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小麦抗条锈病相关性状元分析及候选基因分析

张飞飞1，何万龙1，焦文娟1，白斌2，耿洪伟1，程宇坤1,*   

  1. 1 疆农业大学农学院 / 新疆农业大学优质专用麦类作物工程技术研究中心, 新疆乌鲁木齐830052; 2 肃农科院小麦研究所, 甘肃兰州730070
  • 收稿日期:2024-10-12 修回日期:2025-04-27 接受日期:2025-04-27 出版日期:2025-05-09 网络出版日期:2025-05-09
  • 基金资助:
    本研究由自治区高校基本科研业务费科研项目(XIEDU20241042), 自治区重点研发计划项目(2022B02015-3)和中国博士后科学基金(2021MD703887)资助。

Meta-Analysis of stripe rust resistance-associated traits and candidate gene identification in Wheat

ZHANG Fei-Fei1,HE Wan-Long1,JIAO Wen-Juan1,BAI Bin2,GENG Hong-Wei1,CHENG Yu-Kun1,*   

  1. 1 College of Agronomy, Xinjiang Agricultural University / Special High Quality Triticeae Crops Engineering and Technology Research Center, Xinjiang Agricultural University, Urumqi 830052, Xinjiang, China; 2 Wheat Research Institute, Gansu Academy of Agricultural Sciences, Lanzhou 730070, Gansu, China
  • Received:2024-10-12 Revised:2025-04-27 Accepted:2025-04-27 Published:2025-05-09 Published online:2025-05-09
  • Supported by:
    This study was supported by the Fundamental Research Funds for Universities of Autonomous Region (XIEDU20241042), Key Research and Development Program project of Autonomous Region (2022B02015-3), and China Postdoctoral Science Foundation (2021MD703887).

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摘要： 小麦条锈病是由条形柄锈菌小麦专化型(Puccinia striiformis f. sp. Tritici)引起的真菌病害，是小麦生产中主要病害之一。利用元分析(meta-analysis)对已报道的小麦条锈病抗病数量性状位点(quantitative trait locus, QTL)和已知抗病基因(Yr)进行统合分析，将480个不同分子标记类型QTL通过构建的参考图谱进行映射，获得meta-QTL (meta-quantitative trait locus, MQTL) 90个，其中16个与严重度(disease severity, DS)相关、10个与反应型(infection type, IT)相关、7个与病程曲线下面积相关(area under disease progress curve, AUDPC)、3个与其他抗条锈病性状相关；有19个同时与DS和IT共相关、20个与DS和AUDPC共相关、15个与IT和AUDPC共相关。获得的MQTL非均匀分布于21条染色体上，部分MQTL聚合成簇；解释表型变异率范围2.00%~63.01%，置信区间范围为0.01~24.60 cM；在映射的MQTL包含13个抗病基因：Yr5，Yr7，Yr17，Yr18，Yr28，Yr29，Yr30，Yr44，Yr48，Yr52，Yr54，Yr67和Yr82。进一步对MQTL进行候选基因分析，鉴定了72个候选基因(candidate gene, CG)，功能注释和表达模式分析发现，CG编码的蛋白质含有与抗病相关的如NBS-LRR结构域、WRKY结构域、F-box结构域、糖转运蛋白等；并且研究了CG在小麦发育过程中不同叶片组织中的表达情况。本研究通过分子标记辅助育种将抗条锈病基因或QTL聚合培育获得小麦抗病品种，为有效提高小麦抗病水平、保障粮食安全提供参考。

关键词: 小麦, 条锈病, 元分析, MQTL

Abstract:

