LGG_2025v16n1

Legume Genomics and Genetics 2025, Vol.16, No.1, 11-22 http://cropscipublisher.com/index.php/lgg 22 Ouyang W., Chen L., Ma J., Liu X., Chen H., Yang H., Guo W., Shan Z., Yang Z., Chen S., Zhan Y., Zhang H., Cao D., and Zhou X., 2022, Identification of quantitative trait locus and candidate genes for drought tolerance in a soybean recombinant inbred line population, International Journal of Molecular Sciences, 23(18): 10828. https://doi.org/10.3390/ijms231810828 Rani R., Raza G., Ashfaq H., Rizwan M., Razzaq M., Waheed M., Shimelis H., Babar A., and Arif M., 2023, Genome-wide association study of soybean (Glycine max [L.] Merr.) germplasm for dissecting the quantitative trait nucleotides and candidate genes underlying yield-related traits, Frontiers in Plant Science, 14: 1229495. https://doi.org/10.3389/fpls.2023.1229495 Ravelombola W., Qin J., Shi A., Song Q., Yuan J., Wang F., Chen P., Yan L., Feng Y., Zhao T., Meng Y., Guan K., Yang C., and Zhang M., 2021, Genome-wide association study and genomic selection for yield and related traits in soybean, PLoS ONE, 16(8): e0255761. https://doi.org/10.1371/journal.pone.0255761 Ren H., Jianan H., Wang X., Zhang B., Yu L., Gao H., Huilong H., Rujian S., Tian Y., Qi X., Liu Z., Wu X., and Qiu L., 2020, QTL mapping of drought tolerance traits in soybean with SLAF sequencing, Crop Journal, 8: 977-989. https://doi.org/10.1016/j.cj.2020.04.004 Schneider K., and Kelly J., 1997, Marker‐assisted selection to improve drought resistance in common bean, Crop Science, 37: 51-60. https://doi.org/10.2135/CROPSCI1997.0011183X003700010008X Shook J., Zhang J., Jones S., Singh A., Diers B., and Singh A., 2020, Meta-GWAS for quantitative trait loci identification in soybean, G3: Genes|Genomes|Genetics, 11(7): jkab117. https://doi.org/10.1093/g3journal/jkab117 Sonah H., O'Donoughue L., Cober E., Rajcan I., and Belzile F., 2015, Identification of loci governing eight agronomic traits using a GBS-GWAS approach and validation by QTL mapping in soya bean, Plant Biotechnology Journal, 13(2): 211-221. https://doi.org/10.1111/pbi.12249 Sun M., Li Y., Zheng J., Wu D., Li C., Li Z., Zang Z., Zhang Y., Fang Q., Li W., Han Y., Zhao X., and Li Y., 2022, A nuclear factor Y-B transcription factor, GmNFYB17, regulates resistance to drought stress in soybean, International Journal of Molecular Sciences, 23(13): 7242. https://doi.org/10.3390/ijms23137242 Suo R., Sandhu K., Wang M., You F., Conner R., Cober E., and Hou A., 2022, Soybean (Glycine max L.) seed germination in response to waterlogging and cold climate: a review on the genetics and molecular mechanisms of resistance to the abiotic stress, Canadian Journal of Plant Science, 103: 13-28. https://doi.org/10.1139/cjps-2022-0111. Wang H.P., and Li H.M., 2024, Application of molecular marker assisted selection in wheat stress resistance breeding, Triticeae Genomics and Genetics, 15(1): 1-9. https://doi.org/10.5376/tgg.2024.15.0001 Wang W., Zhou B., He J., Zhao J., Liu C., Chen X., Xing G., Chen S., Xing H., and Gai J., 2020, Comprehensive identification of drought tolerance QTL-allele and candidate gene systems in Chinese cultivated soybean population, International Journal of Molecular Sciences, 21(14): 4830. https://doi.org/10.3390/ijms21144830 Xiong R., Liu S., Considine M., Siddique K., Lam H., and Chen Y., 2020, Root system architecture, physiological and transcriptional traits of soybean (Glycine max L.) in response to water deficit: a review, Physiologia Plantarum, 172(2): 405-418. https://doi.org/10.1111/ppl.13201 Yang J., Jiang H., Yeh, C., Yu J., Jeddeloh J., Nettleton D., and Schnable P., 2015, Extreme-phenotype genome-wide association study (XP-GWAS): a method for identifying trait-associated variants by sequencing pools of individuals selected from a diversity panel, The Plant Journal, 84(3): 587-596. https://doi.org/10.1111/tpj.13029 Yu K., Miao H., Liu H., Zhou J., Sui M., Zhan Y., Xia N., Zhao X., and Han Y., 2022, Genome-wide association studies reveal novel QTLs, QTL-by-environment interactions and their candidate genes for tocopherol content in soybean seed, Frontiers in Plant Science, 13: 1026581. https://doi.org/10.3389/fpls.2022.1026581 Zhang Y., Wang Y., Zhou W., Zheng S., and Ye R., 2021, Detection of candidate gene networks involved in resistance to Sclerotinia sclerotiorum in soybean, Journal of Applied Genetics, 63: 1-14. https://doi.org/10.1007/s13353-021-00654-z

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