小麦苗期耐热性全基因组关联分析

doi:10.3864/j.issn.0578-1752.2025.09.001

Abstract

Abstract:

【Objective】 Wheat is a cornerstone of global food security, with its production being pivotal in both China and the international community. With global climate change, the threat of high temperature has become increasingly prominent, posing a significant challenge to wheat cultivation. The strategic identification and selection of heat-tolerant germplasm, coupled with the exploration of genes associated with heat resistance, are crucial steps. These efforts are essential for broadening the genetic diversity of heat tolerance in wheat within China, providing prerequisites for breeding heat-tolerant wheat varieties and ultimately contributing to the safeguarding of our nation’s food security in the face of a warming climate. 【Method】 In this study, a natural population of 331 wheat accessions was utilized, and artificial climate chambers were employed to simulate high temperatures conditions. The heat tolerance of wheat seedlings was assessed by monitoring their survival rate under various durations of treatment, using heat resistance grade as the evaluative metric. Meanwhile, a genome-wide association study (GWAS) was conducted using the 55K SNP chip to identify genetic loci associated with heat tolerance. Expression data from multiple tissues, including roots, leaves under heat stress were analyzed, leading to the selection of genes related to heat tolerance. Subsequently, qPCR validation of candidate genes was performed using the extremely heat-tolerant accession Xinong 889 and the heat-sensitive accession Chinese Spring (CS) as materials. 【Result】 Under high-temperature stress, significant variations in survival rates were observed among different wheat accessions. The extremely heat-tolerant, moderately heat-tolerant, moderately heat-sensitive, and extremely heat-sensitive germplasm accounted for 110, 104, 110, and 7, respectively, representing 33.23%, 31.42%, 33.23%, and 2.12% of the total. Heat-tolerant germplasms, including Xinong 889, Zhengmai 7698, Zhongmai 895, Zhoumai 18, and Fengchan 3, were identified. Through GWAS, a total of 293 SNP loci significantly associated with the 12-hour survival rates (SR) and heat resistance grades (HRG) were detected, with the phenotypic variation explained ranging from 4.40% to 12.46%. Among these, 200 loci were related to the 12-hour survival rates, and 257 were related to the heat resistance grades, with 164 loci identified as the same heat-related loci. Based on significantly associated SNP markers, 313 heat-related genes were predicted. According to gene annotation information and expression data under heat stress, 23 heat tolerance candidates were selected, and after qPCR validation of differentially expressed candidate’s genes, 20 key heat tolerance candidate genes were identified. 【Conclusion】 At the seedling stage, 331 wheat germplasms were identified for heat tolerance. A rapid method was developed for determining the survival rate of wheat seedlings subjected to treatments of varying durations at 45 ℃ to assess their heat tolerance In total, 38 heat-tolerant germplasms and 293 loci significantly associated with seedling heat tolerance were screened. Also, TraesCS1A02G355900, TraesCS1A02G389500, TraesCS5A02G550700, TraesCS5D02G557100, TraesCS6D02G402500 and TraesCS7A02G232500 represented as candidate genes were filtered out.

Key words: wheat, heat stress, 55K SNP array, genome-wide association analysis, candidate genes

LI YunLi, DIAO DengChao, LIU YaRui, SUN YuChen, MENG XiangYu, WU ChenFang, WANG Yu, WU JianHui, LI ChunLian, ZENG QingDong, HAN DeJun, ZHENG WeiJun. Genome-Wide Association Study of Heat Tolerance at Seedling Stage in A Wheat Natural Population[J].Scientia Agricultura Sinica, 2025, 58(9): 1663-1683.

Figures/Tables 10

Table 1

Table 2

Fig. 1

Fig. 2

Fig. 3

Fig. 4

Table 3

SNP loci significantly associated with heat tolerance index at seedling stage and their phenotypic variation explained (PVE)"