Wheat stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst), poses a serious threat to global wheat production. In this study, we performed a comprehensive meta-analysis of 480 published quantitative trait loci (QTL) and known resistance genes (Yr) associated with stripe rust resistance in wheat. These QTLs were projected onto a consensus genetic map, resulting in the identification of 90 meta-QTLs (MQTLs). Among these MQTLs, 16 were associated with disease severity (DS), 10 with infection type (IT), 7 with the area under the disease progress curve (AUDPC), and 3 with other resistance-related traits. Additionally, 19 MQTLs were associated with both DS and IT, 20 with DS and AUDPC, and 15 with IT and AUDPC. The MQTLs were unevenly distributed across the 21 wheat chromosomes, with several forming clusters. These MQTLs explained phenotypic variances ranging from 2.00% to 63.01%, with confidence intervals spanning 0.01 to 24.60 cM. Thirteen MQTLs co-localized with known resistance genes, including Yr5, Yr7, Yr17, Yr18, Yr28, Yr29, Yr30, Yr44, Yr48, Yr52, Yr54, Yr67, and Yr82. Furthermore, candidate gene (CG) analysis identified 72 genes within the MQTL regions. Functional annotation and expression profiling revealed that many of these CGs encode proteins involved in sugar transport or contain resistance-related domains such as NBS-LRR, WRKY, and F-box. Expression analysis across different leaf tissues further supported their potential roles in defense responses. These findings provide valuable molecular markers and candidate genes for the pyramiding of resistance QTLs/genes, offering a promising strategy for developing stripe rust-resistant wheat cultivars and contributing to global food security.

Key words: wheat, stripe rust, meta-analysis, MQTL

[1] Wellings C R. Global status of stripe rust: a review of historical and current threats. Euphytica, 2011, 179: 129‒141.

[2] Rapilly F. Yellow rust epidemiology. Annu Rev Phytopathol, 1979, 17: 59‒73.

[3] Front Matter. Roelfs A P, Bushnell W R. Diseases, Distribution, Epidemiology, and Control. Academic Press, 1985, pp 61‒101.

[4] 李振岐, 曾士迈. 中国小麦锈病. 北京: 中国农业出版, 2002. pp 370‒373.

Li Z Q, Zeng S M. Wheat Rusts in China. Beijing: China Agriculture Press, 2002. pp 370‒373 (in Chinese).

[5] 刘万才, 王保通, 赵中华, 李跃, 康振生. 我国小麦条锈病历次大流行的历史回顾与对策建议. 中国植保导刊, 2022, 42(6): 21‒27.

Liu W C, Wang B T, Zhao Z H, Li Y, Kang Z S. Historical review and countermeasures of wheat stripe rust epidemics in China. China Plant Prot, 2022, 42(6): 21‒27 (in Chinese with English abstract).

[6] Zeng Q D, Zhao J, Wu J H, Zhan G M, Han D J, Kang Z S. Wheat stripe rust and integration of sustainable control strategies in China. Fron Agric Sci Eng, 2022, 9: 37.

[7] Moore J W, Herrera-Foessel S, Lan C X, Schnippenkoetter W, Ayliffe M, Huerta-Espino J, Lillemo M, Viccars L, Milne R, Periyannan S, et al. A recently evolved hexose transporter variant confers resistance to multiple pathogens in wheat. Nat Genet, 2015, 47: 1494‒1498.

[8] Klymiuk V, Yaniv E, Huang L, Raats D, Fatiukha A, Chen S S, Feng L H, Frenkel Z, Krugman T, Lidzbarsky G, et al. Cloning of the wheat Yr15 resistance gene sheds light on the plant tandem kinase-pseudokinase family. Nat Commun, 2018, 9: 3735.

[9] Zhang C Z, Huang L, Zhang H F, Hao Q Q, Lyu B, Wang M N, Epstein L, Liu M, Kou C L, Qi J, et al. An ancestral NB-LRR with duplicated 3'UTRs confers stripe rust resistance in wheat and barley. Nat Commun, 2019, 10: 4023.

[10] Kumar A, Saini D K, Saripalli G, Sharma P K, Balyan H S, Gupta P K. Meta-QTLs, ortho-meta QTLs and related candidate genes for yield and its component traits under water stress in wheat (Triticum aestivum L.). Physiol Mol Biol Plants, 2023, 29: 525‒542.

[11] Glass G V. Primary, secondary, and meta-analysis of research. Educ Res, 1976, 5: 3‒8

[12] Arcade A, Labourdette A, Falque M, Mangin B, Chardon F, Charcosset A, Joets J. BioMercator: integrating genetic maps and QTL towards discovery of candidate genes. Bioinformatics, 2004, 20: 2324‒2326.

