Abstract
Plants deploy cell-surface pattern recognition receptors (PRRs) and intracellular nucleotide-binding site–leucine-rich repeat receptors (NLRs) to recognize pathogens. However, how plant immune receptor repertoires evolve in responding to changed pathogen burdens remains elusive. Here we reveal the convergent reduction of NLR repertoires in plants with diverse special lifestyles/habitats (SLHs) encountering low pathogen burdens. Furthermore, a parallel but milder reduction of PRR genes in SLH species was observed. The reduction of PRR and NLR genes was attributed to both increased gene loss and decreased gene duplication. Notably, pronounced loss of immune receptors was associated with the complete absence of signalling components from the enhanced disease susceptibility 1 (EDS1) and the resistance to powdery mildew 8 (RPW8)-NLR (RNL) families. In addition, evolutionary pattern analysis suggested that the conserved toll/interleukin-1 receptor (TIR)-only proteins might function tightly with EDS1/RNL. Taken together, these results reveal the hierarchically adaptive evolution of the two-tiered immune receptor repertoires during plant adaptation to diverse SLHs.
This is a preview of subscription content, access via your institution
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
27,99 € / 30 days
cancel any time
Subscribe to this journal
Receive 12 digital issues and online access to articles
118,99 € per year
only 9,92 € per issue
Buy this article
- Purchase on SpringerLink
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout






Similar content being viewed by others
Data availability
With reference to PlaBI (https://www.plabipd.de/pubplant_cladogram1.html), we collected accessions of sequenced plant genomes that have been published in peer-reviewed journals. Accordingly, the annotated proteomes of 808 angiosperm genomes were downloaded from publicly available databases, such as NCBI (https://www.ncbi.nlm.nih.gov/assembly/), NGDC (https://ngdc.cncb.ac.cn/gwh/), CNGBdb (https://db.cngb.org/), Phytozome (https://phytozome-next.jgi.doe.gov/), CoGe (https://genomevolution.org/coge/), GigaDB (http://gigadb.org/), Ensembl Plants (http://plants.ensembl.org/index.html) and Plant GARDEN (https://plantgarden.jp/en/index). The complete list of species taxa, references and download links is curated in Supplementary Table 1. The information on the sequencing, assembly and annotation of each genome retrieved from the N3 database (http://ibi.zju.edu.cn/N3database/)96, original publications and deposited databases is also curated in Supplementary Table 1. The protein sequences of the PRR, NLR, EDS1, cTIR, TNP and MLKL genes from 808 angiosperms that were identified and classified in this study have been deposited in AirDB (https://efg.nju.edu.cn/AirDB/). Source data are provided with this paper.
References
Jones, J. D. G. & Dangl, J. L. The plant immune system. Nature 444, 323–329 (2006).
Jones, J. D. G., Staskawicz, B. J. & Dangl, J. L. The plant immune system: from discovery to deployment. Cell 187, 2095–2116 (2024).
Yuan, M. et al. Pattern-recognition receptors are required for NLR-mediated plant immunity. Nature 592, 105–109 (2021).
Ngou, B. P. M., Ahn, H. K., Ding, P. & Jones, J. D. G. Mutual potentiation of plant immunity by cell-surface and intracellular receptors. Nature 592, 110–115 (2021).
Pruitt, R. N. et al. The EDS1-PAD4-ADR1 node mediates Arabidopsis pattern-triggered immunity. Nature 598, 495–499 (2021).
Tian, H. et al. Activation of TIR signalling boosts pattern-triggered immunity. Nature 598, 500–503 (2021).
Tang, D., Wang, G. & Zhou, J. M. Receptor kinases in plant-pathogen interactions: more than pattern recognition. Plant Cell 29, 618–637 (2017).
DeFalco, T. A. & Zipfel, C. Molecular mechanisms of early plant pattern-triggered immune signaling. Mol. Cell 81, 3449–3467 (2021).
