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Genome-wide association study for charcoal rot resistance in soybean harvested in Kazakhstan ; Полногеномный анализ ассоциации устойчивости к пепельной гнили сои, выращенной в Казахстане

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  • Additional Information
    • Contributors:
      The authors would like to acknowledge the funding from the Ministry of Science and Higher Education of the Republic of Kazakhstan, under the science and technology program O.001 “Biological safety of the Republic of Kazakhstan: assessment of threats, scientific and technical basis for their prevention and elimination”
    • Publication Information:
      Institute of Cytology and Genetics of Siberian Branch of the RAS
    • Publication Date:
      2023
    • Collection:
      Vavilov Journal of Genetics and Breeding / Вавиловский журнал генетики и селекции
    • Abstract:
      Charcoal rot (CR) caused by the fungal pathogen Macrophomina phaseolina is a devastating disease affecting soybean (Glycine max (L.) Merrill.) worldwide. Identifying the genetic factors associated with resistance to charcoal rot is crucial for developing disease-resistant soybean cultivars. In this research, we conducted a genome-wide association study (GWAS) using different models and genotypic data to unravel the genetic determinants underlying soybean resistance to сharcoal rot. The study relied on a panel of 252 soybean accessions, comprising commercial cultivars and breeding lines, to capture genetic variations associated with resistance. The phenotypic evaluation was performed under natural conditions during the 2021–2022 period. Disease severity and survival rates were recorded to quantify the resistance levels in the accessions. Genotypic data consisted of two sets: the results of genotyping using the Illumina iSelect 6K SNP (single-nucleotide polymorphism) array and the results of whole-genome resequencing. The GWAS was conducted using four different models (MLM, MLMM, FarmCPU, and BLINK) based on the GAPIT platform. As a result, SNP markers of 11 quantitative trait loci associated with CR resistance were identified. Candidate genes within the identified genomic regions were explored for their functional annotations and potential roles in plant defense responses. The findings from this study may further contribute to the development of molecular breeding strategies for enhancing CR resistance in soybean cultivars. Marker-assisted selection can be efficiently employed to accelerate the breeding process, enabling the development of cultivars with improved resistance to сharcoal rot. Ultimately, deploying resistant cultivars may significantly reduce yield losses and enhance the sustainability of soybean production, benefiting farmers and ensuring a stable supply of this valuable crop. ; Пепельная гниль, вызываемая грибным патогеном Macrophomina phaseolina, представляет собой опасное заболевание, поражающее ...
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      application/pdf
    • Relation:
      https://vavilov.elpub.ru/jour/article/view/3927/1742; Akem C.N. Management of Soybean Diseases. IITA Research Guide 40. Training Program. Ibadan, Nigeria: International Institute of Tropical Agriculture (IITA), 1996. Bandara A.Y., Weerasooriya D.K., Bradley C.A., Allen T.W., Esker P.D. Dissecting the economic impact of soybean diseases in the United States over two decades. PLoS One. 2020;15(4):e0231141. DOI:10.1371/journal.pone.0231141.; Coser S.M., Chowda Reddy R.V., Zhang J., Mueller D.S., Mengistu A., Wise K.A., Allen T.W., Singh A., Singh A.K. Genetic architecture of charcoal rot (Macrophomina phaseolina) resistance in soybean revealed using a diverse panel. Front. Plant Sci. 2017;8:1626. DOI:10.3389/fpls.2017.01626.; Didorenko S.V., Sagitov A.O., Kudaibergenov M.S. Main diseases on crops of soybean and methods of dealing with them. Agroalem. 