[13] Saini D K, Srivastava P, Pal N, Gupta P K. Meta-QTLs, ortho-meta-QTLs and candidate genes for grain yield and associated traits in wheat (Triticum aestivum L.). Theor Appl Genet, 2022, 135: 1049‒1081.

[14] Chardon F, Virlon B, Moreau L, Falque M, Joets J, Decousset L, Murigneux A, Charcosset A. Genetic architecture of flowering time in maize as inferred from quantitative trait loci meta-analysis and synteny conservation with the rice genome. Genetics, 2004, 168: 2169‒2185.

[15] 吴琼, 齐照明, 刘春燕, 胡国华, 陈庆山.基于元分析的大豆生育期QTL的整合.作物学报, 2009, 35: 1418‒1424.

Wu Q, Qi Z M, Liu C Y, Hu G H, Chen Q S. An integrated QTL map of growth stage in soybean [Glycine max (L.) merr.]: constructed through meta-analysis. Acta Agron Sin, 2009, 35: 1418‒1424 (in Chinese with English abstract).

[16] 倪胜利, 何瑞, 刘媛, 张沛沛, 李兴茂, 杨德龙. 不同水分条件下小麦粒重QTL定位及其元分析. 甘肃农业大学学报, 2021, 56: 45‒54.

Ni S L, He R, Liu Y, Zhang P P, Li X M, Yang D L. QTL mapping and meta-analysis for grain weight of wheat under different moisture conditions. J Gansu Agr Univ, 2021, 56: 45‒54 (in Chinese with English abstract). 

[17] Amo A, Soriano J M. Unravelling consensus genomic regions conferring leaf rust resistance in wheat via meta-QTL analysis. Plant Genome, 2022, 15: 463‒473.

[18] Goffinet B, Gerber S. Quantitative trait loci: a meta-analysis. Genetics, 2000, 155: 463‒473.

[19] 刘志勇, 张怀志, 白斌, 李俊, 黄林, 徐智斌, 陈永兴, 刘旭, 曹廷杰, 李淼淼, 等. 中国小麦抗条锈病基因育种利用现状与策略. 中国农业科学, 2024, 57: 34‒51.

Liu Z Y, Zhang H Z, Bai B, Li J, Huang L, Xu Z B, Chen Y X, Liu X, Cao T J, Li M M, et al. Current status and strategies for utilization of stripe rust resistance genes in wheat breeding program of China. Sci Agric Sin, 2024, 57: 34‒51 (in Chinese with English abstract).

[20] 赵霞, 王长彪, 赵兴华, 刘江, 崔婷, 任永康, 牛瑜琦, 唐朝晖. 小麦抗病相关基因聚合育种的研究进展. 山西农业科学, 2017, 45: 308‒313.

Zhao X, Wang C B, Zhao X H, Liu J, Cui T, Ren Y K, Niu Y Q, Tang Z H. Research progress on pyramiding breeding of disease resistance related genes in wheat. J Shanxi Agric Sci, 2017, 45: 308‒313 (in Chinese with English abstract).

[21] 鲁秀梅, 张宁, 陈劲枫, 钱春桃. 作物基因聚合育种的研究进. 分子植物育种, 2017, 15: 1445‒1454.

Lu X M, Zhang N, Chen J F, Qian C T. The research progress in crops pyramiding breeding. Mol Plant Breed, 2017, 15: 1445‒1454 (in Chinese with English abstract).

[22] Song Q J, Shi J R, Singh S, Fickus E W, Costa J M, Lewis J, Gill B S, Ward R, Cregan P B. Development and mapping of microsatellite (SSR) markers in wheat. Theor Appl Genet, 2005, 110: 550‒560.

[23] Somers D J, Isaac P, Edwards K. A high-density microsatellite consensus map for bread wheat (Triticum aestivum L.). Theor Appl Genet, 2004, 109: 1105‒1114.

