Abstract
Parasitoid wasps are important biological control resources, yet their genetic manipulation has long been constrained by small body size and parasitization behavior, limiting their broader application in pest management. Here we report a chromosome-level genome assembly of the ectoparasitoid Gregopimpla kuwanae (322.87 Mb, 24 chromosomes), a relatively large species that parasitizes various lepidopteran pests. In the first part of this study, we established a foundational genomic resource and experimental platform by producing a high-quality genome and demonstrating the feasibility of functional genetics: RNA interference successfully silenced the cinnabar gene, while CRISPR/Cas9 editing generated vestigial knockout mutants, thus establishing G. kuwanae as a tractable system for gene manipulation. In the second part, we applied comparative genomics to identify lineage-specific gene-family expansions linked to parasitism, including venom-related genes, immune suppression factors, and detoxification enzymes (cytochrome P450s and UDP-glucosyltransferases), and we identified eight HGT candidates; one candidate (JSFChr12G01362) showed pre-feeding expression in females and caused increased adult mortality upon RNAi. Our study provides both the means and the candidates for mechanistic dissection of parasitoid adaptations, laying a foundation for the broader application of parasitoid wasps in sustainable biocontrol programs.
Data availability
The genome assembly and all raw sequencing data generated in this study have been deposited in the NCBI under BioProject accession PRJNA1242975. This includes raw short-read sequencing data (SRX28190072), PacBio HiFi long-read data (SRX28190073), Hi-C data (SRX28190084 and SRX28190095), and RNA-seq data (SRX28190074-SRX28190083, SRX28190085-SRX28190094, SRX28190096-SRX28190111), as well as the final chromosome-level genome assembly of G. kuwanae (GCA_052576135.1). Source data underlying the figures of this manuscript can be found in Supplementary Data 1. All other data supporting the findings of this study are also available from the corresponding author upon reasonable request.
Code availability
The software and parameters used in this study are described in the Methods section. No specific custom codes or scripts were utilized. Data processing was conducted according to the manuals and protocols provided with the respective software.
References
Beddington, J. Food security: contributions from science to a new and greener revolution. Philos. Trans. R. Soc. B: Biol. Sci. 365, 61–71 (2010).
Oerke, E.-C. Crop losses to pests. J. Agric. Sci. 144, 31–43 (2006).
Barzman, M. et al. Eight principles of integrated pest management. Agron. Sustain. Dev. 35, 1199–1215 (2015).
Damalas, C. A. & Eleftherohorinos, I. G. Pesticide Exposure, Safety Issues, and Risk Assessment Indicators. Int. J. Environ. Res. Public Health 8, 1402–1419 (2011).
Mancini, F., Woodcock, B. A. & Isaac, N. J. B. Agrochemicals in the wild: Identifying links between pesticide use and declines of nontarget organisms. Curr. Opin. Environ. Sci. Health 11, 53–58 (2019).
Blaimer, B. B. et al. Key innovations and the diversification of Hymenoptera. Nat. Commun. 14, 1212 (2023).
Burke, G. R. & Sharanowski, B. J. Parasitoid wasps. Curr. Biol. 34, R483–R488 (2024).
Fei, M., Gols, R. & Harvey, J. A. The Biology and Ecology of Parasitoid Wasps of Predatory Arthropods. Annu. Rev. Entomol. 68, 109–128 (2023).
Chen, X. & van Achterberg, C. Systematics, Phylogeny, and Evolution of Braconid Wasps: 30 Years of Progress. Annu. Rev. Entomol. 64, 335–358 (2019).
Polaszek, A. & Vilhemsen, L. Biodiversity of hymenopteran parasitoids. Curr. Opin. Insect Sci. 56, 101026 (2023).
Strand, M. R. Teratocytes and their functions in parasitoids. Curr. Opin. Insect Sci. 6, 68–73 (2014).
Wang, Y. et al. Symbiotic bracovirus of a parasite manipulates host lipid metabolism via tachykinin signaling. PLOS Pathog. 17, e1009365 (2021).
Ye, X., Yang, Y., Zhao, X., Fang, Q. & Ye, G. The state of parasitoid wasp genomics. Trends Parasitol. 40, 914–929 (2024).
