Population genomic analyses reveal extensive genomic regions within selective sweeps associated with adaptation and demographic history of a wheat fungal pathogen

Abstract

Plant pathogens rapidly evolve in response to changes in their hosts and environments, resulting in destructive epidemics. The fungus Puccinia striiformis f. sp. tritici (Pst), responsible for wheat stripe rust disease, exemplifies such evolutionary dynamics. Host population changes impose selective pressures on pathogens; however, the selection footprints and demographic patterns of Pst are not well understood. In this study, we performed whole-genome sequencing of 69 Pst isolates collected from diverse regions across China to investigate genome-wide patterns of gene flow and divergence. Our findings reveal significant gene flow within China but limited exchange between Chinese and international Pst populations, characterized by a slower decay of linkage disequilibrium compared to fungi with known sexual reproduction. We identified extensive hard and soft sweeps associated with Pst adaptation. The genes involved in these sweeps are enriched for secreted proteins and effectors, with functions related to pathogenicity, temperature tolerance, and fungicide resistance, indicating positive selection driven by both host and abiotic pressures. Demographic reconstruction shows strong bottlenecks in Pst populations during the domestication of wheat approximately 10,000 years ago and the advent of modern agriculture 100 years ago, suggesting that crop domestication and breeding programs have significantly influenced pathogen population dynamics. Our study provides valuable insights into the genomic evolution of Pst in China and highlights the impact of modern agricultural practices on pathogen demography.

Keywords

demographic history / population genomics / Puccinia striiformis f. sp. tritici / selective sweeps / wheat stripe rust

References

[1] Velásquez, A. C., Castroverde, C. D. M., & He, S. Y. (2018). Plant-pathogen warfare under changing climate conditions. Current Biology, 28(10), 619-634. https://doi.org/10.1016/j.cub.2018.03.054

[2] Ristaino, J. B., Anderson, P. K., Bebber, D. P., Brauman, K. A., Cunniffe, N. J., Fedoroff, N. V., Finegold, C., Garrett, K. A., Gilligan, C. A., Jones, C. M., Martin, M. D., MacDonald, G. K., Neenan, P., Records, A., Schmale, D. G., Tateosian, L., & Wei, Q. (2021). The persistent threat of emerging plant disease pandemics to global food security. Proceedings of the National Academy of Sciences of the USA, 118(23), e2022239118. https://doi.org/10.1073/PNAS.2022239118

[3] Croll, D., & McDonald, B. A. (2017). The genetic basis of local adaptation for pathogenic fungi in agricultural ecosystems. Molecular Ecology, 26(7), 2027-2040. https://doi.org/10.1111/mec.13870

[4] Wan, A. M., Chen, X. M., & He, Z. H. (2007). Wheat stripe rust in China. Australian Journal of Agricultural Research, 58(6), 605-619. https://doi.org/10.1071/AR06142

[5] Milus, E. A., Kristensen, K., & Hovmøller, M. S. (2008). Evidence for increased aggressiveness in a recent widespread strain of Puccinia striiformis f. sp. tritici causing stripe rust of wheat. Phytopathology, 99(1), 89-94. https://doi.org/10.1094/PHYTO-99-1-0089

[6] Estep, L. K., Torriani, S. F. F., Zala, M., Anderson, N. P., Flowers, M. D., McDonald, B. A., Mundt, C. C., & Brunner, P. C. (2015). Emergence and early evolution of fungicide resistance in North American populations of Zymoseptoria tritici. Plant Pathology, 64(4), 961-971. https://doi.org/10.1111/ppa.12314

[7] Gladieux, P., Feurtey, A., Hood, M. E., Snirc, A., Clavel, J., Dutech, C., Roy, M., & Giraud, T. (2015). The population biology of fungal invasions. Molecular Ecology, 24(9), 1969-1986. https://doi.org/10.1111/mec.13028

[8] Chen, W. Q., Kang, Z. S., Ma, Z. H., Xu, S. C., Jin, S. L., & Jiang, Y. Y. (2013). Integrated management of wheat stripe rust caused by Puccinia striiformis f. sp. tritici in China. Scientia Agricultura Sinica, 46(20), 4254-4262. https://doi.org/10.3864/j.issn.0578-1752.2013.20.008

