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Abstract
Background: Soil salinization is one of the key factors restricting the production of cropland. Once rice is subjected to alkali stress at the bud burst stage, the yield will suffer irreparable serious loss. Compared with salt tolerance, studies on QTL mapping and candidate gene analysis of rice alkali tolerance are limited.
Results: In this study, we used the F2:3 population derived from the alkali-tolerant cultivar LD21 and the alkali-sensitive cultivar WL138 to construct an alkali-tolerant DNA mixing pool, and the BSA (Bulked Segregation Analysis) method was used for re-sequencing. The main QTL qRSLB9 controlling the relative shoot length of rice under alkali stress was mapped by QTL-seq. The candidate interval was narrowed to 346.5 kb by regional linkage mapping, which containing 6 DEGs screened through transcriptome sequencing. The qRT-PCR and candidate gene sequencing showed that LOC_Os09g24260 was most likely to control relative shoot length (RSL) in rice as a major gene who encodes the WD domain, G-beta repeat domain-containing protein.
Conclusions: Based on these results, LOC_Os09g24260 was the candidate gene of qRSLB9 conferring alkalinity tolerance to rice at the bud burst stage. Our study provides valuable genetic information and materials for breeding new rice varieties with alkalinity tolerance.
References
Gao Y, Liu C, Li Y, et al. QTL analysis for chalkiness of rice and fine mapping of a candidate gene for qACE9. Rice 2016;9(1):41. https://doi.org/10.1186/s12284-016-0114-5 PMid: 27549111
Takagi H, Tamiru M, Abe A, et al. MutMap accelerates breeding of a salt-tolerant rice cultivar. Nat Biotech 2015;33:445–449. https://doi.org/10.1038/nbt.3188 PMid: 25798936
Wei LX, Lv BS, Li XW, et al. Priming of rice (Oryza sativa L.) seedlings with abscisic acid enhances seedling survival, plant growth, and grain yield in saline-alkaline paddy fields. Field Crops Res 2017;203:86–93. https://doi.org/10.1016/j.fcr.2016.12.024
Wang C, Zhang Y, Zhao L, et al. Research Status, Problems and Suggestions on Salt-alkali Tolerant Rice. China Rice. 2019;25(1):1-6. https://doi.org/10.3969/j.issn.1006-8082.2019.01.001
Li J, Pu L, Han M, et al. Soil salinization research in China: Advances and prospects. J Geogr Sci 2014:24:943–960. https://doi.org/10.1007/s11442-014-1130-2
Ganapati RK, Naveed SA, Zafar S, et al. Saline-alkali tolerance in rice: Physiological response, molecular mechanism, and QTL identification and application to breeding. Rice Science 2022;29(5):412-434. https://doi.org/10.1016/j.rsci.2022.05.002
Shi Y, Gao L, Wu Z, et al. Genome-wide association study of salt tolerance at the seed germination stage in rice. BMC Plant Biol 2017;17:92. https://doi.org/10.1186/s12870-017-1044-0
Lei L, Zheng H, Bi Y, et al. Identification of a major QTL and candidate gene analysis of salt tolerance at the bud burst stage in rice (Oryza sativa L.) using QTL-Seq and RNA-Seq. Rice 2020;13(1):55. https://doi.org/10.1186/s12284-020-00416-1 PMid: 32778977
Li N, Sun J, Wang J, et al. QTL analysis for alkaline tolerance of rice and verification of a major QTL. Plant Breeding 2017;136(6):881-891. https://doi.org/10.1111/pbr.12539
Sun J, Xie D, Zhang E, et al. QTL mapping of photosynthetic-related traits in rice under salt and alkali stresses. Euphytica 2019;215:147. https://doi.org/10.1007/s10681-019-2470-x
Tiwari S, SL K, Kumar V, et al. Mapping QTLs for salt tolerance in rice (Oryza sativa L.) by bulked segregant analysis of recombinant inbred lines using 50K SNP Chip. PLOS ONE 2016;11(4):e0153610. https://doi.org/10.1371/journal.pone.0153610 PMid: 27077373
Li X, Zheng H, Wu W, et al. QTL mapping and candidate gene analysis for alkali tolerance in Japonica rice at the bud stage based on linkage mapping and genome-wide association study. Rice 2020;13(1):48. https://doi.org/10.1186/s12284-020-00412-5 PMid: 32676742
Liang JL, Qu YP, Yang CG, et al. Identification of QTLs associated with salt or alkaline tolerance at the seedling stage in rice under salt or alkaline stress. Euphytica 2015;201(3):441-452. https://doi.org/10.1007/s10681-014-1236-8