模型 Model	性状 Character	标记 Marker	染色体 Chromosome	位置 Position (bp)	P值 P value	表型变异解释率 PVE (%)
GLM	SR/HRG	Affx-110203639	1	49968001	1.13E-05	5.67
GLM	SR/HRG	Affx-110259327	1	50496236	1.64E-05	5.46
GLM	HRG	Affx-109674237	1	538774197	9.91E-05	4.48
GLM	SR/HRG	Affx-110640791	1	557461051	1.16E-05	5.66
GLM	SR/HRG	Affx-88398227	1	557559230	8.36E-07	7.09
GLM/MLM	SR/HRG	Affx-109638477	1	558084863	9.74E-07	7.00
GLM/MLM	SR/HRG	Affx-109123802	1	568519872	1.27E-07	8.10
GLM	SR/HRG	Affx-109894023	1	568536246	2.11E-06	6.58
GLM	SR/HRG	Affx-110933596	2	363956701	4.45E-05	4.92
GLM	SR/HRG	Affx-109481111	2	364490098	3.89E-05	4.99
GLM/MLM	SR/HRG	Affx-109680038	2	415260451	5.56E-09	9.78
GLM	SR/HRG	Affx-109296086	2	687299508	5.20E-06	6.09
GLM	SR/HRG	Affx-109074941	2	687414153	9.70E-07	7.00
GLM	HRG	Affx-111756085	2	687563841	8.81E-05	4.55
MLM	SR/HRG	Affx-92851507	3	478121127	5.26E-05	4.81
GLM	HRG	Affx-110533812	4	30823301	5.25E-05	4.83
GLM	HRG	Affx-110656171	4	30873784	7.33E-05	4.65
GLM	HRG	Affx-111407436	7	669182809	8.96E-06	5.80
GLM	HRG	Affx-88482618	7	669567157	2.17E-05	5.31
GLM	SR/HRG	Affx-108908406	7	715655099	1.92E-07	7.88
GLM	HRG	Affx-110877304	9	596092037	3.82E-06	6.26
GLM	HRG	Affx-109610822	9	596160889	1.86E-05	5.40
GLM	HRG	Affx-92882408	9	596667885	9.79E-05	4.49
GLM	HRG	Affx-109992803	9	596719240	4.31E-05	4.94
GLM	HRG	Affx-109248342	9	596783243	1.37E-05	5.56
GLM	HRG	Affx-110040862	9	596918477	8.43E-05	4.57
GLM	HRG	Affx-111157176	9	596981313	6.53E-05	4.71
GLM	HRG	Affx-109233700	9	596997315	9.40E-05	4.51
MLM	SR/HRG	Affx-109675350	10	177137946	3.69E-06	6.21
MLM	SR/HRG	Affx-109262328	10	350961409	1.17E-06	6.83
GLM	SR/HRG	Affx-108903932	13	70663254	3.60E-05	5.04
GLM	SR/HRG	Affx-111642655	13	71232276	2.26E-05	5.29
GLM	HRG	Affx-109362879	13	704336151	6.75E-05	4.69
GLM	SR/HRG	Affx-111121454	13	706549941	1.22E-05	5.63
MLM	SR/HRG	Affx-111502569	14	557349764	3.77E-05	5.00
GLM	HRG	Affx-109166219	15	542651449	3.77E-05	5.01
GLM	HRG	Affx-111824230	15	543266757	7.22E-05	4.66
GLM/MLM	HRG	Affx-88453586	15	543509336	1.76E-06	6.68
GLM	HRG	Affx-88405117	15	559746041	1.16E-04	4.40
MLM	SR/HRG	Affx-92741886	15	50782762	2.01E-05	5.34
MLM	SR/HRG	Affx-110196154	15	547839798	1.25E-05	5.57
MLM	SR/HRG	Affx-108863028	17	140466504	2.53E-05	5.19
GLM	HRG	Affx-88610450	18	466894251	3.25E-06	6.35
GLM	SR/HRG	Affx-88552720	18	472303256	6.75E-06	5.95
GLM	HRG	Affx-111744400	18	472304296	3.50E-05	5.05
GLM	SR/HRG	Affx-110231695	19	92790790	1.21E-05	5.63
GLM	SR/HRG	Affx-109123340	19	93120026	2.63E-05	5.21
GLM	SR/HRG	Affx-109154771	19	136533979	2.07E-05	5.34
GLM	SR/HRG	Affx-110241168	19	136761050	6.22E-06	5.99
GLM	SR/HRG	Affx-111653438	19	155162964	3.76E-05	5.01
GLM	SR/HRG	Affx-109191237	19	156264119	1.36E-05	5.57
GLM	SR/HRG	Affx-111167533	19	168994686	3.15E-05	5.11
GLM	SR/HRG	Affx-88778846	19	171435266	1.72E-05	5.44
GLM/MLM	SR/HRG	Affx-110244104	19	452295538	1.04E-10	11.87
GLM/MLM	SR/HRG	Affx-110433752	19	452307903	3.40E-11	12.46
MLM	SR/HRG	Affx-111880833	19	202738729	1.69E-05	5.41
GLM/MLM	SR/HRG	Affx-108977126	20	135773041	1.55E-07	8.00
GLM/MLM	SR/HRG	Affx-110431431	20	137367874	2.37E-07	7.77
GLM	SR/HRG	Affx-111742284	20	726432033	7.66E-07	7.13
GLM	SR/HRG	Affx-109626634	20	726567819	2.72E-07	7.69
GLM	HRG	Affx-111473128	21	57857093	9.77E-05	4.49
GLM	SR/HRG	Affx-108998170	21	89304658	2.30E-05	5.28
GLM	HRG	Affx-111304820	21	89471033	6.10E-05	4.75
GLM	HRG	Affx-111880319	21	89530482	9.05E-05	4.53
GLM	SR/HRG	Affx-110923201	21	89532556	2.19E-05	5.31
GLM	SR/HRG	Affx-109041698	21	89556144	1.76E-07	7.93
GLM	SR/HRG	Affx-111854248	21	89598649	8.63E-07	7.07
GLM	SR/HRG	Affx-111809041	21	90634443	3.72E-05	5.02

Table 3

Fig. 5

Table 4

Prediction and annotation of the candidate gene underlying heat tolerance"