Lehti-Shiu, M. D. & Shiu, S. H. Diversity, classification and function of the plant protein kinase superfamily. Phil. Trans. R. Soc. Lond. B 367, 2619–2639 (2012).
Dievart, A., Gottin, C., Perin, C., Ranwez, V. & Chantret, N. Origin and diversity of plant receptor-like kinases. Annu. Rev. Plant Biol. 71, 131–156 (2020).
Man, J., Harrington, T. A., Lally, K. & Bartlett, M. E. Asymmetric evolution of protein domains in the leucine-rich repeat receptor-like kinase family of plant signaling proteins. Mol. Biol. Evol. 40, msad220 (2023).
Ngou, B. P. M., Ding, P. & Jones, J. D. G. Thirty years of resistance: zig-zag through the plant immune system. Plant Cell 34, 1447–1478 (2022).
Ngou, B. P. M., Heal, R., Wyler, M., Schmid, M. W. & Jones, J. D. G. Concerted expansion and contraction of immune receptor gene repertoires in plant genomes. Nat. Plants 8, 1146–1152 (2022).
Ngou, B. P. M., Wyler, M., Schmid, M. W., Kadota, Y. & Shirasu, K. Evolutionary trajectory of pattern recognition receptors in plants. Nat. Commun. 15, 308 (2024).
Liu, Y., Zhang, Y. M., Tang, Y., Chen, J. Q. & Shao, Z. Q. The evolution of plant NLR immune receptors and downstream signal components. Curr. Opin. Plant Biol. 73, 102363 (2023).
Shao, Z. Q. et al. Large-scale analyses of angiosperm nucleotide-binding site-leucine-rich repeat genes reveal three anciently diverged classes with distinct evolutionary patterns. Plant Physiol. 170, 2095–2109 (2016).
Kourelis, J. & van der Hoorn, R. A. L. Defended to the nines: 25 years of resistance gene cloning identifies nine mechanisms for R protein function. Plant Cell 30, 285–299 (2018).
Bonardi, V. et al. Expanded functions for a family of plant intracellular immune receptors beyond specific recognition of pathogen effectors. Proc. Natl Acad. Sci. USA 108, 16463–16468 (2011).
Castel, B. et al. Diverse NLR immune receptors activate defence via the RPW8-NLR NRG1. New Phytol. 222, 966–980 (2019).
Wu, Z. et al. Differential regulation of TNL-mediated immune signaling by redundant helper CNLs. New Phytol. 222, 938–953 (2019).
Saile, S. C. et al. Two unequally redundant ‘helper’ immune receptor families mediate Arabidopsis thaliana intracellular ‘sensor’ immune receptor functions. PLoS Biol. 18, e3000783 (2020).
Wang, J. et al. Ligand-triggered allosteric ADP release primes a plant NLR complex. Science 364, eaav5868 (2019).
Wang, J. et al. Reconstitution and structure of a plant NLR resistosome conferring immunity. Science 364, eaav5870 (2019).
Bi, G. et al. The ZAR1 resistosome is a calcium-permeable channel triggering plant immune signaling. Cell 184, 3528–3541.e12 (2021).
Forderer, A. et al. A wheat resistosome defines common principles of immune receptor channels. Nature 610, 532–539 (2022).
Jacob, P. et al. Plant ‘helper’ immune receptors are Ca2+-permeable nonselective cation channels. Science 373, 420–425 (2021).
Wu, C. H. et al. NLR network mediates immunity to diverse plant pathogens. Proc. Natl Acad. Sci. USA 114, 8113–8118 (2017).
Adachi, H. et al. An N-terminal motif in NLR immune receptors is functionally conserved across distantly related plant species. eLife 8, e49956 (2019).
Ma, S. et al. Oligomerization-mediated autoinhibition and cofactor binding of a plant NLR. Nature 632, 869–876 (2024).
