Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

An NLR–transposase fusion gene from rye provides broadly effective resistance to stripe rust in wheat

Nature Plants (2026)Cite this article

Subjects

Abstract

Stripe rust, caused by Puccinia striiformis f. sp. tritici, is a major threat to global wheat production. To explore new resistance resources, we screened 100 hexaploid triticale accessions using the predominant Chinese P. striiformis f. sp. tritici races CYR32, CYR33 and CYR34 and found that most accessions showed high resistance, with the cultivar Rozovskaya displaying near-immunity. Through map-based cloning, we identified a resistance gene located on chromosome 6RL. Analysis of resequencing data from 117 rye accessions revealed two major haplotypes, both of which conferred near-immunity and broadly effective resistance to stripe rust in transgenic wheat. Sequence analysis and virus-induced gene silencing collectively confirmed the identity of this gene as Yr83. Yr83 encodes an atypical nucleotide-binding and leucine-rich repeat protein (NLR) fused to a Harbinger transposase-derived nuclease domain (HTDND). Truncation of the HTDND abolishes resistance, indicating that this domain is essential for Yr83-mediated immune function. Phylogenetic analysis showed that NLR–HTDND proteins are restricted to the Pooideae subfamily. For breeding applications, we employed a small 6RL translocation line that shows excellent agronomic performance, not only conferring strong resistance but also increasing spikelet number and grain number per spike. Our study reveals a transposase-integrated NLR as a valuable resource for wheat stripe rust resistance breeding.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on SpringerLink
  • Instant access to the full article PDF.

USD 39.95

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Fine mapping of the stripe rust resistance gene in triticale cultivar Rozovskaya.
Fig. 2: Functional validation of SECCE6Rv1G0452990.
Fig. 3: The HTDND is essential for the strip rust resistance of Yr83.
Fig. 4: Evaluation of main agronomic traits of small fragment translocation lines 6R/6A containing Yr83.

Similar content being viewed by others

Data availability

All sequencing data generated in this study have been deposited in the National Genomics Data Center. The corresponding accession numbers are CRA019047, CRA019069 and CRA032335.

References

  1. Beddow, J. M. et al. Research investment implications of shifts in the global geography of wheat stripe rust. Nat. Plants 1, 15132 (2015.

    Article  PubMed  Google Scholar 

  2. Zhao, J. & Kang, Z. Fighting wheat rusts in China: a look back and into the future. Phytopathol. Res. 5, 6 (2023).

    Article  CAS  Google Scholar 

  3. Sharma, D. et al. A single NLR gene confers resistance to leaf and stripe rust in wheat. Nat. Commun. 15, 9925 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Hafeez, A. N. et al. Creation and judicious application of a wheat resistance gene atlas. Mol. Plant 14, 1053–1070 (2021).

    Article  CAS  PubMed  Google Scholar 

  5. Schwessinger, B. Fundamental wheat stripe rust research in the 21st century. New Phytol. 213, 1625–1631 (2017).

    Article  CAS  PubMed  Google Scholar 

  6. Hu, C. et al. Resistance analyses on wheat stripe rust resistance genes to the predominant races of Puccinia striiformis f. sp. tritici in China. Sci. Agric. Sin. 55, 491–502 (2022).

    Google Scholar 

  7. Jones, J. & Dangl, J. J. N. The plant immune system. Nature 444, 323–329 (2006).

    Article  CAS  PubMed  Google Scholar 

  8. Wan, L. et al. TIR domains of plant immune receptors are NAD+-cleaving enzymes that promote cell death. Science 365, 799–803 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Wang, J. et al. Reconstitution and structure of a plant NLR resistosome conferring immunity. Science 364, eaav5870 (2019).

    Article  CAS  PubMed  Google Scholar 

  10. Sarris, P. F., Cevik, V., Dagdas, G., Jones, J. D. & Krasileva, K. V. Comparative analysis of plant immune receptor architectures uncovers host proteins likely targeted by pathogens. BMC Biol. 14, 8 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  11. Sarris, P. F. et al. A plant immune receptor detects pathogen effectors that target WRKY transcription factors. Cell 161, 1089–1100 (2015).

