Meta-QTL Analysis and Prediction of Candidate Genes for Cold Tolerance at Seedling Stage in Rice

doi:10.16819/j.1001-7216.2026.250207

Chinese Journal OF Rice Science ›› 2026, Vol. 40 ›› Issue (3): 312-326.DOI: 10.16819/j.1001-7216.2026.250207

• Research Papers • Previous Articles Next Articles

Meta-QTL Analysis and Prediction of Candidate Genes for Cold Tolerance at Seedling Stage in Rice

WANG Yangyang¹^,², YANG Chuanming¹^,², ZHANG Xijuan²^,⁴, YANG Xianli²^,⁴, WANG Lizhi²^,⁴, CUI Shize²^,⁴, XU Xinkai¹^,², LI Hongyu¹^,^*(), JIANG Shukun²^,³^,⁴^,^*()

¹ Agricultural College, Heilongjiang Bayi Agricultural University, Daqing 163319, China
² Crop Cultivation and Tillage Institute, Heilongjiang Academy of Agricultural Sciences/Heilongjiang Provincial Key Laboratory of Crop Physiology and Ecology in Cold Region/Heilongjiang Provincial Engineering Technology Research Center of Crop Cold Damage, Harbin 150086, China
³ Qiqihar Branch of Heilongjiang Academy of Agricultural Sciences/Heilongjiang Provincial Engineering Technology Research Center of Crop Germplasm Resources Innovation and Utilization in Songnen Plain, Qiqihar 161006, China
⁴ Northeast Center of National Salt-Alkali Tolerant Rice Technology Innovation Center, Harbin 150086, China

Received:2025-02-18 Revised:2025-04-16 Online:2026-05-10 Published:2026-05-13
Contact: LI Hongyu, JIANG Shukun

水稻苗期耐冷性Meta-QTL分析及候选基因预测

王洋洋¹^,², 杨传铭¹^,², 张喜娟²^,⁴, 杨贤莉²^,⁴, 王立志²^,⁴, 崔士泽²^,⁴, 许鑫凯¹^,², 李红宇¹^,^*(), 姜树坤²^,³^,⁴^,^*()

¹ 黑龙江八一农垦大学农学院，黑龙江大庆 163319
² 黑龙江省农业科学院耕作栽培研究所/黑龙江省寒地作物生理生态重点实验室/黑龙江省农作物低温冷害工程技术研究中心，哈尔滨 150086
³ 黑龙江省农业科学院齐齐哈尔分院/黑龙江省松嫩平原西部作物种质资源创新与利用工程技术研究中心，黑龙江齐齐哈尔 161006
⁴ 国家耐盐碱水稻技术创新中心东北中心，哈尔滨 150086

通讯作者: 李红宇,姜树坤
基金资助:
国家重点研发计划项目资助(2024YFD2301303);黑龙江省农业科技创新跨越工程重大需求科技创新攻关项目(CX23ZD01);黑龙江省自然基金杰出青年基金资助项目(JQ2023C009);省属科研院所科研业务费专项(CZKYF2025-1-A004)

Abstract

Abstract:

【Objective】Low-temperature stress poses a significant threat to rice production, and the development of cold-tolerant varieties through the identification of cold resistance-related genes represents a critical strategy to address this challenge. Meta-QTL analysis offers a powerful approach to integrate quantitative trait loci governing complex agronomic traits, such as cold tolerance, across diverse genetic backgrounds. By improving the precision and reliability of candidate gene localization, this method provides a robust foundation for the cloning and breeding application of cold tolerance genes in rice. 【Methods】We conducted a comprehensive meta-analysis of 353 quantitative trait loci (QTLs) associated with cold tolerance at the seedling stage, derived from 38 independent studies. These QTLs were integrated using BioMercator 4.2, followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses to identify candidate genes within the Meta-QTL regions. 【Results】A total of 82 Meta-QTLs were identified, of which 67 (81.71%) had confidence intervals of less than 1 Mb. These regions encompassed 9282 annotated genes, including 25 previously reported genes associated with cold tolerance at the seedling stage. GO analysis revealed 99, 230, and 119 genes associated with abiotic stress response, environmental stress response, and transcription factors, respectively. KEGG enrichment analysis further identified 27, 69, and 9 significantly enriched genes related to abiotic stress response, stress response, and transcription factors, respectively. 【Conclusion】Through the integration and analysis of 353 QTLs related to cold tolerance at the seedling stage, 82 Meta-QTLs were identified. GO analysis pinpointed 448 candidate genes, while KEGG analysis further refined this list to 105 differentially enriched candidate genes. These findings provide valuable insights for molecular marker-assisted breeding and gene cloning for cold tolerance at the rice seedling stage.

Key words: rice, cold tolerance, QTL, Meta analysis, candidate gene

摘要：

【目的】挖掘鉴定耐冷基因进而选育耐冷品种是解决水稻低温冷害难题的最简单、直接和有效的手段之一。利用Meta-QTL分析可以有效整合不同遗传背景下控制水稻耐冷等农艺性状的基因位点，提高候选基因定位的精度和可靠性，为水稻耐冷基因的克隆和育种利用提供数据支撑。【方法】本研究收集并整理了38项独立研究中的353个水稻苗期耐冷相关QTL，利用BioMercator 4.2软件对QTL关键信息进行整合分析。并利用GO分析和KEGG分析对鉴定的Meta-QTL进行候选基因挖掘。【结果】共鉴定出了82个Meta-QTL，其中67个(81.71%)的置信区间小于1 Mb，共包含9282个注释基因，包括已报道的25个苗期耐冷基因。利用GO分析筛选出了99、230和119个分别与非生物逆境应答、环境胁迫反应和转录因子相关的基因。进一步利用KEGG富集筛选出27、69和9个分别与非生物逆境应答、胁迫反应和转录因子相关的差异显著性基因。【结论】对353个苗期耐冷QTL进行整合分析鉴定出82个苗期耐冷Meta-QTL，GO分析确定了448个候选基因，KEGG进一步确定了105个差异表达候选基因。上述结果为水稻苗期耐冷的分子标记辅助育种和基因克隆提供有用的信息。

关键词: 水稻, 耐冷性, 数量性状位点, Meta分析, 候选基因

WANG Yangyang, YANG Chuanming, ZHANG Xijuan, YANG Xianli, WANG Lizhi, CUI Shize, XU Xinkai, LI Hongyu, JIANG Shukun. Meta-QTL Analysis and Prediction of Candidate Genes for Cold Tolerance at Seedling Stage in Rice[J]. Chinese Journal OF Rice Science, 2026, 40(3): 312-326.

王洋洋, 杨传铭, 张喜娟, 杨贤莉, 王立志, 崔士泽, 许鑫凯, 李红宇, 姜树坤. 水稻苗期耐冷性Meta-QTL分析及候选基因预测[J]. 中国水稻科学, 2026, 40(3): 312-326.