[9] Jin, Y., Szabo, L. J., & Carson, M. (2010). Century-old mystery of Puccinia striiformis life history solved with the identification of Berberis as an alternate host. Phytopathology, 100(5), 432-435. https://doi.org/10.1094/PHYTO-100-5-0432

[10] Zhao, J., & Kang, Z. (2023). Fighting wheat rusts in China: A look back and into the future. Phytopathology Research, 5(1), 6. https://doi.org/10.1186/s42483-023-00159-z

[11] Zhao, J., Wang, M. N., Chen, X. M., & Kang, Z. S. (2016). Role of alternate hosts in epidemiology and pathogen variation of cereal rusts. Annual Review of Phytopathology, 54(1), 207-228. https://doi.org/10.1146/annurev-phyto-080615-095851

[12] Chen, X. M. (2014). Integration of cultivar resistance and fungicide application for control of wheat stripe rust. Canadian Journal of Plant Pathology, 36(3), 311-326. https://doi.org/10.1080/07060661.2014.924560

[13] Milus, E. A., Seyran, E., & McNew, R. (2006). Aggressiveness of Puccinia striiformis f. sp. tritici isolates in the south-central United States. Plant Disease, 90(7), 847-852. https://doi.org/10.1094/PD-90-0847

[14] Esmail, S. M., Draz, I. S., Ashmawy, M. A., & El-Orabey, W. M. (2021). Emergence of new aggressive races of Puccinia striiformis f. sp. tritici causing yellow rust epiphytotic in Egypt. Physiological and Molecular Plant Pathology, 114(1), 101612. https://doi.org/10.1016/j.pmpp.2021.101612

[15] Wellings, C. R. (2011). Global status of stripe rust: A review of historical and current threats. Euphytica, 179(1), 129-141. https://doi.org/10.1007/s10681-011-0360-y

[16] Chen, W. Q., Wu, L. R., Liu, T. G., Xu, S. C., Jin, S. L., Peng, Y. L., & Wang, B. T. (2009). Race dynamics, diversity, and virulence evolution in Puccinia striiformis f. sp. tritici, the causal agent of wheat stripe rust in China from 2003 to 2007. Plant Disease, 93(11), 1093-1101. https://doi.org/10.1094/PDIS-93-11-1093

[17] Liu, B., Liu, T. G., Zhang, Z. Y., Jia, Q. Z., Wang, B. T., Gao, L., Peng, Y. L., Jin, S. L., & Chen, W. Q. (2017). Discovery and pathogenicity of CYR34, a new race of Puccinia striiformis f. sp. tritici in China. Acta Phytopathologica Sinica, 47, 681-687. https://doi.org/10.13926/j.cnki.apps.000071

[18] Hovmøller, M. S., Walter, S., Bayles, R. A., Hubbard, A., Flath, K., Sommerfeldt, N., Leconte, M., Czembor, P., Rodriguez-Algaba, J., Thach, T., Hansen, J. G., Lassen, P., Justesen, A. F., Ali, S., & de Vallavieille-Pope, C. (2016). Replacement of the European wheat yellow rust population by new races from the centre of diversity in the near-Himalayan region. Plant Pathology, 65(3), 402-411. https://doi.org/10.1111/ppa.12433

[19] Zeng, S. M., & Luo, Y. (2008). Systems analysis of wheat stripe rust epidemics in China. European Journal of Plant Pathology, 121(4), 425-438. https://doi.org/10.1007/s10658-007-9267-9

[20] Zeng, S. M., & Luo, Y. (2006). Long-distance spread and interregional epidemics of wheat stripe rust in China. Plant Disease, 90(8), 980-988. https://doi.org/10.1094/PD-90-0980

[21] Ali, S., Gladieux, P., Leconte, M., Gautier, A., Justesen, A. F., Hovmøller, M. S., Enjalbert, J., & de Vallavieille-Pope, C. (2014). Origin, migration routes and worldwide population genetic structure of the wheat yellow rust pathogen Puccinia striiformis f. sp. tritici. PLoS Pathogens, 10(1), e1003903. https://doi.org/10.1371/journal.ppat.1003903