Hammond, A. et al. A CRISPR-Cas9 gene drive system targeting female reproduction in the malaria mosquito vector Anopheles gambiae. Nat. Biotechnol. 34, 78–83 (2016).
Xu, H. et al. Comparative Genomics Sheds Light on the Convergent Evolution of Miniaturized Wasps. Mol. Biol. Evol. 38, 5539–5554 (2021).
Zhu, K. Y. & Palli, S. R. Mechanisms, Applications, and Challenges of Insect RNA Interference. Annu. Rev. Entomol. 65, 293–311 (2020).
Bai, X. et al. CRISPR/Cas9-mediated mutagenesis of the white gene in an ectoparasitic wasp, Habrobracon hebetor. Pest Manag. Sci. 80, 1219–1227 (2024).
Li, M. et al. Generation of heritable germline mutations in the jewel wasp Nasonia vitripennis using CRISPR/Cas9. Sci. Rep. 7, 901 (2017).
Li, Y. et al. Identification of candidate chemosensory genes by antennal transcriptome analysis in an ectoparasitoid wasp. J. Appl. Entomol. 146, 335–351 (2022).
Ueno, T. Oviposition and Development in Gregopimpla kuwanae Viereck (Hymenoptera: Ichneumonidae), a Gregarious Ectoparasitoid Wasp Attacking the Rice Skipper Parnara guttata. J. Insects 2016, e4706376 (2016).
Zhou, H., Yu, Y., Tan, X., Chen, A. & Feng, J. Biological control of insect pests in apple orchards in China. Biol. Control 68, 47–56 (2014).
Qu, Y. et al. Ground tit genome reveals avian adaptation to living at high altitudes in the Tibetan plateau. Nat. Commun. 4, 2071 (2013).
Pavlovich, S. S. et al. The Egyptian Rousette Genome Reveals Unexpected Features of Bat Antiviral Immunity. Cell 173, 1098–1110.e18 (2018).
Li, Y. et al. HGT is widespread in insects and contributes to male courtship in lepidopterans. Cell 185, 2975–2987.e10 (2022).
Branstetter, M. G. et al. Phylogenomic Insights into the Evolution of Stinging Wasps and the Origins of Ants and Bees. Curr. Biol. 27, 1019–1025 (2017).
Peters, R. S. et al. Evolutionary History of the Hymenoptera. Curr. Biol. 27, 1013–1018 (2017).
Shi, Y. et al. Divergent amplifications of CYP9A cytochrome P450 genes provide two noctuid pests with differential protection against xenobiotics. Proc. Natl. Acad. Sci. 120, e2308685120 (2023).
Thurmond, J. et al. FlyBase 2.0: the next generation. Nucleic Acids Res. 47, D759–D765 (2019).
Shen, X.-X. et al. Tempo and Mode of Genome Evolution in the Budding Yeast Subphylum. Cell 175, 1533–1545.e20 (2018).
Ye, X. et al. Genomic signatures associated with maintenance of genome stability and venom turnover in two parasitoid wasps. Nat. Commun. 13, 6417 (2022).
Yang, Y. et al. Genome of the pincer wasp Gonatopus flavifemur reveals unique venom evolution and a dual adaptation to parasitism and predation. BMC Biol. 19, 145 (2021).
Christiaens, O., Swevers, L. & Smagghe, G. DsRNA degradation in the pea aphid (Acyrthosiphon pisum) associated with lack of response in RNAi feeding and injection assay. Peptides 53, 307–314 (2014).
Guo, X., Wang, Y., Sinakevitch, I., Lei, H. & Smith, B. H. Comparison of RNAi knockdown effect of tyramine receptor 1 induced by dsRNA and siRNA in brains of the honey bee, Apis mellifera. J. Insect Physiol. 111, 47–52 (2018).
Singh, I. K., Singh, S., Mogilicherla, K., Shukla, J. N. & Palli, S. R. Comparative analysis of double-stranded RNA degradation and processing in insects. Sci. Rep. 7, 17059 (2017).
