فراتحلیل QTLهای مرتبط با فتوسنتز، شناسایی ژن‌های کاندیدا و مسیرهای عملکردی در برنج

Abdelkhalik, A. F., Shishido, R., Nomura, K., & Ikehashi, H. 2005. QTL-based analysis of leaf senescence in an indica/japonica hybrid in rice (Oryza sativa L.). Theoretical and Applied Genetics, 110, 1226-1235. https://doi.org/10.1007/s00122-005-1955-2

Adachi, S., Yamamoto, T., Nakae, T., Yamashita, M., Uchida, M., Karimata, R., Ichihara, N., Soda, K., Ochiai, T., Ao, R., Otsuka, C., Nakano, R., Takai, T., Ikka, T., Kondo, K., Ueda, T., Ookawa, T., & Hirasawa, T. 2019. Genetic architecture of leaf photosynthesis in rice revealed by different types of reciprocal mapping populations. Journal of Experimental Botany, 70(19), 5131-5144. https://doi.org/10.1093/jxb/erz303

Asif, S., Kim, E.G., Jang, Y.H., Jan, R., Kim, N., Asaf, S., Lubna., Farooq, M., & Kim, K.M. 2022. Identification of the OsCML4 gene in rice related to salt stress using QTL analysis. Plants, 11(19), 2467. https://doi.org/10.3390/plants11192467

Anilkumar, C., Sah, R. P., Muhammed Azharudheen, T. P., Behera, S., Singh, N., Prakash, N. R., Sunitha, N. C., Devanna, B. N., Marndi, B. C., Patra, B. C., & Nair, S. K. 2022. Understanding complex genetic architecture of rice grain weight through QTL-meta analysis and candidate gene identification. Scientific Reports, 12(1), 13832. https://doi.org/10.1038/s41598-022-17402-w

Bae, H., Kim, S. K., Cho, S. K., Kang, B. G., & Kim, W. T. 2011. Overexpression of OsRDCP1, a rice RING domain-containing E3 ubiquitin ligase, increased tolerance to drought stress in rice (Oryza sativa L.). Plant Science, 180(6), 775-782. https://doi.org/10.1016/j.plantsci.2011.02.008

Barik, S. R., Pandit, E., Mohanty, S. P.  Deepak Kumar, N. & Sharat Kumar, P. 2020.  Genetic mapping of physiological traits associated with terminal stage drought tolerance in rice. BMC Genetics, 21, 76. https://doi.org/10.1186/s12863-020-00883-x

Barik, J., Kumar, V., Lenka, S. K., & Panda, D. 2019. Genetic potentiality of lowland indigenous indica rice (Oryza sativa L.) landraces to anaerobic germination potential. Plant Physiology Reports, 24, 249-261. https://doi.org/10.1007/s40502-019-00441-3

Bing, Y. U. E., Wei-Ya, X. U. E., Li-Jun, L. U. O., & Yong-Zhong, X. I. N. G. 2006. QTL analysis for flag leaf characteristics and their relationships with yield and yield traits in rice. Acta Genetica Sinica, 33(9), 824-832. https://doi.org/10.1016/s0379-4172(06)60116-9

Boonburapong, B., & Buaboocha, T. 2007. Genome-wide identification and analyses of the rice calmodulin and related potential calcium sensor proteins. BMC Plant Biology, 7, 4. https://doi.org/10.1186/1471-2229-7-4

Buchner, P., Takahashi, H., & Hawkesford, M. J. 2004. Plant sulphate transporters: co-ordination of uptake, intracellular and long-distance transport. Journal of Experimental Botany, 55(404), 1765-1773. https://doi.org/10.1093/jxb/erh206 

Chen, X., Mei, Q., Liang, W., Sun, J., Wang, X., Zhou, J., Wang, J., Zhou, Y., Zheng, B., Yang, Y., & Chen, J. 2020. Gene mapping, genome-wide transcriptome analysis, and WGCNA reveals the molecular mechanism for triggering programmed cell death in rice mutant pir1. Plants, 9(11), 1607. https://doi.org/10.3390/plants9111607

Chinpongpanich, A., Limruengroj, K., Phean-O-Pas, S., Limpaseni, T., & Buaboocha, T. 2012. Expression analysis of calmodulin and calmodulin-like genes from rice, Oryza sativa L. BMC Research Notes, 5, 1-12. https://doi.org/10.1186/1756-0500-5-625 