Figures/Tables 9

References 64

[1]	姜树坤. 寒地水稻低温冷害的致灾机理与减灾保产关键技术[M]. 哈尔滨: 黑龙江科学技术出版社, 2021: 55-58.
	Jiang S K. Disaster mechanism of low temperature chilling injury of rice in cold region and key technologies for reducing disaster and ensuring yield[M]. Harbin: Heilongjiang Science and Technology Press, 2021: 55-58. (in Chinese)
[2]	徐敏, 徐经纬, 高苹, 于庚康, 单婵. 江苏水稻障碍型冷害时空变化特征及敏感性分析[J]. 气象, 2015, 41(11): 1367-1373.
	Xu M, Xu J W, Gao P, Yu G K, Shan C. Analysis of spatiotemporal variation characteristics and sensitivity of rice sterile-type chilling injury in Jiangsu[J]. Meteorological Monthly, 2015, 41(11): 1367-1373. (in Chinese with English abstract)
[3]	张喜娟, 来永才, 曾山. 寒地水稻直播栽培机理与技术[M]. 北京: 中国农业出版社, 2018: 21-29.
	Zhang X J, Lai Y C, Zeng S. Mechanism and technology of direct seeding cultivation of rice in cold region[M]. Beijing: China Agriculture Press, 2018: 21-29. (in Chinese)
[4]	Zu X, Luo L, Wang Z, Gong J, Yang C, Wang Y, Xu C, Qiao X, Deng X, Song X, Chen C, Tan B C, Cao X. A mitochondrial pentatricopeptide repeat protein enhances cold tolerance by modulating mitochondrial superoxide in rice[J]. Nature Communications, 2023, 14(1): 6789.
[5]	Qian Q, Zeng D, He P, Zheng X, Chen Y, Zhu L. QTL analysis of the rice seedling cold tolerance in a double haploid population derived from anther culture of a hybrid between indica and japonica rice[J]. Chinese Science Bulletin, 2000, 45(5): 448-453.
[6]	Andaya V C, MacKill D J. Mapping of QTLs associated with cold tolerance during the vegetative stage in rice[J]. Journal of Experimental Botany, 2003, 54(392): 2579-2585.
[7]	韩龙植, 张三元, 乔永利, 阮仁超, 张俊国, 曹桂兰, 高熙宗. 冷水胁迫下水稻幼苗期根系性状的QTL分析[J]. 作物学报, 2005, 31(11): 1415-1421.
	Han L Z, Zhang S Y, Qiao Y L, Ruan R C, Zhang J G, Cao G L, Gao X Z. QTL analysis of root traits at the seedling stage in rice under cold water irrigation[J]. Acta Agronomica Sinica, 2005, 31(11): 1415-1421. (in Chinese)
[8]	Lou Q, Chen L, Sun Z, Xing Y, Li J, Xu X, Mei H, Luo L. A major QTL associated with cold tolerance at seedling stage in rice (Oryza sativa L.)[J]. Euphytica, 2007, 158(1): 87-94.
[9]	Jiang L, Xun M, Wang J, Wan J. QTL analysis of cold tolerance at seedling stage in rice (Oryza sativa L.) using recombination inbred lines[J]. Journal of Cereal Science, 2008, 48(1): 173-179.
[10]	Suh J P, Lee C K, Lee J H, Kim J J, Kim S M, Cho Y C, Park S H, Shin J C, Kim Y G, Jena K K. Identification of quantitative trait loci for seedling cold tolerance using RILs derived from a cross between japonica and tropical japonica rice cultivars[J]. Euphytica, 2012, 184(1): 101-108.
[11]	Cheng L R, Wang J M, Uzokwe V, Meng L J, Wang Y, Sun Y, Zhu L H, Xu J L, Li Z K. Genetic analysis of cold tolerance at seedling stage and heat tolerance at anthesis in rice (Oryza sativa L.)[J]. Journal of Integrative Agriculture, 2012, 11(3): 359-367.
[12]	Goffinet B, Gerber S. Quantitative trait loci: A meta-analysis[J]. Genetics, 2000, 155(1): 463-473.
[13]	郭书磊, 张君, 齐建双, 岳润清, 韩小花, 燕树锋, 卢彩霞, 傅晓雷, 陈娜娜, 库丽霞, 铁双贵. 玉米叶形相关性状的Meta-QTL及候选基因分析[J]. 植物学报, 2018, 53(4): 487-501.
	Guo S L, Zhang J, Qi J S, Yue R Q, Han X H, Yan S F, Lu C X, Fu X L, Chen N N, Ku L X, Tie S G. Analysis of meta-quantitative trait loci and their candidate genes related to leaf shape in maize[J]. Chinese Bulletin of Botany, 2018, 53(4): 487-501. (in Chinese with English abstract)
[14]	江培顺, 张焕欣, 吕香玲, 郝转芳, 李博, 李明顺, 王宏伟, 慈晓科, 张世煌. 玉米产量相关性状Meta-QTL及候选基因分析[J]. 作物学报, 2013, 39(6): 969-978.
	Jiang P S, Zhang H X, Lü X L, Hao Z F, Li B, Li M S, Wang H W, Ci X K, Zhang S H. Analysis of meta-QTL and candidate genes related to yield components in maize[J]. Acta Agronomica Sinica, 2013, 39(6): 969-978. (in Chinese)
[15]	Yin Z, Qi H, Chen Q, Zhang Z, Jiang H, Zhu R, Hu Z, Wu X, Li C, Zhang Y, Liu C, Hu G, Xin D, Qi Z. Soybean plant height QTL mapping and meta-analysis for mining candidate genes[J]. Plant Breeding, 2017, 136(5): 688-698.
[16]	Gong Q C, Yu H X, Mao X R, Qi H D, Shi Y, Xiang W, Chen Q S, Qi Z M. Meta-analysis of soybean amino acid QTLs and candidate gene mining[J]. Journal of Integrative Agriculture, 2018, 17(5): 1074-1084.
[17]	Courtois B, Ahmadi N, Khowaja F, Price A H, Rami J F, Frouin J, Hamelin C, Ruiz M. Rice root genetic architecture: Meta-analysis from a drought QTL database[J]. Rice, 2009, 2(2): 115-128.
[18]	Tian T, Chen L, Ai Y, He H. Selection of candidate genes conferring blast resistance and heat tolerance in rice through integration of meta-QTLs and RNA-seq[J]. Genes, 2022, 13(2): 224.
[19]	邱红梅, 厉志, 于妍, 高淑芹, 马晓萍, 郑宇宏, 孟凡凡, 侯云龙, 王跃强. 基于元分析的大豆含硫氨基酸相关基因挖掘与信息学分析[J]. 中国油料作物学报, 2015, 37(2): 141-147.
	Qiu H M, Li Z, Yu Y, Gao S Q, Ma X P, Zheng Y H, Meng F F, Hou Y L, Wang Y Q. Mining and analysis of genes related to sulfur-containing amino acids in soybean based on Meta-QTL[J]. Chinese Journal of Oil Crop Sciences, 2015, 37(2): 141-147. (in Chinese)
[20]	刘鑫, 甄善继, 王家军, 王洋. 大豆根长QTL的Meta分析及候选基因挖掘[J]. 大豆科学, 2023, 42(1): 32-40.
	Liu X, Zhen S J, Wang J J, Wang Y. Meta-analysis and candidate gene mining of soybean root length QTLs[J]. Soybean Science, 2023, 42(1): 32-40. (in Chinese with English abstract)
[21]	Darvasi A, Soller M. A simple method to calculate resolving power and confidence interval of QTL map location[J]. Behavior Genetics, 1997, 27(2): 125-132.
[22]	Guo B, Sleper D A, Lu P, Shannon J G, Nguyen H T, Arelli P R. QTLs associated with resistance to soybean cyst nematode in soybean meta-analysis of QTL locations: Retraction[J]. Crop Science, 2006, 46(1): 202.
[23]	Courtois B, Ahmadi N, Khowaja F, Price A H, Rami J F, Frouin J, Hamelin C, Ruiz M. Rice root genetic architecture: Meta-analysis from a drought QTL database[J]. Rice, 2009, 2(2): 115-128.
[24]	田甜, 陈丽娟, 何华勤. 基于Meta-QTL和RNA-seq的整合分析挖掘水稻抗稻瘟病候选基因[J]. 作物学报, 2022(6): 1372-1388.
	Tian T, Chen L J, He H Q. Identification of rice blast resistance candidate genes based on integrating Meta-QTL and RNA-seq analysis[J]. Acta Agronomica Sinica, 2022(6): 1372-1388. (in Chinese with English abstract)
[25]	Ashburner M, Ball C A, Blake J A, Botstein D, Butler H, Cherry J M, Davis A P, Dolinski K, Dwight S S, Eppig J T, Harris M A, Hill D P, Issel-Tarver L, Kasarskis A, Lewis S, Matese J C, Richardson J E, Ringwald M, Rubin G M, Sherlock G. Gene Ontology: Tool for the unification of biology[J]. Nature Genetics, 2000, 25(1): 25-29.
[26]	屈婷婷, 陈立艳, 章志宏, 胡中立, 李平, 朱立煌, 朱英国. 水稻籼粳交DH群体苗期耐冷性基因的分子标记定位[J]. 武汉植物学研究, 2003, 21(5): 385-389.
	Qu T T, Chen L Y, Zhang Z H, Hu Z L, Li P, Zhu L H, Zhu Y G. Molecular mapping of genes conferring cold tolerance at seedling stage using doubled haploid lines from an indica-Japonica cross in rice[J]. Journal of Wuhan Botanical Research, 2003, 21(5): 385-389. (in Chinese with English abstract)
[27]	胡莹, 王奕众. 水稻RIL群体苗期耐冷性QTL分析[J]. 武汉植物学研究, 2005, 23(3): 211-215.
	Hu Y, Wang Y Z. Mapping of QTL controlling seedling cold tolerance using recombinant inbred lines of rice (Oryza sativa L.)[J]. Journal of Wuhan Botanical Research, 2005, 23(3): 211-215. (in Chinese)
[28]	吴杏春, 王茵, 林文雄. 水稻苗期耐冷性状的QTL分析[J]. 中国生态农业学报, 2008, 16(4): 1067-1069.
	Wu X C, Wang Y, Lin W X. QTL mapping in controlling seedling cold tolerance in rice (Oryza sativa L.)[J]. Chinese Journal of Eco-Agriculture, 2008, 16(4): 1067-1069. (in Chinese)
[29]	刘晓, 巩迎军, 董彦君, 林冬枝. 一个水稻苗期耐冷性的主效QTL精细定位研究[J]. 中国农学通报, 2009, 25(22): 62-66.
	Liu X, Gong Y J, Dong Y J, Lin D Z. Study on fine mapping of a major QTL for cold tolerance at seedling stage of rice[J]. Chinese Agricultural Science Bulletin, 2009, 25(22): 62-66. (in Chinese with English abstract)
[30]	夏瑞祥, 肖宁, 洪义欢, 张超, 苏琰, 张小蒙, 陈建民. 东乡野生稻苗期耐冷性的QTL定位[J]. 中国农业科学, 2010, 43(3): 443-451.
	Xia R X, Xiao N, Hong Y H, Zhang C, Su Y, Zhang X M, Chen J M. QTLs mapping for cold tolerance at seedling stage in Dongxiang wild rice (Oryza rufipogon Griff.)[J]. Scientia Agricultura Sinica, 2010, 43(3): 443-451. (in Chinese with English abstract)
[31]	姜树坤, 张喜娟, 姜辉, 孙世臣, 洛育, 白良明, 徐正进, 张凤鸣. 水稻苗期抗冷QTL的检测[J]. 沈阳农业大学学报, 2011, 42(6): 654-657.
	Jiang S K, Zhang X J, Jiang H, Sun S C, Luo Y, Bai L M, Xu Z J, Zhang F M. Detection of QTLs for cold tolerance at seedling stage in rice[J]. Journal of Shenyang Agricultural University, 2011, 42(6): 654-657. (in Chinese)
