Abstract
Many insects metamorphose from antagonistic larvae into mutualistic adult pollinators, with reciprocal adaptation leading to specialized insect–plant associations. It remains unknown how such interactions are established at molecular level. Here we assemble high-quality genomes of a fig species, Ficus pumila var. pumila, and its specific pollinating wasp, Wiebesia pumilae. We combine multi-omics with validation experiments to reveal molecular mechanisms underlying this specialized interaction. In the plant, we identify the specific compound attracting pollinators and validate the function of several key genes regulating its biosynthesis. In the pollinator, we find a highly reduced number of odorant-binding protein genes and an odorant-binding protein mainly binding the attractant. During antagonistic interaction, we find similar chemical profiles and turnovers throughout the development of galled ovules and seeds, and a significant contraction of detoxification-related gene families in the pollinator. Our study identifies some key genes bridging coevolved mutualists, establishing expectations for more diffuse insect–pollinator systems.
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Overlaps in olfactive signalling coupled with geographic variation may result in localised pollinator sharing between closely related Ficus species
BMC Ecology and Evolution Open Access 13 August 2022
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Asymmetric sharing of pollinator fig wasps between two sympatric dioecious fig trees: a reflection of supply and demand or differences in the size of their figs?
Botanical Studies Open Access 22 March 2022
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Data availability
The data that support the findings of this study have been deposited in the CNSA (https://db.cngb.org/cnsa/) of CNGBdb with accession code CNP0000674.
Code availability
All analyses in this study were conducted using published programs, and all codes for data analysis are provided in the Methods.
References
Lamichhaney, S. et al. Evolution of Darwin’s finches and their beaks revealed by genome sequencing. Nature 518, 371–375 (2015).
Simões, M. et al. The evolving theory of evolutionary radiations. Trends Ecol. Evol. 31, 27–34 (2016).
Arnegard, M. E. et al. Genetics of ecological divergence during speciation. Nature 511, 307–311 (2014).
Hoffmann, A. A. & Sgrò, C. M. Climate change and evolutionary adaptation. Nature 470, 479–485 (2011).
Olsen, J. L. et al. The genome of the seagrass Zostera marina reveals angiosperm adaptation to the sea. Nature 530, 331–335 (2016).
Becerra, J. X., Nogeb, K. & Venable, D. L. Macroevolutionary chemical escalation in an ancient plant–herbivore arms race. Proc. Natl Acad. Sci. USA 106, 18062–18066 (2009).
Edger, P. P. et al. The butterfly plant arms-race escalated by gene and genome duplications. Proc. Natl Acad. Sci. USA 112, 8362–8366 (2015).
Adler, L. S. & Bronstein, J. L. Attracting antagonists: does floral nectar increase leaf herbivory? Ecology 85, 1519–1526 (2004).
McCall, A. C. & Irwin, R. E. Florivory: the intersection of pollination and herbivory. Ecol. Lett. 9, 1351–1365 (2006).
Cook, J. M. & Rasplus, J.-Y. Mutualists with attitude: coevolving fig wasps and figs. Trends Ecol. Evol. 18, 241–248 (2003).
Zhang, X. et al. Genomes of the banyan tree and pollinator wasp provide insights into fig–wasp coevolution. Cell 183, 875–889 (2020).
Herre, E. A., Jandér, K. C. & Machado, C. A. Evolutionary ecology of figs and their associates: recent progress and outstanding puzzles. Annu. Rev. Ecol. Evol. Syst. 39, 439–458 (2008).
Souza, C. D. et al. Diversity of fig glands is associated with nursery mutualism in fig trees. Am. J. Bot. 102, 1564–1577 (2015).
Souto-Vilarós, D. et al. Pollination along an elevational gradient mediated both by floral scent and pollinator compatibility in the fig and fig–wasp mutualism. J. Ecol. Evol. 106, 2256–2273 (2018).
Wang, R. et al. Loss of top-down biotic interactions changes the relative benefits for obligate mutualists. Proc. R. Soc. B 286, 20182501 (2019).