2014;8(61):42-46. (in Russian); Ehret G.B. Genome-wide association studies: contribution of genomics to understanding blood pressure and essential hypertension. Curr. Hypertens. Rep. 2010;12:17-25. DOI:10.1007/s11906-009-0086-6.; Evanno G., Regnaut S., Goudet J. Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol. Ecol. 2005;14(8):2611-2620. DOI:10.1111/j.1365-294X.2005.02553.x.; Hartman G.L., Rupe J.C., Sikora E.J., Domier L.L., Davis J.A., Steffey K.L. Compendium of Soybean Diseases and Pests. St. Paul, Minnesota: The American Phytopathological Society, 2015. DOI:10.1094/9780890544754.; Huang M., Liu X., Zhou Y., Summers R.M., Zhang Z. BLINK: A package for the next level of genome-wide association studies with both individuals and markers in the millions. GigaScience. 2019;8(2): giy154. DOI:10.1093/gigascience/giy154.; Iquira E., Humira S., Francois B. Association mapping of QTLs for sclerotinia stem rot resistance in a collection of soybean plant introductions using a genotyping by sequencing (GBS) approach. BMC Plant Biol. 2015;15:5. DOI:10.1186/s12870-014-0408-y.; Kaler A.S., Gillman J.D., Beissinger T., Purcell L.C. Comparing different statistical models and multiple testing corrections for association mapping in soybean and maize. Front. Plant Sci. 2020;10:1794. DOI:10.3389/fpls.2019.01794.; Korte A., Farlow A. The advantages and limitations of trait analysis with GWAS: a review. Plant Methods. 2013;9:29. DOI:10.1186/1746-4811-9-29.; Lin F., Chhapekar S.S., Vieira C.C., Da Silva M.P., Rojas A., Lee D., Liu N., Pardo E.M., Lee Y.-C., Dong Z., Pinheiro J.B., Ploper L.D., Rupe J., Chen P., Wang D., Nguyen H.T. Breeding for disease resistance in soybean: a global perspective. Theor. Appl. Genet. 2022; 135:3773-3872. DOI:10.1007/s00122-022-04101-3.; Liu X., Huang M., Fan B., Buckler E.S., Zhang Z. Iterative usage of fixed and random effect models for powerful and efficient genomewide association studies. PLoS Genet. 2016;12(2):e1005767. DOI:10.1371/journal.pgen.1005767.; Lu S., Dong L., Fang C., Liu S., Kong L., Cheng Q., Chen L., Su T., Nan H., Zhang D., Zhang L., Wang Z., Yang Y., Yu D., Liu X., Yang Q., Lin X., Tang Y., Zhao X., Yang X., Tian C., Xie Q., Yuan X., Tian Z., Liu B., Weller J.L., Kong F. Stepwise selection on homeologous PRR genes controlling flowering and maturity during soybean domestification. Nat. Genet. 2020;52(4):428-436. DOI:10.1038/s41588-020-0604-7.; Mengistu A., Ray J.D., Smith J.R., Paris R.L. Charcoal rot disease assessment of soybean genotypes using a colony-forming unit index. Crop Sci. 2007;47(6):2453-2461. DOI:10.2135/cropsci2007.04.0186.; Mombekova G.A., Shemshurova O.N., Seitbattalova A.I., Aitkhozhina N.A., Bekmakhanova N.E. Phytopathogens of sugar beet and soybean cultivated in soil and climatic conditions of Almaty region. Vestnik NAN RK = Bulletin of the National Academy of Sciences of the Republic of Kazakhstan. 2013;4:8-11. (in Russian); Paris R.L., Mengistu A., Tyler J.M., Smith J.R. Registration of soybean germplasm line DT97–4290 with moderate resistance to charcoal rot. Crop Sci. 2006;46(5):2324-2325. DOI:10.2135/cropsci2005.09.0297.; Pawlowski M.L., Hill C.B., Hartman G.L. Resistance to charcoal rot identified in ancestral soybean germplasm. Crop Sci. 2015;55(3): 1230-1235. DOI:10.2135/cropsci2014.10.0687.; Pratap A., Gupta S.K., Kumar J., Mehandi S., Pandey V.R. Soybean. In: Breeding Oilseed Crops for Sustainable Production. Ch. 12. Academic Press, 2016;293-315. DOI:10.1016/b978-0-12-801309-0.00012-4.; Pritchard J.K., Stephens M., Rosenberg N.A., Donnelly P. Association mapping in structured populations. Am. J. Hum. Genet. 2000;67(1): 170-181. DOI:10.1086/302959.; Segura V., Vilhjalmsson B., Platt A., Korte A., Seren U., Long Q., Nordborg M. An efficient multi-locus mixed-model approach for genome-wide association studies in structured populations. Nat. Genet. 