[22] Ding, Y., Cuddy, W. S., Wellings, C. R., Zhang, P., Thach, T., Hovmøller, M. S., Qutob, D., Brar, G. S., Kutcher, H. R., & Park, R. F. (2021). Incursions of divergent genotypes, evolution of virulence and host jumps shape a continental clonal population of the stripe rust pathogen Puccinia striiformis. Molecular Ecology, 30(24), 6566-6584. https://doi.org/10.1111/mec.16182

[23] Jones, J. D., & Dangl, J. L. (2006). The plant immune system. Nature, 444(7117), 323-329. https://doi.org/10.1038/nature05286

[24] Giraldo, M. C., & Valent, B. (2013). Filamentous plant pathogen effectors in action. Nature Reviews Microbiology, 11(11), 800-814. https://doi.org/10.1038/nrmicro3119

[25] Presti, L. L., Lanver, D., Schweizer, G., Tanaka, S., Liang, L., Tollot, M., Zuccaro, A., Reissmann, S., & Kahmann, R. (2015). Fungal effectors and plant susceptibility. Annual Review of Plant Biology, 66(1), 513-545. https://doi.org/10.1146/annurev-arplant-043014-114623

[26] Vitti, J. J., Grossman, S. R., & Sabeti, P. C. (2013). Detecting natural selection in genomic data. Annual Review of Genetics, 47(1), 97-120. https://doi.org/10.1146/annurev-genet-111212-133526

[27] Everhart, S., Gambhir, N., & Stam, R. (2020). Population genomics of filamentous plant pathogens-A brief overview of research questions, approaches, and pitfalls. Phytopathology, 111(1), 12-22. https://doi.org/10.1094/PHYTO-11-20-0527-FI

[28] Badouin, H., Gladieux, P., Gouzy, J., Siguenza, S., Aguileta, G., Snirc, A., Le Prieur, S., Jeziorski, C., Branca, A., & Giraud, T. (2017). Widespread selective sweeps throughout the genome of model plant pathogenic fungi and identification of effector candidates. Molecular Ecology, 26(7), 2041-2062. https://doi.org/10.1111/mec.13976

[29] Duan, X., Tellier, A., Wan, A., Leconte, M., de Vallavieille-Pope, C., & Enjalbert, J. (2010). Puccinia striiformis f. sp. tritici presents high diversity and recombination in the over-summering zone of Gansu, China. Mycologia, 102(1), 44-53. https://doi.org/10.3852/08-098

[30] Hartmann, F. E., McDonald, B. A., & Croll, D. (2018). Genome-wide evidence for divergent selection between populations of a major agricultural pathogen. Molecular Ecology, 27(12), 2725-2741. https://doi.org/10.1111/mec.14711

[31] Mohd-Assaad, N., McDonald, B. A., & Croll, D. (2018). Genome-wide detection of genes under positive selection in worldwide populations of the barley scald pathogen. Genome Biology and Evolution, 10(5), 1315-1332. https://doi.org/10.1093/gbe/evy087

[32] Grandaubert, J., Dutheil, J. Y., & Stukenbrock, E. H. (2019). The genomic determinants of adaptive evolution in a fungal pathogen. Evolution Letters, 3(3), 299-312. https://doi.org/10.1002/evl3.117

[33] Miller, M. E., Nazareno, E. S., Rottschaefer, S. M., Riddle, J., Pereira, D., Li, F., Nguyen-Phuc, H., Henningsen, E. C., Persoons, A., Saunders, D. G. O., Stukenbrock, E., Dodds, P. N., Kianian, S. F., & Figueroa, M. (2020). Increased virulence of Puccinia coronata f. sp. avenae populations through allele frequency changes at multiple putative Avr loci. PLoS Genetics, 16(12), e1009291. https://doi.org/10.1371/journal.pgen.1009291

[34] Schweizer, G., Haider, M. B., Barroso, G. V., Rössel, N., Münch, K., Kahmann, R., & Dutheil, J. Y. (2020). Population genomics of the maize pathogen Ustilago maydis: Demographic history and role of virulence clusters in adaptation. Genome Biology and Evolution, 3(5), evab073. https://doi.org/10.1093/gbe/evab073