[32]	Liu F, Xu W, Song Q, Tan L, Liu J, Zhu Z, Fu Y, Su Z, Sun C. Microarray-assisted fine-mapping of quantitative trait loci for cold tolerance in rice[J]. Molecular Plant, 2013, 6(3): 757-767.
[33]	Zhang S, Zheng J, Liu B, Peng S, Leung H, Zhao J, Wang X, Yang T, Huang Z. Identification of QTLs for cold tolerance at seedling stage in rice (Oryza sativa L.) using two distinct methods of cold treatment[J]. Euphytica, 2014, 195(1): 95-104.
[34]	Ranawake A L, Manangkil O E, Yoshida S, Ishii T, Mori N, Nakamura C. Mapping QTLs for cold tolerance at germination and the early seedling stage in rice (Oryza sativa L.)[J]. Biotechnology & Biotechnological Equipment, 2014, 28(6): 989-998.
[35]	Kim S M, Suh J P, Lee C K, Lee J H, Kim Y G, Jena K K. QTL mapping and development of candidate gene-derived DNA markers associated with seedling cold tolerance in rice (Oryza sativa L.)[J]. Molecular Genetics and Genomics, 2014, 289(3): 333-343.
[36]	Verma S K, Xalxo M S, Saxena R R, Verulkar S B. Identification of QTLs for cold tolerance at seedling stage in rice (Oryza sativa L.)[J]. Indian Journal of Genetics and Plant Breeding (the), 2014, 74(1): 86.
[37]	Liu W Q, Lu T T, Li Y C, Pan X W, Duan Y H, Min J, Fu X Q, Sheng X N, Xiao J Z, Liu S X, Tan J, Yao Y, Li X X. Mapping of quantitative trait loci for cold tolerance at the early seedling stage in landrace rice Xiang 743[J]. Euphytica, 2015, 201(3): 401-409.
[38]	Mao D, Yu L, Chen D, Li L, Zhu Y, Xiao Y, Zhang D, Chen C. Multiple cold resistance loci confer the high cold tolerance adaptation of Dongxiang wild rice (Oryza rufipogon) to its high-latitude habitat[J]. Theoretical and Applied Genetics, 2015, 128(7): 1359-1371.
[39]	彭强, 张大双, 吴健强, 王际凤, 黄培英, 朱速松. 水稻苗期耐冷性的QTL定位分析[J]. 贵州农业科学, 2015, 43(5): 11-13, 18.
	Peng Q, Zhang D S, Wu J Q, Wang J F, Huang P Y, Zhu S S. QTL analysis of cold-tolerance at seedling stage in rice[J]. Guizhou Agricultural Sciences, 2015, 43(5): 11-13, 18. (in Chinese with English abstract)
[40]	Luo X D, Zhao J, Dai L F, Zhang F T, Zhou Y, Wan Y, Xie J K. Linkage map construction and QTL mapping for cold tolerance in Oryza rufipogon Griff. at early seedling stage[J]. Journal of Integrative Agriculture, 2016, 15(12): 2703-2711.
[41]	Biswas P S, Khatun H, Das N, Sarker M M, Anisuzzaman M. Mapping and validation of QTLs for cold tolerance at seedling stage in rice from an indica cultivar Habiganj Boro VI (Hbj.BVI)[J]. 3 Biotech, 2017, 7(6): 359.
[42]	Yu S, Li M, Xiao Y, Huang D, Chen D. Mapping QTLs for cold tolerance at seedling stage using an Oryza sativa × O. rufipogon backcross inbred line population[J]. Czech Journal of Genetics and Plant Breeding, 2018, 54(2): 59-64.
[43]	吴爱婷, 宋佳谕, 胡涛, 刘思彤, 高继平, 黄丽湘, 高银隆, 赵明辉. 超级稻沈农265苗期耐冷性QTL定位[J]. 核农学报, 2018, 32(8): 1477-1482.
	Wu A T, Song J Y, Hu T, Liu S T, Gao J P, Huang L X, Gao Y L, Zhao M H. QTLs mapping for cold tolerance at seedling stage in super rice variety Shennong 265[J]. Journal of Nuclear Agricultural Sciences, 2018, 32(8): 1477-1482. (in Chinese)
[44]	Deng X, Gan L, Liu Y, Luo A, Jin L, Chen J, Tang R, Lei L, Tang J, Zhang J, Zhao Z. Locating QTLs controlling overwintering seedling rate in perennial glutinous rice 89-1 (Oryza sativa L.)[J]. Genes & Genomics, 2018, 40(12): 1351-1361.
[45]	Li L, Mao D. Deployment of cold tolerance loci from Oryza sativa ssp. japonica cv. ‘Nipponbare’ in a high-yielding Indica rice cultivar ‘93-11’[J]. Plant Breeding, 2018, 137(4): 553-560.
[46]	Das N, Alam N, Hossain K, Biswas P S. Mapping quantitative trait loci for cold tolerance in rice at seedling stage[J]. Bangladesh Journal of Botany, 2020, 48(4): 1021-1028.
[47]	王棋, 范淑秀, 郭江华, 陈兆赫, 梁银培, 刘振宇, 殷业超, 王嘉宇. 利用籼粳交RIL群体对水稻发芽期和苗期耐冷性的QTL分析[J]. 华北农学报, 2019, 34(1): 83-88.
	Wang Q, Fan S X, Guo J H, Chen Z H, Liang Y P, Liu Z Y, Yin Y C, Wang J Y. QTL analysis of cold tolerance at germination and seedling stages of rice[J]. Acta Agriculturae Boreali-Sinica, 2019, 34(1): 83-88. (in Chinese)
[48]	Liu H, Yang L, Xu S, Lü M J, Wang J, Wang H, Zheng H, Xin W, Liu J, Zou D. OsWRKY115 on qCT7 links to cold tolerance in rice[J]. Theoretical and Applied Genetics, 2022, 135(7): 2353-2367.
[49]	Guo Z, Yao J, Cheng Y, Zhang W, Xu Z, Li M, Huang J, Ma D, Zhao M. Identification of QTL under brassinosteroid-combined cold treatment at seedling stage in rice using genotyping-by-sequencing (GBS)[J]. Plants, 2022, 11(17): 2324.
[50]	Shi H, Zhang W, Cao H, Zhai L, Song Q, Xu J. Identification of candidate genes for cold tolerance at seedling stage by GWAS in rice (Oryza sativa L.)[J]. Biology, 2024, 13(10): 784.
[51]	杨传铭, 王立志, 张喜娟, 杨贤莉, 王洋洋, 侯本福, 崔士泽, 李青超, 刘凯, 马瑞, 冯延江, 来永才, 李红宇, 姜树坤. 基于高密度遗传图谱的粳稻苗期耐冷QTL分析[J]. 中国水稻科学, 2025, 39(1): 82-91.
	Yang C M, Wang L Z, Zhang X J, Yang X L, Wang Y Y, Hou B F, Cui S Z, Li Q C, Liu K, Ma R, Feng Y J, Lai Y C, Li H Y, Jiang S K. Analysis of QTL controlling cold tolerance at seedling stage by using a high-density SNP linkage map in Japonica rice[J]. Chinese Journal of Rice Science, 2025, 39(1): 82-91. (in Chinese with English abstract)
[52]	Singh G, Pradhan A K, Das Jyoti S, Harper C L, Elumalai P, Sanchez D L, Samonte S O P, Talukder S K. Deciphering the genomic regions associated with seedling cold tolerance traits in rice (Oryza sativa L.)[J]. Plant Stress, 2025, 15: 100707.
[53]	Islam M S, Ontoy J, Subudhi P K. Meta-analysis of quantitative trait loci associated with seedling-stage salt tolerance in rice (Oryza sativa L.)[J]. Plants, 2019, 8(2): 33.
[54]	Xiong D, Wang J, Wang R, Wang Y, Li Y, Sun G, Yao S. A point mutation in VIG1 boosts development and chilling tolerance in rice[J]. Nature Communications, 2024, 15(1): 8212.
[55]	Wu J, Liu H, Zhang Y, Zhang Y, Li D, Liu S, Lu S, Wei L, Hua J, Zou B. A major gene for chilling tolerance variation in Indica rice codes for a kinase OsCTK1 that phosphorylates multiple substrates under cold[J]. The New Phytologist, 2024, 242(5): 2077-2092.
[56]	Shi Y, Phan H, Liu Y, Cao S, Zhang Z, Chu C, Schläppi M R. Glycosyltransferase OsUGT90A1 helps protect the plasma membrane during chilling stress in rice[J]. Journal of Experimental Botany, 2020, 71(9): 2723-2739.
[57]	Guo X, Zhang D, Wang Z, Xu S, Batistič O, Steinhorst L, Li H, Weng Y, Ren D, Kudla J, Xu Y, Chong K. Cold-induced calreticulin OsCRT3 conformational changes promote OsCIPK7 binding and temperature sensing in rice[J]. The EMBO Journal, 2023, 42(1): e110518.
[58]	Byun M Y, Cui L H, Oh T K, Jung Y J, Lee A, Park K Y, Kang B G, Kim W T. Homologous U-box E3 ubiquitin ligases OsPUB2 and OsPUB3 are involved in the positive regulation of low temperature stress response in rice (Oryza sativa L.)[J]. Frontiers in Plant Science, 2017, 8: 16.
[59]	Khan M I R, Kumari S, Nazir F, Khanna R R, Gupta R, Chhillar H. Defensive role of plant hormones in advancing abiotic stress-resistant rice plants[J]. Rice Science, 2023, 30(1): 15-35.
[60]	Chen M, Presting G, Barbazuk W B, Goicoechea J L, Blackmon B, Fang G, Kim H, Frisch D, Yu Y, Sun S, Higingbottom S, Phimphilai J, Phimphilai D, Thurmond S, Gaudette B, Li P, Liu J, Hatfield J, Main D, Farrar K, Henderson C, Barnett L, Costa R, Williams B, Walser S, Atkins M, Hall C, Budiman M A, Tomkins J P, Luo M, Bancroft I, Salse J, Regad F, Mohapatra T, Singh N K, Tyagi A K, Soderlund C, Dean R A, Wing R A. An integrated physical and genetic map of the rice genome[J]. The Plant Cell, 2002, 14(3): 537-545.
[61]	Chaikam V, Karlson D T. Response and transcriptional regulation of rice SUMOylation system during development and stress conditions[J]. BMB Reports, 2010, 43(2): 103-109.
[62]	Miura K, Ohta M. SIZ1, a small ubiquitin-related modifier ligase, controls cold signaling through regulation of salicylic acid accumulation[J]. Journal of Plant Physiology, 2010, 167(7): 555-560.
[63]	Hossain M A, Cho J I, Han M, Ahn C H, Jeon J S, An G, Park P B. The ABRE-binding bZIP transcription factor OsABF2 is a positive regulator of abiotic stress and ABA signaling in rice[J]. Journal of Plant Physiology, 2010, 167(17): 1512-1520.
[64]	Liu X, Hu Q, Yan J, Sun K, Liang Y, Jia M, Meng X, Fang S, Wang Y, Jing Y, Liu G, Wu D, Chu C, Smith S M, Chu J, Wang Y, Li J, Wang B. ζ-carotene isomerase suppresses tillering in rice through the coordinated biosynthesis of strigolactone and abscisic acid[J]. Molecular Plant, 2020, 13(12): 1784-1801.

