研究报告

水稻种子耐储性基因的挖掘及不同老化方式的转录组分析

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  • 1湖南农业大学 农学院,长沙 410128
    2湖南省农业科学院 湖南杂交水稻研究中心,长沙 410125
    3国家耐盐碱水稻技术创新中心,三亚 572019
第一联系人:共同第一作者

收稿日期: 2024-11-18

  修回日期: 2025-01-06

  网络出版日期: 2026-01-21

基金资助

国家水稻产业技术体系资助项目(CARS-01-19)

Identification of Genes for Rice Seed Storability and Transcriptome Analysis Under Different Aging Conditions

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  • 1College of Agronomy, Hunan Agricultural University, Changsha 410128, China
    2Hunan Hybrid Rice Research Center, Hunan Academy of Agricultural Sciences, Changsha 410125, China
    3National Center of Technology Innovation for Saline-Alkali Tolerant Rice, Sanya 572019, China
First author contact:These authors contributed equally to this work

Received date: 2024-11-18

  Revised date: 2025-01-06

  Online published: 2026-01-21

摘要

【目的】水稻种子耐储性对种质资源保护、粮食安全和可持续发展具有重要意义。本研究旨在挖掘控制水稻种子耐储性的QTL,并探索不同老化方式下耐储性的遗传基础。【方法】以籼稻93-11为背景的131个尼瓦拉野生稻渗入系为材料,分别采用自然老化和人工老化处理,测定发芽率进行QTL定位。通过转录组测序比较携带qASS1.1/qNSS1.1野生稻等位基因的耐储材料Ra32与不携带增效等位基因的不耐储材料Ra146,筛选差异表达基因(Differentially expressed genes, DEGs),并通过GO和KEGG分析挖掘候选基因。【结果】共检测到6个耐储性QTL,分布在1、3、6、7、9号染色体上,每个QTL可解释3.3%~21.0%的表型变异。其中,主效QTL qASS1.1/qNSS1.1在两种老化处理中均稳定检测到,且野生稻等位基因显著提高种子耐储性。转录组分析共鉴定出人工老化下2077个DEG、自然老化下1468个DEG,两种处理下共有733个DEG。GO富集和KEGG代谢途径分析显示,人工老化下DEG可富集到1428个GO条目和97个代谢途径;自然老化下分别为1199个条目和85个代谢途径。在最显著富集的10个生物学过程和30个代谢途径中,昼夜节律调控翻译和过氧化氢分解过程等生物学过程以及MAPK信号传导通路、细胞分裂素生物合成、组氨酸代谢、抗坏血酸和醛糖酸代谢等代谢是两种老化处理共有的富集通路,表明种子耐储性可能受抗氧化系统调控、能量代谢及种子储藏物质积累等机制影响。基于这些富集通路,经RT-qPCR验证,初步筛选到主效QTL qASS1.1/qNSS1.1的5个候选基因,包括Os01g0842400Os01g0842500(编码漆酶前体蛋白)、Os01g0847800(编码醛酮还原酶家族蛋白)、Os01g0855900(编码CDC6-DNA复制起始蛋白)和Os01g0860400(编码糖基水解酶)。【结论】本研究挖掘到耐储性QTL并筛选出多个候选基因,揭示了不同老化处理下水稻种子主要通过调节抗氧化防御、维持细胞稳定性和代谢过程来提高其耐储性,为水稻耐储性改良提供了新的基因资源和理论支持。

本文引用格式

廖政明, 郭梁, 潘孝武, 黎用朝, 董铮, 李小湘 . 水稻种子耐储性基因的挖掘及不同老化方式的转录组分析[J]. 中国水稻科学, 2026 , 40(1) : 95 -105 . DOI: 10.16819/j.1001-7216.2026.241110