Dai, G. J., Cheng, S. H., Hua, Z. T., Zhang, M. L., Jiang, H. B., Feng, Y., Shen, X. H., Su, Y. A., He, N., Ma, Z. B., Ma, X. Q., Hou, S. G., & Wang, Y. R. 2015. Mapping quantitative trait loci for nitrogen uptake and utilization efficiency in rice (Oryza sativa L.) at different nitrogen fertilizer levels. Genetics and Molecular Research, 14, 10404-10414. https://doi.org/10.4238/2015.september.8.1 

Darvasi, A. & Soller, M. 1997. A Simple Method to Calculate Resolving Power and Confidence Interval of QTL Map Location. Behavior Genetics, 27, 125–132. https://doi.org/10.1023/A:1025685324830

De Leon, T.B., Linscombe, S. & Subudhi, P.K. 2016. Molecular Dissection of Seedling Salinity Tolerance in Rice (Oryza sativa L.) Using a High-Density GBS-Based SNP Linkage Map. Rice, 9, 52. https://doi.org/10.1186/s12284-016-0125-2

Dong, Y.J., 2007. Quantitative trait loci for leaf chlorophyll content at two developmental stages of rice (Oryza sativa L.), Communications in Biometry and Crop Science, 2, 1-7.

Dwiningsih, Y., Kumar, A., Thomas, J., Ruiz, C., Alkahtani, J., Baisakh, N., & Pereira, A. 2021. Quantitative trait loci and candidate gene identification for chlorophyll content in RIL rice population under drought conditions. Indonesian Journal of Natural Pigments, 3(2), 54-54. https://doi.org/10.33479/ijnp.2021.03.2.54 

Feizi, N., Sabouri, A., Abedi, A., & Bakhshipour, A. 2025. Meta-analysis of quantitative trait loci associated with grain quality traits in rice (Oryza sativa L.). Acta Physiologiae Plantarum, 47, 29 https://doi.org/10.1007/s11738-025-03780-x

Fu, J.D., Yan, Y.F., Kim, M.Y., Lee, S.H. & Lee, B.W. 2011. Population-specific quantitative trait loci mapping for functional stay-green trait in rice (Oryza sativa L.). Genome, 54(3): 235-243. https://doi.org/10.1139/g10-113

Gu, J., Yin, X., Zhang, C., Wang, H., & Struik, P. C. 2014. Linking ecophysiological modelling with quantitative genetics to support marker-assisted crop design for improved yields of rice (Oryza sativa) under drought stress. Annals of Botany, 114(3), 499-511. https://doi.org/10.1093/aob/mcu127

Guan, J.C., Jinn, T.L., Yeh, C.H., Feng, S.P., Chen, Y.M., & Lin, C.Y. 2004. Characterization of the genomic structures and selective expression profiles of nine class I small heat shock protein genes clustered on two chromosomes in rice (Oryza sativa L.). Plant Molecular Biology, 56, 795-809. https://doi.org/10.1007/s11103-004-5182-z 

Gimhani, D.R., Gregorio, G.B., Kottearachchi, N.S., & Samarasinghe, W.L. 2016. SNP-based discovery of salinity-tolerant QTLs in a biparental population of rice (Oryza sativa). Molecular Genetics and Genomics, 291:2081–2099. https://doi.org/10.1007/s00438- 016- 1241-9

Hu, S. P., Zhou, Y., Zhang, L., Zhu, X. D., Li, L., Luo, L. J., Liu, G. L., & Zhou, Q. M. 2009. Correlation and quantitative trait loci analyses of total chlorophyll content and photosynthetic rate of rice (Oryza sativa) under water stress and well‐watered conditions. Journal of Integrative Plant Biology, 51(9), 879-888. https://doi.org/10.1111/j.1744-7909.2009.00846.x 

Huang, L., Dai, L., Wang, L., Leng, Y., Yang, Y., Xu, J., Hu, J., Rao, Y., Zhang, G., Zhu, L., Dong, G., Guo, L., Qian, Q., & Zeng, D. 2015. Genetic dissection for chlorophyll content of the top three leaves during grain filling in rice (Oryza sativa L.). Journal of Plant Growth Regulation, 34, 381-391. https://doi.org/10.1007/s00344-014-9474-5