[24] Franco M F, Polacco A N, Campos P E, Pontaroli A C, Vanzetti L S. Genome-wide association study for resistance in bread wheat (Triticum aestivum L.) to stripe rust (Puccinia striiformis f. sp. tritici) races in Argentina. BMC Plant Biol, 2022, 22: 543.

[25] Cavanagh C R, Chao S, Wang S C, Huang B E, Stephen S, Kiani S, Forrest K, Saintenac C, Brown-Guedira G L, Akhunova A, et al. Genome-wide comparative diversity uncovers multiple targets of selection for improvement in hexaploid wheat landraces and cultivars. Proc Natl Acad Sci USA, 2013, 110: 8057‒8062.

[26] Cui F, Zhang N, Fan X L, Zhang W, Zhao C H, Yang L J, Pan R Q, Chen M, Han J, Zhao X Q, et al. Utilization of a Wheat660K SNP array-derived high-density genetic map for high-resolution mapping of a major QTL for kernel number. Sci Rep, 2017, 7: 3788.

[27] Wang S, Wong D, Forrest K, Allen A, Chao S, Huang B E, Maccaferri M, Salvi S, Milner S G, Cattivelli L, et al. Characterization of polyploid wheat genomic diversity using a high-density 90,000 single nucleotide polymorphism array. Plant Biotechnol J, 2014, 12: 787‒796.

[28] Burridge A J, Winfield M O, Allen A M, Wilkinson P A, Barker G L A, Coghill J, Waterfall C, Edwards K J. High-density SNP genotyping array for hexaploid wheat and its relatives. Methods Mol Biol, 2017, 1679: 293‒306.

[29] Veyrieras J B, Goffinet B, Charcosset A. MetaQTL: a package of new computational methods for the meta-analysis of QTL mapping experiments. BMC Bioinformatics, 2007, 8: 49.

[30] Darvasi A, Soller M. A simple method to calculate resolving power and confidence interval of QTL map location. Behavior Genetics, 1997, 27: 125‒132.

[31] 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. Crop Sci, 2006, 46: 595‒602.

[32] Ramírez-González R H, Borrill P, Lang D, Harrington S A, Brinton J, Venturini L, Davey M, Jacobs J, Van Ex F, Pasha A, et al. The transcriptional landscape of polyploid wheat. Science, 2018, 361: eaar6089.

[33] Yang Y, Amo A, Wei D, Chai Y M, Zheng J, Qiao P F, Cui C G, Lu S, Chen L, Hu Y G. Large-scale integration of meta-QTL and genome-wide association study discovers the genomic regions and candidate genes for yield and yield-related traits in bread wheat. Theor Appl Genet, 2021, 134: 3083‒3109.

[34] Saini D K, Chahal A, Pal N, Srivastava P, Gupta P K. Meta-analysis reveals consensus genomic regions associated with multiple disease resistance in wheat (Triticum aestivum L.). Mol Breed, 2022, 42: 11.

[35] Pal N, Jan I, Saini D K, Kumar K, Kumar A, Sharma P K, Kumar S, Balyan H S, Gupta P K. Meta-QTLs for multiple disease resistance involving three rusts in common wheat (Triticum aestivum L.). Theor Applied Genet, 2022, 135: 2385‒2405.

[36] Soriano J M, Royo C. Dissecting the genetic architecture of leaf rust resistance in wheat by QTL meta-analysis. Phytopathology, 2015, 105: 1585‒1593.

[37] Liu Y, Salsman E, Wang R H, Galagedara N, Zhang Q J, Fiedler J D, Liu Z H, Xu S, Faris J D, Li X H. Meta-QTL analysis of tan spot resistance in wheat. Theor Appl Genet, 2020, 133: 2363‒2375.

[38] Venske E, Dos Santos R S, Farias D D R, Rother V, da Maia L C, Pegoraro C, Costa de Oliveira A. Meta-analysis of the QTLome of fusarium head blight resistance in bread wheat: refining the current puzzle. Front Plant Sci, 2019, 10: 727.

[39] Zheng T, Hua C, Li L, Sun Z X, Yuan M M, Bai G H, Humphreys G, Li T. Integration of meta-QTL discovery with omics: towards a molecular breeding platform for improving wheat resistance to Fusarium head blight. Crop J, 2021, 9: 739‒749.