作图群体亲本 Mapping population parents	群体类型 Population type	群体大小 Number of population	作图方法 Mapping method	QTL 数目 Number of QTLs	参考文献 Reference
ZYQ8, JX17	DH	128	IM	4	[5]
M-202, IR50	RIL	191	IM	15	[6]
圭630, 02428	DH	81	CIM	3	[26]
Lemont, 特青	RIL	139	CIM	5	[27]
密阳23, 吉冷1号	F_2:3	200	IM	17	[7]
AAV002863, Zhenshan 97B	DH	193	IM	5	[8]
Dular, Lemont	RIL	123	CIM	5	[28]
Asominori, IR24	RIL	71	CIM	3	[9]
越光/Kasalath, 越光	BIL	182	CIM	4	[29]
DXWR, 南京11	BC, F_2:3	144	CIM	2	[30]
Nipponbare, Kasalath；Nipponbare/Kasalath//Nipponbare	BIL	98	CIM	3	[31]
Geumobyeo, IR66160-121-4-4-2	RIL	153	CIM	2	[10]
Xiushui 09, IR2061	RIL	240	ND	4	[11]
GC2, IL112	F_2:3	394	IM	7	[32]
Lijiangxintuanheigu, Sanhuangzhan-2	RIL	204	ND	15	[33]
HGKN, Hokuriku-142 or Yume-Toiro	RIL	162	IM	9	[34]
Jinbu, BR29	RIL	123	CIM	6	[35]
Milyang 23, Hapcheonaengmi 3	F₂	98	ND	4	[36]
Xiang 743, Katy	F_2:3	190	CIM, MIM	7	[37]
Xiang 743, Dular	F_2:3	181	IM, MIM	5	[37]
DXWR, XQZB	BIL	94	IM	15	[38]
IR24, Asominori	RIL	213	ICIM	3	[39]
Xieqingzao B, DXWR	BIL	229	CIM	19	[40]
BR1, Hbj.BVI	F_2:3	151	ICIM	6	[41]
XB, XB/DWR	BIL	202	IM, CIM, MIM	2	[42]
XB, XB/DWR 亚群	BIL	138	IM, CIM, MIM	3	[42]
SN265, 七山占	RIL	118	ICIM	2	[43]
SN265, IR30	RIL	218	ICIM	2	[43]
Gr89-1, Shuhui 527	RIL	286	IM	3	[44]
93-11, Nipponbare	F_2:3	114	CIM	7	[45]
93-11, NIL11	NIL	229	CIM	2	[45]
BR1, BR18	F_2:3	856	CIM, IM, SMA	5	[46]
泸恢 99, SN625	RIL	144	ICIM	1	[47]
DN422, KY131	F_2:3	2570	CIM	2	[48]
DXWR, SN625	BIL	140	ND	114	[49]
National germplasms	NG	1992	GWAS	9	[50]
丽江新团黑谷, 沈农265	RIL	144	ICIM	4	[51]
National germplasms	NG	204	GWAS	29	[52]

作图群体亲本 Mapping population parents	群体类型 Population type	群体大小 Number of population	作图方法 Mapping method	QTL 数目 Number of QTLs	参考文献 Reference
ZYQ8, JX17	DH	128	IM	4	[5]
M-202, IR50	RIL	191	IM	15	[6]
圭630, 02428	DH	81	CIM	3	[26]
Lemont, 特青	RIL	139	CIM	5	[27]
密阳23, 吉冷1号	F_2:3	200	IM	17	[7]
AAV002863, Zhenshan 97B	DH	193	IM	5	[8]
Dular, Lemont	RIL	123	CIM	5	[28]
Asominori, IR24	RIL	71	CIM	3	[9]
越光/Kasalath, 越光	BIL	182	CIM	4	[29]
DXWR, 南京11	BC, F_2:3	144	CIM	2	[30]
Nipponbare, Kasalath；Nipponbare/Kasalath//Nipponbare	BIL	98	CIM	3	[31]
Geumobyeo, IR66160-121-4-4-2	RIL	153	CIM	2	[10]
Xiushui 09, IR2061	RIL	240	ND	4	[11]
GC2, IL112	F_2:3	394	IM	7	[32]
Lijiangxintuanheigu, Sanhuangzhan-2	RIL	204	ND	15	[33]
HGKN, Hokuriku-142 or Yume-Toiro	RIL	162	IM	9	[34]
Jinbu, BR29	RIL	123	CIM	6	[35]
Milyang 23, Hapcheonaengmi 3	F₂	98	ND	4	[36]
Xiang 743, Katy	F_2:3	190	CIM, MIM	7	[37]
Xiang 743, Dular	F_2:3	181	IM, MIM	5	[37]
DXWR, XQZB	BIL	94	IM	15	[38]
IR24, Asominori	RIL	213	ICIM	3	[39]
Xieqingzao B, DXWR	BIL	229	CIM	19	[40]
BR1, Hbj.BVI	F_2:3	151	ICIM	6	[41]
XB, XB/DWR	BIL	202	IM, CIM, MIM	2	[42]
XB, XB/DWR 亚群	BIL	138	IM, CIM, MIM	3	[42]
SN265, 七山占	RIL	118	ICIM	2	[43]
SN265, IR30	RIL	218	ICIM	2	[43]
Gr89-1, Shuhui 527	RIL	286	IM	3	[44]
93-11, Nipponbare	F_2:3	114	CIM	7	[45]
93-11, NIL11	NIL	229	CIM	2	[45]
BR1, BR18	F_2:3	856	CIM, IM, SMA	5	[46]
泸恢 99, SN625	RIL	144	ICIM	1	[47]
DN422, KY131	F_2:3	2570	CIM	2	[48]
DXWR, SN625	BIL	140	ND	114	[49]
National germplasms	NG	1992	GWAS	9	[50]
丽江新团黑谷, 沈农265	RIL	144	ICIM	4	[51]
National germplasms	NG	204	GWAS	29	[52]