Islam, M. S., Ontoy, J., & Subudhi, P. K. 2019. Meta-analysis of quantitative trait loci associated with seedling-stage salt tolerance in rice (Oryza sativa L.). Plants, 8(2), 33. https://doi.org/10.3390/plants8020033

Jang, Y. H., Park, J. R., Kim, E. G., & Kim, K. M. 2022. OsbHLHq11, the basic helix-loop-helix transcription factor, involved in regulation of chlorophyll content in rice. Biology, 11(7), 1000. https://doi.org/10.3390/biology11071000

Jiang, S. K., Zhang, X. J., Zheng-Jin, X. U., & Wen-Fu, C. H. E. N. 2010. Comparison between QTLs for chlorophyll content and genes controlling chlorophyll biosynthesis and degradation in japonica rice. Acta Agronomica Sinica, 36(3), 376-384. https://doi.org/10.1016/s1875-2780(09)60036-5

Jiang, S., Zhang, X., Zhang, F., Xu, Z., Chen, W., & Li, Y. 2012. Identification and fine mapping of qCTH4, a quantitative trait loci controlling the chlorophyll content from tillering to heading in rice (Oryza sativa L.). Journal of Heredity, 103(5), 720-726. https://doi.org/10.1093/jhered/ess041

Kaur, S., Das, A., Sheoran, S., & Rakshit, S. 2023. QTL Meta-Analysis: An Approach to Detect Robust and Precise QTL. Tropical Plant Biology, 16(4), 225-243. https://doi.org/10.1007/s12042-023-09335-z

Kumar, S., Asif, M. H., Chakrabarty, D., Tripathi, R. D., & Trivedi, P. K. 2011. Differential expression and alternative splicing of rice sulphate transporter family members regulate sulphur status during plant growth, development and stress conditions. Functional & Integrative Genomics, 11, 259-273. https://doi.org/10.1007/s10142-010-0207-y

Lin, D., Zhang, J., Zuo. H., Xu, J. Luo, L. & Dong, Y. 2010. Mapping quantitative trait loci associated with leaf senescence during maturation of rice (Oryza sativa L.). Asian Journal of Plant Sciences. 9(1), 51-57.

Lim, J. H., & Paek, N. C. 2015. Quantitative trait locus mapping and candidate gene analysis for functional stay-green trait in rice. Plant Breeding and Biotechnology, 3(2), 95-107. https://doi.org/10.9787/PBB.2015.3.2.095

Ling, S., Chen, C., Wang, Y., Sun, X., Lu, Z., Ouyang, Y., & Yao, J. 2015. The mature anther-preferentially expressed genes are associated with pollen fertility, pollen germination and anther dehiscence in rice. BMC Genomics, 16, 1-17. https://doi.org/ 10.1186/s12864-015-1305-y 

Ma, H., Zhao, H., Liu, Z., & Zhao, J. 2011. The phytocyanin gene family in rice (Oryza sativa L.): genome-wide identification, classification and transcriptional analysis. PLOS One, 6(10), e25184. https://doi.org/10.1371/journal.pone.0025184

McCouch, S.R., Teytelman, L., Xu, Y., Lobos, K.B., Clare, K., Walton, M., Fu, B., Maghirang, R., Li, Z., Xing, Y., Zhang, Q., Kono, I., Yano, M., Fjellstrom, R., DeClerck, G., Schneider, D., Cartinhour, S., Ware, D. & Stein, L. 2002. Development and mapping of 2240 new SSR Markers for rice (Oryza sativa L.). DNA Research. 9(6), 199-207. https://doi.org/10.1093/dnares/9.6.199

Okada, S., & Yamasaki, M. 2019. Validation of a quantitative trait locus for the white-core expression rate of grain on chromosome 6 in a brewing rice cultivar and development of DNA markers for marker-assisted selection. Breeding Science, 69(3), 401-409. https://doi.org/10.1270/jsbbs.18166

Panesar, P. S., & Kaur, S. 2016. Rice: types and composition. In: Caballero B, Finglas PM, Toldrá F, editors. Encyclopedia of Food and Health. Oxford: Academic Press, 646-652.  https://doi.org/10.1016/B978-0-12-384947-2.00596-1

Rabiei, B. & Sabouri, H. 2008. Mapping Genes Controlling Quantitative Traits. Guilan, University of Guilan Press. 193 pages.  [In Persian]