Mori, K. et al. Identification of RAN1 orthologue associated with sex determination through whole genome sequencing analysis in fig (Ficus carica L.). Sci. Rep. 7, 41124 (2017).
Proffit, M. et al. Chemical signal is in the blend: bases of plant–pollinator encounter in a highly specialized interaction. Sci. Rep. 10, 10071 (2020).
Chen, C. et al. Private channel: a single unusual compound assures specific pollinator attraction in Ficus semicordata. Funct. Ecol. 23, 941–950 (2009).
Wang, G., Cannon, C. H. & Chen, J. Pollinator sharing and gene flow among closely related sympatric dioecious fig taxa. Proc. R. Soc. B 283, 20152963 (2016).
Yu, H. et al. De novo transcriptome sequencing in Ficus hirta Vahl. (Moraceae) to investigate gene regulation involved in the biosynthesis of pollinator attracting volatiles. Tree Genet. Genomes 11, 91 (2015).
Soler, C. C. L., Proffit, M., Bessière, J.-M., Hossaert -McKey, M. & Schatz, B. Evidence for intersexual chemical mimicry in a dioicous plant. Ecol. Lett. 15, 978–985 (2012).
Volf, M. et al. Community structure of insect herbivores is driven by conservatism, escalation and divergence of defensive traits in Ficus. Ecol. Lett. 21, 83–92 (2018).
Martinson, E. O., Hackett, J. D., Machado, C. A. & Arnold, A. E. Metatranscriptome analysis of fig flowers provides insights into potential mechanisms for mutualism stability and gall induction. PLoS ONE 10, e0130745 (2015).
Zhang, H. et al. Leaf-mining by Phyllonorycter blancardella reprograms the host–leaf transcriptome to modulate phytohormones associated with nutrient mobilization and plant defense. J. Insect Physiol. 84, 114–127 (2016).
Schultz, J. C., Edger, P. P., Body, M. & Appel, H. M. A galling insect activates plant reproductive programs during gall development. Sci. Rep. 9, 1833 (2019).
The Nasonia Genome Working Group Functional and evolutionary insights from the genomes of three parasitoid Nasonia species. Science 327, 343–348 (2010).
Xiao, J.-H. et al. Obligate mutualism within a host drives the extreme specialization of a fig wasp genome. Genome Biol. 14, R141 (2013).
Ohri, D. & Khoshoo, T. N. Nuclear DNA contents in the genus Ficus (Moraceae). Plant Syst. Evol. 156, 1–4 (1987).
Chen, Y., Compton, S. G., Liu, M. & Chen, X.-Y. Fig trees at the northern limit of their range: the distributions of cryptic pollinators indicate multiple glacial refugia. Mol. Ecol. 21, 1687–1701 (2012).
Chen, L.-G. et al. Binding affinity characterization of an antennae-enriched chemosensory protein from the white-backed planthopper, Sogatella furcifera (Horváth), with host plant volatiles. Pestic. Biochem. Phys. 152, 1–7 (2018).
Gu, S.-H. et al. Functional characterization and immunolocalization of odorant binding protein 1 in the lucerne plant bug, Adelphocoris lineolatus (GOEZE). Arch. Insect Biochem. Physiol. 77, 81–99 (2011).
Leal, W. S. et al. Reverse and conventional chemical ecology approaches for the development of oviposition attractants for Culex mosquitoes. PLoS ONE 3, e3045 (2008).
Rizzo, W. B. et al. Fatty aldehyde and fatty alcohol metabolism: review and importance for epidermal structure and function. Biochim. Biophys. Acta 1841, 377–389 (2014).
Schwab, W., Davidovich‐Rikanati, R. & Lewinsohn, E. Biosynthesis of plant‐derived flavor compounds. Plant J. 54, 712–732 (2008).
Capella, M., Ribone, P. A., Arce, A. L. & Chan, R. L. Arabidopsis thaliana HomeoBox 1 (AtHB1), a Homedomain-Leucine Zipper I (HD-Zip I) transcription factor, is regulated by PHYTOCHROME-INTERACTING FACTOR 1 to promote hypocotyl elongation. New Phytol. 207, 669–682 (2015).