元QTL Meta-QTL	染色体 Chr.	侧翼标记 Flanking marker	物理区间 Physical interval (Mb)	元QTL位置 Meta-QTL location	置信区间 95% CI (Mb)	原始QTL数目 No. of original QTLs	基因数目 Gene number	已报道的耐冷基因 Published cold tolerance gene
Meta-QTL 1	1	S01_8430459−RM323	3.785−4.096	3.940	0.311	6	53	OsbZIP01(VIG1)
Meta-QTL 2	1	RM1−RM283	4.662−4.859	4.760	0.197	9	34
Meta-QTL 3	1	S01_12150755−S01_12275956	6.813−7.347	7.080	0.534	4	104	OsCTK1, OsP3B
Meta-QTL 4	1	Y5714L−RM10829	12.914−13.264	13.089	0.350	10	60
Meta-QTL 5	1	S01_27714994−S01_27766901	17.235−17.605	17.420	0.370	3	73
Meta-QTL 6	1	S01_28250887−S01_28381910	18.015−18.270	18.142	0.255	3	38
Meta-QTL 7	1	S01_40759127−C808	25.428−25.527	25.477	0.099	10	16
Meta-QTL 8	1	RM297−RM319	32.355−33.654	33.004	1.299	7	258	TCM1
Meta-QTL 9	1	RM8231−R1468C	38.735−38.953	38.844	0.218	9	49	OsCRT3
Meta-QTL 10	2	RG409a−RM423	3.573−3.829	3.701	0.256	5	60
Meta-QTL 11	2	S02_141987−S02_15359168	6.348−6.383	6.365	0.035	4	4
Meta-QTL 12	2	S02_18887339−S02_19405835	7.926−8.568	8.247	0.642	4	108
Meta-QTL 13	2	S02_23029608−S02_23147657	13.060−14.008	13.534	0.948	3	153
Meta-QTL 14	2	C424−S02_34742671	25.567−26.142	25.854	0.575	9	96	OsLMS
Meta-QTL 15	2	S02_35709093−R2ID2877	28.499−28.729	28.614	0.230	7	50
Meta-QTL 16	2	RM530−RM250	30.746−32.239	31.492	1.493	5	293	OsRING1
Meta-QTL 17	3	RM14586−S03_7188874	6.073−6.532	6.302	0.459	2	99
Meta-QTL 18	3	S03_10154153−S03_10484949	8.893−8.898	8.895	0.005	2	6
Meta-QTL 19	3	S03_11339312−CT339	9.486−9.621	9.553	0.135	4	25
Meta-QTL 20	3	S03_22803832−S03_24600250	19.107−20.001	19.556	0.899	3	152
Meta-QTL 21	3	R250−S03_31399395	25.189−25.436	25.312	0.247	3	48
Meta-QTL 22	3	R2856−G164	31.514−33.891	32.703	2.379	3	512	OsSAPK8, OsTCP8
Meta-QTL 23	3	R1927−RM227	33.885−34.655	34.270	0.770	5	166
Meta-QTL 24	4	S04_2035471−S04_2361227	3.5615−3.7105	3.636	0.149	7	22
Meta-QTL 25	4	S04_753684−S04_7920307	7.828−9.825	8.826	1.997	2	369
Meta-QTL 26	4	S04_17868488−S04_20190493	15.633−17.295	16.464	1.662	3	229	OsUGT90A1
Meta-QTL 27	4	S04_25345578−S04_30302637	21.377−24.730	23.053	3.353	2	671	OsV4
Meta-QTL 28	4	S04_30444673−RM1018	26.231−26.740	26.485	0.509	3	125
Meta-QTL 29	4	RM349−RM3648	32.793−32.900	32.846	0.107	2	20
Meta-QTL 30	4	S04_35487338−RM1113	33.869−34.065	33.967	0.196	4	49
Meta-QTL 31	5	S05_1622816−S05_2206645	0.687−1.626	1.156	0.939	3	187
Meta-QTL 32	5	S05_15157600−S05_16169826	10.909−12.182	11.545	1.273	2	206
Meta-QTL 33	5	S05_22950610−S05_23110060	14.654−15.233	14.943	0.579	2	101	OsWRKY45
Meta-QTL 34	5	S05_27988265−C1268	19.641−19.941	19.791	0.300	3	51
Meta-QTL 35	5	S05_28253886−RM305	20.424−20.96	20.692	0.536	5	106
Meta-QTL 36	5	S05_29195759−S05_29385239	21.591−22.247	21.919	0.656	4	119
Meta-QTL 37	5	S05_29385239−RM480	22.342−24.074	23.208	1.732	3	371	OsPUB2, OsWRKY70
Meta-QTL 38	6	S06_34346−R6ID0027	0.011−0.051	0.031	0.040	6	5
Meta-QTL 39	6	MRG3332−S06_76033	0.788−1.155	0.971	0.367	7	84
Meta-QTL 40	6	S06_76033−S06_86257	1.537−1.779	1.658	0.242	11	50	OsDREB1C, COLD6
Meta-QTL 41	6	RM587−RM3805	2.651−2.843	2.747	0.192	8	49
Meta-QTL 42	6	S06_2026942−S06_2573648	5.166−5.691	5.428	0.525	2	87
Meta-QTL 43	6	RM557−S06_6242039	7.367−8.225	7.796	0.858	3	143
Meta-QTL 44	6	S06_8551070−S06_9117287	10.944−11.184	11.064	0.240	9	40
Meta-QTL 45	6	S06_12025018−R6ID1693	15.176−16.863	16.019	1.687	7	268
Meta-QTL 46	6	S06_26319487−RM5371	25.263−25.311	25.287	0.048	12	11
Meta-QTL 47	7	S07_2206752−S07_2342190	1.543−1.878	1.710	0.335	4	48
Meta-QTL 48	7	RM428−RM481	2.643−2.873	2.758	0.230	4	35	OsTCP14
Meta-QTL 49	7	S07_29374392−RM432	18.112−18.679	18.395	0.567	6	101	ANIP1
Meta-QTL 50	7	RM182−RM10	21.721−22.013	21.867	0.292	8	40
Meta-QTL 51	7	R7ID2633−RM134	26.474−26.512	26.493	0.038	10	8
Meta-QTL 52	8	R8ID1243−S08_10035358	12.475−12.882	12.678	0.407	11	65
Meta-QTL 53	8	RZ323a−R8ID1537	13.958−15.344	14.651	1.386	4	216
Meta-QTL 54	8	RM404−S08_21108492	15.581−15.866	15.723	0.285	12	45
Meta-QTL 55	8	RM330A−S08_27371918	25.657−26.163	25.910	0.506	5	118
Meta-QTL 56	9	S09_2137067−S09_2195182	2.902−3.316	3.109	0.414	2	67
Meta-QTL 57	9	S09_2195182−S09_2547956	3.487−4.352	3.919	0.865	2	141
Meta-QTL 58	9	S09_5908433−S09_5989512	6.857−7.184	7.020	0.327	2	40
Meta-QTL 59	9	S09_11240451−S09_11542598	9.226−9.763	9.494	0.537	2	90
Meta-QTL 60	9	S09_15958987−S09_16117267	14.258−14.551	14.404	0.293	5	58	qCTS9
Meta-QTL 61	9	S09_16774761−RM434	15.114−15.556	15.335	0.442	7	74
Meta-QTL 62	9	S09_20394456−S09_20840172	20.145−20.190	20.167	0.045	3	11
Meta-QTL 63	11	S11_6640029−S11_6662625	4.353−4.591	4.472	0.238	7	35
Meta-QTL 64	11	R11M17−S11_9024140	6.139−6.533	6.336	0.394	7	69
Meta-QTL 65	11	RM536−S11_16884915	9.012−9.329	9.170	0.317	13	55
Meta-QTL 66	11	S11_16889698−R11ID1009	9.615−10.059	9.837	0.444	14	65
Meta-QTL 67	11	S11_22758863−RM21	17.137-19.312	18.224	2.175	6	322	OsICE1
Meta-QTL 68	11	S11_23793431−C1172	19.335−19.679	19.507	0.344	16	65
Meta-QTL 69	11	S11_23795247−S11_25462014	20.632−22.264	21.448	1.632	5	262	COG1, CTP1A58
Meta-QTL 70	11	S11_26184650−RG553c	23.884−24.421	24.152	0.537	6	91	OsRAD51A1
Meta-QTL 71	11	S11_27302936−RM1233	25.320−26.517	25.918	1.197	6	201
Meta-QTL 72	11	S11_27344371−S11_27818224	28.302−28.648	28.475	0.346	7	47
Meta-QTL 73	12	G24B−S12_3267494	0.292−1.087	0.689	0.795	3	190
Meta-QTL 74	12	R3375−S12_8957623	5.610−5.855	5.732	0.245	11	35	OsGSTZ1, OsGSTZ2
Meta-QTL 75	12	S12_13855860−R12ID1072	8.906−10.487	9.696	1.581	11	277
Meta-QTL 76	12	RM101−RM270	8.789−10.603	9.696	1.814	12	319
Meta-QTL 77	12	S12_18216503−S12_18487234	11.696−11.716	11.706	0.020	15	4
Meta-QTL 78	12	RM1337−S12_19944345	12.072−12.377	12.224	0.305	12	55
Meta-QTL 79	12	S12_20179243−S12_20499113	12.808−13.235	13.021	0.427	15	70
Meta-QTL 80	12	R12ID1349−RM179	13.737−14.287	14.012	0.550	13	68
Meta-QTL 81	12	S12_20643952−S12_20912019	16.114−16.475	16.294	0.361	8	55
Meta-QTL 82	12	C449−R12ID2187	21.550−21.646	21.598	0.096	10	20

