The predatory natural enemy Eocanthecona furcellata plays a crucial role in agricultural ecosystems due to its effective pest control measures and defensive venom. Predator venom contains serine protease inhibitors (SPIs), which are the primary regulators of serine protease activity and play key roles in digestion, development, innate immunity, and other physiological regulatory processes. However, the regulation mechanism of SPIs in the salivary glands of predatory natural enemies is still unknown. In this study, we sequenced the transcriptome of E. furcellata salivary gland and identified 38 SPIs genes named EfSPI1∼EfSPI38. Through gene structure, multiple sequence alignment and phylogenetic tree analysis, real-time quantitative PCR (RT-PCR) expression profiles of different developmental stages and different tissues were analyzed. RNAi technology was used to explore the gene function of EFSPI20. The results showed that these 38 EfSPIs genes contained 8 SPI domains, which were serpin, TIL, Kunitz, Kazal, Antistasin, Pacifastin, WAP and A2M. The expression profile results showed that the expression of different types of EfSPIs genes was different at different developmental stages and different tissues. Most of the EfSPIs genes were highly expressed in the egg stage. The EfSPI20, EfSPI21, EfSPI22, and EfSPI24 genes of the Pacifastin subfamily and the EfSPI35 gene of the A2M subfamily were highly expressed in the nymphal and adult stages, which was consistent with the RT-qPCR verification results. These five genes are positively correlated with each other and have a synergistic effect on E. furcellata, and they were highly expressed in salivary glands. After interfering with the expression of the EfSPI20 gene, the survival rate and predatory amount of male and female adults were significantly decreased. Taken together, we speculated some EfSPIs may inhibit trypsin, chymotrypsin, and elastase, and some EfSPIs may be involved in autoimmune responses. EfSPI20 was essential for the predation and digestion of E. furcellata, and the functions of other EfSPIs were discussed. Our findings provide valuable insights into the diversity of EfSPIs in E. furcellata and the potential functions of regulating their predation, digestion and innate immunity, which may be of great significance for developing new pest control strategies.

Evidence is accumulating that evolutionary changes are not only common during biological invasions but may also contribute directly to invasion success. The genomic basis of such changes is still largely unexplored. Yet, understanding the genomic response to invasion may help to predict the conditions under which invasiveness can be enhanced or suppressed. Here we characterized the genome response of the spotted wing drosophila Drosophila suzukii during the worldwide invasion of this pest insect species, by conducting a genome-wide association study to identify genes involved in adaptive processes during invasion. Genomic data from 22 population samples were analyzed to detect genetic variants associated with the status (invasive versus native) of the sampled populations based on a newly developed statistic, we called C 2, that contrasts allele frequencies corrected for population structure. This new statistical framework has been implemented in an upgraded version of the program BayPass. We identified a relatively small set of single nucleotide polymorphisms (SNPs) that show a highly significant association with the invasive status of populations. In particular, two genes RhoGEF64C and cpo , the latter contributing to natural variation in several life-history traits (including diapause) in Drosophila melanogaster , contained SNPs significantly associated with the invasive status in the two separate main invasion routes of D. suzukii . Our methodological approaches can be applied to any other invasive species, and more generally to any evolutionary model for species characterized by non-equilibrium demographic conditions for which binary covariables of interest can be defined at the population level.

Deciphering invasion routes from molecular data is crucial to understanding biological invasions, including identifying bottlenecks in population size and admixture among distinct populations. Here, we unravel the invasion routes of the invasive pest Drosophila suzukii using a multi-locus microsatellite dataset (25 loci on 23 worldwide sampling locations). To do this, we use approximate Bayesian computation (ABC), which has improved the reconstruction of invasion routes, but can be computationally expensive. We use our study to illustrate the use of a new, more efficient, ABC method, ABC random forest (ABC-RF) and compare it to a standard ABC method (ABC-LDA). We find that Japan emerges as the most probable source of the earliest recorded invasion into Hawaii. Southeast China and Hawaii together are the most probable sources of populations in western North America, which then in turn served as sources for those in eastern North America. European populations are genetically more homogeneous than North American populations, and their most probable source is northeast China, with evidence of limited gene flow from the eastern US as well. All introduced populations passed through bottlenecks, and analyses reveal five distinct admixture events. These findings can inform hypotheses concerning how this species evolved between different and independent source and invasive populations. Methodological comparisons indicate that ABC-RF and ABC-LDA show concordant results if ABC-LDA is based on a large number of simulated datasets but that ABC-RF out-performs ABC-LDA when using a comparable and more manageable number of simulated datasets, especially when analyzing complex introduction scenarios.