Effect of Population Size on Genome-Wide Association Study of Agronomic Traits in Soybean

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, 11 (12), 1–11.10.1371/journal.pone.0166894513223227907027Search in Google Scholar

Abugaliyeva, A. I., Didorenko, S. V. (2016). Genetic diversity of soybean cultivars belonging to different ripeness groups with regard to performance and quality. Vavilov J. Gen. Breed.,20 (3), 303–310.10.18699/VJ16.168Search in Google Scholar

Anonymous (2020a). Official website of the Ministry of National Economy of the Republic of Kazakhstan. Statistics committee. Available at: http://stat.gov.kz/. (accessed 28.04.2020).Search in Google Scholar

Anonymous (2020b). Official website of the United States government. Department of Agriculture. World Agricultural Supply and Demand Estimates. Available at: http://usda.gov/ (accessed 28.04.2020).Search in Google Scholar

Bradbury, P. J., Zhang, Z., Kroon, D. E., Casstevens, T. M., Ramdoss, Y., Buckler, E. S. (2007). TASSEL: software for association mapping of complex traits in diverse samples. Bioinformatics, 23, 2633–2635.10.1093/bioinformatics/btm30817586829Search in Google Scholar

Chen, L., Fang, Y., Li, X., Zeng, K., Chen, H., Zhang H., Yang H., Cao, D., Hao, Q., Yuyan, S. (2019). Identification of soybean drought-tolerant genotypes and loci correlated with agronomic traits contributes new candidate genes for breeding. Plant Mol. Biol.,102, 109–122.Search in Google Scholar

Collard, B. C., Mackill, D. J. (2008). Marker-assisted selection: An approach for precision plant breeding in the twenty-first century. Philos.Transact. Roy. Soc. B: Biol. Sci.,363 (1491), 557–572.10.1098/rstb.2007.2170261017017715053Search in Google Scholar

Contreras-Soto, R. Mora, F., de Oliveira, M. A. R., Higashi, W., Scapim, C. A., Schuster, I. (2017). A genome-wide association study for agronomic traits in soybean using SNP markers and SNP based haplotype analysis. PLoS ONE, 12 (2).10.1371/journal.pone.0171105528953928152092Search in Google Scholar

Contreras-Soto, R. I., Mora, F., Lazzari, F., de Oliveira, M. A. R., Scapim, C. A., Schuster, I. (2017). Genome-wide association mapping for flowering and maturity in tropical soybean: Implications for breeding strategies. Breeding Sci.,67 (5), 435–449.10.1270/jsbbs.17024579004229398937Search in Google Scholar

Didorenko, S. V., Sprygailova, Y. N., Kudaibergonov, M. S., Abugalieva, A. I. (2015). Selection of soybean in East Kazakhstan. Science World, 1, 83–88.Search in Google Scholar

Do, T. D., Vuong, T. D., Dunn, D., Clubb, M., Valliyodan, B., Patil, G., Chen, P., Xu, D., Nhuyyen, H. T., Shannon, J. G. (2019). Identification of new loci for salt tolerance in soybean by high-resolution genome-wide association mapping. BMC Genom.,20 (1), 318.10.1186/s12864-019-5662-9648511131023240Search in Google Scholar

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. Int. J. Biol. Chem.,12 (1), 33–40.10.26577/ijbch-2019-1-i5Search in Google Scholar

Earl, D. A., von Holdt, B. M. (2012). STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method. Conserv. Genet. Resour., 4 (2), 359–361.10.1007/s12686-011-9548-7Search in Google Scholar

Evanno, G., Regnaut, S., Goudet, J. (2005). Detecting the number of clusters of individuals using the software STRUCTURE: A simulation study. Mol. Ecol., 14 (8), 2611–2620.10.1111/j.1365-294X.2005.02553.x15969739Search in Google Scholar

Fang, C., Ma, Y., Wu, S., Liu, Z., Wang, Z., Yang, R., Hu, G. (2017). Genome-wide association studies dissect the genetic networks underlying agronomical traits in soybean. Genome Biol.,18 (1), 161.10.1186/s13059-017-1289-9Search in Google Scholar