元QTL Meta-QTL	染色体 Chr.	侧翼标记 Flanking marker	物理区间 Physical interval (Mb)	元QTL位置 Meta-QTL location	置信区间 95% CI (Mb)	原始QTL数目 No. of original QTLs	基因数目 Gene number	已报道的耐冷基因 Published cold tolerance gene
Meta-QTL 1	1	S01_8430459−RM323	3.785−4.096	3.940	0.311	6	53	OsbZIP01(VIG1)
Meta-QTL 2	1	RM1−RM283	4.662−4.859	4.760	0.197	9	34
Meta-QTL 3	1	S01_12150755−S01_12275956	6.813−7.347	7.080	0.534	4	104	OsCTK1, OsP3B
Meta-QTL 4	1	Y5714L−RM10829	12.914−13.264	13.089	0.350	10	60
Meta-QTL 5	1	S01_27714994−S01_27766901	17.235−17.605	17.420	0.370	3	73
Meta-QTL 6	1	S01_28250887−S01_28381910	18.015−18.270	18.142	0.255	3	38
Meta-QTL 7	1	S01_40759127−C808	25.428−25.527	25.477	0.099	10	16
Meta-QTL 8	1	RM297−RM319	32.355−33.654	33.004	1.299	7	258	TCM1
Meta-QTL 9	1	RM8231−R1468C	38.735−38.953	38.844	0.218	9	49	OsCRT3
Meta-QTL 10	2	RG409a−RM423	3.573−3.829	3.701	0.256	5	60
Meta-QTL 11	2	S02_141987−S02_15359168	6.348−6.383	6.365	0.035	4	4
Meta-QTL 12	2	S02_18887339−S02_19405835	7.926−8.568	8.247	0.642	4	108
Meta-QTL 13	2	S02_23029608−S02_23147657	13.060−14.008	13.534	0.948	3	153
Meta-QTL 14	2	C424−S02_34742671	25.567−26.142	25.854	0.575	9	96	OsLMS
Meta-QTL 15	2	S02_35709093−R2ID2877	28.499−28.729	28.614	0.230	7	50
Meta-QTL 16	2	RM530−RM250	30.746−32.239	31.492	1.493	5	293	OsRING1
Meta-QTL 17	3	RM14586−S03_7188874	6.073−6.532	6.302	0.459	2	99
Meta-QTL 18	3	S03_10154153−S03_10484949	8.893−8.898	8.895	0.005	2	6
Meta-QTL 19	3	S03_11339312−CT339	9.486−9.621	9.553	0.135	4	25
Meta-QTL 20	3	S03_22803832−S03_24600250	19.107−20.001	19.556	0.899	3	152
Meta-QTL 21	3	R250−S03_31399395	25.189−25.436	25.312	0.247	3	48
Meta-QTL 22	3	R2856−G164	31.514−33.891	32.703	2.379	3	512	OsSAPK8, OsTCP8
Meta-QTL 23	3	R1927−RM227	33.885−34.655	34.270	0.770	5	166
Meta-QTL 24	4	S04_2035471−S04_2361227	3.5615−3.7105	3.636	0.149	7	22
Meta-QTL 25	4	S04_753684−S04_7920307	7.828−9.825	8.826	1.997	2	369
Meta-QTL 26	4	S04_17868488−S04_20190493	15.633−17.295	16.464	1.662	3	229	OsUGT90A1
Meta-QTL 27	4	S04_25345578−S04_30302637	21.377−24.730	23.053	3.353	2	671	OsV4
Meta-QTL 28	4	S04_30444673−RM1018	26.231−26.740	26.485	0.509	3	125
Meta-QTL 29	4	RM349−RM3648	32.793−32.900	32.846	0.107	2	20
Meta-QTL 30	4	S04_35487338−RM1113	33.869−34.065	33.967	0.196	4	49
Meta-QTL 31	5	S05_1622816−S05_2206645	0.687−1.626	1.156	0.939	3	187
Meta-QTL 32	5	S05_15157600−S05_16169826	10.909−12.182	11.545	1.273	2	206
Meta-QTL 33	5	S05_22950610−S05_23110060	14.654−15.233	14.943	0.579	2	101	OsWRKY45
Meta-QTL 34	5	S05_27988265−C1268	19.641−19.941	19.791	0.300	3	51
Meta-QTL 35	5	S05_28253886−RM305	20.424−20.96	20.692	0.536	5	106
Meta-QTL 36	5	S05_29195759−S05_29385239	21.591−22.247	21.919	0.656	4	119
Meta-QTL 37	5	S05_29385239−RM480	22.342−24.074	23.208	1.732	3	371	OsPUB2, OsWRKY70
Meta-QTL 38	6	S06_34346−R6ID0027	0.011−0.051	0.031	0.040	6	5
Meta-QTL 39	6	MRG3332−S06_76033	0.788−1.155	0.971	0.367	7	84
Meta-QTL 40	6	S06_76033−S06_86257	1.537−1.779	1.658	0.242	11	50	OsDREB1C, COLD6
Meta-QTL 41	6	RM587−RM3805	2.651−2.843	2.747	0.192	8	49
Meta-QTL 42	6	S06_2026942−S06_2573648	5.166−5.691	5.428	0.525	2	87
Meta-QTL 43	6	RM557−S06_6242039	7.367−8.225	7.796	0.858	3	143
Meta-QTL 44	6	S06_8551070−S06_9117287	10.944−11.184	11.064	0.240	9	40
Meta-QTL 45	6	S06_12025018−R6ID1693	15.176−16.863	16.019	1.687	7	268
Meta-QTL 46	6	S06_26319487−RM5371	25.263−25.311	25.287	0.048	12	11
Meta-QTL 47	7	S07_2206752−S07_2342190	1.543−1.878	1.710	0.335	4	48
Meta-QTL 48	7	RM428−RM481	2.643−2.873	2.758	0.230	4	35	OsTCP14
Meta-QTL 49	7	S07_29374392−RM432	18.112−18.679	18.395	0.567	6	101	ANIP1
Meta-QTL 50	7	RM182−RM10	21.721−22.013	21.867	0.292	8	40
Meta-QTL 51	7	R7ID2633−RM134	26.474−26.512	26.493	0.038	10	8
Meta-QTL 52	8	R8ID1243−S08_10035358	12.475−12.882	12.678	0.407	11	65
Meta-QTL 53	8	RZ323a−R8ID1537	13.958−15.344	14.651	1.386	4	216
Meta-QTL 54	8	RM404−S08_21108492	15.581−15.866	15.723	0.285	12	45
Meta-QTL 55	8	RM330A−S08_27371918	25.657−26.163	25.910	0.506	5	118
Meta-QTL 56	9	S09_2137067−S09_2195182	2.902−3.316	3.109	0.414	2	67
Meta-QTL 57	9	S09_2195182−S09_2547956	3.487−4.352	3.919	0.865	2	141
Meta-QTL 58	9	S09_5908433−S09_5989512	6.857−7.184	7.020	0.327	2	40
Meta-QTL 59	9	S09_11240451−S09_11542598	9.226−9.763	9.494	0.537	2	90
Meta-QTL 60	9	S09_15958987−S09_16117267	14.258−14.551	14.404	0.293	5	58	qCTS9
Meta-QTL 61	9	S09_16774761−RM434	15.114−15.556	15.335	0.442	7	74
Meta-QTL 62	9	S09_20394456−S09_20840172	20.145−20.190	20.167	0.045	3	11
Meta-QTL 63	11	S11_6640029−S11_6662625	4.353−4.591	4.472	0.238	7	35
Meta-QTL 64	11	R11M17−S11_9024140	6.139−6.533	6.336	0.394	7	69
Meta-QTL 65	11	RM536−S11_16884915	9.012−9.329	9.170	0.317	13	55
Meta-QTL 66	11	S11_16889698−R11ID1009	9.615−10.059	9.837	0.444	14	65
Meta-QTL 67	11	S11_22758863−RM21	17.137-19.312	18.224	2.175	6	322	OsICE1
Meta-QTL 68	11	S11_23793431−C1172	19.335−19.679	19.507	0.344	16	65
Meta-QTL 69	11	S11_23795247−S11_25462014	20.632−22.264	21.448	1.632	5	262	COG1, CTP1A58
Meta-QTL 70	11	S11_26184650−RG553c	23.884−24.421	24.152	0.537	6	91	OsRAD51A1
Meta-QTL 71	11	S11_27302936−RM1233	25.320−26.517	25.918	1.197	6	201
Meta-QTL 72	11	S11_27344371−S11_27818224	28.302−28.648	28.475	0.346	7	47
Meta-QTL 73	12	G24B−S12_3267494	0.292−1.087	0.689	0.795	3	190
Meta-QTL 74	12	R3375−S12_8957623	5.610−5.855	5.732	0.245	11	35	OsGSTZ1, OsGSTZ2
Meta-QTL 75	12	S12_13855860−R12ID1072	8.906−10.487	9.696	1.581	11	277
Meta-QTL 76	12	RM101−RM270	8.789−10.603	9.696	1.814	12	319
Meta-QTL 77	12	S12_18216503−S12_18487234	11.696−11.716	11.706	0.020	15	4
Meta-QTL 78	12	RM1337−S12_19944345	12.072−12.377	12.224	0.305	12	55
Meta-QTL 79	12	S12_20179243−S12_20499113	12.808−13.235	13.021	0.427	15	70
Meta-QTL 80	12	R12ID1349−RM179	13.737−14.287	14.012	0.550	13	68
Meta-QTL 81	12	S12_20643952−S12_20912019	16.114−16.475	16.294	0.361	8	55
Meta-QTL 82	12	C449−R12ID2187	21.550−21.646	21.598	0.096	10	20

