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Abstract
Granule-Bound Starch Synthase I (GBSSI) merupakan enzim kunci dalam biosintesis amilosa yang menentukan sifat fungsional pati pada padi (Oryza sativa L.). Penelitian ini bertujuan mengkaji karakteristik molekuler gen GBSSI secara in silico melalui analisis sekuens, konservasi nukleotida, anotasi domain, serta prediksi struktur protein. Sebanyak 13 pasangan transkrip–protein diperoleh dari basis data NCBI, mencakup sekuens terkurasi RefSeq (NM/NP) dan hasil prediksi (XM/XP). Panjang coding sequence berkisar antara 1.827–1.836 nukleotida dengan panjang protein 608–611 asam amino, menunjukkan tingkat homogenitas yang tinggi antar isoform. Multiple sequence alignment menggunakan Clustal Omega mengungkap dominasi wilayah konservatif pada CDS, terutama di bagian awal gen, disertai variasi terbatas yang diduga tidak mengganggu fungsi katalitik utama. Salah satu sekuens RefSeq, NM_001402723.1, dipilih sebagai representatif untuk analisis lanjutan. Translasi dan penentuan open reading frame menunjukkan keberadaan kerangka baca lengkap, sementara anotasi domain mengidentifikasi motif glikosiltransferase serta situs pengikatan ADP-glukosa khas starch synthase tanaman. Prediksi struktur tiga dimensi berbasis AlphaFold menghasilkan model dengan tingkat kepercayaan tinggi dan kesesuaian penuh terhadap protein referensi UniProt.Secara keseluruhan, hasil ini menegaskan konservasi struktural GBSSI pada padi dan menyediakan kerangka molekuler untuk menafsirkan implikasi variasi sekuens terhadap jalur metabolisme pati serta sifat mutu beras.
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References
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References
Artimo, P., Jonnalagedda, M., Arnold, K., Baratin, D., Csardi, G., de Castro, E., Duvaud, S., Flegel, V., Fortier, A., Gasteiger, E., Grosdidier, A., Hernandez, C., Ioannidis, V., Kuznetsov, D., Liechti, R., Moretti, S., Mostaguir, K., Redaschi, N., Rossier, G., Xenarios, I., Stockinger, H., (2012). ExPASy: SIB bioinformatics resource portal, Nucleic Acids Research, Volume 40, Issue W1, 1 July 2012, Pages W597–W603, https://doi.org/10.1093/nar/gks400
Butardo, V.M., Anacleto, A., Parween, S., Samson, I., de Guzman, K., Alhambra, C.M., Misra, G., Sreenivasulu, N. (2017). Systems Genetics Identifies a Novel Regulatory Domain of Amylose Synthesis, Plant Physiology, Volume 173, Issue 1, Pages 887–906, https://doi.org/10.1104/pp.16.01248
Chaichoompu, E., Ruengphayak, S., Wattanavanitchakorn, S., Wansuksri, R., Yonkoksung, U., Suklaew, P. O., Chotineeranat, S., Raungrusmee, S., Vanavichit, A., Toojinda, T., & Kamolsukyeunyong, W. (2024). Development of Whole-Grain Rice Lines Exhibiting Low and Intermediate Glycemic Index with Decreased Amylose Content. Foods, 13(22), 3627. https://doi.org/10.3390/foods13223627
Farooq, M. A., & Yu, J. (2025). Starches in Rice: Effects of Rice Variety and Processing/Cooking Methods on Their Glycemic Index. Foods, 14(12), 2022. https://doi.org/10.3390/foods14122022
Feng, H., Li, Y., Dai, G. et al. (2025). Integrative phenomics, metabolomics and genomics analysis provides new insights for deciphering the genetic basis of metabolism in polished rice. Genome Biol 26, 55. https://doi.org/10.1186/s13059-025-03513-w
Hasan, S., Huang, L., Liu, Q. et al. (2022). The Long Read Transcriptome of Rice (Oryza sativa ssp. japonica var. Nipponbare) Reveals Novel Transcripts. Rice 15, 29. https://doi.org/10.1186/s12284-022-00577-1