Lapin, D. et al. A coevolved EDS1-SAG101-NRG1 module mediates cell death signaling by TIR-___domain immune receptors. Plant Cell 31, 2430–2455 (2019).
Lapin, D., Bhandari, D. D. & Parker, J. E. Origins and immunity networking functions of EDS1 family proteins. Annu. Rev. Phytopathol. 58, 253–276 (2020).
Sun, X. et al. Pathogen effector recognition-dependent association of NRG1 with EDS1 and SAG101 in TNL receptor immunity. Nat. Commun. 12, 3335 (2021).
Ma, S. et al. Direct pathogen-induced assembly of an NLR immune receptor complex to form a holoenzyme. Science 370, eabe3069 (2020).
Martin, R. et al. Structure of the activated ROQ1 resistosome directly recognizing the pathogen effector XopQ. Science 370, eabd9993 (2020).
Jia, A. et al. TIR-catalyzed ADP-ribosylation reactions produce signaling molecules for plant immunity. Science 377, eabq8180 (2022).
Huang, S. et al. Identification and receptor mechanism of TIR-catalyzed small molecules in plant immunity. Science 377, eabq3297 (2022).
Shao, Z. Q., Xue, J. Y., Wang, Q., Wang, B. & Chen, J. Q. Revisiting the origin of plant NBS-LRR genes. Trends Plant Sci. 24, 9–12 (2019).
Feng, X. Y., Li, Q., Liu, Y., Zhang, Y. M. & Shao, Z. Q. Evolutionary and immune-activating character analyses of NLR genes in algae suggest the ancient origin of plant intracellular immune receptors. Plant J. 119, 2316–2330 (2024).
Tian, D., Traw, M. B., Chen, J. Q., Kreitman, M. & Bergelson, J. Fitness costs of R-gene-mediated resistance in Arabidopsis thaliana. Nature 423, 74–77 (2003).
Liu, Y. et al. An angiosperm NLR Atlas reveals that NLR gene reduction is associated with ecological specialization and signal transduction component deletion. Mol. Plant 14, 2015–2031 (2021).
Baggs, E. L. et al. Convergent loss of an EDS1/PAD4 signaling pathway in several plant lineages reveals coevolved components of plant immunity and drought response. Plant Cell 32, 2158–2177 (2020).
Wang, J., Tan, S. J., Zhang, L., Li, P. & Tian, D. C. Co-variation among major classes of LRR-encoding genes in two pairs of plant species. J. Mol. Evol. 72, 498–509 (2011).
Li, P. et al. RGAugury: a pipeline for genome-wide prediction of resistance gene analogs (RGAs) in plants. BMC Genomics 17, 852 (2016).
Yin, Z., Liu, J. & Dou, D. RLKdb: a comprehensively curated database of plant receptor-like kinase families. Mol. Plant 17, 513–515 (2024).
Dufayard, J. F. et al. New insights on leucine-rich repeats receptor-like kinase orthologous relationships in angiosperms. Front. Plant Sci. 8, 381 (2017).
Kourelis, J., Sakai, T., Adachi, H. & Kamoun, S. RefPlantNLR is a comprehensive collection of experimentally validated plant disease resistance proteins from the NLR family. PLoS Biol. 19, e3001124 (2021).
Qin, H., Cheng, J., Han, G.-Z. & Gong, Z. Phylogenomic insights into the diversity and evolution of RPW8-NLRs and their partners in plants. Plant J. 120, 1032–1046 (2024).
Sudalaimuthuasari, N. et al. The genome of the mimosoid legume Prosopis cineraria, a desert tree. Int. J. Mol. Sci. 23, 8503 (2022).
Kong, W. et al. Genome and evolution of Prosopis alba Griseb., a drought and salinity tolerant tree legume crop for arid climates. Plants People Planet 5, 933–947 (2023).