[40] Salvi S, Tuberosa R. The crop QTLome comes of age. Curr Opin Biotechnol, 2015, 32: 179‒185.

[41] Kumar S, Saini D K, Jan F, Jan S, Tahir M, Djalovic I, Latkovic D, Khan M A, Kumar S, Vikas V K, et al. Comprehensive meta-QTL analysis for dissecting the genetic architecture of stripe rust resistance in bread wheat. BMC Genomics, 2023, 24: 259.

[42] 程宇坤, 姚方杰, 叶雪玲, 江千涛, 李伟, 邓梅, 魏育明, 陈国跃. 小麦抗条锈病一致性数量性状位点(MQTL)图谱构建. 植物病理学报, 2019, 49: 632‒649.

Cheng Y K, Yao F J, Ye X L, Jiang Q T, Li W, Deng M, Wei Y M, Chen G Y. Construction of linkage map of the meta quantitative trait loci (MQTL) on stripe rust resistance in wheat (Triticum aestivum L.). Acta Phytopathol Sin, 2019, 49: 632‒649 (in Chinese with English abstract).

[43] Jan I, Saripalli G, Kumar K, Kumar A, Singh R, Batra R, Sharma P K, Balyan H S, Gupta P K. Meta-QTLs and candidate genes for stripe rust resistance in wheat. Sci Rep, 2021, 11: 22923.

[44] Liu W, Frick M, Huel R, Nykiforuk C L, Wang X, Gaudet D A, Eudes F, Conner R L, Kuzyk A, Chen Q, et al. The stripe rust resistance gene Yr10 encodes an evolutionary-conserved and unique CC–NBS–LRR sequence in wheat. Mol Plant, 2014, 7: 1740‒1755.

[45] Garcia A V, Al-Yousif M, Hirt H. Role of AGC kinases in plant growth and stress responses. Cell Mol Life Sci: CMLS, 2012, 69: 3259‒3267.

[46] Gupta S K, Rai A K, Kanwar S S, Sharma T R. Comparative analysis of zinc finger proteins involved in plant disease resistance. PLoS One, 2012, 7: e42578.

[47] Gunupuru L R, Arunachalam C, Malla K B, Kahla A, Perochon A, Jia J G, Thapa G, Doohan F M. A wheat cytochrome P450 enhances both resistance to deoxynivalenol and grain yield. PLoS One, 2018, 13: e0204992.

[48] Liu J, Zhi P H, Wang X Y, Fan Q X, Chang C. Wheat WD40-repeat protein TaHOS15 functions in a histone deacetylase complex to fine-tune defense responses to Blumeria graminis f. sp. tritici. J Exp Bot, 2019, 70: 255‒268.

[49] Liao Z H, Wang L, Li C Z, Cao M J, Wang J N, Yao Z L, Zhou S Y, Zhou G X, Zhang D Y, Lou Y G. The lipoxygenase gene OsRCI-1 is involved in the biosynthesis of herbivore-induced JAs and regulates plant defense and growth in rice. Plant Cell Environ, 2022, 45: 2827‒2840.

[50] Wang J H, Wang J J, Li J, Shang H S, Chen X H, Hu X P. The RLK protein TaCRK10 activates wheat high-temperature seedling-plant resistance to stripe rust through interacting with TaH2A.1. Plant J, 2021, 108:1241–1255.

[51] Chen H, Pan X W, Wang F F, Liu C K, Wang X, Li Y S, Zhang Q Y. Novel QTL and meta-QTL mapping for major quality traits in soybean. Front Plant Sci, 2021, 12: 774270.

[52] Wang Y J, Xu J, Deng D X, Ding H D, Bian Y L, Yin Z T, Wu Y R, Zhou B, Zhao Y. A comprehensive meta-analysis of plant morphology, yield, stay-green, and virus disease resistance QTL in maize (Zea mays L.). Planta, 2016, 243: 459‒471.