Jiang, W. et al. Two transcription factors TaPpm1 and TaPpb1 co-regulate anthocyanin biosynthesis in purple pericarps of wheat. J. Exp. Bot. 69, 2555–2567 (2018).
Guan, R. et al. Draft genome of the living fossil Ginkgo biloba. GigaScience 5, 49 (2016).
Mithöfer, A. & Boland, W. Plant defense against herbivores: chemical aspects. Annu. Rev. Plant Biol. 63, 431–450 (2012).
Salazar, D. et al. Origin and maintenance of chemical diversity in a species-rich tropical tree lineage. Nat. Ecol. Evol. 2, 983–990 (2018).
Després, L., David, J. P. & Gallet, C. The evolutionary ecology of insect resistance to plant chemicals. Trends Ecol. Evol. 22, 298–307 (2007).
Segar, S. T., Volf, M., Sisol, M., Pardikes, N. & Souto-Vilarós, A. D. Chemical cues and genetic divergence in insects on plants: conceptual cross pollination between mutualistic and antagonistic systems. Curr. Opin. Insect Sci. 32, 83–90 (2019).
Cook, J. M. & Segar, S. T. Speciation in fig wasps. Ecol. Entomol. 35, 54–66 (2010).
Cruaud, A. et al. An extreme case of plant–insect codiversification: figs and fig-pollinating wasps. Syst. Biol. 61, 1029–1047 (2012).
Yu, H. et al. Multiple parapatric pollinators have radiated across a continental fig tree displaying clinal genetic variation. Mol. Ecol. 28, 2391–2405 (2019).
Satler, J. D. et al. Inferring processes of coevolutionary diversification in a community of Panamanian strangler figs and associated pollinating wasps. Evolution 73, 2295–2311 (2019).
Wang, G. et al. Genomic evidence of prevalent hybridization throughout the evolutionary history of the fig–wasp pollination mutualism. Nat. Commun. 12, 718 (2021).
Hoballah, M. E. et al. Single gene-mediated shift in pollinator attraction in Petunia. Plant Cell 19, 779–790 (2007).
Potts, S. G. et al. Global pollinator declines: trends, impacts and drivers. Trends Ecol. Evol. 25, 345–353 (2010).
Kiers, E. T., Palmer, T. M., Ives, A. R., Bruno, J. F. & Bronstein, J. L. Mutualisms in a changing world: an evolutionary perspective. Ecol. Lett. 13, 1459–1474 (2010).
Segar, S. T. et al. The role of evolution in shaping ecological networks. Trends Ecol. Evol. 35, 454–466 (2020).
Stoy, K. S., Gibson, A. K., Gerardo, N. M. & Morran, L. T. A need to consider the evolutionary genetics of host–symbiont mutualisms. J. Evol. Biol. 33, 1656–1668 (2020).
Marçais, G. & Kingsford, C. A fast, lock-free approach for efficient parallel counting of occurrences of k-mers. Bioinformatics 27, 764–770 (2011).
Xiao, C.-L. et al. MECAT: fast mapping, error correction, and de novo assembly for single-molecule sequencing reads. Nat. Methods 14, 1072–1074 (2017).
Walker, B. J. et al. Pilon: an integrated tool for comprehensive microbial variant detection and genome assembly improvement. PLoS ONE 9, e112963 (2014).
Pryszcz, L. P. & Gabaldón, T. Redundans: an assembly pipeline for highly heterozygous genomes. Nucleic Acids Res. 44, e113 (2016).
Zhang, Z., Schwartz, S., Wagner, L. & Miller, W. A greedy algorithm for aligning DNA sequences. J. Comput. Biol. 7, 203–214 (2000).
English, A. C. et al. Mind the gap: upgrading genomes with Pacific Biosciences RS long-read sequencing technology. PLoS ONE 7, e47768 (2012).