Fehr, W. R., Cavines, C. E. (1977) Stages of Soybean Development. Special Report. 87. Cooperative Extention Service, Iowa State University, Ames, Iowa, USA.Search in Google Scholar

Han, B. Z., Rombouts, F. M., Nout, M. J. R. (2001). A Chinese fermented soybean food. Int. J. Food Microbiol.,65, 1–10.10.1016/S0168-1605(00)00523-7Search in Google Scholar

Hwang, E.-Y., Song, Q., Jia, G., Specht, J. E., Hyten, D. L., Costa, J., Cregan, P. B. (2014). A genome-wide association study of seed protein and oil content in soybean. BMC Genom., 15 (1), 1.10.1186/1471-2164-15-1389052724382143Search in Google Scholar

Ikram, M., Han, X., Zuo, J.-F., Song, J., Han, C.-Y., Zhang, Y.-W., Zhang, Y.-M. (2020). Identification of QTNs and their candidate genes for 100-seed weight in soybean (Glycine max L.) using multi-locus genome-wide association studies. Genes, 11 (7), 714.Search in Google Scholar

Korsakov, N. I., Makasheva, R. H., Adamova, O. P. (1968). Methodology for Studying the Collection of Legumes [Корсаков Н.И., Макашева Р.Х., Адамова О.П Методика изучения коллекции зернобобовых культур. VIR, Leningrad. 175 pp. (in Russian).Search in Google Scholar

Korte, A., Farlow, A. (2013). The advantages and limitations of trait analysis with GWAS: A review. Plant Methods, 9 (1), 29.10.1186/1746-4811-9-29375030523876160Search in Google Scholar

Kumar, J., Choudhary, A. K., Solanki, R. K., Pratap, A. (2011). Towards marker-assisted selection in pulses: A review. Plant Breed., 130 (3), 297–313.10.1111/j.1439-0523.2011.01851.xSearch in Google Scholar

Lee, S., Van, K., Sung, M., Nelson, R., LaMantia, J., McHale, L. K., Rouf Mian, M. A. (2019). Genome-wide association study of seed protein, oil and amino acid contents in soybean from maturity groups I to IV. Theor. Appl. Gen.,132, 1639–1659.10.1007/s00122-019-03304-5653142530806741Search in Google Scholar

Li, J., Zhao, J., Li, Y., Gao, Y., Hua, S., Nadeem, M., Sun, G., Zhang, W., Hou, J., Wang, X., Qiu, L. (2019). Identification of a novel seed size associated locus SW9-1 in soybean. Crop J., 7, 548–559.10.1016/j.cj.2018.12.010Search in Google Scholar

Lu, H., Yang, Y., Li, H., Liu, Q., Zhang, J., Yin, J., Chu S., Zhang, X., Kaiye, Y., Lv, L., Chen, X. (2018). Genome-wide association studies of photosynthetic traits related to phosphorus efficiency in soybean. Frontiers Plant Sci.,9, 1226.10.3389/fpls.2018.01584622007530429867Search in Google Scholar

Makulbekova, A., Iskakov, A., Kulkarni, K. P., Song, J. T, Lee, J. D. (2017). Current status of future prospects of soybean production in Kazakhstan. Plant Breed. Biotechnol.,5, 55–66.10.9787/PBB.2017.5.2.55Search in Google Scholar

Maui, Ą. Ą., Sauranbaev, B. N., Orazbaev, K. I. (2016). Soybean pathogens in the south-east of Kazakhstan. J. Hum. Admin. Sci.,3 (5), 20–26.Search in Google Scholar

Moose, S. P., Mumm, R. H. (2008). Molecular plant breeding as the foundation for 21st century crop improvement. Plant Physiol.,147 (3), 969–977.10.1104/pp.108.118232244252518612074Search in Google Scholar

Pimental, D., Patzek, T. W. (2005). Ethanol production using corn, switchgrass, and wood, biodiesel production using soybean and sunflower. Nat. Res.Res.,14 (1), 65–76.10.1007/s11053-005-4679-8Search in Google Scholar

Ray, D. K., Mueller, N. D., West, P. C, Foley, J. A. (2013). Yield trends are insufficient to double global crop production by 2050. PLoS ONE, 8 (6), e66428.10.1371/journal.pone.0066428368673723840465Search in Google Scholar