[35] Milla, R., Osborne, C. P., Turcotte, M. M., & Violle, C. (2015). Plant domestication through an ecological lens. Trends in Ecology & Evolution, 30(8), 463-469. https://doi.org/10.1016/j.tree.2015.06.006

[36] Silk, M. J., & Hodgson, D. J. (2020). Life history and population regulation shape demographic competence and influence the maintenance of endemic disease. Nature Ecology & Evolution, 5(1), 82-91. https://doi.org/10.1038/s41559-020-01333-8

[37] Grünwald, N. J., McDonald, B. A., & Milgroom, M. G. (2016). Population genomics of fungal and oomycete pathogens. Annual Review of Phytopathology, 54(1), 323-346. https://doi.org/10.1146/annurev-phyto-080614-115913

[38] Beichman, A. C., Huerta-Sanchez, E., & Lohmueller, K. E. (2018). Using genomic data to infer historic population dynamics of nonmodel organisms. Annual Review of Ecology, Evolution and Systematics, 49(1), 433-456. https://doi.org/10.1146/annurev-ecolsys-110617-062431

[39] Skrede, I., Murat, C., Hess, J., Maurice, S., Snsteb, J. H., Kohler, A., Barry-Etienne, D., Eastwood, D., Högberg, N., Martin, F., & Kauserud, H. (2021). Contrasting demographic histories revealed in two invasive populations of the dry rot fungus Serpula lacrymans. Molecular Ecology, 30(12), 2772-2789. https://doi.org/10.1111/mec.15934

[40] Kozhar, O., Kim, M. S., Ibarra Caballero, J., Klopfenstein, N. B., Cannon, P. G., & Stewart, J. E. (2022). Long evolutionary history of an emerging fungal pathogen of diverse tree species in eastern Asia, Australia and the Pacific Islands. Molecular Ecology, 31(7), 2013-2031. https://doi.org/10.1111/mec.16384

[41] Liu, T. G., Peng, Y. L., Chen, W. Q., & Zhang, Z. Y. (2010). First detection of virulence in Puccinia striiformis f. sp. tritici in China to resistance genes Yr24 (=Yr26) present in wheat cultivar Chuanmai 42. Plant Disease, 94(9), 1163. https://doi.org/10.1094/PDIS-94-9-1163C

[42] Hubbard, A., Lewis, C. M., Yoshida, K., Ramirez-Gonzalez, R. H., De Vallavieille-Pope, C., Thomas, J., Kamoun, S., Bayles, R., Uauy, C., & Saunders, D. G. (2015). Field pathogenomics reveals the emergence of a diverse wheat yellow rust population. Genome Biology, 16(1), 23. https://doi.org/10.1186/s13059-015-0590-8

[43] Cuomo, C. A., Bakkeren, G., Khalil, H. B., Panwar, V., Joly, D., Linning, R., Sakthikumar, S., Song, X., Adiconis, X., Fan, L., Goldberg, J. M., Levin, J. Z., Young, S., Zeng, Q., Anikster, Y., Bruce, M., Wang, M., Yin, C., McCallum, B., … Fellers, J. P. (2017). Comparative analysis highlights variable genome content of wheat rusts and divergence of the mating loci. G3 (Bethesda), 7(2), 361-376. https://doi.org/10.1534/g3.116.032797

[44] Kiran, K., Rawal, H. C., Dubey, H., Jaswal, R., Bhardwaj, S. C., Prasad, P., Pal, D., Devanna, B. N., & Sharma, T. R. (2017). Dissection of genomic features and variations of three pathotypes of Puccinia striiformis through whole genome sequencing. Scientific Reports, 7(1), 42419. https://doi.org/10.1038/srep42419

[45] Schwessinger, B., Sperschneider, J., Cuddy, W. S., Garnica, D. P., Miller, M. E., Taylor, J. M., Dodds, P. N., Figueroa, M., Park, R. F., & Rathjen, J. P. (2018). A near-complete haplotype-phased genome of the dikaryotic wheat stripe rust fungus Puccinia striiformis f. sp. tritici reveals high interhaplotype diversity. mBio, 9(1), 022755-17. https://doi.org/10.1128/mBio.02275-17