Wang, M., Zhang, L., Tong, S., Jiang, D. & Fu, Z. Chromosome-level genome assembly of a xerophytic plant, Haloxylon ammodendron. DNA Res. 29, dsac006 (2022).
Lapin, D., Johanndrees, O., Wu, Z. S., Li, X. & Parker, J. E. Molecular innovations in plant TIR-based immunity signaling. Plant Cell 34, 1479–1496 (2022).
Johanndrees, O. et al. Variation in plant toll/interleukin-1 receptor ___domain protein dependence on ENHANCED DISEASE SUSCEPTIBILITY 1. Plant Physiol. 191, 626–642 (2023).
Ogden, S. C., Nishimura, M. T. & Lapin, D. Functional diversity of toll/interleukin-1 receptor domains in flowering plants and its translational potential. Curr. Opin. Plant Biol. 76, 102481 (2023).
Meyers, B. C., Morgante, M. & Michelmore, R. W. TIR-X and TIR-NBS proteins: two new families related to disease resistance TIR-NBS-LRR proteins encoded in Arabidopsis and other plant genomes. Plant J. 32, 77–92 (2002).
Nandety, R. S. et al. The role of TIR-NBS and TIR-X proteins in plant basal defense responses. Plant Physiol. 162, 1459–1472 (2013).
Zhang, Y.-M. et al. Divergence and conservative evolution of XTNX genes in land plants. Front. Plant Sci. 8, 1844 (2017).
Mahdi, L. K. et al. Discovery of a family of mixed lineage kinase ___domain-like proteins in plants and their role in innate immune signaling. Cell Host Microbe 28, 813–824.e6 (2020).
Shen, Q. et al. Cytoplasmic calcium influx mediated by plant MLKLs confers TNL-triggered immunity. Cell Host Microbe 32, 453–465.e6 (2024).
Li, H. et al. Wheat powdery mildew resistance gene Pm13 encodes a mixed lineage kinase ___domain-like protein. Nat. Commun. 15, 2449 (2024).
LEAKE, J. R. The biology of myco-heterotrophic (‘saprophytic’) plants. New Phytol. 127, 171–216 (1994).
Merckx, V. S. F. T. et al. Mycoheterotrophy in the wood-wide web. Nat. Plants 10, 710–718 (2024).
Xu, Y. et al. A chromosome-scale Gastrodia elata genome and large-scale comparative genomic analysis indicate convergent evolution by gene loss in mycoheterotrophic and parasitic plants. Plant J. 108, 1609–1623 (2021).
Li, M.-H. et al. Genomes of leafy and leafless Platanthera orchids illuminate the evolution of mycoheterotrophy. Nat. Plants 8, 373–388 (2022).
Hu, W. et al. Aridity-driven shift in biodiversity–soil multifunctionality relationships. Nat. Commun. 12, 5350 (2021).
Kahlon, P. S. et al. Population studies of the wild tomato species Solanum chilense reveal geographically structured major gene-mediated pathogen resistance. Proc. R. Soc. B 287, 20202723 (2020).
Wang, Y. et al. Comparison of the levels of bacterial diversity in freshwater, intertidal wetland, and marine sediments by using millions of Illumina tags. Appl. Environ. Microbiol. 78, 8264–8271 (2012).
Castel, B., El Mahboubi, K., Jacquet, C. & Delaux, P. M. Immunobiodiversity: conserved and specific immunity across land plants and beyond. Mol. Plant 17, 92–111 (2024).
Zhuang, H. et al. Aphid (Myzus persicae) feeding on the parasitic plant dodder (Cuscuta australis) activates defense responses in both the parasite and soybean host. New Phytol. 218, 1586–1596 (2018).
Hadariová, L., Vesteg, M., Hampl, V. & Krajcovic, J. Reductive evolution of chloroplasts in non-photosynthetic plants, algae and protists. Curr. Genet. 64, 365–387 (2018).
Liu, J. et al. Chloroplast immunity: a cornerstone of plant defense. Mol. Plant 17, 686–688 (2024).