序号 Serial	染色体 Chr.	基因名称 Gene	已报道基因 Published tolerance gene	GO 注释 GO annotation	序号 Serial	染色体 Chr.	基因名称 Gene	已报道基因 Published tolerance gene	GO 注释 GO annotation
1	1	LOC_Os01g56200	OsNPR2; NH2	乙烯应答(GO:0009723)	23	4	LOC_Os04g40540	OsPIMT2	脱落酸应答(GO:0009737)
2	1	LOC_Os01g56330	FLR2; DRUS2	赤霉素生物合成调控(GO:0010371)	24	5	LOC_Os05g02500	OsMKP1; GSN1	细胞分裂素合成(GO:0009691)
3	1	LOC_Os01g66890	OsBTBZ1	脱落酸信号通路调控(GO:0009787)	25	5	LOC_Os05g03430	OsSIZ1; OsPHD29	脱落酸应答(GO:0009737)
4	2	LOC_Os02g50480	OHK5; OsHk6	细胞分裂素信号传导(GO:0009736)	26	5	LOC_Os05g34830	OsNAC52	脱落酸信号通路调控(GO:0009787)
5	2	LOC_Os02g50970	DSM1; OsMAPKKK6	脱落酸应答(GO:0009737)	27	5	LOC_Os05g37690	OsCOI1b	茉莉酸信号通路(GO:0009867
6	2	LOC_Os02g51750	OsANN1; OsANN2	茉莉酸信号通路调控(GO:2000022)	28	5	LOC_Os05g38150	OsP5CS; OsP5CS1	正调控脱落酸信号(GO:0009789)
7	2	LOC_Os02g52150	OsHSP24.1	脱落酸应答(GO:0009737)	29	5	LOC_Os05g39720	OsWRKY70	脱落酸信号通路调控(GO:0009787)
8	2	LOC_Os02g52250	OsSKIPa	脱落酸应答(GO:0009737)	30	5	LOC_Os05g41070	OsbZIP42; HBF1	脱落酸信号通路调控(GO:0009787)
9	3	LOC_Os03g55540	OsADR3	脱落酸信号通路调控(GO:0009787)	31	6	LOC_Os06g06050	D3; SOLS	独脚金内酯细胞应答(GO:1902348)
10	3	LOC_Os03g55600	OsSAPK8	脱落酸信号通路调控(GO:0009787)	32	6	LOC_Os06g10230	OsERECTA; OsER1	细胞分裂素分解(GO:0009823)
11	3	LOC_Os03g55800	OsAOS1	茉莉酸合成(GO:0009695)	33	6	LOC_Os06g10880	OsAREB1; OsbZIP46	生长素信号通路调控(GO:0010928)
12	3	LOC_Os03g58350	OsIAA14	生长素信号转导(GO:0009734)	34	6	LOC_Os06g14406	CHR720; OsSYD	水杨酸应答(GO:0009751)
13	3	LOC_Os03g58390	OsSIRP2	脱落酸应答(GO:0009737)	35	6	LOC_Os06g27760	OsMSRB1.1	脱落酸应答(GO:0009737)
14	3	LOC_Os03g59610	OsABA2; XanDH	脱落酸生物合成(GO:0009688)	36	6	LOC_Os06g29310	OsOTS1	脱落酸生物合成调控(GO:0010115)
15	3	LOC_Os03g60080	SNAC1; OsNAC9	脱落酸信号通路调控(GO:0009787)	37	7	LOC_Os07g04180	OsAAP1	细胞分裂素含量(TO:0002660)
16	4	LOC_Os04g35190	OsDRF1	脱落酸应答(GO:0009737)	38	7	LOC_Os07g30970	OsNDPK1	水杨酸应答(GO:0009751)
17	4	LOC_Os04g35210	Bph6	水杨酸信号通路调控(GO:2000031)	39	8	LOC_Os08g41190	OsMBTB32	脯氨酸含量(TO:0006002)
18	4	LOC_Os04g37619	OSZEP1; OsABA1	脱落酸生物合成(GO:0009688)	40	9	LOC_Os09g15240	OsZAS	独脚金内酯生物合成(GO:1901601)
19	4	LOC_Os04g37920	OsCRY1b; OsCCT1b	赤霉素分解代谢(GO:0045487)	41	11	LOC_Os11g08340	OsGH3-12	生长素信号传导(GO:0009734)
20	4	LOC_Os04g38950	TDD1; OASB1	生长素含量(TO:0002672)	42	11	LOC_Os11g42660	WED	水杨酸代谢调控(GO:0010337)
21	4	LOC_Os04g39150	OsMLP423	脱落酸信号通路调控(GO:0009787)	43	12	LOC_Os12g16720	OsSL; ELL1	水杨酸生物合成调控(GO:0080142)
22	4	LOC_Os04g40410	OsNAR2.2	赤霉素应答(GO:0009739)

Meta-QTL Analysis and Prediction of Candidate Genes for Cold Tolerance at Seedling Stage in Rice

水稻苗期耐冷性Meta-QTL分析及候选基因预测

RichHTML

PDF

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 9

References 64

Related Articles 15

Recommended Articles

Metrics

染色体Chromosome	SR	RC	RDW	RD	RRS	RN	WI	LC	RLI	LAIR	SDW	RL	CSH	SWW	Total
1	22	0	0	1	2	0	9	0	0	1	4	7	2	3	51
2	12	0	1	1	1	1	3	0	3	0	3	2	2	0	29
3	12	1	0	0	0	0	3	0	0	1	1	1	1	1	21
4	8	0	0	0	0	0	8	0	0	0	1	1	1	1	20
5	7	1	0	0	0	0	1	0	0	0	1	4	0	1	15
6	13	0	0	1	0	0	5	0	0	0	18	5	2	8	52
7	8	1	0	0	0	0	4	1	2	0	0	2	1	1	20
8	9	0	0	0	0	0	11	0	0	0	6	1	0	0	27
9	3	0	0	0	0	0	4	0	0	0	5	3	0	1	16
10	2	2	0	0	0	0	3	0	0	0	1	2	0	1	11
11	17	0	1	2	1	0	12	0	0	1	2	2	3	2	43
12	19	0	0	0	0	1	9	0	0	1	7	7	0	4	48
总计Total	132	5	2	5	4	2	72	1	5	4	49	37	12	23	353

