Legume Genomics and Genetics 2025, Vol.16, No.1, 23-32 http://cropscipublisher.com/index.php/lgg 31 References Almeida-Silva F., Moharana K., Machado F., and Venancio T., 2020, Exploring the complexity of soybean (Glycine max) transcriptional regulation using global gene co-expression networks, Planta, 252(6): 104. https://doi.org/10.1007/s00425-020-03499-8 Chen K., Wang Y., Zhang R., Zhang H., and Gao C., 2019, CRISPR/Cas genome editing and precision plant breeding in agriculture, Annual Review of Plant Biology, 70: 667-697. https://doi.org/10.1146/annurev-arplant-050718-100049 Copley T., Duceppe M., and O'Donoughue L., 2018, Identification of novel loci associated with maturity and yield traits in early maturity soybean plant introduction lines, BMC Genomics, 19: 167. https://doi.org/10.1186/s12864-018-4558-4 Diers B., Specht J., Rainey K., Cregan P., Song Q., Ramasubramanian V., Graef G., Nelson R., Schapaugh W., Wang D., Shannon G., McHale L., Kantartzi S., Xavier A., Mian R., Stupar R., Michno J., An Y., Goettel W., Ward R., Fox C., Lipka A., Hyten D., Cary T., and Beavis W., 2018, Genetic architecture of soybean yield and agronomic traits, G3: Genes|Genomes|Genetics, 8: 3367-3375. https://doi.org/10.1534/g3.118.200332 Do P., Nguyen C., Bui H., Tran L., Stacey G., Gillman J., Zhang Z., and Stacey M., 2019, Demonstration of highly efficient dual gRNA CRISPR/Cas9 editing of the homeologous GmFAD2-1A and GmFAD2-1B genes to yield a high oleic, low linoleic and α-linolenic acid phenotype in soybean, BMC Plant Biology, 19: 311. https://doi.org/10.1186/s12870-019-1906-8 Fu M., Qi B., Li S., Xu H., Wang Y., Zhao Z., Yu X., Pan L., and Yang J., 2022, Detection of hub QTLs underlying the genetic basis of three modules covering nine agronomic traits in an F2 syobean population, Agronomy, 12(12): 3135. https://doi.org/10.3390/agronomy12123135 Guan J.N., Xie Z.M., Adnan R., Wang T.C., Zhao Q., Zhang Z., Zhao Z., John J.G., Ishtiaq A., Wang X.X., Wei J., and Gai Y.H., 2022, CRISPR/Cas9 applications for improvement of soybeans, current scenarios, and future perspectives, Notulae Botanicae Horti Agrobotanici Cluj-Napoca, 50(2): 12678. https://doi.org/10.15835/nbha50212678 Hashemi S., Perry G., Rajcan I., and Eskandari M., 2022, SoyMAGIC: an unprecedented platform for genetic studies and breeding activities in soybean, Frontiers in Plant Science, 13: 945471. https://doi.org/10.3389/fpls.2022.945471 He Y., Dong Y., Yang X., Guo D., Qian X., Yan F., Wang Y., Li J., and Wang Q., 2019, Functional activation of a novel R2R3-MYB protein gene, GmMYB68, confers salt-alkali resistance in soybean (Glycine max L.), Genome, 63(1): 13-26. https://doi.org/10.1139/gen-2018-0132 Hu B., Li Y., Wu H., Zhai H., Xu K., Gao Y., Zhu J., Li Y., and Xia Z., 2021, Identification of quantitative trait loci underlying five major agronomic traits of soybean in three biparental populations by specific length amplified fragment sequencing (SLAF-seq), PeerJ, 9: e12416. https://doi.org/10.7717/peerj.12416 Hong Z.M., and Huang W.Z., 2024, Agronomic traits of cassava and their genetic bases: a focus on yield and quality improvements, Tree Genetics and Molecular Breeding, 14(1): 22-31. https://doi.org/10.5376/tgmb.2024.14.0004 Kim S., Tayade R., Kang B., Hahn B., Ha B., and Kim Y., 2023b, Genome-wide association studies of seven root traits in soybean (Glycine max L.) landraces, International Journal of Molecular Sciences, 24(1): 873. https://doi.org/10.3390/ijms24010873 Kim W., Kang B., Moon C., Kang S., Shin S., Chowdhury S., Jeong S., Choi M., Park S., Moon J., and Ha B., 2023a, Genome-wide association study for agronomic traits in wild soybean (Glycine soja), Agronomy, 13(3): 739. https://doi.org/10.3390/agronomy13030739 Ku Y., Cheung M., Cheng S., Nadeem M., Chung G., and Lam H., 2022, Using the knowledge of post-transcriptional regulations to guide gene selections for molecular breeding in soybean, Frontiers in Plant Science, 13: 867731. https://doi.org/10.3389/fpls.2022.867731 Lakhssassi N., Zhou Z., Cullen M., Badad O., Baze A., Chetto O., Embaby M., Knizia D., Liu S., Neves L., and Meksem K., 2021, TILLING-by-sequencing+ to decipher oil biosynthesis pathway in soybeans: a new and effective platform for high-throughput gene functional analysis, International Journal of Molecular Sciences, 22(8): 4219. https://doi.org/10.3390/ijms22084219 Li M., Chen L., Zeng J., Razzaq M., Xu X., Xu Y., Wang W., He J., Xing G., and Gai J., 2020, Identification of additive-epistatic QTLs conferring seed traits in soybean using recombinant inbred lines, Frontiers in Plant Science, 11: 566056. https://doi.org/10.3389/fpls.2020.566056 Li S., Cao Y., Wang C., Yan C., Sun X., Zhang L., Wang W., and Song S., 2023, Genome-wide association mapping for yield-related traits in soybean (Glycine max) under well-watered and drought-stressed conditions, Frontiers in Plant Science, 14: 1265574. https://doi.org/10.3389/fpls.2023.1265574 Lodhi B., Kumar P., Chouhan M., Rajpoot A., and Jha A., 2023, Comprehensive genetic analysis of yield and yield-related traits in soybean germplasms for enhanced crop improvement, International Journal of Plant & Soil Science, 35(22): 9-17. https://doi.org/10.9734/ijpss/2023/v35i224109
RkJQdWJsaXNoZXIy MjQ4ODYzNA==