(contact: Prof. Laurent GENTZBITTEL, L.Gentzbittel@skoltech.ru, In the frame of collab. with RU private seed company and public research inst.)

The development of high-performance soybean varieties tailored for diverse agroclimatic regions in Russia is an important aim. Our approach integrates whole-genome methods and advanced breeding techniques to enhance the efficiency to create original resources. We will utilize two distinct germplasms: 1) a Nested Mapping Population (NAM) derived from 15 diverse founders crossed with three elite varieties adapted to several key soybean production areas, and 2) a diversity panel sourced from the soybean collection of our partner institute. Our focus lies on achieving earliness, high productivity, and elevated protein content, crucial breeding targets for soybean improvement.

The objectives of this project include:

1. To derive the Nested Mapping Population using Speed breeding until a usable stage for breeders.
2. To genotype the Nested Mapping Population and the diversity panel using Genotyping-By-Sequencing.
3. To build the genetic map for the NAM.
4. To assess the genetic diversity and population structure in the diversity panel based on SNP data.
5. To phenotype the Nested Mapping Population for earliness, yield and protein content in a multi-environmental trial (MET) carried out in key Russian production regions, in collaboration with our partners.
6. To detect QTL for the three major agronomical traits under study, namely earliness, yield and seed protein content, on both NAM and diversity panel.
7. To develop molecular markers associated with identified QTL to help in breeding
8. To implement genomic prediction for the complex traits.

Required skills: Bio-computational analysis of NGS datasets (incl. de novo sequence alignment, SNP calling), Biostatistics (incl. GLM and MLM), Quantitative genetics incl. (GWAS, genomic prediction), molecular biology (for molecular markers development), and knowledge of plant breeding (incl. Multi-environmental trials data analysis and GXE analysis).

Deadline for application: April 15, 2024