候选基因 Candidate genes	染色体位置 Chromosomal location (bp)	基因注释或编码蛋白 Gene annotation or coding proteins
TraesCS1A02G355900	Chr.1A:539279131-539279556(-)	核转录因子Y组分C3 Nuclear transcription factor Y subunit C3
TraesCS1A02G356100	Chr.1A:539323095-539324401(+)	过氧化物酶1 Peroxidase 1
TraesCS1A02G387700	Chr.1A:556297389-556306081(-)	26S蛋白酶体非ATP酶调节亚基5 26S proteasome non-ATPase regulatory subunit 5
TraesCS1A02G389500	Chr.1A:557487151-557491334(+)	蛋白NINJA同源物1 Protein NINJA homolog 1
TraesCS1A02G391600	Chr.1A:558505998-558517659(-)	高尔基体候选蛋白5 Golgin candidate 5
TraesCS1A02G391900	Chr.1A:558550095-558553987(+)	类金属核蛋白PRN Pirin-like protein
TraesCS1B02G202800	Chr.1B:364418491-364420737(+)	UPF0496蛋白4 UPF0496 protein 4
TraesCS1D02G426000	Chr.1D:479494708-479499893(-)	糖转运蛋白ERDL6 Sugar transporter ERD6-like 6
TraesCS5A02G065400	Chr.5A:70676153-70676518(-)	乙烯响应转录因子ERF098 Ethylene-responsive transcription factor ERF098
TraesCS5A02G550700	Chr.5A:704338188-704339287(+)	热激转录因子HSF-C2a Heat stress transcription factor C-2a
TraesCS5A02G554100	Chr.5A:706235563-706237619(+)	重金属异戊二烯化植物蛋白39 Heavy metal-associated isoprenylated plant protein 39
TraesCS5B02G380400	Chr.5B:558341804-558347101(-)	丝氨酸/苏氨酸蛋白激酶STY13 Serine/threonine-protein kinase STY13
TraesCS5D02G055400	Chr.5D:52053749-52059633(+)	DnaJ同源超家族C成员14 DnaJ homolog subfamily C member 14
TraesCS5D02G557600	Chr.5D:559921945-559927074(-)	抗病蛋白RGA5 Disease resistance protein RGA5
TraesCS5D02G558500	Chr.5D:560226208-560228561(-)	泛素结合酶E2-23kDa Ubiquitin-conjugating enzyme E2-23 kDa
TraesCS5D02G557000	Chr.5D:559833743-559834390(+)	富含羟脯氨酸的糖蛋白Hydroxyproline-rich glycoprotein
TraesCS5D02G557100	Chr.5D:559856525-559861088(-)	核因子Y，推定的Nuclear factor Y, putative
TraesCS6D02G397000	Chr.6D:469205255-469207520(+)	转录因子TCP7 Transcription factor TCP7
TraesCS6D02G402500	Chr.6D:470902211-470908141(-)	热休克蛋白HSP70 Heat shock cognate 70 kDa protein
TraesCS7A02G232500	Chr.7A:203695192-203697934(+)	热休克蛋白26.2 kDa，线粒体26.2 kDa heat shock protein, mitochondrial
TraesCS7D02G139800	Chr.7D:89475764-89478415(-)	BSD结构域蛋白BSD domain containing protein
TraesCS7D02G140200	Chr.7D:89598936-89605640(-)	推定的网格组装蛋白Putative clathrin assembly protein
TraesCS7D02G142300	Chr.7D:90628658-90650108(+)	可待因O-甲基化酶Codeine O-demethylase