Takagi H, Abe A, Yoshida K, et al. QTL-seq: rapid mapping of quantitative trait loci in rice by whole genome resequencing of DNA from two bulked populations. Plant J. 2013;74(1):174–183. https://doi.org/10.1111/tpj.12105 PMid: 23289725
Zhao H, Zheng Y, Bai F, et al. Bulked segregant analysis coupled with whole-genome sequencing (BSA-Seq) and identification of a novel locus, qGL3.5, that regulates grain length. PREPRINT (Version 1) Research Square 2021. https://doi.org/10.21203/rs.3.rs-263682/v1
Zhang C, Jin F, Li S, et al. Fine mapping of major QTLs for alkaline tolerance at the seedling stage in maize (Zea mays L.) through genetic linkage analysis combined with high-throughput DNA sequencing. Euphytica 2018;214(7):120. https://doi.org/10.1007/s10681-018-2190-7
Ochar K, Su BH, Zhou MM, et al. Identification of the genetic locus associated with the crinkled leaf phenotype in a soybean (Glycine max L.) mutant by BSA-Seq technology. Journal of Integrative Agriculture 2022;21(12):3524-3539. https://doi.org/10.1016/j.jia.2022.08.095
Sun J, Wang J, Guo W, et al. Identification of alkali-tolerant candidate genes using the NGS-assisted BSA strategy in rice. Molecular Breeding 2021;41(7):44. https://doi.org/10.1007/s11032-021-01228-x PMid: 37309384
Martin JA, Wang Z. Next-generation transcriptome assembly. Nature Reviews Genetics 2011;12(10):671-682. https://doi.org/10.1038/nrg3068 PMid: 21897427
Cohen SP, Leach JE. Abiotic and biotic stresses induce a core transcriptome response in rice. Scientific Reports 2019;9(1):6273. https://doi.org/10.1038/s41598-019-42731-8 PMid: 31000746
Mao J, Yu Y, Yang J, et al. Comparative transcriptome analysis of sweet corn seedlings under low-temperature stress. The Crop Journal 2017;5(5):396-406. https://doi.org/10.1016/j.cj.2017.03.005
Rodrigues FA, Fuganti-Pagliarini R, Marcolino-Gomes J, et al. Daytime soybean transcriptome fluctuations during water deficit stress. BMC Genomics 2015;16(1):505. https://doi.org/10.1186/s12864-015-1731-x PMid: 26149272
Sun BR, Fu CY, Fan ZL, et al. Genomic and transcriptomic analysis reveal molecular basis of salinity tolerance in a novel strong salt-tolerant rice landrace Changmaogu. Rice, 2019;12:99. https://doi.org/10.1186/s12284-019-0360-4 PMid: 31883029
Mei S, Zhang G, Jiang J, et al. Combining genome-wide association study and gene-based haplotype analysis to identify candidate genes for alkali tolerance at the germination stage in rice. Frontiers in Plant Science 2022;13:887239. https://doi.org/10.3389/fpls.2022.887239 PMid: 35463411
Campbell MT, Bandillo N, Al Shiblawi FRA, et al. Allelic variants of OsHKT1;1 underlie the divergence between indica and japonica subspecies of rice (Oryza sativa) for root sodium content. PLoS Genet 2017;13(6):e1006823. https://doi.org/10.1371/journal.pgen.1006823 PMid: 28582424
Song JM, Xie WZ, Wang S, et al. Two gap-free reference genomes and a global view of the centromere architecture in rice. Molecular Plant 2021;14(10):1757-1767. https://doi.org/10.1016/j.molp.2021.06.018 PMid: 34171480
Nielsen SM, Hougaard HA, Balling O. Uncertainty quantification with maximum entropy method for fatigue life estimation. Proceedings of the ASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. Volume 5: 24th Reliability, Stress Analysis, and Failure Prevention Conference (RSAFP). Virtual, Online. August 17–19, 2020. V005T05A008. ASME. https://doi.org/10.1115/DETC2020-22728
Mansfeld BN, Grumet R. QTLseqr: An R package for bulk segregant analysis with next-generation sequencing. Plant Genome 2018;11(2):180006. https://doi.org/10.3835/plantgenome2018.01.0006
Hill J T, Demarest BL, Bisgrove BW, et al. MMAPPR: Mutation Mapping Analysis Pipeline for Pooled RNA-seq. Genome Res 2013;23:687–697. https://doi.org/10.1101/gr.146936.112 PMid: 23299975
Magwene PM, Willis JH, Kelly JK. The statistics of bulk segregant analysis using next generation sequencing. PLoS Comput Biol 2011;7(11):e1002255. https://doi.org/10.1371/journal.pcbi.1002255 PMid: 22072954
Fisher RA. On the interpretation of ?2 from contingency tables, and the calculation of P. Journal of the Royal Statistical Society 1922;85(1):87-94. https://doi.org/10.2307/2340521