Wang, K. et al. Variation in RNAi efficacy among insect species is attributable to dsRNA degradation in vivo. Insect Biochem. Mol. Biol. 77, 1–9 (2016).
Laudani, F. et al. RNAi-mediated gene silencing in Rhynchophorus ferrugineus (Oliver) (Coleoptera: Curculionidae). Open Life Sci. 12, 214–222 (2017).
Prentice, K. et al. RNAi-based gene silencing through dsRNA injection or ingestion against the African sweet potato weevil Cylas puncticollis (Coleoptera: Brentidae). Pest Manag. Sci. 73, 44–52 (2017).
Rangasamy, M. & Siegfried, B. D. Validation of RNA interference in western corn rootworm Diabrotica virgifera virgifera LeConte (Coleoptera: Chrysomelidae) adults. Pest Manag. Sci. 68, 587–591 (2012).
Rodrigues, T. B., Dhandapani, R. K., Duan, J. J. & Palli, S. R. RNA interference in the Asian Longhorned Beetle: Identification of Key RNAi Genes and Reference Genes for RT-qPCR. Sci. Rep. 7, 8913 (2017).
Ghosh, S., Tibbit, C. & Liu, J.-L. Effective knockdown of Drosophila long non-coding RNAs by CRISPR interference. Nucleic Acids Res. 44, e84 (2016).
Konermann, S. et al. Genome-scale transcriptional activation by an engineered CRISPR-Cas9 complex. Nature 517, 583–588 (2015).
Nauen, R., Bass, C., Feyereisen, R. & Vontas, J. The Role of Cytochrome P450s in Insect Toxicology and Resistance. Annu. Rev. Entomol. 67, 105–124 (2022).
Zhu, S. et al. Expression of a viral ecdysteroid UDP-glucosyltransferase enhanced the insecticidal activity of the insect pathogenic fungus. Pest Manag. Sci. 80, 4915–4923 (2024).
Feyereisen, R. 8 - Insect CYP Genes and P450 Enzymes. in Insect Molecular Biology and Biochemistry (ed. Gilbert, L. I.) 236–316 (Academic Press, San Diego, 2012).
Honutagi, R. M. et al. Protein-protein interaction of LDH and CRP-1 with hematotoxin snake venom proteins of all species of snake: An in silico approach. Int. J. Health Sci. 17, 10 (2023).
Deng, Y. et al. Lipolytic Activity of a Carboxylesterase from Bumblebee (Bombus ignitus) Venom. Toxins 13, 239 (2021).
Andersen, A. S., Hansen, P. H., Schäffer, L. & Kristensen, C. A New Secreted Insect Protein Belonging to the Immunoglobulin Superfamily Binds Insulin and Related Peptides and Inhibits Their Activities *. J. Biol. Chem. 275, 16948–16953 (2000).
Zhu, J.-Y. Deciphering the main venom components of the ectoparasitic ant-like bethylid wasp, Scleroderma guani. Toxicon 113, 32–40 (2016).
Chen, Y. et al. SOAPnuke: a MapReduce acceleration-supported software for integrated quality control and preprocessing of high-throughput sequencing data. GigaScience 7, gix120 (2018).
Hoover, A. & Miller, L. A numerical study of the benefits of driving jellyfish bells at their natural frequency. J. Theor. Biol. 374, 13–25 (2015).
Vurture, G. W. et al. GenomeScope: fast reference-free genome profiling from short reads. Bioinformatics 33, 2202–2204 (2017).
Cheng, H., Concepcion, G. T., Feng, X., Zhang, H. & Li, H. Haplotype-resolved de novo assembly using phased assembly graphs with hifiasm. Nat. Methods 18, 170–175 (2021).
Durand, N. C. et al. Juicer Provides a One-Click System for Analyzing Loop-Resolution Hi-C Experiments. Cell Syst. 3, 95–98 (2016).
Seppey, M., Manni, M. & Zdobnov, E. M. BUSCO: Assessing Genome Assembly and Annotation Completeness. in Gene Prediction: Methods and Protocols (ed. Kollmar, M.) 227–245 (Springer, New York, NY, 2019).