Table 4

Fig. 6

References 49

[1]	WEISS E, ZOHARY D. The neolithic southwest asian founder crops: Their biology and archaeobotany. Current Anthropology, 2011, 52(S4): S237-S254.
[2]	王一杰, 辛岭, 胡志全, 安晓宁. 我国小麦生产、消费和贸易的现状分析. 中国农业资源与区划, 2018, 39(5): 36-45.
	WANG Y J, XIN L, HU Z Q, AN X N. Current situation of production, consumption and trade of wheat in China. Chinese Journal of Agricultural Resources and Regional Planning, 2018, 39(5): 36-45. (in Chinese)
[3]	MAULANA F, AYALEW H, ANDERSON J D, KUMSSA T T, HUANG W Q, MA X F. Genome-wide association mapping of seedling heat tolerance in winter wheat. Frontiers in Plant Science, 2018, 9: 1272. doi: 10.3389/fpls.2018.01272 pmid: 30233617
[4]	KHAN A, AHMAD M, SHAH M K N, AHMED M. Performance of wheat genotypes for Morpho-physiological traits using multivariate analysis under terminal heat stress. Pakistan Journal of Botany, 2020, 52(6): 1981-1988.
[5]	刘振山. 小麦苗期干旱、高温和旱热共胁迫转录表达谱及ABD部分同源基因表达分化分析[D]. 北京: 中国农业大学, 2015.
	LIU Z S. Transcriptional expression profile of drought, high temperature and drought-heat co-stress in wheat seedling stage and analysis of expression and differentiation of ABD homologous genes[D]. Beijing: China Agricultural University, 2015. (in Chinese)
[6]	LU L, LIU H, WU Y, YAN G J. Wheat genotypes tolerant to heat at seedling stage tend to be also tolerant at adult stage: The possibility of early selection for heat tolerance breeding. The Crop Journal, 2022, 10(4): 1006-1013.
[7]	李鹏程, 汪军成, 姚立蓉, 司二静, 杨轲, 孟亚雄, 马小乐, 李葆春, 尚勋武, 王化俊. 全基因组关联分析在小麦育种研究中的应用. 植物生理学报, 2023, 59(3): 465-480.
	LI P C, WANG J C, YAO L R, SI E J, YANG K, MENG Y X, MA X L, LI B C, SHANG X W, WANG H J. Application of genome-wide association studies in wheat breeding. Plant Physiology Journal, 2023, 59(3): 465-480. (in Chinese)
[8]	张颖, 石婷瑞, 曹瑞, 潘文秋, 宋卫宁, 王利, 聂小军. ICARDA引进-小麦苗期抗旱性的全基因组关联分析. 中国农业科学, 2024, 57(9): 1658-1681. doi: 10.3864/j.issn.0578-1752.2024.09.004.
	ZHANG Y, SHI T R, CAO R, PAN W Q, SONG W N, WANG L, NIE X J. Genome-wide association study of drought tolerance at seedling stage in ICARDA-introduced wheat. Scientia Agricultura Sinica, 2024, 57(9): 1658-1681. doi: 10.3864/j.issn.0578-1752.2024.09.004. (in Chinese)
[9]	魏昭然. 水稻苗期高温关键候选位点鉴定[D]. 泰安: 山东农业大学, 2020.
	WEI Z R. Identification of key candidate sites for high temperature in rice seedling stage[D]. Tai’an: Shandong Agriculture University, 2020. (in Chinese)
[10]	WEI Z R, YUAN Q L, LIN H, LI X X, ZHANG C, GAO H S, ZHANG B, HE H Y, LIU T J, JIE Z, GAO X, SHI S D, WANG B, GAO Z Y, KONG L R, QIAN Q, SHANG L G. Linkage analysis, GWAS transcriptome analysis to identify candidate genes for rice seedlings in response to high temperature stress. BMC Plant Biology, 2021, 21(1): 85.
[11]	LI P P, JIANG J, ZHANG G G, MIAO S Y, LU J B, QIAN Y K, ZHAO X Q, WANG W S, QIU X J, ZHANG F, XU J L. Integrating GWAS and transcriptomics to identify candidate genes conferring heat tolerance in rice. Frontiers in Plant Science, 2023, 13: 1102938.
[12]	许静. 玉米结实性耐热基因ZmHT1的功能分析[D]. 郑州: 河南农业大学, 2022.
	XU J. Functional analysis of the heat tolerant gene ZmHT1 related to seed setting in maize[D]. Zhengzhou: Henan Agriculture University, 2022. (in Chinese)
[13]	胡俊杰. 玉米耐热性评价体系的建立和应用[D]. 武汉: 华中农业大学, 2022.
	HU J J. Establishment and application of maize heat tolerance evaluation system[D]. Wuhan: Huazhong Agricultural University, 2022. (in Chinese)
[14]	CHOPRA R, BUROW G, BURKE J J, GLADMAN N, XIN Z G. Genome-wide association analysis of seedling traits in diverse Sorghum germplasm under thermal stress. BMC Plant Biology, 2017, 17(1): 12.
[15]	FU C, ZHOU Y, LIU A K, CHEN R, YIN L, LI C, MAO H L. Genome-wide association study for seedling heat tolerance under two temperature conditions in bread wheat (Triticum aestivum L.). BMC Plant Biology, 2024, 24(1): 430.
[16]	TRUONG H A, JEONG C Y, LEE W J, LEE B C, CHUNG N, KANG C S, CHEONG Y K, HONG S W, LEE H. Evaluation of a rapid method for screening heat stress tolerance using three Korean wheat (Triticum aestivum L.) cultivars. Journal of Agricultural and Food Chemistry, 2017, 65(28): 5589-5597.
[17]	ALEXANDER D H, NOVEMBRE J, LANGE K. Fast model-based estimation of ancestry in unrelated individuals. Genome Research, 2009, 19(9): 1655-1664. doi: 10.1101/gr.094052.109 pmid: 19648217