Abstract

【Objective】Seed storability is crucial for germplasm conservation, food security, and sustainable development. This study aims to identify QTLs associated with rice seed storability and explore the genetic basis of seed storability under different aging conditions.【Method】A set of 131 Oryza nivara introgression lines in the genetic background of the indica variety 93-11 was used. Seeds were subjected to natural aging and artificial aging treatments, and germination rates were measured for QTL mapping. RNA sequencing was performed to analyze genome-wide gene expression patterns in embryos from the storage-tolerant line Ra32 (carrying the O. nivara-derived allele of qASS1.1/qNSS1.1) and the storage-sensitive line Ra146 (without the allele). GO and KEGG enrichment analyses were conducted to explore enriched pathways and to identify genes related to seed storability.【Result】Six QTLs for seed storability were identified on chromosomes 1, 3, 6, 7, and 9, with individual QTLs explaining 3.3% to 21.0% of phenotypic variance. Among them, qASS1.1/qNSS1.1 was consistently detected under both natural and artificial aging treatments, and the O. nivara-derived allele at this QTL enhanced seed storability. Transcriptome analysis revealed 2077 differentially expressed genes (DEGs) under artificial aging and 1468 DEGs under natural aging, with 733 shared DEGs between the two treatments. GO and KEGG analyses showed that DEGs under artificial aging were enriched in 1428 GO terms and 97 metabolic pathways, while DEGs under natural aging were enriched in 1199 GO terms and 85 pathways. Two biological processes (circadian regulation of translation and hydrogen peroxide catabolic process) and 12 metabolic pathways (including MAPK signaling pathway, zeatin biosynthesis, histidine metabolism, and ascorbate and aldarate metabolism) were commonly enriched in both treatments, suggesting that seed storability may be regulated by antioxidant systems, energy metabolism, and accumulation of seed storage substances. Based on functional annotation of DEGs near the qASS1.1/qNSS1.1 locus, five candidate genes for qASS1.1/qNSS1.1 were further identified.【Conclusion】This study identified QTLs related to seed storability and screened multiple candidate genes, revealing that rice seeds enhance storability under different aging treatments mainly by regulating antioxidant defense, maintaining cellular stability, and modulating metabolic processes. These findings provide new genetic resources for improving seed storability in rice.

