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HomeAP 13068118 (superviser Zatybekov А.Kh.)

AP 13068118 (superviser Zatybekov А.Kh.)

Brief description of the project

(2022-2024)

 Project title: IRN AP13068118 «Mining for genes associated with agronomic traits of soybean (Glycine max (L.) Merr.)  using whole-genome resequencing of world collection».

 Relevance. The main goal of the project is the identification of genes associated with yield components and quality using whole-genome re-sequencing (WGRS) technology for world soybean collection. The analysis will use a data matrix containing the nucleotide sequences of 252 cultivars genomes, including 31 genotypes from Kazakhstan and more than 3 million polymorphic SNPs. Bioinformatics analysis of the WGRS data and field experiments will be used in association mapping and identification new genes in soybean enhancing breeding programs. Additionally, results of the project will help to select promising soybean material based on field data and association mapping, to develop KASP markers

 The goal of the project: Identification of quantitative trait loci and genes that control productivity and quality, based on the whole-genome re-sequencing of 252 samples of the world soybean collection and the development of two sets of KASP markers for agronomic traits in the southeast and north regions of the country

 Expected results:

  1. WGRS of 31 local accessions using Illumina HiSeq X Ten System platform, in addition to the 221 accessions that already re-sequenced as a groundwork for the project. The genetic variation in soybean collection (252 samples) will be evaluated; polymorphic SNPs will be identified; matrix data for GWAS will be prepared.
  2. Soybean collection consisting of 252 accessions harvested in southeast and north Kazakhstan will be studied for agronomic traits. The variability of morphological, yield, and quality traits tested in two regions will be assessed.
  3. Based on WGRS of 252 accessions, GWAS will be carried out to identify QTLs and genes significantly associated with morphological, yield and quality traits.
  4. Population analysis will be done to determine the genetic clustering of Kazakh and foreign genotypes, including samples of wild-growing soybeans.
  5. SNP markers will be validated for the traits that determine soybean yield and quality.
  6. Informative sets of KASPs will be developed for the breeding of soybeans with high values of agronomic traits.

Scientific Supervisor of the project: Zatybekov Alibek, Ph.D., senior researcher, laboratory of molecular genetics, IPBB, 11-years experience, including 5-years  experience on the project topic, co-author of 23 scientific articles: 6 in peer-reviewed editions Web of Science and Scopus (H-index 3, https://www2.scopus.com/authid/detail.uri?authorId=57196942983), 17 papers in editions recommended by CCSES; co-author of the soybean cultivar (Danelia), 1 scientific-methodological recommendations, 2 patents for utility model.

 Research group: 

Zinchenko Alena, senior researcher, Laboratory of agricultural crops breeding, Agricultural Experimental Station «Zarechnoye», Kostanay region. Master of sciences, PhD student at the Omsk Agrarian University. Co-author of 25 articles, including 18 on soybean; co-author of 3 released   soybeans cultivars: Ivushka, Svetlyachok, Danelia.

Anuarbek Shynar, PhD, researcher at the molecular genetics laboratory, IPBB, 8-years work experience, has 20 scientific papers, incl. 6 articles (4 in peer-reviewed journals, indexed in Web of Science and Scopus (H-index 2, https://www2.scopus.com/authid/detail.uri?authorId=57192177334); 3 articles in CCSES journals), 1 scientific and methodological recommendations, 2 Patents etc.

Genievskaya Yulia, junior researcher, the molecular genetics lab, IPBB; MSci, has 15 scientific papers, including 10 articles in peer-reviewed journals indexed in Web of Science and Scopus (H-index 5, https://www2.scopus.com/authid/detail.uri?authorId=57196939730); 5 articles in CCSES journals, co-author of the Patent.

Abildaeva Dzhyldyz, junior researcher, Department of leguminous crops, Kazakh Research Institute of Agronomy and Plant growing (KRIAPG), Almaty region, ORСID ID 0000-0001-7898-0887.

Doszhanova Botakoz, MSci, junior researcher IPBB, PhD student at al-Farabi Kazakh National University, 3 publications in CCSES editions, co-author of 1 patent, ORCID ID 0000-0002-5085-7657. Trained in Japan scientific centers.

Podzorova Tamila, bachelor, laboratory assistant at the IPBB, 2rd-year MSci course at KazNU named after al-Farabi, ORCID ID 0000-0002-9521-5754.

 List of publications of the project’s participants (2017-2022)