[18]	ZHANG C, DONG S S, XU J Y, HE W M, YANG T L. PopLDdecay: A fast and effective tool for linkage disequilibrium decay analysis based on variant call format files. Bioinformatics, 2019, 35(10): 1786-1788. doi: 10.1093/bioinformatics/bty875 pmid: 30321304
[19]	WANG J B, ZHANG Z W. GAPIT version 3: Boosting power and accuracy for genomic association and prediction. Genomics, Proteomics & Bioinformatics, 2021, 19(4): 629-640.
[20]	王小波, 关攀锋, 辛明明, 汪永法, 陈希勇, 赵爱菊, 刘曼双, 李红霞, 张明义, 逯腊虎, 魏亦勤, 刘旺清, 张金波, 倪中福, 姚颖垠, 胡兆荣, 彭惠茹, 孙其信. 小麦种质资源耐热性评价. 中国农业科学, 2019, 52(23): 4191-4200. doi: 10.3864/j.issn.0578-1752.2019.23.001.
	WANG X B, GUAN P F, XIN M M, WANG Y F, CHEN X Y, ZHAO A J, LIU M S, LI H X, ZHANG M Y, LU L H, WEI Y Q, LIU W Q, ZHANG J B, NI Z F, YAO Y Y, HU Z R, PENG H R, SUN Q X. Evaluation of heat tolerance in wheat germplasm resources. Scientia Agricultura Sinica, 2019, 52(23): 4191-4200. doi: 10.3864/j.issn.0578-1752.2019.23.001. (in Chinese)
[21]	方保停, 李向东, 邵运辉, 王汉芳, 岳俊芹, 张德奇, 杨程, 秦峰. 黄淮麦区冬小麦品种耐热性比较研究. 河南农业科学, 2019, 48(7): 19-23.
	FANG B T, LI X D, SHAO Y H, WANG H F, YUE J Q, ZHANG D Q, YANG C, QIN F. Comparative study on heat tolerance of winter wheat cultivars in Huang-Huai Region. Journal of Henan Agricultural Sciences, 2019, 48(7): 19-23. (in Chinese)
[22]	隋新霞, 刘学俊, 樊庆琦, 崔德周, 李永波, 黄琛, 黄承彦, 楚秀生. 利用智能温室鉴定小麦灌浆期耐热性. 山东农业科学, 2021, 53(5): 128-132.
	SUI X X, LIU X J, FAN Q Q, CUI D Z, LI Y B, HUANG C, HUANG C Y, CHU X S. Heat-tolerance identification of wheat at filling stage in intelligent greenhouse. Shandong Agricultural Sciences, 2021, 53(5): 128-132. (in Chinese)
[23]	许东旭, 黄长志, 周秋峰. 小麦耐热型种质资源的鉴定与筛选. 农业科技通讯, 2020(1): 68-71.
	XU D X, HUANG C Z, ZHOU Q F. Identification and screening of heat-resistant wheat germplasm resources. Bulletin of Agricultural Science and Technology, 2020(1): 68-71. (in Chinese)
[24]	耿晓丽, 张月伶, 臧新山, 赵月, 张金波, 尤明山, 倪中福, 姚颖垠, 辛明明, 彭惠茹, 孙其信. 北方冬麦区与黄淮北片优良小麦品种(系)耐热性评价. 麦类作物学报, 2016, 36(2): 172-181.
	GENG X L, ZHANG Y L, ZANG X S, ZHAO Y, ZHANG J B, YOU M S, NI Z F, YAO Y Y, XIN M M, PENG H R, SUN Q X. Evaluation the thermotolerance of the wheat (Triticum aestivum L.) cultivars and advanced lines collected from the Northern China and north area of Huanghuai winter wheat regions. Journal of Triticeae Crops, 2016, 36(2): 172-181. (in Chinese)
[25]	肖静, 田纪春. 小麦 (T. aestivum L.) D基因组的研究进展. 分子植物育种, 2008(3): 537-541.
	XIAO J, TIAN J C. Reviewed on D Genome of T. aestivum L.. Molecular Plant Breeding, 2008(3): 537-541. (in Chinese)
[26]	PARISOD C, BADAEVA E D. Chromosome restructuring among hybridizing wild wheats. New Phytologist, 2020, 226(5): 1263-1273. doi: 10.1111/nph.16415 pmid: 31913521
[27]	张乐欢, 邹昌玉, 朱天翔, 杜美霞, 邹修平, 何永睿, 陈善春, 龙琴. 茉莉酸在植物抗逆性中的研究进展. 生物工程学报, 2024, 40(1): 15-34.
	ZHANG L H, ZOU C Y, ZHU T X, DU M X, ZOU X P, HE Y R, CHEN S C, LONG Q. The role of jasmonic acid in stress resistance of plants: A review. Chinese Journal of Biotechnology, 2024, 40(1): 15-34. (in Chinese)
[28]	魏昕, 刘雨恒, 刘宇阳, 殷晓浦, 谢恬, 谌容, 卫秋慧. 植物JAZ蛋白家族研究进展. 植物生理学报, 2021, 57(5): 1039-1046.
	WEI X, LIU Y H, LIU Y Y, YIN X P, XIE T, CHEN R, WEI Q H. Advances of JAZ family in plants. Plant Physiology Journal, 2021, 57(5): 1039-1046. (in Chinese)
[29]	LI M Y, YU G H, CAO C L, LIU P. Metabolism, signaling, and transport of jasmonates. Plant Communications, 2021, 2(5): 100231.
[30]	ZHOU X E, ZHANG Y G, YAO J, ZHENG J, ZHOU Y X, HE Q, MORENO J, LAM V Q, CAO X M, SUGIMOTO K, VANEGAS- CANO L, KARIAPPER L, SUINO-POWELL K, ZHU Y Y, NOVICK S, GRIFFIN P R, ZHANG F, HOWE G A, MELCHER K. Assembly of JAZ-JAZ and JAZ-NINJA complexes in jasmonate signaling. Plant Communications, 2023, 4(6): 100639.
[31]	孙雨桐, 刘德帅, 齐迅, 冯美, 黄栩筝, 姚文孔. 茉莉酸调控植物生长发育和胁迫的研究进展. 生物技术通报, 2023, 39(11): 99-109. doi: 10.13560/j.cnki.biotech.bull.1985.2023-0323
	SUN Y T, LIU D S, QI X, FENG M, HUANG X Z, YAO W K. Advances in jasmonic acid regulating plant growth and development as well as stress. Biotechnology Bulletin, 2023, 39(11): 99-109. (in Chinese)
[32]	JOHNSON K L, CASSIN A M, LONSDALE A, BACIC A, DOBLIN M S, SCHULTZ C J. Pipeline to identify hydroxyproline-rich glycoproteins. Plant Physiology, 2017, 174(2): 886-903. doi: 10.1104/pp.17.00294 pmid: 28446635
[33]	CHEN J, MIAO W Q, FEI K Q, SHEN H L, ZHOU Y J, SHEN Y, LI C Q, HE J, ZHU K Y, WANG Z Q, YANG J C. Jasmonates alleviate the harm of high-temperature stress during anthesis to stigma vitality of photothermosensitive genetic male sterile rice lines. Frontiers in Plant Science, 2021, 12: 634959.