Boller, T. & Felix, G. A renaissance of elicitors: perception of microbe-associated molecular patterns and danger signals by pattern-recognition receptors. Annu. Rev. Plant Biol. 60, 379–406 (2009).
Shimizu, M. et al. A genetically linked pair of NLR immune receptors shows contrasting patterns of evolution. Proc. Natl Acad. Sci. USA 119, e2116896119 (2022).
Wu Y. et al. A canonical protein complex controls immune homeostasis and multipathogen resistance. Science 386, 1405–1412 (2024).
The Angiosperm Phylogeny Group et al. An update of the Angiosperm Phylogeny Group classification for the orders and families of flowering plants: APG IV. Bot. J. Linn. Soc. 10.1111/boj.12385 (2016).
Jin, Y. & Qian, H. V.PhyloMaker2: an updated and enlarged R package that can generate very large phylogenies for vascular plants. Plant Divers. 44, 335–339 (2022).
Li, C. et al. Ancient DNA analysis of Panicum miliaceum (broomcorn millet) from a Bronze Age cemetery in Xinjiang, China. Veg. Hist. Archaeobot. 25, 469–477 (2016).
Yang, W. et al. The draft genome sequence of a desert tree Populus pruinosa. GigaScience 6, gix075 (2017).
Delgado-Salinas, A., Bibler, R. & Lavin, M. Phylogeny of the genus Phaseolus (Leguminosae): a recent diversification in an ancient landscape. Syst. Bot. 31, 779–791 (2006).
Messeder, J. V. S. et al. A highly resolved nuclear phylogeny uncovers strong phylogenetic conservatism and correlated evolution of fruit color and size in Solanum L. New Phytol. 243, 765–780 (2024).
Xu, S. et al. Ggtree: a serialized data object for visualization of a phylogenetic tree and annotation data. iMeta 1, e56 (2022).
Krogh, A., Larsson, B., von Heijne, G. & Sonnhammer, E. L. L. Predicting transmembrane protein topology with a hidden Markov model: application to complete genomes. J. Mol. Biol. 305, 567–580 (2001).
Eddy, S. R. Accelerated profile HMM searches. PLoS Comput. Biol. 7, e1002195 (2011).
Fritz-Laylin, L. K., Krishnamurthy, N., Tör, M., Sjölander, K. V. & Jones, J. D. G. Phylogenomic analysis of the receptor-like proteins of rice and Arabidopsis. Plant Physiol. 138, 611–623 (2005).
Camacho, C. et al. BLAST+: architecture and applications. BMC Bioinformatics 10, 421 (2009).
Chen, T. Identification and characterization of the LRR repeats in plant LRR-RLKs. BMC Mol. Cell Biol. 22, 9 (2021).
Bailey, T. L., Johnson, J., Grant, C. E. & Noble, W. S. The MEME Suite. Nucleic Acids Res. 43, W39–W49 (2015).
Katoh, K. & Standley, D. M. MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol. Biol. Evol. 30, 772–780 (2013).
Minh, B. Q. et al. IQ-TREE 2: new models and efficient methods for phylogenetic inference in the genomic era. Mol. Biol. Evol. 37, 1530–1534 (2020).
Kalyaanamoorthy, S., Minh, B. Q., Wong, T. K. F., von Haeseler, A. & Jermiin, L. S. ModelFinder: fast model selection for accurate phylogenetic estimates. Nat. Methods 14, 587–589 (2017).
Anisimova, M., Gil, M., Dufayard, J. F., Dessimoz, C. & Gascuel, O. Survey of branch support methods demonstrates accuracy, power, and robustness of fast likelihood-based approximation schemes. Syst. Biol. 60, 685–699 (2011).
Hoang, D. T., Chernomor, O., von Haeseler, A., Minh, B. Q. & Vinh, L. S. UFBoot2: improving the ultrafast bootstrap approximation. Mol. Biol. Evol. 35, 518–522 (2018).