Sabouri, A., Toorchi, M., Rabiei, B., Aharizad, S., Moumeni, A., & Singh, R. 2010. Identification and mapping of QTLs for agronomic traits in indica-indica cross of rice (Oryza sativa L.). Cereal Research Communications, 38(3), 317-326. https://doi.org/10.1556/CRC.38.2010.3.2

Saito, R., Smoot, M. E., Ono, K., Ruscheinski, J., Wang, P. L., Lotia, S., Pico, A. R., Bader, G. D., & Ideker, T. 2012. A travel guide to Cytoscape plugins. Nature Methods, 9(11), 1069-1076.  https://doi.org/10.1038/nmeth.2212

Selamat, N., & Nadarajah, K. K. 2021. Meta-analysis of quantitative traits loci (QTL) identified in drought response in rice (Oryza sativa L.). Plants, 10(4), 716. https://doi.org/10.3390/plants10040716

Shafique, M. S., Yapei, L., Man, L., Hongjie, W., Ruyi, S., Chunlian, W., & Zhiyuan, J. 2024. Coevolution unveiled: Sulfate transporters mediate rice resistance and susceptibility to Xanthomonas oryzae pv. oryzicola. Plant Biotechnology Journal, 22(9), 2632-2634. https://doi.org/10.1111/pbi.14377

Singh, A., Kanwar, P., Pandey, A., Tyagi, A. K., Sopory, S. K., Kapoor, S., & Pandey, G. K. 2013. Comprehensive genomic analysis and expression profiling of phospholipase C gene family during abiotic stresses and development in rice. PLOS One, 8(4), e62494. https://doi.org/10.1371/journal.pone.0062494

Sun, J., Xie, D., Zhang, E., Zheng, H., Wang, J., Liu, H., Yang, L., Zhang, S., Wang, L., & Zou, D. 2019. QTL mapping of photosynthetic-related traits in rice under salt and alkali stresses. Euphytica, 215, 1-14. https://doi.org/10.1007/s10681-019-2470-x

Takai, T., Kondo, M., Yano, M., & Yamamoto, T. 2010. A quantitative trait locus for chlorophyll content and its association with leaf photosynthesis in rice. Rice, 3, 172-180. https://doi.org/10.1007/s12284-010-9047-6

Takai, T., Arai‐Sanoh, Y., Iwasawa, N., Hayashi, T., Yoshinaga, S., & Kondo, M. 2012. Comparative Mapping Suggests Repeated Selection of the Same Quantitative Trait Locus for High Leaf Photosynthesis Rate in Rice High‐Yield Breeding Programs. Crop Science, 52(6), 2649-2658. https://doi.org/10.2135/cropsci2012.03.0179

Teng, S., Qian, Q., Zeng, D., Kunihiro, Y., Fujimoto, K., Huang, D., & Zhu, L. 2004. QTL analysis of leaf photosynthetic rate and related physiological traits in rice (Oryza sativa L.). Euphytica, 135(1), 1-7. https://doi.org/10.1023/b:euph.0000009487.89270.e9

Ujiie, K., Kashiwagi, T., & Ishimaru, K. 2012. Identification and functional analysis of alleles for productivity in two sets of chromosome segment substitution lines of rice. Euphytica, 187, 325-337. https://doi.org/10.1007/s10681-012-0660-x.

Veisi, Sh., Sabouri, A., & Abedi, A. 2022. Meta-analysis of QTLs and candidate genes associated with seed germination in rice (Oryza sativa L.). Physiology and Molecular Biology of Plants. 28(8): 1587-1605. https://doi.org/10.1007/s12298-022-01232-1

Vishnukiran, T., Neeraja, C. N., Jaldhani, V., Vijayalakshmi, P., Raghuveer Rao, P., Subrahmanyam, D., & Voleti, S. R. 2020. A major pleiotropic QTL identified for yield components and nitrogen content in rice (Oryza sativa L.) under differential nitrogen field conditions. PLOS One, 15(10), e0240854. https://doi.org/10.1371/journal.pone.0240854

Xing, Y., Tan, Y., Hua, J. P., Sun, X., Xu, C., & Zhang, Q. 2002. Characterization of the main effects, epistatic effects and their environmental interactions of QTLs on the genetic basis of yield traits in rice. Theoretical and Applied Genetics, 105(2), 248-257. https://doi.org/10.1007/s00122-002-0952-y

Xue, H., Gao, X., He, P., & Xiao, G. 2022. Origin, evolution, and molecular function of DELLA proteins in plants. The Crop Journal, 10(2), 287-299. https://doi.org/10.1016/j.cj.2021.06.005