[34]	GOUVEIA D G, SIQUEIRA J A, NUNES-NESI A, ARAÚJO W L. Memories of heat: Autophagy and Golgi recovery. Trends in Plant Science, 2024, 29(6): 607-609.
[35]	WANG X J, TAN N W K, CHUNG F Y, YAMAGUCHI N, GAN E S, ITO T. Transcriptional regulators of plant adaptation to heat stress. International Journal of Molecular Sciences, 2023, 24(17): 13297.
[36]	WU Z, LI T, DING L P, WANG C P, TENG R D, XU S J, CAO X, TENG N J. Lily LlHSFC2 coordinates with HSFAs to balance heat stress response and improve thermotolerance. New Phytologist, 2024, 241(5): 2124-2142. doi: 10.1111/nph.19507 pmid: 38185817
[37]	HUANG J Y, ZHAO X B, BÜRGER M, WANG Y R, CHORY J. Two interacting ethylene response factors regulate heat stress response. The Plant Cell, 2021, 33(2): 338-357.
[38]	PACHECO J M, RANOCHA P, KASULIN L, FUSARI C M, SERVI L, APTEKMANN A A, GABARAIN V B, PERALTA J M, BORASSI C, MARZOL E, RODRÍGUEZ-GARCIA D R, DEL CARMEN RONDÓN GUERRERO Y, SARDOY M C, FERRERO L, BOTTO J F, MENESES C, ARIEL F, NADRA A D, PETRILLO E, DUNAND C, ESTEVEZ J M. Apoplastic class III peroxidases PRX62 and PRX69 promote Arabidopsis root hair growth at low temperature. Nature Communications, 2022, 13(1): 1310.
[39]	SWATHIK CLARANCIA P, NAVEENARANI M, ASHWIN NARAYAN J, KRISHNA S S, THIRUGNANASAMBANDAM P P, VALARMATHI R, SURESHA G S, GOMATHI R, KUMAR R A, MANICKAVASAGAM M, JEGADEESAN R, ARUN M, HEMAPRABHA G, APPUNU C. Genome-wide identification, characterization and expression analysis of plant nuclear factor (NF-Y) gene family transcription factors in Saccharum spp. Genes, 2023, 14(6): 1147.
[40]	STEPHENSON T J, MCINTYRE C L, COLLET C, XUE G P. TaNF-YC11 one of the light-upregulated NF-YC members in Triticum aestivum, is co-regulated with photosynthesis-related genes. Functional & Integrative Genomics, 2010, 10(2): 265-276.
[41]	STEPHENSON T J, MCINTYRE C L, COLLET C, XUE G P. TaNF-YB3 is involved in the regulation of photosynthesis genes in Triticum aestivum. Functional & Integrative Genomics, 2011, 11(2): 327-340.
[42]	LI X, LI C J, SHI L, LV G F, LI X, LIU Y X, JIA X J, LIU J Y, CHEN Y Q, ZHU L, FU Y. Jasmonate signaling pathway confers salt tolerance through a NUCLEAR FACTOR-Y trimeric transcription factor complex in Arabidopsis. Cell Reports, 2024, 43(3): 113825.
[43]	ZHAO Y J, MA C Y, ZHENG M J, YAO Y R, LV L H, ZHANG L H, FU X X, ZHANG J T, XIAO K. Transcription factor TaNF-YB2 interacts with partners TaNF-YA7/YC7 and transcriptionally activates distinct stress-defensive genes to modulate drought tolerance in T. aestivum. BMC Plant Biology, 2024, 24(1): 705.
[44]	NIU J H, GUAN Y N, YU X, WANG R F, QIN L, CHEN E Y, YANG Y B, ZHANG H W, WANG H L, LI F F. SiNF-YC₂ regulates early maturity and salt tolerance in Setaria italica. International Journal of Molecular Sciences, 2023, 24(8): 7217.
[45]	YADAV D, SHAVRUKOV Y, BAZANOVA N, CHIRKOVA L, BORISJUK N, KOVALCHUK N, ISMAGUL A, PARENT B, LANGRIDGE P, HRMOVA M, LOPATO S. Constitutive overexpression of the TaNF-YB4 gene in transgenic wheat significantly improves grain yield. Journal of Experimental Botany, 2015, 66(21): 6635-6650. doi: 10.1093/jxb/erv370 pmid: 26220082
[46]	LI X Y, ZHANG G F, LIANG Y H, HU L, ZHU B N, QI D M, CUI S J, ZHAO H T. TCP7 interacts with Nuclear Factor-Ys to promote flowering by directly regulating SOC1 in Arabidopsis. The Plant Journal, 2021, 108(5): 1493-1506.
[47]	BARTH O, VOGT S, UHLEMANN R, ZSCHIESCHE W, HUMBECK K. Stress induced and nuclear localized HIPP26 from Arabidopsis thaliana interacts via its heavy metal associated domain with the drought stress related zinc finger transcription factor ATHB29. Plant Molecular Biology, 2009, 69(1/2): 213-226.
[48]	GUO T Q, WEBER H, NIEMANN M C E, THEISL L, LEONTE G, NOVÁK O, WERNER T. Arabidopsis HIPP proteins regulate endoplasmic reticulum-associated degradation of CKX proteins and cytokinin responses. Molecular Plant, 2021, 14(11): 1918-1934.
[49]	ZHANG X, LIU Y, YUAN G X, WANG S W, WANG D L, ZHU T T, WU X F, MA M Q, GUO L W, GUO H L, BHADAURIA V, LIU J F, PENG Y L. The synthetic NLR RGA5HMA5 requires multiple interfaces within and outside the integrated domain for effector recognition. Nature Communications, 2024, 15(1): 1104.