Schneider, R., Rolling, W., Song, Q., Cregan, P., Dorrance, A. E., McHale, L. K. (2016). Genome-wide association mapping of partial resistance to Phytophthora sojae in soybean plant introductions from the Republic of Korea. BMC Genomics, 17 (1), 607.10.1186/s12864-016-2918-5498211327515508Search in Google Scholar

Teng, W., Han, Y., Du, Y., Sun, D., Zhang, Z., Qiu, L., Sun, G., Li, W. (2009). QTL analyses of seed weight during the development of soybean (Glycine max L. Merr.). Heredity, 102 (4), 372–380.10.1038/hdy.2008.10818971958Search in Google Scholar

Vaughn, J. N., Nelson, R. L., Song, Q., Cregan, P. B., Li, Z. (2014). The genetic architecture of seed composition in soybean is refined by genome-wide association scans across multiple populations. G3: Genes|Genomes|Genetics, 4, 2283–2294.10.1534/g3.114.013433423255425246241Search in Google Scholar

Voorrips, R. E. (2002). MapChart: software for the graphical presentation of linkage maps and QTLs. J. Hered., 93, 77–78.10.1093/jhered/93.1.7712011185Search in Google Scholar

Vuong, T. D., Sonah, H., Meinhardt, C. G., Deshmukh, R., Kadam, S., Nelson, R. L., Shannon, J. G., Nguyen, H. T. (2015). Genetic architecture of cyst nematode resistance revealed by genome-wide association study in soybean. BMC Genom., 16 (1), 593.10.1186/s12864-015-1811-y453377026263897Search in Google Scholar

Wang, H., Smith, K. P., Combs, E., Blake, T., Horsley, R. D., Muehlbauer, G. J. (2012). Effect of population size and unbalanced data sets on QTL detection using genome-wide association mapping in barley breeding germplasm. Theor. Appl. Genet., 124, 111–124.10.1007/s00122-011-1691-821898052Search in Google Scholar

Wang, J., Zhao, X., Wang, W., Qu, Y., Teng, W., Qiu, L., Zheng, H., Han, Y., Li, W. (2019). Genome-wide association study of inflorescence length of cultivated soybean based on the high-throughout single-nucleotide markers. Molecular Genetics and Genomics, 294 (3), 607–620.10.1007/s00438-019-01533-330739204Search in Google Scholar

Zatybekov, A., Abugalieva, S., Didorenko, S., Gerasimova, Y., Sidorik, I., Anuarbek, S., Turuspekov, Y. (2017). GWAS of agronomic traits in soybean collection included in breeding pool in Kazakhstan. BMC Plant Biology, 17 (S1), 179.10.1186/s12870-017-1125-0568846029143671Search in Google Scholar

Zatybekov, A., Abugalieva, S., Didorenko, S., Rsaliyev, A., Turuspekov, Y. (2018). GWAS of soybean breeding collection for resistance to fungal diseases in condition of South-East and South Kazakhstan. Vavilov J. Gen. Breed.,22 (5), 536–543.10.18699/VJ18.392Search in Google Scholar

Zatybekov, A. K., Agibaev, A. Z., Didorenko, S. V., Abugalieva, S. I., Turuspekov, Y. K. (2018). Analysis of resistance to Septoria glycines in soybean world collection harvested in south-eastern Kazakhstan. News NAS of RK. Ser. Agricult. Sci.,5, 44–52.Search in Google Scholar

Zhang, J., Song, Q., Cregan, P. B., Jiang, G. L. (2016). Genome-wide association study. genomic prediction and marker-assisted selection for seed weight in soybean (Glycine max). Theor. Appl. Genet., 129, 117–130.10.1007/s00122-015-2614-x470363026518570Search in Google Scholar

Zhang, Z., Ersoz, E., Lai, C., Todhunter, R., Tiwari, H., Gore, M., Bradbury, P., et al. (2010). Mixed linear model approach adapted for genome-wide association studies. Nat. Genet., 42, 355–360.10.1038/ng.546293133620208535Search in Google Scholar