Dangthaisong P, Sookgul P, Wanchana S,et al. Abiotic stress at the early grain filling stage affects aromatics, grain quality and grain yield in thai fragrant rice (Oryza sativa) cultivars. Agricultural Research 2023;12:285-297. https://doi.org/10.1007/s40003-023-00646-x
Liu XL, Zhang H, Jin Y, et al. Abscisic acid primes rice seedlings for enhanced tolerance to alkaline stress by upregulating antioxidant defense and stress tolerance-related genes. Plant and Soil 2019;438:39-55. https://doi.org/10.1007/s11104-019-03992-4
Siahpoosh MR, Sanchez DH, Schlereth A, et al. Modification of OsSUT1 gene expression modulates the salt response of rice Oryza sativa cv. Taipei 309. Plant Science 2012;182:101-111. https://doi.org/10.1016/j.plantsci.2011.01.001 PMid: 22118621
Krishnamurthy SL, Sharma PC, Sharma SK, et al. Effect of salinity and use of stress indices of morphological and physiological traits at the seedling stage in rice. Indian Journal of Experimental Biology 2016;54(12):843-850. PMid: 30183182
Wang ZF, Chen ZW, Cheng JP, et al. QTL analysis of Na+ and K+ concentrations in roots and shoots under different levels of NaCl stress in rice (Oryza sativa L.). PLoS One 2012;7(12):e5120258. https://doi.org/10.1371/journal.pone.0051202 PMid: 23236455
Singh L, Coronejo S, Pruthi R, et al. Integration of QTL mapping and whole genome sequencing identifies candidate genes for alkalinity tolerance in rice (Oryza sativa). Int. J. Mol. Sci 2022;23(19):11791. https://doi.org/10.3390/ijms231911791 PMid: 36233092
Sabouri H, Sabouri A. New evidence of QTLs attributed to salinity tolerance in rice. Afr. J. Biotechnol. 2008;7(24):4376–4383.
Peethambaran PK, Glenz R, Höninger S, et al. Salt-inducible expression of OsJAZ8 improves resilience against salt-stress. BMC Plant Biology 2018;18:311. https://doi.org/10.1186/s12870-018-1521-0 PMid: 30497415
Wang B, Liu Y, Wang W, et al. OsbZIP72 is involved in transcriptional gene-regulation pathway of abscisic acid signal transduction by activating rice high-affinity potassium transporter OsHKT1;1. Rice Science 2021;28(3):257-267. https://doi.org/10.1016/j.rsci.2021.04.005
Fu S, Fu L, Zhang X, et al. OsC2DP, a novel C2 domain-containing protein is required for salt tolerance in rice. Plant and Cell Physiology 2019;60(10):2220-2230. https://doi.org/10.1093/pcp/pcz115 PMid: 31198970
Sun L, Zhang Q, Wu J, et al. Two rice authentic histidine phosphotransfer proteins, OsAHP1 and OsAHP2, mediate cytokinin signaling and stress responses in rice. Plant Physiology 2014;165(1):335-345. https://doi.org/10.1104/pp.113.232629 PMid: 24578505
Wang Z, Gerstein M, Snyder M. RNA-Seq: a revolutionary tool for transcriptomics. Nat Rev Genet 2009;10:57–63. https://doi.org/10.1038/nrg2484 PMid: 19015660
Guo Z, Cai L, Chen Z, et al. Identification of candidate genes controlling chilling tolerance of rice in the cold region at the booting stage by BSA-Seq and RNA-Seq. Royal Society Open Science 2020;7(11):201081. https://doi.org/10.1098/rsos.201081 PMid: 33391797
Yang L, Lei L, Li P, et al. Identification of candidate genes conferring cold tolerance to rice (Oryza sativa L.) at the bud-bursting stage using bulk segregant analysis sequencing and linkage mapping. Frontiers in Plant Science 2021;12:647239. https://doi.org/10.3389/fpls.2021.647239 PMid: 33790929
Han S, Yu B, Wang Y, et al. Role of plant autophagy in stress response. Protein & Cell 2011;2(10):784-791. https://doi.org/10.1007/s13238-011-1104-4 PMid: 22058033
Avin?Wittenberg T. Autophagy and its role in plant abiotic stress management. Plant, Cell & Environment 2019;42(3):1045-1053. https://doi.org/10.1111/pce.13404 PMid: 29998609
Liu Y, Xiong Y, Bassham DC. Autophagy is required for tolerance of drought and salt stress in plants. Autophagy 2009;5(7):954-963. https://doi.org/10.4161/auto.5.7.9290 PMid: 19587533
Shin JH, Yoshimoto K, Ohsumi Y, et al. OsATG10b, an autophagosome component, is needed for cell survival against oxidative stresses in rice. Molecules & Cells 2009;27(1):67-74. https://doi.org/10.1007/s10059-009-0006-2 PMid: 19214435
Zhao Q, Feng Q, Lu H, et al. Pan-genome analysis highlights the extent of genomic variation in cultivated and wild rice. Nat Genet 2018;50:278–284. https://doi.org/10.1038/s41588-018-0041-z PMid: 29335547
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