序号 Serial	染色体 Chr.	基因 Gene	已报道基因 Published tolerance gene	基因名称 Gene name	序号 Serial	染色体 Chr.	基因 Gene	已报道基因 Published tolerance gene	基因名称 Gene name
1	1	LOC_Os01g09450			35	5	LOC_Os05g41070	OsbZIP42; HBF1	bZIP转录因子
2	1	LOC_Os01g57730			36	5	LOC_Os05g37690	OsCOI1b	F-box蛋白
3	2	LOC_Os02g51470			37	5	LOC_Os05g40230
4	2	LOC_Os02g51150			38	5	LOC_Os05g35290	OsPAL7	苯丙氨酸脱氨酶
5	2	LOC_Os02g14430	OsPrx30	第三类过氧化物酶	39	5	LOC_Os05g40420
6	2	LOC_Os02g47020			40	5	LOC_Os05g25640		细胞色素P450
7	2	LOC_Os02g14440			41	6	LOC_Os06g13720
8	2	LOC_Os02g07230	OsSPL42	卟胆原脱氨酶	42	6	LOC_Os06g06090	OsMAPK6; OsMPK6	丝裂原活化蛋白激酶
9	3	LOC_Os03g12350	ORR1	B型响应调节子	43	6	LOC_Os06g29110
10	3	LOC_Os03g58040			44	6	LOC_Os06g27850
11	3	LOC_Os03g55410			45	6	LOC_Os06g04070	OsAdc1	精氨酸脱羧酶
12	3	LOC_Os03g12030	CUT1L; WSL4	脂肪酸延长酶	46	6	LOC_Os06g10880	OsAREB1; OsbZIP46	bZIP转录因子
13	3	LOC_Os03g57200			47	6	LOC_Os06g14510
14	3	LOC_Os03g17070			48	6	LOC_Os06g29220
15	3	LOC_Os03g59610	OsABA2; XanDH	黄质醛脱氢酶	49	6	LOC_Os06g42130
16	3	LOC_Os03g55600	OsSAPK8	应激活化蛋白激酶	50	7	LOC_Os07g31270
17	3	LOC_Os03g58290			51	7	LOC_Os07g31300
18	3	LOC_Os03g55800	OsAOS1	丙二烯氧化物合酶	52	7	LOC_Os07g31380
19	3	LOC_Os03g58350	OsIAA14	Aux/IAA转录抑制因子	53	7	LOC_Os07g30970	OsNDPK1	核苷二磷酸激酶
20	3	LOC_Os03g11720			54	8	LOC_Os08g40680
21	3	LOC_Os03g59430			55	8	LOC_Os08g41100
22	4	LOC_Os04g36054	OsARF9	生长素应答因子	56	8	LOC_Os08g41090
23	4	LOC_Os04g35240	OsSAPK7	应激活化蛋白激酶	57	8	LOC_Os08g40690
24	4	LOC_Os04g36680			58	8	LOC_Os08g21590
25	4	LOC_Os04g40950	OsGapC2	甘油醛-3-磷酸脱氢酶	59	9	LOC_Os09g15850
26	4	LOC_Os04g38950	TDD1; OASB1	邻氨基苯甲酸合酶β亚基	60	9	LOC_Os09g15420
27	4	LOC_Os04g35520	OsAPx7	抗坏血酸过氧化物酶	61	9	LOC_Os09g15510
28	4	LOC_Os04g16680	OsSBPase	景天庚酮糖-1,7-二磷酸酶	62	9	LOC_Os09g15500
29	4	LOC_Os04g41620	OsChia2b; Cht4	几丁质酶	63	9	LOC_Os09g15860
30	4	LOC_Os04g39020	OsALDH10A5; OsBADH1	甜菜碱醛脱氢酶	64	9	LOC_Os09g15850
31	4	LOC_Os04g37619	ZEP1; OsABA1	玉米黄质环氧化酶	65	11	LOC_Os11g11430	OsIAA29	Aux/IAA蛋白
32	5	LOC_Os05g37170	OsTGA1; OsbZIP41	TGA转录因子	66	11	LOC_Os11g11410	OsIAA27	生长素应答因子
33	5	LOC_Os05g37470	OsAUX3; qGL5	生长素内向转运载体	67	11	LOC_Os11g08300	OsALDH3H2	水稻乙醛脱氢酶
34	5	LOC_Os05g38170			68	12	LOC_Os12g17600	OsRBCS2	核酮糖-1,5-二磷酸羧化酶/加氧酶小亚基

[1]	CHEN Chunxiao, FU Linli, ZHANG Wei, BU Qingyun, TIAN Xiaojie. Research Progress on the Functions of Rice MAPK Family Genes [J]. Chinese Journal OF Rice Science, 2026, 40(4): 425-435.
[2]	FU Yao, LI Na, XU Jingru, QIN Yiyan, CHENG Xiaoran, SUN Haofeng, ZHANG Qi, CUI Zhibo, YANG Xinyu, ZHAO Minghui. Function Study of OsST2 in Regulating Salt Tolerance in Rice Seedlings [J]. Chinese Journal OF Rice Science, 2026, 40(4): 436-446.
[3]	ZHU Jun, YANG Yanming, YANG Zhongnan. Mutagenesis and Creation of Photoperiod/Thermo-sensitive Genic Male Sterile Lines in Rice [J]. Chinese Journal OF Rice Science, 2026, 40(4): 460-468.
[4]	LIAO Ping, LIU Ruotong, MENG Yi, WENG Wenan, DU Hanmeng, LI Jun, GAO Hui, ZHANG Hongcheng. Effects of One-time Basal Application of Controlled-release Blended Fertilizer on Rice Yield and Lodging-related Traits [J]. Chinese Journal OF Rice Science, 2026, 40(4): 469-475.
[5]	CHEN Chuanyan, SONG Zhiwen, LI Yuxiang, HAO Quanyou, ZHU Lan. Effects of Fe-Mg Nano-priming on Germination of Rice Seeds and Seedling Growth Under Salt Stress [J]. Chinese Journal OF Rice Science, 2026, 40(4): 476-486.
[6]	ZHONG Xiaoyuan, WANG Zhong, CHEN Lei, ZHANG Xiaoli, HUANG Yan, ZHU Defeng, WANG Yaliang, QIN Yong, GAO Guoqing, ZHANG Longkui, TANG Maoyan, LIANG Tianfeng. Effects of Precision Drill Sowing on Transplanting Quality, Dry Matter Production, and Yield of Machine-transplanted Rice in Guangxi Zhuang Autonomous Region [J]. Chinese Journal OF Rice Science, 2026, 40(4): 487-501.
[7]	MA Yihu, ZHOU Cui, ZHU Lianfeng, YU Shanhong. Effects of Key Cultivation Measures on Grain Yield Formation, Quality and Growth Characteristics of High-quality Super Rice Huazheyou 261 [J]. Chinese Journal OF Rice Science, 2026, 40(4): 502-518.
[8]	WANG Chaorui, ZHANG Nan, RU Yan, YAN Yu, MENG Qinghao, WEN Ya, ZHANG Ying, XIAO Zhilin, ZHANG Hao. Effects of Alternate Wetting and Moderate Soil Drying Irrigation and Straw Returning Methods on Rice Yield and Greenhouse Gas Emissions [J]. Chinese Journal OF Rice Science, 2026, 40(4): 531-547.
[9]	LIANG Jinxiong, FENG Yanyi, XIAO Maohua, WANG Faan, SHEN Cheng, XU Wenxiang, MENG Weiguo. Design and Validation of an Assisted Steering System for Wheeled Tractor Path Tracking in Field Operations [J]. Chinese Journal OF Rice Science, 2026, 40(4): 548-559.
[10]	LIU Qing, GU Qing, ZHU Yihang, LOU Weidong, HUANG Fudeng, ZHU Ying, ZHANG Xiaobin. Prediction of Rice Heading Date Based on Panicle Detection and Machine Learning [J]. Chinese Journal OF Rice Science, 2026, 40(4): 560-568.
[11]	LIU Dibin, CHEN Xiongfei, FANG Peng, YU Jiajia, XIAO Liping, LIU Muhua, ZENG Bohan, CHEN Chenchen. Design and Experiment of a Direct Seeding Machine with Synchronous Mulching of Powdery Organic Materials [J]. Chinese Journal OF Rice Science, 2026, 40(3): 414-424.
[12]	JIA Meijie, CHEN Haotian, ZHONG Xiaohan, WANG Weilu, ZHANG Weiyang. Formation Mechanisms and Functions of Plant Rhizosheath and Its Application in Rice Production [J]. Chinese Journal OF Rice Science, 2026, 40(3): 292-301.
[13]	YI Haokun, LUO Yanmu, HUANG Min, DU Hewei, LI Manfei. Identification and Expression Analysis of the Rice Lateral Root Development Mutant lrp1 [J]. Chinese Journal OF Rice Science, 2026, 40(3): 302-311.
[14]	XU Yang, WANG Fangquan, LI Wenqi, TAO Yajun, FAN Fangjun, CHEN Zhihui, JIANG Yanjie, ZHU Jianping, LI Xia, YANG Jie. Gene Mapping and Transcriptome Analysis of a Green-revertible Yellow Leaf Mutant 818-6-8 in Rice [J]. Chinese Journal OF Rice Science, 2026, 40(3): 327-340.
[15]	WANG Zhaojun, HE Yuxuan, LIU Junrong, XU Qun, ZHANG Mengchen, WANG Shan, SUN Yanfei, WEI Xinghua, YANG Yaolong, GUO Xiaohong, FENG Yue. QTL Mapping and Analysis of Tiller Angle Based on High Density Genetic Map in Rice [J]. Chinese Journal OF Rice Science, 2026, 40(3): 341-350.