Legume Genomics and Genetics 2026, Vol.17, No.1, 49-67 http://cropscipublisher.com/index.php/lgg 66 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 Riaz A., Raza Q., Kumar A., Dean D., Chiwina K., Phiri T., Thomas J., and Shi A., 2023, GWAS and genomic selection for marker-assisted development of sucrose enriched soybean cultivars, Euphytica, 219(8): 117. https://doi.org/10.1007/s10681-023-03224-y Satyawan D., and Tasma I.M., 2021, Identification of prospective soybean accessions for the creation of a genebank core collection based on high density DNA marker data, IOP Conference Series: Earth and Environmental Science, 762(1): 012069. https://doi.org/10.1088/1755-1315/762/1/012069 Shaibu A.S., Ibrahim H.Y., Miko S., Mohammed I.S., Mohammed S.G., Yusuf H., Kamara A.Y., Omoigui L.O., and Karikari B., 2022, Assessment of the genetic structure and diversity of soybean (Glycine max L.) germplasm using diversity array technology and single nucleotide polymorphism markers, Plants, 11(1): 68. https://doi.org/10.3390/plants11010068 Sharmin R., Karikari B., Chang F., Amin M.N.G., Bhuiyan M.S.R., Hina A., Lv W., Zhao C., Begum N., and Zhao T., 2021, Genome-wide association study uncovers major genetic loci associated with seed flooding tolerance in soybean, BMC Plant Biology, 21(1): 497. https://doi.org/10.1186/s12870-021-03268-z 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 Song Q., Hyten D.L., Jia G., Quigley C.V., Fickus E.W., Nelson R.L., and Cregan P.B., 2015, Fingerprinting soybean germplasm and its utility in genomic research, G3: Genes Genomes Genetics, 5(10): 1999-2006. https://doi.org/10.1534/g3.115.019000 Song Q., Quigley C., He R., Wang D., Nguyen H.T., Miranda C., and Li Z., 2024, Development and implementation of nested single-nucleotide polymorphism (SNP) assays for breeding and genetic research applications, The Plant Genome, 17(2): e20491. https://doi.org/10.1002/tpg2.20491 Song Q., Yan L., Quigley C., Fickus E., Wei H., Chen L., Dong F., Araya S., Liu J., Hyten D., Pantalone V., and Nelson R., 2020, Soybean BARCSoySNP6K: An assay for soybean genetics and breeding research, The Plant Journal, 104(3): 800-811. https://doi.org/10.1111/tpj.14960 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 Suela M., Azevedo C.F., Nascimento A.C.C., Morota G., da Silva F.F., Malone G., Giasson N., and Nascimento M., 2025, Using structural equation models to interpret genome-wide association studies for morphological and productive traits in soybean [Glycine max (L.) Merr.], Plants, 14(19): 3015. https://doi.org/10.3390/plants14193015 T. N., S. R., and L. R., 2022, Population structure and genetic diversity characterization of soybean for seed longevity, PLOS ONE, 17(12): e0278631. https://doi.org/10.1371/journal.pone.0278631 Tsindi A., Eleblu J.S.Y., Gasura E., Mushoriwa H., Tongoona P., Danquah E.Y., Mwadzingeni L., Zikhali M., Ziramba E., Mabuyaye G.T., and Derera J., 2023, Analysis of population structure and genetic diversity in a Southern African soybean collection based on single nucleotide polymorphism markers, CABI Agriculture and Bioscience, 4(1): 58. https://doi.org/10.1186/s43170-023-00158-2 Ullah A., Akram Z., Malik S.I., and Khan K.S., 2021, Assessment of phenotypic and molecular diversity in soybean [Glycine max (L.) Merr.] germplasm using morpho-biochemical attributes and SSR markers, Genetic Resources and Crop Evolution, 68(7): 2827-2847. https://doi.org/10.1007/s10722-021-01157-w Valliyodan B., Brown A.V., Wang J., Patil G., Liu Y., Otyama P.I., Nelson R.T., Vuong T.D., Song Q., Musket T.A., Wagner R., Marri P.R., Reddy S.K., Sessions A., Wu X., Grant D., Bayer P.E., Roorkiwal M., Varshney R.K., Liu X., Edwards D., Xu D., Joshi T., Cannon S.B., and Nguyen H.T., 2021, Genetic variation among 481 diverse soybean accessions, inferred from genomic re-sequencing, Scientific Data, 8(1): 50. https://doi.org/10.1038/s41597-021-00834-w Viana J.P.G., Fang Y., Avalos A.E., Song Q., Nelson R.L., and Hudson M.E., 2022, Impact of multiple selective breeding programs on genetic diversity in soybean germplasm, Theoretical and Applied Genetics, 135(5): 1591-1602. https://doi.org/10.1007/s00122-022-04056-5 Wibisono K., Dyah R., Utari R., Suparjo S., Umar U., Rijzaani H., Hakim L., Suhendar A., Purwanto O., Satyawan D., Witjaksono W., Mastur M., Lestari P., and Tasma I.M., 2025, Genetic diversity and DNA barcoding construction of tropical soybean advanced lines based on SSR markers, Jurnal Ilmu Pertanian Indonesia, 30(2): 293-302. https://doi.org/10.18343/jipi.30.2.293 Xue Y., Tang X., Zhu X., Zhang R., Yao Y., Cao D., He W., Liu Q., Luan X., Shu Y., and Liu X., 2025, Leveraging GWAS-identified markers in combination with bayesian and machine learning models to improve genomic selection in soybean, International Journal of Molecular Sciences, 26(19): 9586. https://doi.org/10.3390/ijms26199586
RkJQdWJsaXNoZXIy MjQ4ODYzNA==