Relevance

For the first time in Kazakhstan, genome-wide association studies (GWAS) and genotyping-by-sequencing (GBS) are planned to investigate sunflower resistance to Plasmopara halstedii. Unlike most foreign studies, which focus primarily on already known resistance genes, this project is aimed at local sunflower populations adapted to the agroclimatic conditions of Kazakhstan. This approach is expected to reveal novel SNP markers unique to the national gene pool.

The project envisages the deposition of Pl. halstedii races in international databases and the integration of the resulting data with global resources (NCBI, Sunflower Genome Database, HeliaGene), thereby ensuring a tangible contribution of Kazakhstan to global sunflower genomics. The use of state-of-the-art next-generation sequencing (NGS) technologies will enable the development of a panel of molecular markers for breeding and their potential application in CRISPR/Cas-based gene editing.

Project Aim

The aim of the project is to investigate the distribution of Pl. halstedii races and strains circulating in sunflower-growing regions and to identify single nucleotide polymorphisms (SNPs) associated with resistance to the pathogen, as well as chromosomal loci in parental sunflower lines, using modern molecular-genetic methods (GBS) and genome-wide association studies (GWAS).

Expected Results

1. At least 200 plant samples and at least 40 Pl. halstedii isolates will be collected from different sunflower-growing zones. Pure cultures of sunflower downy mildew will be obtained, and races and strains of the pathogen will be identified using differential sunflower lines and molecular-genetic methods, followed by deposition of the corresponding materials and/or data.
2. Phenotypic data on resistance to downy mildew will be obtained for the studied samples based on at least two years of observations. As a data source, breeders’ and phytopathologists’ reports on the assessment of resistance to downy mildew under field trial conditions over two growing seasons will be used.

3. The collected samples will be screened to assess the degree of resistance of breeding material to different Pl. halstedii races using a controlled laboratory assay based on incubating sunflower seedlings in suspensions of downy mildew zoospores.

4. Large-scale genotyping of the selected sunflower lines will be carried out for multiple SNP loci using genotyping-by-sequencing (GBS), yielding data for at least 10,000 SNPs.

5. Genome-wide association studies (GWAS) will be performed using GBS-derived genotypic data and phenotypic data on resistance to downy mildew for the studied samples.

6. A phylogenetic analysis of the investigated sunflower lines will be conducted on the basis of GBS-derived SNP data. At least one research article or review will be published in a peer-reviewed international or national journal recommended by the Committee for Quality Assurance in the Field of Science and Higher Education.

7. At least 10 potential molecular markers for resistance to downy mildew, identified from GWAS data, will be validated.

8. The studied samples will be genotyped using known downy mildew resistance markers (Pl loci) previously described in the literature.

9. A panel of molecular markers for marker-assisted selection for resistance to downy mildew will be developed. This marker panel will be tested on sunflower samples. Supporting scientific, technical, and methodological documentation for the use and application of the developed marker panel will be prepared. The validated marker panel, together with the accompanying documentation, will be implemented in the breeding programme of LLP “OCEF”.

10. Sunflower varieties and hybrids of Kazakhstani breeding will be screened for the presence of SNPs associated with resistance to downy mildew. As a result, sunflower genotypes potentially resistant to downy mildew will be identified based on the obtained marker data.

Project Leader

Maxim Y. Sutula, PhD, Associate Professor, h-index: 3, ResearcherID: AAX-2587-2020, ORCID: 0000-0002-3153-6356, Scopus Author ID: 57191078504

Members of the Research Team

1. Shuga A. Manabayeva, PhD, h-index: 5, Researcher ID: A-2529-2015, ORCID: 0000-0001-7884-1713, Scopus Author ID: 55615915000
2. Tatyana S. Khosnutdinova, MSc, PhD student, h-индекс (Хирша): 1; ResearcherID: HGY-2055-2022; ORCID: 0000-0002-0415-4790; Scopus Author ID: 57638950500
3. Aynura M. Smagulova, Candidate of Biological Sciences (PhD equivalent)
4. Prof. Cecile Ben, PhD, Associate Professor (foreign scientist)
5. Elena U. Martynova, Candidate of Biological Sciences (foreign scientist)

Publications and Intellectual Property Related to the Project

Publications in WOS/Scopus databases: Sutula, M., Kakanay, A.; Tussipkan, D., Dzhumanov, S., Manabayeva, S. Phylogenetic Analysis of Rare and Endangered Tulipa Species (Liliaceae) of Kazakhstan Based on Universal Barcoding Markers. Biology 2024, 13, 365. https://doi.org/10.3390/biology13060365 (WOS Q1; SCOPUS 85%; IF 3.6)M. Sutula, T. Khosnutdinova, E. Zhakmanova, A. Akhmadiyeva. The prevalence of recombinant strains of potato virus Y in the East Kazakhstan region. Plant Disease. APS Publications. Vol. 107, No.1. https://doi.org/10.1094/PDIS-05-22-1027-PDN (WOS Q1; SCOPUS 75%; IF 4.5) Sutula, M.Y., Kabataeva, Z.K., Komekova, G.K. Khosnutdinova T. S., Zhakmanova E. A. Isolation of CP-PVY-Specific siRNA from PVY-Infected Plants of Solanum tuberosum. Russ J Plant Physiol 70, 72 (2023). https://doi.org/10.1134/S1021443722700108 (WOS Q3; SCOPUS 48%; IF 1.4)Maulit A, Nugumanova A, Apayev K, Baiburin Y, Sutula M. A Multispectral UAV Imagery Dataset of Wheat, Soybean and Barley Crops in East Kazakhstan. Data. 2023; 8(5):88. https://doi.org/10.3390/data8050088 (WOS Q2; SCOPUS 70%; IF 2.6)Bondarovich A, Illiger P, Schmidt G, Ponkina E, Nugumanova A, Maulit A., Sutula M. Effects of Agricultural Cropping Systems on Soil Water Capacity: The Case in Cross-Border Altai. Span. J. Soil Sci., 13:11493 (2023). https://doi.org/10.3389/sjss.2023.11493 (WOS Q4; SCOPUS 39%; IF 1.1) 6. M. Sutula, A. Kakanay, S. Manabayeva. DNA barcoding of the genus Tulipa (Liliaceae) in Kazakhstan. Eurasian Journal of Applied Biotechnology, 2024 (3), 56–65. https://doi.org/10.11134/btp.3.2024.6  7. Kali, B., Sutula, M., Akhmetollayeva, A., & Manabayeva, S. Identification of plants of the family Fabaceae using molecular barcoding analysis. Eurasian Journal of Applied Biotechnology, 2024 (3), 158–169. https://doi.org/10.11134/btp.3.2024.17  8. Sutula, M., Khosnutdinova, T., Zhakmanova, Y., Dolanbayeva, G., Bogdanova, X., Yessilbekova, Y., Komekova, G., Kabatayeva, Z. Priming of Solanum Tuberosum in vitro plants with PVY-specific interfering RNAs activates anti-viral resistance. Eurasian Journal of Applied Biotechnology, (2022). (3), 14–24. https://doi.org/10.11134/btp.3.2022

Results Obtained

2025:

1. A total of 200 plant samples and 40 Pl. halstedii isolates were collected from different sunflower-growing zones; pure cultures of downy mildew were obtained, and the race and strain of the pathogen were identified using differential lines and molecular-genetic methods, followed by deposition of the corresponding materials and/or data.
2. Phenotypic data on resistance to downy mildew were obtained for the studied samples based on two years of observations. As a data source, breeders’ and phytopathologists’ reports on resistance to downy mildew under field trial conditions over two growing seasons were used.