参考文献

[1] 朱俊峰. 我国粮食产后损失的现状、影响因素及改进对策[J]. 江西社会科学, 2023, 43(9): 29-40.
  Zhu J F. The current situation, influencing factors, and improvement strategies of post-harvest losses in grain production in China[J]. Jianxi Social Sciences, 2023, 43(9): 29-40. (in Chinese with Chinese abstract)
[2] Zhou T S, Yu D, Wu L B, Xu Y S, Duan M J, Yuan D Y. Seed storability in rice: Physiological foundations, molecular mechanisms, and applications in breeding[J]. Rice Science, 2024, 31(4): 401-416.
[3] 王雪彬, 张健, 韦燕燕, 罗继景, 梁云涛, 蔡中全. 基于BSA-seq的水稻籽粒耐陈化QTL定位分析[J]. 分子植物育种, 2023, 21(16): 5337-5347.
  Wang X B, Zhang J, Wei Y Y, Luo J J, Liang Y T, Cai Z Q. QTLs mapping analysis of rice grain aging tolerance based on BSA-seq[J]. Molecular Plant Breeding, 2023, 21(16): 5337-5347. (in Chinese with English abstract)
[4] 曹玉洁, 费月新, 赵文佳, 侯璐燕, 王越, 吴敏, 许珊, 吴洪恺. 以种子电导率为指标定位水稻耐储藏QTL[J]. 中国稻米, 2020, 26(1): 46-49.
  Cao Y J, Fei Y X, Zhao W J, Hou L Y, Wang Y, Wu M, Xu S, Wu H K. Mapping of QTL for rice storability based on seed electric conductivity[J]. China Rice, 2020, 26(1): 46-49. (in Chinese with English abstract)
[5] Jin B C, Qi H N, Jia L Q, Tang Q Z, Gao L, Li Z N, Zhao G W. Determination of viability and vigor of naturally-aged rice seeds using hyperspectral imaging with machine learning[J]. Infrared Physics & Technology, 2022, 122: 104097.
[6] Song P, Wang Z Y, Song P, Yue X, Bai Y H, Feng L L. Evaluating the effect of aging process on the physicochemical characteristics of rice seeds by low field nuclear magnetic resonance and its imaging technique[J]. Journal of Cereal Science, 2021, 99: 103190.
[7] Ye J, Wang C J, Chen L, Zhai R R, Wu M M, Lu Y T, Yu F M, Zhang X M, Zhu G F, Ye S H. Golden hull: A potential biomarker for assessing seed aging tolerance in rice[J]. Agronomy. 2024, 14(10): 2357.
[8] Wang W Q, He A B, Peng S B, Huang J L, Cui K H, Nie L X. The effect of storage condition and duration on the deterioration of primed rice seeds[J]. Frontiers in Plant Science, 2018, 9: 172.
[9] 吴方喜, 罗曦, 魏毅东, 郑燕梅, 林强, 谢国生, 谢华安, 张建福. 世界水稻核心种质的耐储藏特性鉴定[J]. 福建稻麦科技, 2021, 39(1): 1-5.
  Wu F X, Luo X, Wei Y D, Zheng Y M, Lin Q, Xie G S, Xie H A, Zhang J F. Identification of seed storability in rice core collections from 47 countries worldwide[J]. Fujian Science and Technology of Rice and Wheat, 2021, 39(1): 1-5. (in Chinese with English abstract)
[10] 黄祎雯, 张维谊, 王霞, 王敏, 沈斯文, 高猛峰, 梅博, 汪弘康, 童金蓉, 曹黎明, 丰东升, 孙滨. 33份不同基因型水稻耐储性比较[J/OL]. 分子植物育种, 1-13[2025-03-13]. http://kns.cnki.net/kcms/detail/46.1068.S.20240202.1646.010.html
  Huang Y W, Zhang W Y, Wang X, Wang M, Shen S W, Gao M F, Mei B, Wang H K, Tong J R, Cao L M, Feng D S, Sun B. Comparison of storage tolerance among 33 different genotypes of rice[J/OL]. Molecular Plant Breeding, 2024, http://kns.cnki.net/kcms/detail/46.1068.S.20240202.1646.010. (in Chinese with English abstract)
[11] 黄祎雯, 孙滨, 程灿, 牛付安, 周继华, 张安鹏, 涂荣剑, 李瑶, 姚瑶, 代雨婷, 谢开珍, 陈小荣, 曹黎明, 储黄伟. 对水稻种子耐储性QTL的研究[J]. 作物学报, 2022, 48(9): 2255-2264.
  Huang Y W, Sun B, Chen C, Niu F A, Zhou J H, Zhang A P, Tu R J, Li Y, Yao Y, Dai Y T, Xie K Z, Chen X R, Cao L M, Chu H W. QTL mapping of seed storage tolerance in rice (Oryza sativa L.)[J]. Acta Agronomica Sinica, 2022, 48(9): 2255-2264. (in Chinese with English abstract)
[12] 刘进, 姚晓云, 余丽琴, 李慧, 周慧颖, 王嘉宇, 黎毛毛. 水稻耐储藏特性三年动态鉴定与QTL分析[J]. 植物学报, 2019, 54(4): 464-473.
  Liu J, Yao X Y, Yu L Q, Li H, Zhou H Y, Wang J Y, Li M M. Detection and analysis of dynamic quantitative trait loci at three years for seed storability in rice (Oryza sativa)[J]. Chinese Bulletin of Botany, 2019, 54(4): 464-473. (in Chinese with English abstract)
[13] Wu F X, Luo X, Wang L Q, Wei Y D, Li J G, Xie H A, Zhang J F, Xie G S. Genome-wide association study reveals the QTLs for seed storability in world rice core collections[J]. Plants (Basel), 2021, 10(4): 812.
[14] Sasaki K, Fukuta Y, Sato T. Mapping of quantitative trait loci controlling seed longevity of rice (Oryza sativa L.) after various periods of seed storage[J]. Plant Breeding, 2005, 124(4): 361-366.
[15] Li L F, Lin Q Y, Liu S J, Liu X, Wang W Y, Hang N T, Liu F, Zhao Z G, Jiang L, Wan J M. Identification of quantitative trait loci for seed storability in rice (Oryza sativa L.)[J]. Plant Breeding, 2012, 131(6): 739-743.
[16] Long Q Z, Zhang W W, Wang P, Shen W B, Zhou T, Liu N N, Wang R, Jiang L, Huang J X, Wang Y H, Liu Y Q, Wan J M. Molecular genetic characterization of rice seed lipoxygenase 3 and assessment of its effects on seed longevity[J]. Journal of Plant Biology, 2013, 56(4): 232-242.