    Article  CAS  PubMed  Google Scholar 

  12. Maqbool, A. et al. Structural basis of pathogen recognition by an integrated HMA domain in a plant NLR immune receptor. eLife 4, e08709 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  13. Liu, S. et al. A telomere-to-telomere genome assembly coupled with multi-omic data provides insights into the evolution of hexaploid bread wheat. Nat. Genet. 57, 1008–1020 (2025).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Casola, C., Lawing, A. M., Betran, E. & Feschotte, C. PIF-like transposons are common in Drosophila and have been repeatedly domesticated to generate new host genes. Mol. Biol. Evol. 24, 1872–1888 (2007).

    Article  CAS  PubMed  Google Scholar 

  15. Emmons, S. W., Yesner, L., Ruan, K. S. & Katzenberg, D. Evidence for a transposon in Caenorhabditis elegans. Cell 32, 55–65 (1983).

    Article  CAS  PubMed  Google Scholar 

  16. Tang, W. et al. Transposase-derived proteins FHY3/FAR1 interact with PHYTOCHROME-INTERACTING FACTOR1 to regulate chlorophyll biosynthesis by modulating HEMB1 during deetiolation in Arabidopsis. Plant Cell 24, 1984–2000 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Mao, D. et al. The Harbinger transposon-derived gene PANDA epigenetically coordinates panicle number and grain size in rice. Plant Biotechnol. J. 20, 1154–1166 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Tang, Z. X. et al. in Wild Crop Relatives: Genomic and Breeding Resources: Cereals (ed. Kole, C.) 367–396 (Springer Berlin Heidelberg, 2011).

  19. Liu, Y. et al. Past innovations and future possibilities in plant chromosome engineering. Plant Biotechnol. J. 23, 695–708 (2025).

    Article  CAS  PubMed  Google Scholar 

  20. Wang, C. et al. The Yr9 gene encoding a CC-NBS-LRR protein in the 1RS-1BL translocation confers wheat stripe rust resistance. Sci. China Life Sci. 68, 2804–2806 (2025).

    Article  PubMed  Google Scholar 

  21. Li, J. et al. Identification and characterization of a new stripe rust resistance gene Yr83 on rye chromosome 6R in wheat. Theor. Appl. Genet. 133, 1095–1107 (2020).

    Article  CAS  PubMed  Google Scholar 

  22. Li, G. et al. Molecular and cytogenetic dissection of stripe rust resistance gene Yr83 from rye 6R and generation of resistant germplasm in wheat breeding. Front. Plant Sci. 13, 1035784 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Duan, Y. et al. The physical location of stripe rust resistance genes on chromosome 6 of rye (Secale cereale L.) AR106BONE. Front. Plant Sci. 13, 928014 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  24. Rabanus-Wallace, M. T. et al. Chromosome-scale genome assembly provides insights into rye biology, evolution and agronomic potential. Nat. Genet. 53, 564–573 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Sun, Y. et al. Population genomic analysis reveals domestication of cultivated rye from weedy rye. Mol. Plant 15, 552–561 (2022).

    Article  CAS  PubMed  Google Scholar 

  26. Moskal, K., Kowalik, S., Podyma, W., Łapiński, B. & Boczkowska, M. The pros and cons of rye chromatin introgression into wheat genome. Agronomy 11, 456 (2021).

    Article  CAS  Google Scholar 

  27. Zhu, S. et al. Molecular cytogenetic analyses of two new wheat–rye 6RL translocation lines with resistance to wheat powdery mildew. Crop J. 11, 584–592 (2023).

    Article  CAS  Google Scholar 

  28. An, D. et al. Molecular cytogenetic identification of a new wheat–rye 6R chromosome disomic addition line with powdery mildew resistance. PLoS ONE 10, e0134534 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  29. Wen, A. et al. Genetic mapping of a major gene in triticale conferring resistance to bacterial leaf streak. Theor. Appl. Genet. 131, 649–658 (2018).

    Article  CAS  PubMed  Google Scholar 

  30. Dyda, M., Tyrka, M., Golebiowska, G., Rapacz, M. & Wedzony, M. Genetic mapping of adult-plant resistance genes to powdery mildew in triticale. J. Appl. Genet. 63, 73–86 (2022).

    Article  CAS  PubMed  Google Scholar 

  31. Karbarz, M. et al. Quantitative trait loci mapping of adult-plant resistance to powdery mildew in triticale. Ann. Appl. Biol. 177, 223–231 (2020).