[53] Gyawali S, Verma R P S, Kumar S, Bhardwaj S C, Gangwar O P, Selvakumar R, Shekhawat P S, Rehman S, Sharma-Poudyal D. Seedling and adult-plant stage resistance of a world collection of barley genotypes to stripe rust. J Phytopathol, 2018, 166: 18‒27.

[54] Alemu S K, Huluka A B, Tesfaye K, Haileselassie T, Uauy C. Genome-wide association mapping identifies yellow rust resistance loci in Ethiopian durum wheat germplasm. PLoS One, 2021, 16: e0243675.

[55] Habib M, Awan F S, Sadia B, Zia M A. Genome-wide association mapping for stripe rust resistance in Pakistani spring wheat genotypes. Plants, 2020, 9: 1056.

[56] Jia M J, Yang L J, Zhang W, Rosewarne G, Li J H, Yang E N, Chen L, Wang W X, Liu Y K, Tong H W, He W J, Zhang Y Q, Zhu Z W, Gao C B. Genome-wide association analysis of stripe rust resistance in modern Chinese wheat. BMC Plant Biol, 2020, 20: 491.

[57] Juliana P, Singh R P, Huerta-Espino J, Bhavani S, Randhawa M S, Kumar U, Joshi A K, Bhati P K, Mir H E V, Mishra C N, Singh G P. Genome-wide mapping and allelic fingerprinting provide insights into the genetics of resistance to wheat stripe rust in India, kenya and Mexico. Sci Rep, 2020, 10: 10908.

[58] Ledesma-Ramírez L, Solís-Moya E, Iturriaga G, Sehgal D, Reyes-Valdes M H, Montero-Tavera V, Sansaloni C P, Burgueño J, Ortiz C, Aguirre-Mancilla C L, Ramírez-Pimentel J G, Vikram P, Singh S. GWAS to identify genetic loci for resistance to yellow rust in wheat pre-breeding lines derived from diverse exotic crosses. Front Plant Sci, 2019, 10: 1390.

[59] Maccaferri M, Zhang J L, Bulli P, Abate Z, Chao S A M, Cantu D R O, Bossolini E, Chen X M, Pumphrey M, Dubcovsky J. A genome-wide association study of resistance to stripe rust (puccinia striiformis f. sp. tritici) in a worldwide collection of hexaploid spring wheat (Triticum aestivum L.). G3: Genes Genom Genet, 2015, 5: 449–465.

[60] Zegeye H, Rasheed A, Makdis F, Badebo A, Ogbonnaya F C. Genome-wide association mapping for seedling and adult plant resistance to stripe rust in synthetic hexaploid wheat. PLoS One, 2014, 9: e105593.

[61] Zhang P P, Yan X C, Gebrewahid T W, Zhou Y, Yang E N, Xia X C, He Z H, Li Z F, Liu D Q. Genome-wide association mapping of leaf rust and stripe rust resistance in wheat accessions using the 90K SNP array. Theor App Genet, 2021, 134: 1233–1251.

[62] Miedaner T, Rapp M, Flath K, Longin C F H, Würschum T. Genetic architecture of yellow and stem rust resistance in a durum wheat diversity panel. Euphytica, 2019, 215: 71.

[63] Genievskaya Y, Turuspekov Y, Rsaliyev A, Abugalieva S. Genome-wide association mapping for resistance to leaf, stem, and yellow rusts of common wheat under field conditions of south Kazakhstan. PeerJ, 2020, 8: e9820.

[64] Kankwatsa P, Singh D, Thomson P C, Babiker E M, Bonman J M, Newcomb M, Park R F. Characterization and genome-wide association mapping of resistance to leaf rust, stem rust and stripe rust in a geographically diverse collection of spring wheat landraces. Mole Breed, 2017, 37: 113.

[65] Kumar D, Kumar A, Chhokar V, Gangwar O P, Bhardwaj S C, Sivasamy M, Prasad S V S, Prakasha T L, Khan H, Singh R, Sharma P, Sheoran S, Iquebal M A, Jaiswal S, Angadi U B, Singh G, Rai A, Singh G P, Kumar D, Tiwari R. Genome-wide association studies in diverse spring wheat panel for stripe, stem, and leaf rust resistance. Front Plant Sci, 2020, 11: 748.