  1. Zatybekov A., Abugalieva S., Didorenko S., Gerasimova Y., Sidorik I., Anuarbek Sh., Turuspekov Y. (2017). GWAS of agronomic traits in soybean collection included in breeding pool in Kazakhstan. BMC Plant Biology (IF=3.497, Q1-Plant sciences; SJR=1.485, percentile=87). 2017;17(1):64-70. doi:10.1186/s12870-017-1125-0.
  2. Zatybekov A., Abugalieva S., Didorenko S., RsaliyevA., Turuspekov Y. (2018). GWAS of soybean breding collection for resistance to fungal diseases in condition of South-East and South Kazakhstan. Vavilovskii Zhurnal Genetiki i Selektsii (SJR=0.181, percentile=38). 22(5):536-543. doi:10.18699/VJ18.392.
  3. Zatybekov A., Turuspekov Y., Doszhanova B., Didorenko S., Abugalieva S. (2020). Effect of Population Size on Genome-Wide Association Study of Agronomic Traits in Soybean. Proceedings of the Latvian Academy of Sciences, Section B: Natural, Exact, and Applied Sciences (SJR=0.168, percentile=39). 74(4):244–251. DOI:https://doi.org/10.2478/prolas-2020-0039.
  4. Doszhanova B.N., Didorenko S.V., Zatybekov A.K., Turuspekov Y.K., Abugalieva S.I. (2019). Analysis of soybean world collection in conditions of south-eastern Kazakhstan // International Journal of Biology and Chemistry. 12(1):33. doi:10.26577/ijbch-2019-1-i5.
  5. Abugalieva S., Didorenko S., Anuarbek S., Volkova L., Gerasimova Y., Sidorik I., Turuspekov Y. (2016). Assessment of Soybean Flowering and Seed Maturation Time in Different Latitude Regions of Kazakhstan. Plos ONE (IF=3.788, Q2; SJR=1.023, percentile=91). 11(12):e0166894. doi:10.1371/journal.pone.0166894.
  6. Anuarbek S, Abugalieva S, Pecchioni N, Laidò G, Maccaferri M, Tuberosa R, Turuspekov Y. (2020) Quantitative trait loci for agronomic traits in tetraploid wheat for enhancing grain yield in Kazakhstan environments. PLoS ONE (IF=3.788, Q2; SJR=0.990, percentile=92). 15(6):e0234863. doi:10.1371/journal.pone.0234863
  7. Genievskaya, Y., Abugalieva, S., Rsaliyev, A., Yskakova, G., & Turuspekov, Y. (2020). QTL Mapping for Seedling and Adult Plant Resistance to Leaf and Stem Rusts in Pamyati Azieva×Paragon Mapping Population of Bread Wheat. Agronomy (IF=3.64, Q1-Agronomy; SJR=0.707, percentile-65), 10(9), 1285. https://doi.org/10.3390/agronomy10091285
  8. Didorenko S., Yerzhebayeva R., Abildaeva D., Amangeldiyeva A. (2020). Formation of production characters of soya genotypes [Glycine max (L.) Merr.] in the areas of south-east Kazakhstan with sufficient and limited water supply. Agrivita (SJR=0.235, percentile=41). 42(3). DOI:http://doi.org/10.17503/agrivita.v40i0.
  9. Genievskaya Y., Abugalieva S., Rsaliyev A., Turuspekov Y. Genome-wide association mapping for resistance to leaf, stem, and yellow rusts of common wheat under field conditions of South Kazakhstan. PeerJ (IF=2.984, Q2, percentile=84). 2020. 8(7–8):P.e9820. DOI:10.7717/peerj.9820.
  10. Anuarbek S., Abugalieva S., Turuspekov Y. (2019). Validation of bread wheat KASP markers in durum lines in Kazakhstan. Proceeding of the Latvian Academy of Sciences. Section B (SJR=0.168 percentile=39). 73(5):462-465. DOI:10.2478/prolas-2019-0071.
  11. Almerekova S., Genievskaya Y., Abugalieva S., Sato K., Turuspekov Y. (2021). Population structure and genetic diversity of two-rowed barley accessions from Kazakhstan based on SNP genotyping data. Plants (Q1, IF=3.935, Percentile-56). 10(10):2025. https://www.mdpi.com/2223-7747/10/10/2025
  12. Didorenko S.V., Kudaibergenov M.S., Sidorik I.V., Plotnikov V.G., Zinchenko A.V., Karamurzina U.M., Zakieva A.A. Soybean variety Ivushka. Patent Author certificate No.663, application No.15103420 on 27/11/2015, order No.95 on 28/02/2018, issued on 04/04/2018.

 

Results for 2022:

Whole- genome resequencing of 31 domestic accessions (cultivars and lines) of the soybean collection on the Illumina HiSeq X Ten System platform has begun, in addition to the 221 cultivars that have already been resequenced as a background of the project. The study of the variability of the nucleotide sequences of the world collection (252 accessions in total) has begun. The degree of genetic variability in the soybean collection (252 accessions) was assessed, polymorphic SNP markers were identified, and matrix data for GWAS were prepared.

Whole-genome resequencing of 20 Kazakh accessions was carried out on the Illumina HiSeq X Ten System platform. The results of the WGRS of domestic soybean genotypes were combined with the data of accessions from the world collection (221 accessions) and analyzed using the GATK and SAMtools applications to identify polymorphic SNP markers and indels. The annotations of the identified SNPs were compared to the reference genome ZH 13 (Chinese cultivar Zhonghuang 13) using the snpEff software. As a result of the initial processing of the data from the WGRS of the entire studied collection (252 accessions) of soybeans, 2,879,960 SNPs were identified.

As a result of filtering data from whole genome resequencing of 252 soybean accessions, 2,235,250 polymorphic SNP markers were identified. The number of insertions was 150 832 and deletions 106 428. The obtained data will be used to create a matrix used in genome-wide association study (GWAS).

The study of the soybean collection, consisting of 252 cultivars and lines from different regions of the world, grown in the southeast and north of Kazakhstan for economically valuable traits, has begun. An assessment of the variability of yield and quality traits of soybean seeds tested in different regions of the country has begun.

Correlation analysis showed a significant positive relationship between the growing season and traits of morphology and productivity. A negative correlation of the trait «1000 seeds weight» with the flowering period and plant height is shown.

Confirmation of the significance of the identified SNP markers for traits that determine the yield and quality of soybeans has begun, based on the use of additional hybrid populations, RNA samples isolated at various stages of plant growth and development, and the quantitative RT-PCR method.

Validation of identified SNP markers for traits that determine soybean yield and quality has begun.

Previously identified SNP markers associated with soybean yield and quality were converted into KASP markers. For validation, 5 KASP markers associated with economically valuable traits and the soybean hybrid population Zara x Maleta were used.

Study will continue.

 Publications (2022): Absent