Darby, C. A., Stolzer, M., Ropp, P. J., Barker, D. & Durand, D. Xenolog classification. Bioinformatics 33, 640–649 (2017).
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).
Liao, Y., Smyth, G. K. & Shi, W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30, 923–930 (2014).
Manni, M., Berkeley, M. R., Seppey, M., Simão, F. A. & Zdobnov, E. M. BUSCO update: novel and streamlined workflows along with broader and deeper phylogenetic coverage for scoring of eukaryotic, prokaryotic, and viral genomes. Mol. Biol. Evol. 38, 4647–4654 (2021).
Xie, L. et al. Technology-enabled great leap in deciphering plant genomes. Nat. Plants 10, 551–566 (2024).
Acknowledgements
This work was supported by the National Natural Science Foundation of China (32270241 and 32070243 to Z.-Q.S., 32170218 to J.-Q.C., and 32172089 to Y.-M.Z.), the NSFC-FDCT Grant (32461160254 to J.-Q.C.), the Jiangsu Agricultural Science and Technology Independent Innovation Fund (CX(23)3116 to Z.-Q.S.), and the National Postdoctoral Science Foundation of China (2022M721558 and 2024T170408 to Y.L.). Y.L. was supported by the Jiangsu Excellent Postdoctoral Funding (2022ZB45), and Z.-Q.S. was supported by the Outstanding Young Teacher of ‘QingLan Project’ of Jiangsu Province. We thank W.-L. Wu for providing the cartoon elements in Fig. 6.
Author information
Authors and Affiliations
Contributions
Z.-Q.S. and J.-Q.C. conceived and designed the research. S.-X.L., Y.L. and Y.-M.Z. obtained and analysed the data. S.-X.L. and Z.-Q.S. interpreted the data. S.-X.L. constructed the database. S.-X.L. drafted the manuscript. Z.-Q.S. and J.-Q.C. revised the manuscript.
Corresponding authors
Ethics declarations
Competing interests
The authors declare no competing interests.
Peer review
Peer review information
Nature Plants thanks Martin Parniske, Baptiste Castel 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.
Extended data
Extended Data Fig. 1 Comparison of PRR gene numbers identified in this study with previous publications.
a Comparison of IR-RLK gene number in this study with all RLK gene number in Li et al. (RGAugury)43 for the corresponding species. b Comparison of LRR-RLK gene number in this study with LRR-RLK gene number in Yin et al. (HMMER, deepTMHMM)44 for the corresponding species. c Comparison of LRR-RLK XII gene number in this study with LRR-RLK XII gene number in Dufayard et al. (HMMER, TMHMM, TopPred)45 for the corresponding species. d Comparison of IR-RLP gene number in this study with all RLP gene number in Li et al. (RGAugury)43 for the corresponding species. Each scatter plot contains the linear regression trend (solid line), 95% confidence interval (dark gray shade), 95% prediction interval (light gray shade), and Pearson's correlation coefficient with two-sided test. Two-sided Wilcoxon matched-pairs signed-ranks tests were conducted for boxplots (centre line: median; box limits: upper and lower quartiles; whiskers: 1.5x interquartile range).
Extended Data Fig. 2 Comparison of NLR gene numbers identified in this study with previous publications.
a Comparison of NLR gene number in this study with the NLR gene number in Li et al. (RGAugury)43 for the corresponding species. b Comparison of NLR gene number in this study with NLR gene number in Baggs et al. (NLR-Annotator)41 for the corresponding species. c Comparison of NLR gene number in this study with NLR gene number in Krourelis et al. (NLRtracker)46 for the corresponding species. d Comparison of NLR gene number in this study with NLR gene number in Qin et al. (HMMER, MAFFT, Fasttree)47 for the corresponding species. Each scatter plot contains the linear regression trend (solid line), 95% confidence interval (dark gray shade), 95% prediction interval (light gray shade), and Pearson's correlation coefficient with two-sided test. Two-sided Wilcoxon matched-pairs signed-ranks tests were conducted for boxplots (centre line: median; box limits: upper and lower quartiles; whiskers: 1.5x interquartile range).