Sahlin, K., Chikhi & Arvestad, R. L. Assembly scaffolding with PE-contaminated mate-pair libraries. Bioinformatics 32, 1925–1932 (2016).
Belton, J. M. et al. Hi-C: a comprehensive technique to capture the conformation of genomes. Methods 58, 268–276 (2012).
Servant, N. et al. HiC-Pro: an optimized and flexible pipeline for Hi-C data processing. Genome Biol. 16, 259 (2015).
Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows–Wheeler Transform. Bioinformatics 25, 1754–1760 (2009).
Durand, N. C. et al. Juicer provides a one-click system for analyzing loop-resolution Hi-C experiments. Cell Syst. 3, 95–98 (2016).
Dudchenko, O. et al. De novo assembly of the Aedes aegypti genome using Hi-C yields chromosome-length scaffolds. Science 356, 92–95 (2017).
Simão, F. A., Waterhouse, R. M., Ioannidis, P., Kriventseva, E. V. & Zdobnov, E. M. BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs. Bioinformatics 31, 3210–3212 (2015).
Wu, T. D. & Watanabe, C. K. GMAP: a genomic mapping and alignment program for mRNA and EST sequences. Bioinformatics 21, 1859–1875 (2005).
Benson, G. Tandem repeats finder: a program to analyze DNA sequences. Nucleic Acids Res. 27, 573–580 (1999).
Bao, W., Kojima, K. K. & Kohany, O. Repbase Update, a database of repetitive elements in eukaryotic genomes. Mob. DNA 6, 11 (2015).
Xu, Z. & Wang, H. LTR_FINDER: an efficient tool for the prediction of full-length LTR retrotransposons. Nucleic Acids Res. 35, W265–W268 (2007).
Edgar, R. C. & Myers, E. W. PILER: identification and classification of genomic repeats. Bioinformatics 21, i152–i158 (2005).
Price, A. L., Jones, N. C. & Pevzner, P. A. De novo identification of repeat families in large genomes. Bioinformatics 21, i351–i358 (2005).
Lowe, T. M. & Eddy, S. R. tRNAscan-SE: a program for improved detection of transfer RNA genes in genomic sequence. Nucleic Acids Res. 25, 955–964 (1997).
Nawrocki, E. P. & Eddy, S. R. Infernal 1.1: 100-fold faster RNA homology searches. Bioinformatics 29, 2933–2935 (2013).
Nawrocki, E. P. et al. Rfam 12.0: updates to the RNA families database. Nucleic Acids Res. 43, D130–D137 (2015).
Holt, C. & Yandell, M. MAKER2: an annotation pipeline and genome-database management tool for second-generation genome projects. BMC Bioinf. 12, 491 (2011).
Kim, D., Langmead, B. & Salzberg, S. L. HISAT: a fast spliced aligner with low memory requirements. Nat. Methods 12, 357–360 (2015).
Pertea, M. et al. StringTie enables improved reconstruction of a transcriptome from RNA-seq reads. Nat. Biotechnol. 33, 290–295 (2015).
Johnson, A. D. et al. SNAP: a web-based tool for identification and annotation of proxy SNPs using HapMap. Bioinformatics 24, 2938–2939 (2008).
Stanke, M. & Morgenstern, B. AUGUSTUS: a web server for gene prediction in eukaryotes that allows user-defined constraints. Nucleic Acids Res. 33, W465–W467 (2005).
Buels, R. et al. JBrowse: a dynamic web platform for genome visualization and analysis. Genome Biol. 17, 66 (2016).
Buchfink, B., Xie, C. & Huson, D. H. Fast and sensitive protein alignment using DIAMOND. Nat. Methods 12, 59–60 (2015).
Bairoch, A. & Apweiler, R. The SWISS-PROT protein sequence database and its supplement TrEMBL in 2000. Nucleic Acids Res. 28, 45–48 (2000).
Kanehisa, M., Sato, Y., Kawashima, M., Furumichi, M. & Tanabe, M. KEGG as a reference resource for gene and protein annotation. Nucleic Acids Res. 44, D457–D462 (2016).