Metrics

Viewed

Full text

Abstract

Cited

Shared

Discussed

Comments

Recommended 0

No Suggested Reading articles found!

处理时长 Heat treat time (h)	分级标准 Grade scale	耐热级数 HRG	热感类型 Thermal type
16	1.00≥SR≥0.75	1	极耐热Highly heat tolerance
	0.50≤SR<0.75	2	极耐热Highly heat tolerance
	0.25≤SR<0.50	3	极耐热Highly heat tolerance
	0.00≤SR<0.25	4	中等耐热Medium heat tolerance
12	1.00≥SR≥0.75	5	中等耐热Medium heat tolerance
	0.50≤SR<0.75	6	中等耐热Medium heat tolerance
	0.25≤SR<0.50	7	中等热敏感Medium heat sensitive
	0.00≤SR<0.25	8	中等热敏感Medium heat sensitive
8	1.00≥SR≥0.75	9	中等热敏感Medium heat sensitive
	0.50≤SR<0.75	10	极热敏感Highly heat sensitive
	0.25≤SR<0.50	11	极热敏感Highly heat sensitive
	0.00≤SR<0.25	12	极热敏感Highly heat sensitive

来源 Origin	名称 Name
中国China	鄂麦6号、丰产3号、藁城8901、黑宝-4、泾阳60、荆州47、陇黑838、宁春4号、糯麦1号、石家庄54、双大1号、苏麦3号、苏研麦0611、泰山4号、天民369、小白麦、艺麦1号、永良4号、豫圣黑麦1号、镇麦18、中原鼎紫1号、灰毛阿夫、毛颖阿夫 Emai 6 hao, Fengchan 3 hao, Gaocheng 8901, Heibao-4, Jingyang 60, Jingzhou 47, Longhei 838, Ningchun 4 hao, Nuomai 1 hao, Shijiazhuang 54, Shuangda 1 hao, Sumai 3 hao, Suyanmai 0611, Taishan 4 hao, Tianmin 369, Xiaobaimai, Yimai 1 hao, Yongliang 4 hao, Yushengmai 1 hao, Zhenmai 18, Zhongyuandingzi 1 hao, Huimao Funo, Maoying Funo
意大利Italy	阿勃、郑引1号 Abbondanza, St1472/506
智利Chile	欧柔Orofen
日本Japan	农林10号Norin 10
韩国Korea	水原86 Suwon 86
ICRADA	13W-25, 13W-40
其他Others	ARNEL、RUSSIA、捷克G377、小佛手、以色列小麦 ARNEL, RUSSIA, Czech G377, Xiaofoshou, Israel wheat

Genome-Wide Association Study of Heat Tolerance at Seedling Stage in A Wheat Natural Population