2012;44(7):825-830. DOI:10.1038/ng.2314.; Shen Q., Zhao J., Du C., Xiang Y., Cao J., Qin X. Genome-scale identification of MLO domain-containing genes in soybean (Glycine max L. Merr.). Genes Genet. Syst. 2012;87(2):89-98. DOI:10.1266/ggs.87.89.; Song Q., Hyten D.L., Jia G., Quigley C.V., Fickus E.W., Nelson R.L., Cregan P.B. Development and evaluation of SoySNP50K, a highdensity genotyping array for soybean. PLoS One. 2013;8(1):e54985. DOI:10.1371/journal.pone.0054985.; St. Clair D.A. Quantitative disease resistance and quantitative resistance loci in breeding. Annu. Rev. Phytopathol. 2010;48:247-268. DOI:10.1146/annurev-phyto-080508-081904.; Van Ooijen G., Mayr G., Kasiem M.M.A., Albrecht M., Cornelissen B.J., Takken F.L. Structure-function analysis of the NB-ARC domain of plant disease resistance proteins. J. Exp. Bot. 2008;59(6): 1383-1397. DOI:10.1093/jxb/ern045.; Wang J., Zhang Z. GAPIT Version 3: boosting power and accuracy for genomic association and prediction. Genom. Proteom. Bioinform. 2021;19(4):629-640. DOI:10.1016/j.gpb.2021.08.005.; Wrather A., Shannon G., Balardin R., Carregal L., Escobar R., Gupta G.K., Ma Z., Morel W., Ploper D., Tenuta A. Effect of disea ses on soybean yield in the top eight producing countries in 2006. Plant Health Prog. 2010;11(1). Online. DOI:10.1094/PHP-2010-0125-01-RS.; Yin L., Zhang H., Tang Z., Xu J., Yin D., Zhang Z., Yuan X., Zhu M., Zhao S., Li X. rMVP: A memory-efficient, visualization-enhanced, and parallel-accelerated tool for genome-wide association study. Genom. Proteom. Bioinform. 2021;19(4):619-628. DOI:10.1016/j.gpb.2020.10.007.; Yu J., Pressoir G., Briggs W., Bi I., Yamasaki M., Doebley J., McMullen M., Gaut B., Nielson D., Holland J., Kresovich S., Buckler E. A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nat. Genet. 2006;38(2): 203-208. DOI:10.1038/ng1702.; Zatybekov A., Abugalieva S., Didorenko S., Rsaliyev A., Turuspekov Y. GWAS of a soybean breeding collection from South East and South Kazakhstan for resistance to fungal diseases. Vavilovskii Zhurnal Genetiki i Selektsii = Vavilov Journal of Genetics and Breeding. 2018;22(5):536-543. DOI:10.18699/VJ18.392.; Zatybekov A., Abugalieva S., Didorenko S., Turuspekov Y. Effect of population size on genome-wide association study of agronomic traits in soybean. Proc. Latv. Acad. Sci. 2020;74(4):244-251. DOI:10.2478/prolas-2020-0039.; Zhang J., Song Q., Cregan P.B., Nelson R.L., Wang X., Wu J., Jiang G.L. Genome-wide association study for flowering time, maturity dates and plant height in early maturing soybean (Glycine max) germplasm. BMC Genomics. 2015;16(1):217. DOI:10.1186/s12864-015-1441-4.; https://vavilov.elpub.ru/jour/article/view/3927
    • Accession Number:
      10.18699/VJGB-23-68
    • Online Access:
      https://vavilov.elpub.ru/jour/article/view/3927
      https://doi.org/10.18699/VJGB-23-68
    • Rights:
      Authors who publish with this journal agree to the following terms:Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access). ; Авторы, публикующие в данном журнале, соглашаются со следующим:Авторы сохраняют за собой авторские права на работу и предоставляют журналу право первой публикации работы на условиях лицензии Creative Commons Attribution License, которая позволяет другим распространять данную работу с обязательным сохранением ссылок на авторов оригинальной работы и оригинальную публикацию в этом журнале.Авторы сохраняют право заключать отдельные контрактные договорённости, касающиеся не-эксклюзивного распространения версии работы в опубликованном здесь виде (например, размещение ее в институтском хранилище, публикацию в книге), со ссылкой на ее оригинальную публикацию в этом журнале.Авторы имеют право размещать их работу в сети Интернет (например в институтском хранилище или персональном сайте) до и во время процесса рассмотрения ее данным журналом, так как это может привести к продуктивному обсуждению и большему количеству ссылок на данную работу (См. The Effect of Open Access).
    • Accession Number:
      edsbas.B8F97ECB