[46] Schwessinger, B., Chen, Y. J., Tien, R., Vogt, J. K., Sperschneider, J., Nagar, R., McMullan, M., Sicheritz-Ponten, T., Sørensen, C. K., Hovmøller, M. S., Rathjen, J. P., & Justesen, A. F. (2020). Distinct life histories impact dikaryotic genome evolution in the rust fungus Puccinia striiformis causing stripe rust in wheat. Genome Biology and Evolution, 12(5), 597-617. https://doi.org/10.1093/gbe/evaa071

[47] Li, Y., Xia, C., Wang, M., Yin, C., & Chen, X. (2019). Genome sequence resource of a puccinia striiformis isolate infecting wheatgrass. Phytopathology, 109(9), 1509-1512. https://doi.org/10.1094/PHYTO-02-19-0054-A

[48] Schalkwyk, H. J., Adams, T., Persoons, A., Boshoff, W. H. P., Wanyera, R., Hovmøller, M. S., Saunders, D. G. O., Boyd, L., Pretorius, Z. A., & Prins, R. (2021). Pathogenomic analyses of Puccinia striiformis f. sp. tritici supports a close genetic relationship between South and East Africa. Plant Pathology, 71(2), 279-288. https://doi.org/10.1111/PPA.13468

[49] Chen, X. M., Line, R. F., & Leung, H. (1993). Relationship between virulence variation and DNA polymorphism in Puccinia striiformis. Phytopathology, 83(12), 1489-1497. https://doi.org/10.1094/Phyto-83-1489

[50] Bolger, A. M., Lohse, M., & Usadel, B. (2014). Trimmomatic: A flexible trimmer for Illumina sequence data. Bioinformatics, 30(15), 2114-2120. https://doi.org/10.1093/bioinformatics/btu170

[51] Xia, C., Huang, L., Huang, J., Zhang, H., Huang, Y., Benhamed, M., Wang, M., Chen, X., Zhang, M., Liu, T., & Chen, W. (2022). Folding features and dynamics of 3D genome architecture in plant fungal pathogens. Microbiology Spectrum, 10(6), e0260822. https://doi.org/10.1128/spectrum.02608-22

[52] Li, H., & Durbin, R. (2010). Fast and accurate long-read alignment with Burrows-Wheeler transform. Bioinformatics, 26(5), 589-595. https://doi.org/10.1093/bioinformatics/btp698

[53] Li, H. (2011). A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data. Bioinformatics, 27(21), 2987-2993. https://doi.org/10.1093/bioinformatics/btr509

[54] Garcia-Alcalde, F., Okonechnikov, K., Carbonell, J., Cruz, L. M., Gotz, S., Tarazona, S., Dopazo, J., Meyer, T. F., & Conesa, A. (2012). Qualimap: Evaluating next-generation sequencing alignment data. Bioinformatics, 28(20), 2678-2679. https://doi.org/10.1093/bioinformatics/bts503

[55] DePristo, M. A., Banks, E., Poplin, R., Garimella, K. V., Maguire, J. R., Hartl, C., Philippakis, A. A., Del Angel, G., Rivas, M. A., Hanna, M., McKenna, A., Fennell, T. J., Kernytsky, A. M., Sivachenko, A. Y., Cibulskis, K., Gabriel, S. B., Altshuler, D., & Daly, M. J. (2011). A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nature Genetics, 43(5), 491-498. https://doi.org/10.1038/ng.806

[56] Danecek, P., Auton, A., Abecasis, G., Albers, C. A., Banks, E., DePristo, M. A., Handsaker, R. E., Lunter, G., Marth, G. T., Sherry, S. T., McVean, G., & Durbin, R. (2011). The variant call format and VCFtools. Bioinformatics, 27(15), 2156-2158. https://doi.org/10.1093/bioinformatics/btr330

[57] Yang, J., Lee, S. H., Goddard, M. E., & Visscher, P. M. (2011). GCTA: A tool for genome-wide complex trait analysis. American Journal of Human Genetics, 88(1), 76-82. https://doi.org/10.1016/j.ajhg.2010.11.011

[58] Alexander, D. H., Novembre, J., & Lange, K. (2009). Fast model-based estimation of ancestry in unrelated individuals. Genome Research, 19(9), 1655-1664. https://doi.org/10.1101/gr.094052.109