[66] Tomar V, Dhillon G S, Singh D, Singh R P, Poland J, Chaudhary A A, Bhati P K, Joshi A K, Kumar U. Evaluations of genomic prediction and identification of new loci for resistance to stripe rust disease in wheat (Triticum aestivum L.). Front Genet, 2021, 12.

[67] Aoun M, Chen X M, Somo M, Xu S S, Li X H, Elias E M. Novel stripe rust all-stage resistance loci identified in a worldwide collection of durum wheat using genome-wide association mapping. Plant Genome, 2021, 14: e20136.

[68] Jambuthenne D T, Riaz A, Athiyannan N, Alahmad S, Ng W L, Ziems L, Afanasenko O, Periyannan S K, Aitken E, Platz G, Godwin I, Voss-Fels K P, Dinglasan E, Hickey L T. Mining the vavilov wheat diversity panel for new sources of adult plant resistance to stripe rust. Theor App Genet, 2022, 135: 1355–1373.

[69] Qaiser R, Akram Z, Asad S, Haq I U, Malik S I, Fayyaz M, Sufiyan M, Khattak S H, Sandhu K S, Sidhu G S. Genome-wide association mapping and population structure for stripe rust in pakistani wheat germplasm. Pakistan J Bot, 2022, 54.

[70] Wang Y Q, Yu C, Cheng Y K, Yao F J, Long L, Wu Y, Li J, Li H, Wang J R, Jiang Q T, Li W, Pu Z E, Qi P F, Ma J, Deng M, Wei Y M, Chen X M, Chen G Y, Kang H Y, Jiang Y F, Zheng Y L. Genome-wide association mapping reveals potential novel loci controlling stripe rust resistance in a Chinese wheat landrace diversity panel from the southern autumn-sown spring wheat zone. BMC Genomics, 2021, 22: 34.

[71] Tene M, Adhikari E, Cobo N, Jordan K W, Matny O, del Blanco I A, Roter J, Ezrati S, Govta L, Manisterski J, Yehuda P B, Chen X M, Steffenson B, Akhunov E, Sela H N. GWAS for stripe rust resistance in wild emmer wheat (Triticum dicoccoides) population: obstacles and solutions. Crops, 2022, 2: 42–61.

[72] Zhou C, Liu D, Zhang X, Wu Q M, Liu S J, Zeng Q D, Wang Q L, Wang C F, Li C L, Singh R P, Bhavani S, Kang Z S, Han D J, Zheng W J, Wu J H. Combined linkage and association mapping reveals two major QTL for stripe rust adult plant resistance in shaanmai 155 and their haplotype variation in common wheat germplasm. Crop J, 2022, 10: 783–792.

[73] Yao F J, Guan F N, Duan L Y, Long L, Tang H, Jiang Y F, Li H, Jiang Q T, Wang J R, Qi P F, Kang H Y, Li W, Ma J, Pu Z E, Deng M, Wei Y M, Zheng Y L, Chen X M, Chen G Y. Genome-wide association analysis of stable stripe rust resistance loci in a Chinese wheat landrace panel using the 660K SNP array. Front Plant Sci, 2021, 12.

[74] El Messoadi K, El Hanafi S, Gataa Z E, Kehel Z, Bouhouch Y, Tadesse W. Genome wide association study for stripe rust resistance in spring bread wheat (Triticum aestivum L.). J Plant Pathol, 2022, 104: 1049–1059.

[75] Mehrabi A A, Steffenson B J, Pour-Aboughadareh A, Matny O, Rahmatov M. Genome-wide association study identifies two loci for stripe rust resistance in a durum wheat panel from Iran. App Sci, 2022, 12: 4963.

[76] El Messoadi K, Rochdi A, El Yacoubi H, Wuletaw T. Genome wide association study for stripe rust resistance in elite spring bread wheat genotypes (Triticum aestivum L.) in Morocco. Physiol Mol Plant Pathol, 2023, 127: 102106.

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