Jones, P. et al. InterProScan 5: genome-scale protein function classification. Bioinformatics 30, 1236–1240 (2014).
Conesa, A. et al. Blast2GO: a universal tool for annotation, visualization and analysis in functional genomics research. Bioinformatics 21, 3674–3676 (2005).
Li, L., Stoeckert, C. J. Jr & Roos, D. S. OrthoMCL: identification of ortholog groups for eukaryotic genomes. Genome Res. 13, 2178–2189 (2003).
Li, H. et al. TreeFam: a curated database of phylogenetic trees of animal gene families. Nucleic Acids Res. 34, D572–D580 (2006).
Edgar, R. C. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 32, 1792–1797 (2004).
Capella-Gutierrez, S., Silla-Martinez, J. M. & Gabaldon, T. trimAl: a tool for automated alignment trimming in large-scale phylogenetic analyses. Bioinformatics 25, 1972–1973 (2009).
Guindon, S., Delsuc, F., Dufayard, J. F. & Gascuel, O. Estimating maximum likelihood phylogenies with PhyML. Methods Mol. Biol. 537, 113–137 (2009).
Yang, Z. PAML 4: phylogenetic analysis by maximum likelihood. Mol. Biol. Evol. 24, 1586–1591 (2007).
De Bie, T., Cristianini, N., Demuth, J. P. & Hahn, M. W. CAFE: a computational tool for the study of gene family evolution. Bioinformatics 22, 1269–1271 (2006).
Tang, H. et al. Unraveling ancient hexaploidy through multiply-aligned angiosperm gene maps. Genome Res. 18, 1944–1954 (2008).
Schwartz, S. et al. Human–mouse alignments with BLASTZ. Genome Res. 13, 103–107 (2003).
Bailey, J. A., Yavor, A. M., Massa, H. F., Trask, B. J. & Eichler, E. E. Segmental duplications: organization and impact within the current human genome project assembly. Genome Res. 11, 1005–1017 (2001).
Birney, E., Clamp, M. & Durbin, R. GeneWise and Genomewise. Genome Res. 14, 988–995 (2004).
Ruan, J., Li, H., Chen, Z. & Coghlan, A. TreeFam: 2008 update. Nucleic Acids Res. 36, D735–D740 (2008).
Tholl, D. et al. Practical approaches to plant volatile analysis. Plant J. 45, 540–560 (2006).
Wen, B., Mei, Z., Zeng, C. & Liu, S. metaX: a flexible and comprehensive software for processing metabolomics data. BMC Bioinform. 18, 183 (2017).
Wen, P. et al. The sex pheromone of a globally invasive honey bee predator, the Asian eusocial hornet, Vespa velutina. Sci. Rep. 7, 12956 (2017).
Chen, Y. et al. SOAPnuke: a MapReduce acceleration-supported software for integrated quality control and preprocessing of high-throughput sequencing data. Gigascience 7, 1–6 (2018).
Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).
Li, B. & Dewey, C. N. RSEM: accurate transcript quantification from RNA-seq data with or without a reference genome. BMC Bioinform. 12, 323 (2011).
Tian, X., Chen, L., Wang, J., Qiao, J. & Zhang, W. Quantitative proteomics reveals dynamic responses of Synechocystis sp. PCC 6803 to next-generation biofuel butanol. J. Proteom. 78, 326–345 (2013).
Wen, B. et al. IQuant: an automated pipeline for quantitative proteomics based upon isobaric tags. Proteomics 14, 2280–2285 (2014).
Brosch, M., Yu, L., Hubbard, T. & Choudhary, J. Accurate and sensitive peptide identification with Mascot Percolator. J. Proteome Res. 8, 3176–3181 (2009).
Savitski, M. M., Wilhelm, M., Hahne, H., Kuster, B. & Bantscheff, M. A scalable approach for protein false discovery rate estimation in large proteomic data sets. Mol. Cell Proteomics 14, 2394–2404 (2015).
