MPB_2024v15n6

Molecular Plant Breeding 2024, Vol.15, No.6, 371-378 http://genbreedpublisher.com/index.php/mpb 378 Wang Y., 2024, GWAS reveals progress in genes related to rice yield and quality, Rice Genomics and Genetics, 15(2): 48-57. Wang J., Feng H., Jia X., Ma S., Ma C., Wang Y., Pan S., Chen Q., Xin D., and Liu C., 2023, Identifications of QTLs and candidate genes associated with Pseudomonas syringae responses in cultivated soybean (Glycine max) and wild soybean (Glycine soja), International Journal of Molecular Sciences, 24(5): 4618. https://doi.org/10.3390/ijms24054618 PMid:36902050 PMCid:PMC10003559 Wang L., Liu F., Hao X., Wang W., Xing G., Luo J., Zhou G., He J., and Gai J., 2021, Identification of the QTL-allele system underlying two high-throughput physiological traits in the Chinese soybean germplasm population, Frontiers in Genetics, 12: 600444. https://doi.org/10.3389/fgene.2021.600444 PMid:33719333 PMCid:PMC7947801 Yoosefzadeh-Najafabadi M., Torabi S., Torkamaneh D., Tulpan D., Rajcan I., and Eskandari M., 2021, Machine-learning-based genome-wide association studies for uncovering QTL underlying soybean yield and its components, International Journal of Molecular Sciences, 23(10): 5538. https://doi.org/10.3390/ijms23105538 PMid:35628351 PMCid:PMC9141736 Yoosefzadeh-Najafabadi M., Torabi S., Tulpan D., Rajcan I., and Eskandari M., 2023, Application of SVR-Mediated GWAS for identification of durable genetic regions associated with soybean seed quality traits, Plants, 12(14): 2659. https://doi.org/10.3390/plants12142659 PMid:37514272 PMCid:PMC10383196 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 PMid:36388509 PMCid:PMC9647135 Zhang X., Guan Z., Li Z., Liu P., Ma L., Zhang Y., Pan L., He S., Zhang Y., Li P., Ge F., Zou C., He Y., Gao S., Pan G., and Shen Y., 2020, A combination of linkage mapping and GWAS brings new elements on the genetic basis of yield-related traits in maize across multiple environments, Theoretical and Applied Genetics, 133: 2881-2895. https://doi.org/10.1007/s00122-020-03639-4 PMid:32594266 Zhang S.B., 2024, Molecular breeding for enhanced rice yield: the role of key yield-related genes, Rice Genomics and Genetics, 15(4): 153-163. https://doi.org/10.5376/rgg.2024.15.0016

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