Jayhoon, A.S., Kumar, P. (2024). In-silico characterization and expression analysis of the Waxy gene in rice (Oryza sativa L.). agriRxiv. https://doi.org/10.31220/agriRxiv.2024.00260
Jumper, J., Evans, R., Pritzel, A. et al. (2021). Highly accurate protein structure prediction with AlphaFold. Nature 596, 583–589. https://doi.org/10.1038/s41586-021-03819-2
Maung TZ, Yoo J-M, Chu S-H, Kim K-W, Chung I-M, Park Y-J. (2021). Haplotype Variations and Evolutionary Analysis of the Granule-Bound Starch Synthase I Gene in the Korean World Rice Collection. Frontiers in Plant Science. PMID: 34504507. https://pubmed.ncbi.nlm.nih.gov/34504507/
Mitchell, A., Chang, H., Daugherty, L., Fraser, M., Hunter, S., Lopez, R., et al. (2015). The InterPro protein families database: the classification resource after 15 years, Nucleic Acids Research, Volume 43, Issue D1, Pages D213–D221, https://doi.org/10.1093/nar/gku1243
Kim JK, Park Y, et al. Comparative metabolic profiling of pigmented rice (Oryza sativa L.) cultivars reveals primary metabolites are correlated with secondary metabolites. Journal of Cereal Science. (2013). https://www.sciencedirect.com/science/article/abs/pii/S073352101200210X
Rathinasabapathi, P., Purushothaman, N., VL., R., Parani, M. (2015) . Whole genome sequencing and analysis of Swarna, a widely cultivated indica rice variety with low glycemic index. Sci. Rep. 5, 11303;, https://doi.org/10.1038/srep11303
Sievers F, Wilm A, Dineen D, Gibson TJ, Karplus K, Li W, Lopez R, McWilliam H, Remmert M, Söding J, Thompson JD, Higgins DG. (2011). Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega. Mol Syst Biol. 11;7:539. doi: 10.1038/msb.2011.75. PMID: 21988835; PMCID: PMC3261699.
Sievers F, Higgins DG. (2018). Clustal Omega for making accurate alignments of many protein sequences. Protein Sci. 27(1):135-145. doi: 10.1002/pro.3290. PMID: 28884485; PMCID: PMC5734385.
Singh, N., Singh, B., Rai, V., Sidhu, S., Singh, A. K., & Singh, N. K. (2017). Evolutionary Insights Based on SNP Haplotypes of Red Pericarp, Grain Size and Starch Synthase Genes in Wild and Cultivated Rice. Frontiers in Plant Science, 8(16). https://doi.org/10.3389/fpls.2017.00972
Wang C.X., Cai X.G., and Qian Q.S. (2025). Regulation of starch biosynthesis pathway for improved grain quality in rice, Rice Genomics and Genetics, 16(4): 219-236. https://doi.org/10.5376/rgg.2025.16.0019
Wu, H., Wang, S., & Wu, M. (2024). The Waxy Gene Has Pleiotropic Effects on Hot Water-Soluble and -Insoluble Amylose Contents in Rice (Oryza sativa) Grains. International Journal of Molecular Sciences, 25(12), 6561. https://doi.org/10.3390/ijms25126561
Zhang Z, Zhang F, Deng Y, Sun L, Mao M, Chen R, Qiang Q, Zhou J, Long T, Zhao X, Liu X, Wang S, Yang J, Luo J. (2022). Integrated Metabolomics and Transcriptomics Analyses Reveal the Metabolic Differences and Molecular Basis of Nutritional Quality in Landraces and Cultivated Rice. Metabolites;12(5):384. https://doi.org/10.3390/metabo12050384.
Zhang, H., Jang, S.-G., Lar, S. M., Lee, A.-R., Cao, F.-Y., Seo, J., & Kwon, S.-W. (2021). Genome-Wide Identification and Genetic Variations of the Starch Synthase Gene Family in Rice. Plants, 10(6), 1154. https://doi.org/10.3390/plants10061154
Zhao, M., Huang, J., Ren, J., Xiao, X., Li, Y., Zhai, L., Yan, X., Yun, Y., Yang, Q., Tang, Q., Xing, F., & Qiao, W. (2024). Metabolomic Insights into Primary and Secondary Metabolites Variation in Common and Glutinous Rice (Oryza sativa L.). Agronomy, 14(7), 1383. https://doi.org/10.3390/agronomy14071383