Extended Data Fig. 3 Correlations between genome size, CDS number, and immune receptor gene number.
The diagonal boxes include histograms representing the distributions of genome sizes (Mb), CDS numbers, and gene numbers of NLR, LRR-RLK XII, and LRR-RLPID+4LRR from 808 angiosperms, respectively. The bottom left boxes contain the scatter plots between genome sizes, CDS numbers, and immune receptor gene numbers from 808 angiosperms, with the solid lines representing the linear trends and the light blue shades representing 95% confidence intervals. The top right boxes provide the corresponding values of the Pearson correlation coefficient (Pearson’s r) with two-sided statistical test (***: P < 0.001).
Extended Data Fig. 4 Evaluation of the impact of genome quality and species domestication on NLR comparison.
a NLR gene number in SLH and non-SLH species under similar metrics of genome sequencing [third-generation sequencing (TGS), next-generation sequencing (NGS), and Sanger], assembly [chromosome-level and non-chromosome-level; contig N50 size (the length of the shortest contig at 50% of the total assembly length)], and annotation [benchmarking universal single-copy orthologs (BUSCO)]. The distribution of NLR gene numbers is represented by the boxplot (centre line: median; box limits: upper and lower quartiles; whiskers: 1.5x interquartile range; outliers not shown). The SLH species and non-SLH species are indicated in salmon and blue, respectively. Pairwise significance was determined by two-sided Mann‒Whitney U test between SLH and non-SLH angiosperms (****: P < 0.0001). Species lacking the information of genome quality (for example contig N50) were not included in this analysis. b NLR gene number in SLH, wild, and domesticated species. The distribution of NLR gene numbers is represented by the boxplot (centre line: median; box limits: upper and lower quartiles; whiskers: 1.5x interquartile range; outliers not shown). Pairwise significance was determined by two-sided Mann‒Whitney U test between SLH and non-SLH angiosperms, respectively (ns: P > 0.05; ****: P < 0.0001).
Extended Data Fig. 5 Comparison of NLR gene number between SLH and non-SLH species within the same family.
The phylogenetic tree of SLH species within each family is extracted from Supplementary Fig. 1. Clades of Orchidaceae (n = 10), Poaceae (n = 85), Salicaceae (n = 14), Fabaceae (n = 51), Brassicaceae (n = 44), Amaranthaceae (n = 12), and Solanaceae (n = 45) are indicated in alternate color stripes superimposed on the species tree. The NLR gene number is represented by the bar plot, with SLH species indicated in color as Fig. 2a and the average of non-SLH species in each family indicated in gray. Pairwise significance was determined by two-sided one sample Wilcoxon signed-rank test between each SLH plant and its non-SLH relatives within the same family, respectively (ns: P > 0.05; *: P < 0.05; **: P < 0.01; ***: P < 0.001; ****: P < 0.0001).
Extended Data Fig. 6 Evaluation of the impact of genome quality and species domestication on LRR-RLK XII and LRR-RLPID+4LRR comparison.