Cox, J. & Mann, M. MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat. Biotechnol. 26, 1367–1372 (2008).
Bruderer, R. et al. Extending the limits of quantitative proteome profiling with data-independent acquisition and application to acetaminophen-treated three-dimensional liver microtissues. Mol. Cell Proteomics 14, 1400–1410 (2015).
Dunn, W. B. et al. Procedures for large-scale metabolic profiling of serum and plasma using gas chromatography and liquid chromatography coupled to mass spectrometry. Nat. Protoc. 6, 1060–1083 (2011).
Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).
Choi, M. et al. MSstats: an R package for statistical analysis of quantitative mass spectrometry-based proteomic experiments. Bioinformatics 30, 2524–2526 (2014).
Wen, X.-L., Wen, P., Dahlsjö, C. A. L., Sillam-Dussès, D. & Šobotník, J. Breaking the cipher: ant eavesdropping on the variational trail pheromone of its termite prey. Proc. R. Soc. B 284, 20170121 (2017).
Bailey, T. L. & Elkan, C. Fitting a mixture model by expectation maximization to discover motifs in biopolymers. Proc. Int. Conf. Intell. Syst. Mol. Biol. 2, 28–36 (1994).
Lescot, M. et al. PlantCARE, a database of plant cis-acting regulatory elements and a portal to tools for in silico analysis of promoter sequences. Nucleic Acids Res. 30, 325–327 (2002).
Langfelder, P. & Horvath, S. WGCNA: an R package for weighted correlation network analysis. BMC Bioinform. 9, 559 (2008).
Yip, A. M. & Horvath, S. Gene network interconnectedness and the generalized topological overlap measure. BMC Bioinform. 8, 22 (2007).
Langfelder, P., Zhang, B. & Horvath, S. Defining clusters from a hierarchical cluster tree: the Dynamic Tree Cut package for R. Bioinformatics 24, 719–720 (2008).
Gendrel, A. V., Lippman, Z., Martienssen, R. & Colot, V. Profiling histone modification patterns in plants using genomic tiling microarrays. Nat. Methods 2, 213–218 (2005).
Acknowledgements
We thank Y.-J. Wang, Q.-C. Zhu, Q. Sun, Q.-Y. Li, J.-W. Wang, T.-L. Xu, Y. Chen, F.-L. Wei, G.-C. Shen, X.-L. Wen and L.-S. Li for their kind help in field experiments; X.-L. Wen, L.-S. Li and the Public Technology Service Center of XTBG (CAS) for assisting active VOCs analysis; and X.-G. Mao, P.-Y. Hua and D.-Y. Zhang for constructive suggestions in data analysis. This work is supported by NSFC grants 31630008 and 31870356 (X.-Y.C.) and 31870359 (G.W.), and a Talents 1000 Fellowship of Shaanxi Province (D.W.D.). S.T.S. acknowledges departmental support from Harper Adams University.
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X.-Y.C. and R.W. conceived and designed the study. R.W., Y. Yang, S.G.C., S.T.S., H.Y. and Z.Y. conducted the experiments and analysed data. Y.J., Q.-F.L., H.Y., Y.-Y.Z., G.W., J.C., R.M., S.C., Y.C., D.W.D., H.-Q.L., M.L., Y.-Y.D., Y.-Y.L., X.T., P.W., J.-J.Y., X.-T.Z., Q.G., Y. Yin, K.J. and H.-M.Y. contributed to data acquisition and data analyses. R.W., S.T.S., S.G.C., J.-Q.L., J.-Y.R., F.K., C.A.M, A.C., P.M.G., Y.-Y.Z. and X.-Y.C. edited the manuscript. All authors contributed to writing the manuscript.
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Wang, R., Yang, Y., Jing, Y. et al. Molecular mechanisms of mutualistic and antagonistic interactions in a plant–pollinator association. Nat Ecol Evol 5, 974–986 (2021). https://doi.org/10.1038/s41559-021-01469-1
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DOI: https://doi.org/10.1038/s41559-021-01469-1
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