Institute of Science and Technology, Moscow, Russia | Skolkovo Institute of Science and Technology, Moscow, Russia | SOKO, Krasnador, Russia | Skolkovo Institute of Science and Technology, Moscow, Russia | Skolkovo Institute of Science and Technology, Moscow, Russia
Abstract ID: 508
Event: BGRS-abstracts
Sections: [Sym 6] Section “Genomics, genetics and systems biology of plants”

Soybean (Glycine max (L.) Merr.), touted as a miracle food, not only has the potential to meet the growing oil demand but is also poised to play a significant role in satisfying the demand for vegetable protein. The ever-increasing demand for soybean products, such as tofu and soy milk, driven by the growing human population, is putting additional pressure on the available soybean genetic resources. To enhance breeding strategies and preserve these genetic resources, this study assesses the genetic diversity and identifies subpopulations within the currently available Russian soybean germplasm. Advanced genetic techniques, including Admixture, DAPC, and K-means clustering, were employed to analyze a dataset of single nucleotide polymorphisms derived from genotyping-by-sequencing (GBS) and whole genome sequencing (WGS).  Admixture identified 15 ancestral groups, many of which showed homogenous ancestry and 11 genetic clusters were identified by DAPC, revealing significant genetic diversity within the germplasm. Two densely populated clusters exhibited high genetic similarity, whereas others were  less dense and showed greater diversity. These findings provide comprehensive insights into the genetic makeup of Russian soybean germplasm, crucial for germplasm preservation and breeding new cultivars. This study highlights the importance of utilizing multiple analytical methods to capture the complexity of genetic diversity and population structure. Furthermore, the results underscore the potential for exploiting diverse genetic resources to enhance soybean breeding efforts, resulting in robust, high-yielding cultivars suitable for many environmental situations.