Tarailo-Graovac, M. & Chen, N. Using RepeatMasker to Identify Repetitive Elements in Genomic Sequences. Current Protocols in Bioinformatics 25, 4.10.1-4.10.14 (2009).
Ellinghaus, D., Kurtz, S. & Willhoeft, U. LTRharvest, an efficient and flexible software for de novo detection of LTR retrotransposons. BMC Bioinforma. 9, 18 (2008).
Benson, G. Tandem repeats finder: a program to analyze DNA sequences. Nucleic Acids Res. 27, 573–580 (1999).
Keilwagen, J., Hartung, F. & Grau, J. GeMoMa: Homology-Based Gene Prediction Utilizing Intron Position Conservation and RNA-seq Data. in Gene Prediction: Methods and Protocols (ed. Kollmar, M.) 161–177 (Springer, New York, NY, 2019).
Stanke, M. et al. AUGUSTUS: ab initio prediction of alternative transcripts. Nucleic Acids Res. 34, W435–W439 (2006).
Hernández-Salmerón, J. E. & Moreno-Hagelsieb, G. Progress in quickly finding orthologs as reciprocal best hits: comparing blast, last, diamond and MMseqs2. BMC Genomics 21, 741 (2020).
Quevillon, E. et al. InterProScan: protein domains identifier. Nucleic Acids Res. 33, W116–W120 (2005).
Emms, D. M. & Kelly, S. OrthoFinder: phylogenetic orthology inference for comparative genomics. Genome Biol. 20, 238 (2019).
Chen, C. et al. TBtools: An Integrative Toolkit Developed for Interactive Analyses of Big Biological Data. Mol. Plant 13, 1194–1202 (2020).
Katoh, K., Misawa, K., Kuma, K. & Miyata, T. MAFFT: a novel method for rapid multiple sequence alignment based on fast Fourier transform. Nucleic Acids Res. 30, 3059–3066 (2002).
Stamatakis, A. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 30, 1312–1313 (2014).
dos Reis, M. Dating Microbial Evolution with MCMCtree. in Environmental Microbial Evolution: Methods and Protocols (ed. Luo, H.) 3–22 (Springer US, New York, NY, 2022).
Kumar, S. et al. TimeTree 5: An Expanded Resource for Species Divergence Times. Mol. Biol. Evolution 39, msac174 (2022).
Abramova, A., Osińska, A., Kunche, H., Burman, E. & Bengtsson-Palme, J. CAFE: a software suite for analysis of paired-sample transposon insertion sequencing data. Bioinformatics 37, 121–122 (2021).
Johnson, M. et al. NCBI BLAST: a better web interface. Nucleic Acids Res. 36, W5–W9 (2008).
Nguyen, L.-T., Schmidt, H. A., von Haeseler, A. & Minh, B. Q. IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol. Biol. Evolution 32, 268–274 (2015).
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).
Chen, K., Durand, D. & Farach-Colton, M. NOTUNG: A Program for Dating Gene Duplications and Optimizing Gene Family Trees. J. Computational Biol. : J. C. omputational Mol. cell Biol. 7, 429–447 (2004).
Wang, Y. et al. MCScanX: a toolkit for detection and evolutionary analysis of gene synteny and collinearity. Nucleic Acids Res. 40, e49 (2012).
Acknowledgements
This work was supported by the National Science Foundation of China (32573304 and 32400380), the Natural Science Foundation of Jiangsu Province (BK20241861).
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Hao Gao: Conceptualization, Methodology, Investigation, Writing-original draft; Yijiangcheng Li, Yanli Chen: Sample Collection, Experiment, Investigation; Mengying Fang, Shuyu Zhang, Hui Zhang: Sample Collection, Experiment; Jianhao Ding, Dalin Zhu: Investigation, Validation; Anjiang Tang, Sheng Sheng: Funding acquisition, Project administration, Supervision, Writing-review & editing.
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Gao, H., Li, Y., Chen, Y. et al. Genomic landscape and genetic manipulation of an ectoparasitoid wasp, Gregopimpla kuwanae. Commun Biol (2026). https://doi.org/10.1038/s42003-026-09699-4
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DOI: https://doi.org/10.1038/s42003-026-09699-4