    Article  CAS  Google Scholar 

  32. Wei, F., Wing, R. A. & Wise, R. P. Genome dynamics and evolution of the Mla (powdery mildew) resistance locus in barley. Plant Cell 14, 1903–1917 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Trognitz, F. C. & Trognitz, B. R. Survey of resistance gene analogs in Solanum caripense, a relative of potato and tomato, and update on R gene genealogy. Mol. Genet. Genom. 274, 595–605 (2005).

    Article  CAS  Google Scholar 

  34. Kim, S. et al. New reference genome sequences of hot pepper reveal the massive evolution of plant disease-resistance genes by retroduplication. Genome Biol. 18, 210 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  35. Murray, M. & Thompson, W. F. Rapid isolation of high molecular weight plant DNA. Nucleic Acids Res. 8, 4321–4325 (1980).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Maccaferri, M. et al. Durum wheat genome highlights past domestication signatures and future improvement targets. Nat. Genet. 51, 885–895 (2019).

    Article  CAS  PubMed  Google Scholar 

  37. Kato, A. et al. Chromosome painting for plant biotechnology. Methods Mol. Biol. 701, 67–96 (2011).

    Article  CAS  PubMed  Google Scholar 

  38. Han, F., Gao, Z. & Birchler, J. A. Reactivation of an inactive centromere reveals epigenetic and structural components for centromere specification in maize. Plant Cell 21, 1929–1939 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Bolger, A., Lohse, M. & Usadel, B. J. B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 30, 2114–2120 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics. 29, 15–21 (2013).

    Article  CAS  PubMed  Google Scholar 

  41. McKenna, A. et al. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 20, 1297–1303 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Mansfeld, B. & Grumet, R. QTLseqr: an R package for bulk segregant analysis with next-generation sequencing. Plant Genome 11, 180006 (2018).

    Article  Google Scholar 

  43. Kim, D., Paggi, J. M., Park, C., Bennett, C. & Salzberg, S. L. Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype. Nat. Biotechnol. 37, 907–915 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Pertea, M. et al. StringTie enables improved reconstruction of a transcriptome from RNA-seq reads. Nat. Biotechnol. 33, 290–295 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Frazee, A. C. et al. Ballgown bridges the gap between transcriptome assembly and expression analysis. Nat. Biotechnol. 33, 243–246 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Li, H. & Durbin, R. J. B. Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics. 25, 1754–1760 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Meng, L., Li, H., Zhang, L. & Wang, J. QTL IciMapping: integrated software for genetic linkage map construction and quantitative trait locus mapping in biparental populations. Crop J. 3, 269–283 (2015).

    Article  Google Scholar 

  48. Chen, H. et al. Firefly luciferase complementation imaging assay for protein–protein interactions in plants. Plant Physiol. 146, 368–376 (2008).

    Article  CAS  PubMed  Google Scholar 

  49. Chen, S., Zou, Y., Tong, X. & Xu, C. A tomato NBS-LRR gene Mi-9 confers heat-stable resistance to root-knot nematodes. J. Integr. Agric. 24, 2869–2875 (2025).

    Article  CAS  Google Scholar 

  50. Bai, X. et al. Transcription factor BZR2 activates chitinase Cht20.2 transcription to confer resistance to wheat stripe rust. Plant Physiol. 187, 2749–2762 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Bolser, D. M., Staines, D. M., Perry, E. & Kersey, P. J. Ensembl Plants: integrating tools for visualizing, mining, and analyzing plant genomic data. Methods Mol. Biol. 1533, 115–140 (2017).

    Google Scholar 

  52. Yuan, S., Chan, H. C. S., Filipek, S. & Vogel, H. PyMOL and Inkscape bridge the data and the data visualization. Structure 24, 2041–2042 (2016).

    Article  CAS  PubMed  Google Scholar 

  53. Emsley, P., Lohkamp, B., Scott, W. G. & Cowtan, K. Features and development of Coot. Acta Crystallogr. D Biol. Crystallogr. 66, 486–501 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Quinlan, A. R. & Hall, I. M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841–842 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. R Core Team. R: a language and environment for statistical computing. MSOR Connections 1, (2014).

