LGG_2024v15n3

Legume Genomics and Genetics 2024, Vol.15, No.3, 126-139 http://cropscipublisher.com/index.php/lgg 139 Parmley K.A., Nagasubramanian K., Sarkar S., Ganapathysubramanian B., and Singh A.K., 2019, Development of optimized phenomic predictors for efficient plant breeding decisions using phenomic-assisted selection in soybean, Plant Phenomics, 2019: 1-15. https://doi.org/10.34133/2019/5809404 Petereit J., Marsh J.I., Bayer P., Danilevicz M.F., Thomas W.J.W., Batley J., and Edwards D., 2022, Genetic and genomic resources for soybean breeding research, Plants, 11(9): 1181. https://doi.org/10.3390/plants11091181 Pham A., Harris D.K., Buck J., Hoskins A., Serrano J., Abdel-Haleem H., Cregan P., Song Q., Boerma H., and Li Z., 2015, Fine mapping and characterization of candidate genes that control resistance to Cercospora sojina K. Hara in two soybean germplasm accessions, PLoS One, 10(5): e0126753. https://doi.org/10.1371/journal.pone.0126753 Ravelombola W., Qin J., Shi A., Nice L., Bao Y., Lorenz A.J., Orf J.H., Young N.D., and Chen S., 2020, Genome-wide association study and genomic selection for tolerance of soybean biomass to soybean cyst nematode infestation, PLoS One, 15(7): e0235089. https://doi.org/10.1371/journal.pone.0235089 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 Stewart-Brown B.B., Song Q., Vaughn J.N., and Li Z., 2019, Genomic selection for yield and seed composition traits within an applied soybean breeding program, G3: Genes Genomes Genetics, 9(7): 2253-2265. https://doi.org/10.1534/g3.118.200917 Valliyodan B., Ye H., Song L., Murphy M., Shannon J., and Nguyen H., 2016, Genetic diversity and genomic strategies for improving drought and waterlogging tolerance in soybeans, Journal of Experimental Botany, 68: 1835-1849. https://doi.org/10.1093/jxb/erw433 Wang T., Xun H., Wang W., Ding X., Tian H., Hussain S., Dong Q., Li Y., Cheng Y., Wang C., Lin R., Li G., Qian X., Pang J., Feng X., Dong Y., and Liu B., 2021, Mutation of GmAITRgenes by CRISPR/Cas9 genome editing results in enhanced salinity stress tolerance in soybean, Frontiers in Plant Science, 12: 779598. https://doi.org/10.3389/fpls.2021.779598 Wei T., Jiang L., You X., Ma P., Xi Z., and Wang N., 2023, Generation of herbicide-resistant soybean by base editing, Biology, 12(5): 741. https://doi.org/10.3390/biology12050741 Xu K., Zhao Y., Zhao Y., Feng C., Zhang Y., Wang F., Li X., Gao H., Liu W., Jing Y., Saxena R., Feng X., Zhou Y., and Li H., 2022, Soybean F-box-like protein GmFBL144 interacts with small heat shock protein and negatively regulates plant drought stress tolerance, Frontiers in Plant Science, 13: 823529. https://doi.org/10.3389/fpls.2022.823529 Yin K., and Qiu J., 2019, Genome editing for plant disease resistance: applications and perspectives, Philosophical Transactions of the Royal Society B, 374(1767), 20180322. https://doi.org/10.1098/rstb.2018.0322 Zhang M., Liu S., Wang Z., Yuan Y., Zhang Z., Liang Q., Yang X., Duan Z., Liu Y., Kong F., Liu B., and Ren B., 2021, Progress in soybean functional genomics over the past decade, Plant Biotechnology Journal, 20: 256-282. https://doi.org/10.1111/pbi.13682 Zhong C., Sun S., Li Y., Duan C., and Zhu Z., 2018, Next-generation sequencing to identify candidate genes and develop diagnostic markers for a novel phytophthora resistance gene, RpsHC18, in soybean, Theoretical and Applied Genetics, 131: 525-538. https://doi.org/10.1007/s00122-017-3016-z Zhou Z., Jiang Y., Wang Z., Gou Z., Lyu J., Li W., Yu Y., Shu L., Zhao Y., Ma Y., Fang C., Shen Y., Liu T., Li C., Li Q., Wu M., Wang M., Wu Y., Dong Y., Wan W., Wang X., Ding Z., Gao Y., Xiang H., Zhu B., Lee S.H., Wang W., and Tian Z., 2015, Resequencing 302 wild and cultivated accessions identifies genes related to domestication and improvement in soybean, Nature Biotechnology, 33: 408-414. https://doi.org/10.1038/nbt.3096

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