RichHTML

PDF

Abstract

Cite this article

share this article

Figures/Tables 10

References 49

Related Articles 15

Metrics

Comments

Recommended 0

[1]	WANG YaFei, YAN Peng, XUE JinTao, DONG XueRui, MENG FanQi, GUO LiNa, LUO Yi, ZHANG Juan, DONG ZhiQiang, LU Lin. Effects of Ethephon-Glycine Betaine-Salicylic Acid Mixture on Root System Architecture, Physiological Function and Yield of Maize Under Heat Stress [J]. Scientia Agricultura Sinica, 2026, 59(7): 1439-1455.
[2]	ZHU Qi, JIA ZhenPeng, Tahir SHAH, XU ChenSheng, LI ZhiQi, LÜ HuiShuai, ZHU PengChao, WEI XiaoMin, HUANG DongLin, SUN YanNi, CAO WeiDong, GAO YaJun, WANG ZhaoHui, ZHANG DaBin. Green Manure Crops Combined with Enhanced-Efficiency Products Reduced Greenhouse Gas Emissions and Carbon Footprints in Dryland Wheat Fields [J]. Scientia Agricultura Sinica, 2026, 59(7): 1507-1522.
[3]	YE MeJin, WU Lei, MD NAHIBUZZAMAN Lohani, YIN Li, HU XinRong, LIU YaXi, JIANG YunFeng, CHEN GuoYue, PU ZhiEn, LI Yang, LI Ting, ZOU YaYa, WU JiaYi, MA Jian. Genome-Wide Association Study-Based Identification of Loci Controlling Mature Embryo Size in Chinese Wheat Landraces and Their Genetic Effects Analysis [J]. Scientia Agricultura Sinica, 2026, 59(6): 1157-1171.
[4]	LI WenHu, LI HaiFeng, DU YuPeng, DING YuLan, LUO YiNuo, LI YuKe, SHE WenTing, ZHANG Feng, TENG Yu, ZHANG SiQi, HUANG Cui, LI XiaoHan, LIU JinShan, WANG ZhaoHui. Regional Differences in Wheat Zinc Uptake and Translocation Responses to Soil Zinc Fertilization [J]. Scientia Agricultura Sinica, 2026, 59(5): 1034-1047.
[5]	JIAO WenJuan, HE WanLong, GENG HongWei, BAI Bin, LI JianFeng, CHENG YuKun. Stripe Rust Resistance Evaluation and Molecular Characterization of Yr Genes for 155 Spring Wheat Varieties (Lines) [J]. Scientia Agricultura Sinica, 2026, 59(5): 937-950.
[6]	CUI ShiYou, CHEN PengJun, MIAO YuanQing, HAN JiJun, SHEN JunMing. Development and Field Evaluation of Glyphosate-Resistant Wheat Germplasm Generated Through EMS Mutagenesis [J]. Scientia Agricultura Sinica, 2026, 59(4): 723-733.
[7]	QIAN Jin, LI YingXue, WU Fang, ZOU XiaoChen. Improved Leaf Phosphorus Content Estimation of Winter Wheat Using Ensemble Hyperspectral Dimensionality Reduction Method [J]. Scientia Agricultura Sinica, 2026, 59(4): 781-792.
[8]	KONG Yuan, CUI ShaSha, LI Mei, LI Jian, YANG SiYu, FANG Feng, LIU ShuaiShuai, LIU MingPing, ZENG Yan, GAO XingXiang, BAI LianYang. Spatiotemporal Distribution Dynamics of Five Grass Weed Species Including Lolium multiflorum in Winter Wheat Fields of the Huang- Huai-Hai Region [J]. Scientia Agricultura Sinica, 2026, 59(4): 807-823.
[9]	WANG YongSheng, NIU Li, WANG ChangJie, MA LiHua, LIAN XiaoXiao, MENG YaXiong, MA XiaoLe, YAO LiRong, ZHANG Hong, YANG Ke, LI BaoChun, WANG HuaJun, SI ErJing, WANG JunCheng. Genome-Wide Association Study and Candidate Gene Identification for Thousand Grain Weight in Winter Wheat [J]. Scientia Agricultura Sinica, 2026, 59(3): 499-514.
[10]	LI XinYi, LI JiaNing, YANG WenPing, XIA Qing, HUO YingRui, HAO ShiHang, HUANG TingMiao, REN YongKang, CHEN Jie, GAO ZhiQiang, YANG ZhenPing. Effects of Post-Anthesis Foliar Zinc Application on Zinc Nutrition in Colored-Grain Wheat [J]. Scientia Agricultura Sinica, 2026, 59(3): 515-527.
[11]	XIAN QingLin, XIAO JianKe, GAO AQing, GAO LiChuang, LIU Yang. Effects of Planting Patterns Combined with Soil Moisture Measurement and Supplementary Irrigation on the Yield and Water Use Efficiency of Winter Wheat [J]. Scientia Agricultura Sinica, 2026, 59(3): 589-601.
[12]	ZHANG ZhiYong, TAN ShiChao, XIONG ShuPing, MA XinMing, WEI YiHao, WANG XiaoChun. Effects of Annual Water and Nitrogen Optimization on Yield and Nitrogen Migration of Wheat-Maize Rotation System in Irrigation Area of Northern Henan [J]. Scientia Agricultura Sinica, 2026, 59(2): 336-353.
[13]	LÜ XuDong, SUN ShiYuan, LI YaNan, LIU YuLong, WANG YanQun, FU Xin, ZHANG JiaYing, NING Peng, PENG ZhengPing. Effects of Intelligent Mechanized Layered Fertilization on Root-Soil Nutrient Distribution and Yield in Wheat Fields [J]. Scientia Agricultura Sinica, 2026, 59(1): 129-146.
[14]	LU Hao, ZHANG MingLong, HAN Mei, YAN QingBiao, LI ZhengPeng, YIN Wen, FAN ZhiLong, HU FaLong, CHAI Qiang. Green Manure Returning via Sheep Digest with Nitrogen Fertilizer Reduction are Beneficial to Improve Wheat Yield and Soil Quality at Qinghai-Tibet Plateau [J]. Scientia Agricultura Sinica, 2026, 59(1): 147-160.
[15]	YE MeiJin, CHEN JiaTing, ZHOU JieGuang, YIN Li, HU XinRong, LAN YuXin, CHEN Bin, SU LongXing, LIU JiaJun, LIU TianChao, LI XiaoYu, MA Jian. Identification, Validation and Genetic Effect Analysis of Major QTL for Spike Density in Wheat [J]. Scientia Agricultura Sinica, 2026, 59(1): 17-28.