[17] Yuan Z Y, Fan K, Wang Y T, Tian L, Zhang C P, Sun W Q, He H Z, Yu S B. OsGRETCHENHAGEN3-2 modulates rice seed storability via accumulation of abscisic acid and protective substances[J]. Plant Physiology, 2021, 186(1): 469-482.
[18] 黄娟, 梁云涛, 陈成斌, 徐志健, 梁世春, 潘英华. 普通野生稻遗传分化及水稻起源关系研究进展[J]. 南方农业学报, 2015, 46(10): 1756-1760.
  Huang J, Liang Y T, Chen C B, Xu Z J, Liang S C, Pan Y H. Advances in origin of Oryza sativa in terms of genetic differentiation of Oryza fufipogon[J]. Journal of Southern Agriculture, 2015, 46(10): 1756-1760. (in Chinese with English abstract)
[19] 王世林, 吴婷, 周诗琪, 宋思铭, 胡标林. 结合BSA-seq和QTL分析鉴定东乡野生稻耐储性QTL[J]. 中国水稻科学, 2025, 39(6): 789-800.
  Wang S L, Wu T, Zhou S Q, Song S M, Hu B L. Identification of QTL for seed storability in Dongxiang wild rice by integrating BSA-seq and QTL analysis[J]. Chinese Journal of Rice Science, 2025, 39(6): 789-800. (in Chinese with English abstract)
[20] Ma X, Fu Y C, Zhao X H, Jiang L Y, Zhu Z F, Gu P, Xu W Y, Su Z, Sun C Q, Tan L B. Genomic structure analysis of a set of Oryza nivara introgression lines and identification of yield-associated QTLs using whole-genome resequencing[J]. Scientific Reports, 2016, 6: 27425.
[21] Meng L, Li H H, Zhang L Y, Wang J K. QTL IciMapping: integrated software for genetic linkage map construction and quantitative trait locus mapping in biparental populations[J]. The Crop Journal, 2015, 3: 269-283.
[22] McCouch S R, CGSNL (Committee on Gene Symbolization, Nomenclature and Linkage, Rice Genetics Cooperative). Gene nomenclature system for rice[J]. Rice, 2008, 1: 72-84.
[23] Chen S F, Zhou Y Q, Chen Y, Chen Y R, Gu J. Fastp: An ultra-fast all-in-one FASTQ preprocessor[J]. Bioinformatics, 2018, 34(17): i884-i890.
[24] Kim D, Langmead B, Salzberg S L. HISAT: A fast spliced aligner with low memory requirements[J]. Nature Methods, 2015, 12(4): 357-360.
[25] Roberts A, Trapnell C, Donaghey J, Rinn J L, Pachter L. Improving RNA-Seq expression estimates by correcting for fragment bias[J]. Genome Biology, 2011, 12(3): R22.
[26] Anders S, Pyl P T, Huber W. HTSeq: A Python framework to work with high-throughput sequencing data[J]. Bioinformatics, 2015, 31(2): 166-169.
[27] Love M I, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2[J]. Genome Biology, 2014, 15(12): 550.
[28] Dietz K-J, Mittler R, Noctor G. Recent progress in understanding the role of reactive oxygen species in plant cell signaling[J]. Plant Physiology, 2016, 171(3): 1535-1539.
[29] Xue J S, Feng Y F, Zhang M Q, Xu Q L, Xu Y M, Shi J Q, Liu L F, Wu X F, Wang S, Yang Z N. The regulatory mechanism of rapid lignification for timely anther dehiscence[J]. Journal of Integrative Plant Biology, 2024, 66(8): 1788-1800.
[30] 张盛春, 鞠常亮, 王小菁. 拟南芥漆酶基因AtLAC4参与生长及非生物胁迫响应[J]. 植物学报, 2012, 47(4): 357-365.
  Zhang S C, Ju C L, Wang X Q. Arabidopsis laccase gene AtLAC4 regulates plant growth and responses to abiotic stress[J]. Chinese Bulletin of Botany, 2012, 47(4): 357-365. (in Chinese with English abstract)
[31] 徐小萍, 曹清影, 蔡柔荻, 官庆栩, 张梓浩, 陈裕坤, 徐涵, 林玉玲, 赖钟雄. 龙眼miR408与DlLAC12克隆及其在球形胚发生和非生物胁迫下的表达分析[J]. 园艺学报, 2022, 49(9): 1866-1882.
  Xu X P, Cao Q Y, Cai R D, Guan Q X, Zhang Z H, Chen Y K, Xu H, Lin Y L, Lai Z X. Gene cloning and expression analysis of miR408 and its target DlLAC12 in globular embryo development and abiotic stress in Dimocarpus longan[J]. Acta Horticulturae Sinica, 2022, 49(9): 1866-1882. (in Chinese with English abstract)
[32] Simpson P J, Tantitadapitak C, Reed A M, Mather O C, Bunce C M, White S A, Ride J P. Characterization of two novel aldo-keto reductases from Arabidopsis: Expression patterns, broad substrate specificity, and an open active-site structure suggest a role in toxicant metabolism following stress[J]. Journal of Molecular Biology, 2009, 392(2): 465-480.
[33] Saito R, Shimakawa G, Nishi A, Iwamoto T, Sakamoto K, Yamamoto H, Amako K, Makino A, Miyake C. Functional analysis of the AKR4C subfamily of Arabidopsis thaliana: model structures, substrate specificity, acrolein toxicity, and responses to light and [CO2][J]. Bioscience, Biotechnology and Biochemistry, 2013, 77(10): 2038-2045.
[34] Yu X H, Liu Y H, Yin L L, Peng Y B, Peng Y C, Gao Y X, Yuan B W, Zhu Q L, Cao T Y, Xie B W, Sun L Q, Chen Y, Gong Z C, Qiu Y Z, Fan X G, Li X. Radiation-promoted CDC6 protein stability contributes to radioresistance by regulating senescence and epithelial to mesenchymal transition[J]. Oncogene, 2019, 38: 549-563.
[35] Abeles F B, Bosshart R P, Forrence L E, Habig W H. Preparation and purification of glucanase and chitinase from bean leaves[J]. Plant Physiology, 1971, 47(1): 129-134.
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