[59] Tajima, F. (1989). The effect of change in population size on DNA polymorphism. Genetics, 123(3), 597-601. https://doi.org/10.1093/genetics/123.3.597

[60] Xia, C., Lei, Y., Wang, M., Chen, W., & Chen, X. (2020). An avirulence gene cluster in the wheat stripe rust pathogen (Puccinia striiformis f. sp. tritici) identified through genetic mapping and whole-genome sequencing of a sexual population. mSphere, 5(3), 001288-20. https://doi.org/10.1128/mSphere.00128-20

[61] Guo, Y., Betzen, B., Salcedo, A., He, F., Bowden, R. L., Fellers, J. P., Jordan, K. W., Akhunova, A., Rouse, M. N., Szabo, L. J., & Akhunov, E. (2022). Population genomics of Puccinia graminis f. sp. tritici highlights the role of admixture in the origin of virulent wheat rust races. Nature Communications, 13(1), 6287. https://doi.org/10.1038/s41467-022-34050-w

[62] Leonard, K. J., & Szabo, L. J. (2005). Stem rust of small grains and grasses caused by Puccinia graminis. Molecular Plant Pathology, 6(2), 99-111. https://doi.org/10.1111/j.1364-3703.2005.00273.x

[63] Wang, M. N., Wan, A. M., & Chen, X. M. (2015). Barberry as alternate host is important for Puccinia graminis f. sp. tritici but not for Puccinia striiformis f. sp. tritici in the U.S. Pacific Northwest. Plant Disease, 99(11), 1507-1516. https://doi.org/10.1094/PDIS-12-14-1279-RE

[64] Garud, N. R. (2023). Understanding soft sweeps: A signature of rapid adaptation. Nature Reviews Genetics, 24(7), 420. https://doi.org/10.1038/s41576-023-00585-x

[65] Pavlidis, P., Zivkovic, D., Stamatakis, A., & Alachiotis, N. (2013). SweeD: Likelihood-based detection of selective sweeps in thousands of genomes. Molecular Biology and Evolution, 30(9), 2224-2234. https://doi.org/10.1093/molbev/mst112

[66] Delaneau, O., Zagury, J. F., Robinson, M. R., Marchini, J. L., & Dermitzakis, E. T. (2019). Accurate, scalable and integrative haplotype estimation. Nature Communications, 10(1), 5436. https://doi.org/10.1038/s41467-019-13225-y

[67] Pavlidis, P., & Alachiotis, N. (2017). A survey of methods and tools to detect recent and strong positive selection. Journal of Biological Research-Thessaloniki, 24(1), 7. https://doi.org/10.1186/s40709-017-0064-0

[68] Nielsen, R. (2005). Molecular signatures of natural selection. Annual Review of Genetics, 39(1), 197-218. https://doi.org/10.1146/annurev.genet.39.073003.112420

[69] Chen, G. K., Marjoram, P., & Wall, J. D. (2009). Fast and flexible simulation of DNA sequence data. Genome Research, 19(1), 136-142. https://doi.org/10.1101/gr.083634

[70] Gautier, M., Klassmann, A., & Vitalis, R. (2017). rehh 2.0: A reimplementation of the R package rehh to detect positive selection from haplotype structure. Molecular Ecology Resources, 17(1), 78-90. https://doi.org/10.1111/1755-0998.12634

[71] Wu, T., Hu, E., Xu, S., Chen, M., Guo, P., Dai, Z., Feng, T., Zhou, L., Tang, W., Zhan, L., Fu, X., Liu, S., Bo, X., & Yu, G. (2021). clusterProfiler 4.0: A universal enrichment tool for interpreting omics data. Innovation (Camb), 2(3), 100141. https://doi.org/10.1016/j.xinn.2021.100141

[72] Terhorst, J., Kamm, J. A., & Song, Y. S. (2017). Robust and scalable inference of population history from hundreds of unphased whole genomes. Nature Genetics, 49(2), 303-309. https://doi.org/10.1038/ng.3748