Xue, T., Wang, D., Zhang, S., Ehlting, J., Ni, F., Jakab, S., Zheng, C., & Zhong, Y. 2008. Genome-wide and expression analysis of protein phosphatase 2C in rice and Arabidopsis. BMC Genomics, 9, 1-21. https://doi.org/10.1186/1471-2164-9-550

Yamamoto, T., Suzuki, T., Suzuki, K., Adachi, S., Sun, J., Yano, M., Ookawa, T. & Hirasawa, T. 2017. Characterization of a genomic region that maintains chlorophyll and nitrogen contents during ripening in a high-yielding stay-green rice cultivar. Field Crops Research, 206: 54-64. https://doi.org/10.1016/j.fcr.2017.03.001

Yang, D., Liu, X., Yin, X., Dong, T., Yu, M., & Wu, Y. 2021. Rice non-specific phospholipase C6 is involved in mesocotyl elongation. Plant and Cell Physiology, 62(6), 985-1000. https://doi.org/10.1093/pcp/pcab069

Yang, G., Tu, S., Li, S., Feng, L., Kong, J., Li, H., & Li, Y. 2008. Analysis of quantitative trait loci underlying the traits related to chlorophyll content of the flag leaf in rice. Frontiers of Biology in China, 3(4), 443-448. https://doi.org/10.1007/s11515-008-0093-z

Yang, L., Wang, J., Han, Z., Lei, L., Liu, H. L., Zheng, H., Xin, W., & Zou, D. 2021. Combining QTL-seq and linkage mapping to fine map a candidate gene in qCTS6 for cold tolerance at the seedling stage in rice. BMC Plant Biology, 21(1), 278. https://doi.org/10.1186/s12870-021-03076-5.

Ye, W., Hu, S., Wu, L., Ge, C., Cui, Y., Chen, P., Xu, J., Dong, G., Guo, L., & Qian, Q. 2017. Fine mapping a major QTL qFCC7 L for chlorophyll content in rice (Oryza sativa L.) cv. PA64s. Plant Growth Regulation, 81, 81-90. https://doi.org/10.1007/s10725-016-0188-5.

Yoo, S. C., Cho, S. H., Zhang, H., Paik, H. C., Lee, C. H., Li, J., Yoo, J. H., Lee, B. W., Koh, H. J., Seo, H. S., & Paek, N. C. 2007. Quantitative trait loci associated with functional stay-green SNU-SG1 in rice. Molecules & Cells (Springer Science & Business Media BV), 24(1), 83-94. https://doi.org/10.1016/s1016-8478(23)10759-x

Zhang, G. H., Li, S. Y., Wang, L., Ye, W. J., Zeng, D. L., Rao, Y. C., Peng, Y. L., Hu, J., Yang, Y. L., Xu, J., Ren, D. Y., Gao, Z. Y., Zhu, L., Dong, G. J., Hu, X. M., Yan, M. X., Guo, L. B., Li, C. Y., & Qian, Q. 2014. LSCHL4 from japonica cultivar, which is allelic to NAL1, increases yield of indica super rice 93-11. Molecular Plant, 7(8): 1350-1364. https://doi.org/10.1093/mp/ssu055.

Zhang, J., Luo, T., Wang, W., Cao, T., Li, R., & Lou, Y. 2017. Silencing OsSLR1 enhances the resistance of rice to the brown planthopper Nilaparvata lugens. Plant, Cell & Environment, 40(10), 2147-2159. https://doi.org/10.1111/pce.13012.

Zhang, J. P., Yu, Y., Feng, Y. Z., Zhou, Y. F., Zhang, F., Yang, Y. W., Lei, M. Q., Zhang, Y. C., & Chen, Y. Q. 2017. MiR408 regulates grain yield and photosynthesis via a phytocyanin protein. Plant Physiology, 175(3), 1175-1185. https://doi.org/10.1104/pp.17.01169.

Zhao, X. Q., Xu, J. L., Zhao, M., Lafitte, R., Zhu, L. H., Fu, B. Y., Gao, Y. M., & Li, Z. K. 2008. QTLs affecting morph-physiological traits related to drought tolerance detected in overlapping introgression lines of rice (Oryza sativa L.). Plant Science, 174(6), 618-625. https://doi.org/10.1016/j.plantsci.2008.03.009