LGG_2025v16n1

Legume Genomics and Genetics 2025, Vol.16, No.1, 44-53 http://cropscipublisher.com/index.php/lgg 52 Contreras-Soto R., Mora F., Oliveira M., Higashi W., Scapim C., and Schuster I., 2017, A genome-wide association study for agronomic traits in soybean using SNP markers and SNP-based haplotype analysis, PLoS ONE, 12(2): e0171105. https://doi.org/10.1371/journal.pone.0171105 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 Do T., Vuong T., Dunn D., Clubb M., Valliyodan B., Patil G., Chen P., Xu D., Nguyen H., and Shannon J., 2019, Identification of new loci for salt tolerance in soybean by high-resolution genome-wide association mapping, BMC Genomics, 20: 318. https://doi.org/10.1186/s12864-019-5662-9 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 Huang W.Z., 2024, The current situation and future of using GWAS strategies to accelerate the improvement of crop stress resistance traits, Molecular Plant Breeding, 15(2): 52-62. https://doi.org/10.5376/mpb.2024.15.0007 Joukhadar R., Thistlethwaite R., Trethowan R., Keeble-Gagnère G., Hayden M., Ullah S., and Daetwyler H., 2021, Meta-analysis of genome-wide association studies reveal common loci controlling agronomic and quality traits in a wide range of normal and heat stressed environments, Theoretical and Applied Genetics, 134: 2113-2127. https://doi.org/10.1007/s00122-021-03809-y Kim D., Lyu J., Kim J., Seo J., Choi H., Jo Y., Kim S., Eom S., Ahn J., Bae C., and Kwon S., 2022, Identification of loci governing agronomic traits and mutation hotspots via a GBS-based genome-wide association study in a soybean mutant diversity pool, International Journal of Molecular Sciences, 23(18): 10441. https://doi.org/10.3390/ijms231810441 Kim S., Tayade R., Kang B., Hahn B., Ha B., and Kim Y., 2023, 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 McLeod L., Barchi L., Tumino G., Tripodi P., Salinier J., Gros C., Boyaci H., Ozalp R., Borovsky Y., Schafleitner R., Barchenger D., Finkers R., Brouwer M., Stein N., Rabanus-Wallace M., Giuliano G., Voorrips R., Paran I., and Lefebvre V., 2023, Multi-environment association study highlights candidate genes for robust agronomic quantitative trait loci in a novel worldwide Capsicum core collection, The Plant Journal, 116(5): 1508-1528. https://doi.org/10.1111/tpj.16425 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 Priyanatha C., Torkamaneh D., and Rajcan I., 2022, Genome-wide association study of soybean germplasm derived from Canadian ×Chinese crosses to mine for novel alleles to improve seed yield and seed quality traits, Frontiers in Plant Science, 13: 866300. https://doi.org/10.3389/fpls.2022.866300 Qin J., Wang F., Zhao Q., Shi A., Zhao T., Song Q., Ravelombola W., An H., Yan L., Yang C., and Zhang M., 2022, Identification of candidate genes and genomic selection for seed protein in soybean breeding pipeline, Frontiers in Plant Science, 13: 882732. https://doi.org/10.3389/fpls.2022.882732 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 Shook J., Zhang J., Jones S., Singh A., Diers B., and Singh A., 2021, 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 Stewart-Brown B., Song Q., Vaughn J., and Li Z., 2019, Genomic selection for yield and seed composition traits within an applied soybean breeding program, G3: Genes|Genomes|Genetics, 9: 2253-2265. https://doi.org/10.1534/g3.118.200917

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