[73] Xia, C., Wang, M., Yin, C., Cornejo, O. E., Hulbert, S. H., & Chen, X. (2018). Genomic insights into host adaptation between the wheat stripe rust pathogen (Puccinia striiformis f. sp. tritici) and the barley stripe rust pathogen (Puccinia striiformis f. sp. hordei). BMC Genomics, 19(1), 664. https://doi.org/10.1186/s12864-018-5041-y

[74] Jones, P., Binns, D., Chang, H. Y., Fraser, M., Li, W., McAnulla, C., McAnulla, C., McWilliam, Ha., Maslen, J., Mitchell, A., Nuka, G., Pesseat, S., Quinn, A. F., Sangrador-Vegas, A., Scheremetjew, M., Yong, S. Y., Lopez, R., & Hunter, S. (2014). InterProScan 5: Genome-scale protein function classification. Bioinformatics, 30(9), 1236-1240. https://doi.org/10.1093/bioinformatics/btu031

[75] Petersen, T. N., Brunak, S., von Heijne, G., & Nielsen, H. (2011). SignalP 4.0: Discriminating signal peptides from transmembrane regions. Nature Methods, 8(10), 785-786. https://doi.org/10.1038/nmeth.1701

[76] Krogh, A., Larsson, B., von Heijne, G., & Sonnhammer, E. L. L. (2001). Predicting transmembrane protein topology with a hidden Markov model: Application to complete genomes. Journal of Molecular Biology, 305(3), 567-580. https://doi.org/10.1006/jmbi.2000.4315

[77] Urban, M., Cuzick, A., Seager, J., Wood, V., Rutherford, K., Venkatesh, S. Y., De Silva, N., Martinez, M. C., Pedro, H., Yates, A. D., Hassani-Pak, K., & Hammond-Kosack, K. E. (2020). PHI-base: The pathogen-host interactions database. Nucleic Acids Research, 48(1), 613-620. https://doi.org/10.1093/nar/gkz904

[78] Yu, G., Wang, L. G., Han, Y., & He, Q. Y. (2012). clusterProfiler: An R package for comparing biological themes among gene clusters. OMICS, 16(5), 284-287. https://doi.org/10.1089/omi.2011.0118

[79] Upadhyaya, N. M., Garnica, D. P., Karaoglu, H., Sperschneider, J., Nemri, A., Xu, B., Mago, R., Cuomo, C. A., Rathjen, J. P., Park, R. F., Ellis, J. G., & Dodds, P. N. (2015). Comparative genomics of Australian isolates of the wheat stem rust pathogen Puccinia graminis f. sp. tritici reveals extensive polymorphism in candidate effector genes. Frontiers in Plant Science, 5, 759. https://doi.org/10.3389/fpls.2014.00759

[80] Upadhaya, A., Upadhaya, S. G. C., & Brueggeman, R. (2024). Association mapping with a diverse population of Puccinia graminis f. sp. tritici identified avirulence loci interacting with the barley Rpg1 stem rust resistance gene. BMC Genomics, 25(1), 751. https://doi.org/10.1186/s12864-024-10670-y

[81] Stubbs, R. W. (1985). Stripe rust: Diseases, distribution, epidemiology, and control (pp. 61–101). Academic Press. https://doi.org/10.1016/B978-0-12-148402-6.50011-0

[82] Chen, W., Zhang, Z., Chen, X., Meng, Y., Huang, L., Kang, Z., & Zhao, J. (2021). Field production, germinability, and survival of Puccinia striiformis f. sp. tritici teliospores in China. Plant Disease, 105(8), 2122-2128. https://doi.org/10.1094/PDIS-09-20-2018-RE

[83] Wang, Z., Zhao, J., Chen, X., Peng, Y., Ji, J., Zhao, S., Lv, Y., Huang, L., & Kang, Z. (2016). Virulence variations of Puccinia striiformis f. sp. tritici isolates collected from Berberis spp. in China. Plant Disease, 100(1), 131-138. https://doi.org/10.1094/PDIS-12-14-1296-RE

[84] Li, M. J., Zhang, Y. H., Chen, W. Q., Duan, X. Y., Liu, T. G., Jia, Q. Z., Cao, S. Q., & Xu, Z. (2021). Evidence for Yunnan as the major origin center of the dominant wheat fungal pathogen Puccinia striiformis f. sp. tritici. Australasian Plant Pathology, 50(2), 241-252. https://doi.org/10.1007/s13313-020-00770-0

