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 Yangyang^{1, 2}, YANG Chuanming^1,
2, ZHANG Xijuan^{2, 4}, YANG Xianli^{2, 4}, WANG Lizhi^2,
4, CUI Shize^{2, 4}, XU Xinkai^{1, 2}, LI Hongyu^{1, *}, JIANG Shukun^{2, 3, 4, *}

¹Agricultural College, Heilongjiang Bayi Agricultural University, Daqing 163319, China; ²Crop 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; ³Qiqihar 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; ⁴Northeast 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.

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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

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