a LRR-RLK XII and LRR-RLPID+4LRR gene number in SLH and non-SLH species under similar metrics of genome sequencing [third-generation sequencing (TGS), next-generation sequencing (NGS), and Sanger], assembly [chromosome-level and non-chromosome-level; contig N50 size (the length of the shortest contig at 50% of the total assembly length)], and annotation [benchmarking universal single-copy orthologs (BUSCO)]. The distribution of LRR-RLK XII and LRR-RLPID+4LRR gene numbers is represented by the boxplot (centre line: median; box limits: upper and lower quartiles; whiskers: 1.5x interquartile range; outliers not shown). The SLH species and non-SLH species are indicated in salmon and blue, respectively. Pairwise significance was determined by two-sided Mann‒Whitney U test between SLH and non-SLH angiosperms (***: P < 0.001; ****: P < 0.0001). Species lacking the information of genome quality (for example contig N50) were not included in this analysis. b LRR-RLK XII and LRR-RLPID+4LRR gene number in SLH, wild, and domesticated species. The distribution of LRR-RLK XII and LRR-RLPID+4LRR gene numbers is represented by the boxplot (centre line: median; box limits: upper and lower quartiles; whiskers: 1.5x interquartile range; outliers not shown). Pairwise significance was determined by two-sided Mann‒Whitney U test between SLH and non-SLH angiosperms, respectively (ns: P > 0.05; ****: P < 0.0001).
Extended Data Fig. 7 Comparison of LRR-RLK XII and LRR-RLPID+4LRR gene number between SLH and non-SLH species within the same family.
The phylogenetic tree of SLH species within each family is extracted from Supplementary Fig. 1. Clades of Orchidaceae (n = 10), Poaceae (n = 85), Salicaceae (n = 14), Fabaceae (n = 51), Brassicaceae (n = 44), Amaranthaceae (n = 12), and Solanaceae (n = 45) are indicated in alternate color stripes superimposed on the species tree. The LRR-RLK XII (a) and LRR-RLPID+4LRR (b) gene number is represented by the bar plot, with SLH species indicated in color as Fig. 3a and the average of non-SLH species in each family indicated in gray. Pairwise significance was determined by two-sided one sample Wilcoxon signed-rank test between each SLH plant and its non-SLH relatives within the same family, respectively (ns: P > 0.05; *: P < 0.05; **: P < 0.01; ***: P < 0.001; ****: P < 0.0001).
Extended Data Fig. 8 Distribution of RNL and EDS1 family genes across 808 angiosperms.
The phylogenetic tree of 808 angiosperm species is corresponding to Supplementary Fig. 1. The numbers of RNL (NRG1 and ADR1) and EDS1 family (EDS1, SAG101 and PAD4) genes are represented by the heatmap. The color key is shown at the bottom, with white indicating no detectable gene.
Extended Data Fig. 9 Distribution of cTIR, TNP, and MLKL genes across 808 angiosperms.
The phylogenetic tree of 808 angiosperm species is corresponding to Supplementary Fig. 1. The numbers of cTIR, TNP, and MLKL genes are represented by the heatmap. The color key is shown at the bottom, with white indicating no detectable gene.
Extended Data Fig. 10 Presence/absence mode of PTI and ETI pathway components in species lacking EDS1 family genes.
The presence and absence of the PTI and ETI pathway components are indicated by the solid and open circles, respectively, with the color of the circles reflecting presence of the components of ETI (orange) or PTI (green).
Supplementary information
Supplementary Information
Supplementary Figs. 1–10.
Supplementary Table
Supplementary Tables 1–10.
Supplementary Data
Supplementary Data 1–3.
Source data
Source Data Fig. 1
Statistical source data.
Source Data Fig. 2
Statistical source data.
Source Data Fig. 3
Statistical source data.
Source Data Fig. 4
Statistical source data.
Source Data Extended Data Fig. 3
Statistical source data.
Source Data Extended Data Fig. 4
Statistical source data.
Source Data Extended Data Fig. 5
Statistical source data.
Source Data Extended Data Fig. 6
Statistical source data.
Source Data Extended Data Fig. 7
Statistical source data.
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.
About this article
Cite this article
Li, SX., Liu, Y., Zhang, YM. et al. Convergent reduction of immune receptor repertoires during plant adaptation to diverse special lifestyles and habitats. Nat. Plants 11, 248–262 (2025). https://doi.org/10.1038/s41477-024-01901-x
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/s41477-024-01901-x