[85] Barrett, L. G., Thrall, P. H., Dodds, P. N., van der Merwe, M., Linde, C. C., Lawrence, G. J., & Burdon, J. J. (2009). Diversity and evolution of effector loci in natural populations of the plant pathogen Melampsora lini. Molecular Biology and Evolution, 26(11), 2499-2513. https://doi.org/10.1093/molbev/msp166

[86] Richards, J. K., Stukenbrock, E. H., Carpenter, J., Liu, Z. H., Cowger, C., Faris, J. D., Faris, J. D., & Friesen, T. L. (2019). Local adaptation drives the diversification of effectors in the fungal wheat pathogen Parastagonospora nodorum in the United States. PLoS Genetics, 15(10), e1008223. https://doi.org/10.1371/journal.pgen.1008223

[87] Wang, X., Yang, B., Li, K., Kang, Z., Cantu, D., & Dubcovsky, J. (2016). A conserved Puccinia striiformis protein interacts with wheat NPR1 and reduces induction of pathogenesis-related genes in response to pathogens. Molecular Plant-Microbe Interactions, 29(12), 977-989. https://doi.org/10.1094/MPMI-10-16-0207-R

[88] Zhu, X., Guo, J., He, F., Zhang, Y., Tan, C., Yang, Q., Huang, C., Kang, Z., & Guo, J. (2018). Silencing PsKPP4, a MAP kinase kinase kinase gene, reduces pathogenicity of the stripe rust fungus. Molecular Plant Pathology, 19(12), 2590-2602. https://doi.org/10.1111/mpp.12731

[89] Stergiopoulos, I., Zwiers, L. H., & De Waard, M. A. (2002). Secretion of natural and synthetic toxic compounds from filamentous fungi by membrane transporters of the ATP-binding cassette and major facilitator superfamily. European Journal of Plant Pathology, 108(7), 719-734. https://doi.org/10.1023/A:1020604716500

[90] Roohparvar, R., De Waard, M. A., Kema, G. H. J., & Zwiers, L. H. (2007). MgMfs1, a major facilitator superfamily transporter from the fungal wheat pathogen Mycosphaerella graminicola, is a strong protectant against natural toxic compounds and fungicides. Fungal Genetics and Biology, 44(5), 378-388. https://doi.org/10.1016/j.fgb.2006.09.007

[91] Rödel, C., Kirchhoff, S., & Schmidt, H. (1992). The protein sequence and some intron positions are conserved between the switching gene swi10 of Schizosaccharomyces pombe and the human excision repair gene ERCC1. Nucleic Acids Research, 20(23), 6347-6353. https://doi.org/10.1093/nar/20.23.6347

[92] Rödel, C., Jupitz, T., & Schmidt, H. (1997). Complementation of the DNA repair-deficient swi10 mutant of fission yeast by the human ERCC1 gene. Nucleic Acids Research, 25(14), 2823-2827. https://doi.org/10.1093/nar/25.14.2823

[93] Tiwari, S., Thakur, R., & Shankar, J. (2015). Role of heat-shock proteins in cellular function and in the biology of fungi. Biotechnology Research International, 2015, 1326355. https://doi.org/10.1155/2015/132635

[94] Lev-Yadun, S., Gopher, A., & Abbo, S. (2000). The cradle of agriculture. Science, 288(5471), 1602-1603. https://doi.org/10.1126/science.288.5471.1602

[95] Levy, A. A., & Moshe, F. (2022). Evolution and origin of bread wheat. The Plant Cell, 34(7), 2549-2567. https://doi.org/10.1093/plcell/koac130

[96] Venske, E., Dos Santos, R. S., Busanello, C., Gustafson, P., & Costa de Oliveira, A. (2019). Bread wheat: A role model for plant domestication and breeding. Hereditas, 156(1), 16. https://doi.org/10.1186/s41065-019-0093-9

[97] Biffen, R. H. (1905). Mendel's laws of inheritance and wheat breeding. The Journal of Agricultural Science, 1(1), 4-48. https://doi.org/10.1017/S0021859600000137

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