  56. Yu, G., Lam, T. T., Zhu, H. & Guan, Y. Two methods for mapping and visualizing associated data on phylogeny using Ggtree. Mol. Biol. Evol. 35, 3041–3043 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Kumar, S., Stecher, G., Li, M., Knyaz, C. & Tamura, K. MEGA X: molecular evolutionary genetics analysis across computing platforms. Mol. Biol. Evol. 35, 1547–1549 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Ramírez, F., Dündar, F., Diehl, S., Grüning, B. A. & Manke, T. deepTools: a flexible platform for exploring deep-sequencing data. Nucleic Acids Res. 42, W187–191 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank Z. Ni (China Agricultural University) for providing the triticale germplasm, C. Xu (IGDB, CAS) for providing the MiC-4 expression plasmid, Y. Chen (IGDB, CAS) for his contributions to the protein structure prediction and model assembly, Z. Liu (IGDB, CAS) for providing field mixtures of Pst and Q. Li (Northwest A&F University) for providing Pst races. This work was supported by the National Key Research and Development Program of China (grant no. 2022YFF1003303 to F.H.) and the ‘Biological Breeding—National Science and Technology Major Project’ (grant no. 2023ZD04025 to F.H.).

Author information

Author notes

  1. These authors contributed equally: Chunhui Wang, Shulan Fu, Congyang Yi.

Authors and Affiliations

  1. State Key Laboratory of Seed Innovation, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China

    Chunhui Wang, Congyang Yi, Mian Wang, Chen Zhou, Zhen Wang, Renchun Fan, Jing Yuan, Yang Liu & Fangpu Han

  2. College of Advanced Agricultural Sciences, University of the Chinese Academy of Sciences, Beijing, China

    Chunhui Wang, Congyang Yi, Mian Wang, Chen Zhou, Zhen Wang & Fangpu Han

  3. College of Agronomy, Sichuan Agricultural University, Chengdu, China

    Shulan Fu

  4. Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China

    Yanan Chang & Xingguo Ye

  5. Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China

    Tao Wang

  6. School of Life Science, Shandong Agricultural University, Taian, China

    Yonghong Wang

  7. Crop Research Institute, Sichuan Academy of Agricultural Sciences, Chengdu, China

    Wuyun Yang

Authors
  1. Chunhui Wang
    View author publications

    Search author on:PubMed Google Scholar

  2. Shulan Fu
    View author publications

    Search author on:PubMed Google Scholar

  3. Congyang Yi
    View author publications

    Search author on:PubMed Google Scholar

  4. Yanan Chang
    View author publications

    Search author on:PubMed Google Scholar

  5. Mian Wang
    View author publications

    Search author on:PubMed Google Scholar

  6. Chen Zhou
    View author publications

    Search author on:PubMed Google Scholar

  7. Zhen Wang
    View author publications

    Search author on:PubMed Google Scholar

  8. Renchun Fan
    View author publications

    Search author on:PubMed Google Scholar

  9. Jing Yuan
    View author publications

    Search author on:PubMed Google Scholar

  10. Tao Wang
    View author publications

    Search author on:PubMed Google Scholar

  11. Yonghong Wang
    View author publications

    Search author on:PubMed Google Scholar

  12. Wuyun Yang
    View author publications

    Search author on:PubMed Google Scholar

  13. Yang Liu
    View author publications

    Search author on:PubMed Google Scholar

  14. Xingguo Ye
    View author publications

    Search author on:PubMed Google Scholar

  15. Fangpu Han
    View author publications

    Search author on:PubMed Google Scholar

Contributions

F.H. and C.W. designed the research. C.W. contributed to the execution and analysis of most of the experiments. S.F. created the translocation line 6R/6A and characterized its agronomic traits. C.Y. and M.W. were responsible for the genome resequencing data and transcriptome analysis. Y.C. did the genetic transformation of wheat under the guidance of X.Y. C.Z., J.Y. and Y.L. provided assistance with GISH technology, genetic marker development and protein work, respectively. Z.W. and T.W. helped characterize stripe rust resistance in the field. R.F., Y.W., and W.Y. provided constructive suggestions for this work. F.H., X.Y. and Y.L. supervised this study. F.H., Y.L. and C.W. wrote the final version of the paper.

Corresponding authors

Correspondence to Yang Liu, Xingguo Ye or Fangpu Han.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Plants thanks Jorge Dubcovsky, Joshua Hegarty, Yinghui Li and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wang, C., Fu, S., Yi, C. et al. An NLR–transposase fusion gene from rye provides broadly effective resistance to stripe rust in wheat. Nat. Plants (2026). https://doi.org/10.1038/s41477-026-02248-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Version of record:

  • DOI: https://doi.org/10.1038/s41477-026-02248-1

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing