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Article

Reference Gene Identification and RNAi-Induced Gene Silencing in the Redbay Ambrosia Beetle (Xyleborus glabratus), Vector of Laurel Wilt Disease

by
Morgan C. Knutsen
† and
Lynne K. Rieske
*
Department of Entomology, University of Kentucky, S-225 Ag Science North, Lexington, KY 40546-0091, USA
*
Author to whom correspondence should be addressed.
†
This work was part of the Master thesis of the first author, (Morgan C. Knutsen), at University of Kentucky.
Forests 2025, 16(10), 1577; https://doi.org/10.3390/f16101577
Submission received: 20 August 2025 / Revised: 9 October 2025 / Accepted: 10 October 2025 / Published: 14 October 2025
(This article belongs to the Section Forest Health)
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Abstract

Management of invasive species is especially difficult when the organisms involved are endophagous and their interactions complex. Such is the case with laurel wilt disease (LWD), a lethal vascular condition caused by Harringtonia lauricola, the fungal symbiont of the non-native redbay ambrosia beetle (RAB), Xyleborus glabratus Eichoff (Coleoptera: Curculionidae). LWD has caused extensive mortality of coastal redbay, Persea borbonia, and is expanding to utilize additional lauraceous hosts, including sassafras, Sassafras albidum. Current management has not been successful in preventing its spread, warranting investigation into additional techniques. RNA interference (RNAi) is a highly specific gene-silencing mechanism used for integrated pest management of crop pests and currently being investigated for use in forests. When targeting essential genes, RNAi can cause rapid insect mortality. Here we focus on RAB, identifying for the first time species-specific reference genes for quantitative real-time PCR (qPCR) and assessing mortality and gene expression after oral ingestion of double-stranded RNAs (dsRNAs) targeting essential genes (hsp, shi, and iap). Our study validates reference genes for expression analyses and shows significant mortality and changes in gene expression for all three target genes. Our research aims to contribute to the development of innovative management strategies for this invasive pest complex.

1. Introduction

Expansion of market economies, technological advances in transport and packaging, erosion of sociopolitical barriers, and globalization of trade have led to exponential increases in the movement of goods and people and unprecedented, unintentional movement of non-native species [1], some of which will become invasive [2]. Regulatory activities, including visual inspections, trap monitoring, and early detection and rapid response initiatives, are critical mitigation measures [3] but are unable to keep pace. Visual inspections are especially challenging when targeting small, endophagous organisms such as ambrosia beetles [4], which rely on obligate nutritional fungal symbionts for development and survival. In some cases, these beetle–fungal complexes are established and widespread before there is an awareness of their presence in our forests [5]. A relatively recent non-native ambrosia beetle–fungal introduction with substantial impact is that of the redbay ambrosia beetle (RAB), Xyleborus glabratus Eichhoff, and its nutritional symbiont, Harringtonia lauricola (T.C. Harr., Fraedrich & Aghayeva) Z.W. de Beer & M. Procter (Ophiostomatales: Ophiostomataceae). The fungus is the causal agent of laurel wilt disease (LWD), a lethal vascular wilt responsible for extensive mortality within the Lauraceae in its invaded North American range. Fungal propagules are introduced into the tree during beetle host selection, triggering the formation of defensive tyloses that occlude xylem vessels and disrupt water and nutrient transport in susceptible species [6]. Most native ambrosia beetles colonize dead or physiologically compromised trees [7], but RAB is atypical in that it attacks healthy hosts [8].
Native to Asia, LWD was first reported near Port Wentworth, GA, USA, in 2002 [9], causing extensive mortality of redbay, Persea borbonia L. Spreng, a key component in coastal forests of the southeast USA, providing essential resources for wildlife and, importantly, contributing to coastline stability [10]. Utilizing redbay as its primary host and subsequently infecting avocado, P. americana Mill., LWD spread throughout Florida, expanding westward while infecting additional lauraceous hosts, including sassafras, Sassafras albidum (Nutt.) Nees, and spicebush, Lindera benzoin (L.) Blume, [9], key resources for wildlife in eastern deciduous forests [11].
All North American Lauraceae evaluated thus far are viable hosts for LWD, including swampbay, P. palustris [12], pondspice, L. aestivalis [13], pondberry, L. melissifolia [13], silkbay, P. humilis [14], and California bay laurel, Umbellularia californica, which raises concerns about potential westward expansion of the insect–pathogen complex [15]. Southeastern coastal forests have been devastated by the LWD-induced decline of redbay [16,17], but the long-term ecological consequences for eastern deciduous forests remain uncertain [18]. Temperature extremes will not limit expansion of RAB [19], heightening concerns about geographic range expansion of LWD northward. Forests and agriculture in Mexico are equally threatened, as the commercially significant ‘Hass’ avocado and two native laurels, P. schiedeana and Ocotea heribertoi, are highly attractive to beetles [20].
Effective and practical management of LWD has been elusive. Sanitation through wood chipping reduces H. lauricola inoculum in infected material, but because of their small size (2.1–2.4 mm), RAB can survive and further infect susceptible hosts [21]. Contact and systemic insecticides are ineffective due to the beetles’ endophagous lifestyle and their reliance on a nutritional symbiont [22]. The fungicide Propiconazole is effective in redbay [23], avocado [24], and sassafras [25] when administered via macro-injection or root drench, but is limited by slow uptake, short residual, and high costs, limiting its practicality for widespread use in natural settings. Clearly, innovative management tactics are needed.
RNA interference (RNAi) is an emerging pest management strategy in agriculture [26] and horticulture [27] and is increasingly recognized as having potential against tree and forest pests [28,29,30,31]. The RNAi pathway is a conserved cellular immune mechanism that functions by silencing target genes through degradation of messenger RNA (mRNA) following the introduction of double-stranded RNA (dsRNA) [32], typically through oral ingestion or cuticular absorption when used for pest suppression [33]. Once introduced, the dsRNA is processed by the DICER enzyme into small-interfering RNAs (siRNAs) which are then incorporated into the RNA-induced silencing complex (RISC) [32]. Within this complex, the argonaute protein cleaves the passenger strand of the siRNAs, retaining the template strand, which guides the RISC to complementary mRNA sequences for degradation, thereby preventing translation [32]. If the targeted gene is essential for survival, this can cause mortality [34], and coleopterans are highly susceptible [35,36].
Relative to conventional chemical or cultural control tactics, RNAi offers several advantages. RNAi is highly specific [37], reducing risks to non-target organisms; it persists only briefly in the environment [38,39], avoiding many of the persistence issues associated with broad-spectrum insecticides, and can be tailored to disrupt vital physiological processes [40,41] that are otherwise inaccessible to conventional approaches. These qualities make RNAi particularly promising for invasive forest pests like ambrosia beetles.
The ability to induce gene silencing and cause insect mortality through oral ingestion of pest-specific dsRNAs has been demonstrated in many forest pests, including the Asian longhorned beetle (Anoplophora glabripennis Motschulsky) [42], emerald ash borer (Agrilus planipennis Fairmaire) [30], southern pine beetle (Dendroctonus frontalis Zimmermann) [29], mountain pine beetle (D. ponderosae Hopkins) [28], and six-spined ips (Ips calligraphus Germar) [31]. Given these successes, investigations into RNAi-based management strategies for RAB control appear warranted.
Evaluation of gene expression and associated mortality are essential aspects of RNAi technology development for pest management. Quantitative PCR, qPCR, is a powerful approach for assessing gene expression, but its reliability depends on accurate normalization to reference genes [43] that exhibit stable expression across experimental conditions. Selection of inappropriate reference genes can lead to inaccurate conclusions. While reference genes have been identified for several forest pests [29,44,45], such resources are not available for RAB, creating limitations to molecular analyses of this species. Thus, establishing and validating suitable reference genes is a critical prerequisite for both basic gene expression research and applied studies evaluating RNAi as a management strategy.
Here the overall goal was to assess the feasibility of using RNAi technology as a suppression approach for RAB by establishing RAB-specific reference genes, assessing insect mortality following oral ingestion of dsRNAs targeting specific essential RAB genes, and determining the extent of gene silencing in target genes after dsRNA exposure. Our specific objectives were to (i) identify and validate reference genes that exhibit stable expression under varying experimental conditions and (ii) evaluate the RNAi response in X. glabratus following oral ingestion of dsRNAs targeting three genes essential for cellular function and stress responses, including heat shock protein (hsp), shibire (shi), and inhibitor of apoptosis (iap).

2. Materials and Methods

2.1. Candidate Gene Selection and Primer Design

Reference genes serve as internal controls to normalize gene expression data, ensuring accurate quantification of target gene expression [46]. Validation of stably expressed reference genes via quantitative PCR (qPCR) is a critical preliminary step for RNAi evaluation. Candidate reference genes were selected from the literature for their stable expression and functional significance, including 28s ribosomal RNA (rRNA), elongation factor 1-alpha (ef1α), actin (act), 18s rRNA, and 16s rRNA. Candidate target genes, including heat shock protein (hsp), shibire (shi), and inhibitor of apoptosis (iap), were analyzed because they code for proteins necessary for cell function and stress response and were also successful in inducing mortality in other scolytines [28,29,31]. Reads obtained from NCBI (accessed October 2021) were trimmed and corrected using Rcorrector (Version 1.0.4) [47], Transcriptome Assembly Tools (https://github.com/harvardinformatics/TranscriptomeAssemblyTools), and TrimGalore (Version-0.6.0) (https://www.bioinformatics.babraham.ac.uk/projects/trim_galore/) (accessed 15 October 2021). High quality reads were used for a de novo transcriptome assembly with Trinity Version-2.13.2 [48] using default parameters. Long open reading frames (ORFs) were extracted using Transdecoder (Version 5.5.0). Sequences on NCBI from other coleopterans were used as a query for a tBLASTx [49] search using the assembled RAB transcriptome as the database. After confirming identity by using a BLASTx (https://blast.ncbi.nlm.nih.gov) (21 October 2025) search against NCBI’s nonredundant (NR) database, the online IDT primer building tool (PrimerQuest™) was used to design primers for dsRNA synthesis and quantitative PCR (qPCR) for reference gene and gene expression analyses (Table 1).
Primer pairs with an amplicon length between 80 and 120 bp, a GC% of ~50%, and a melt temperature of 60 °C, as well as with the lowest self and any scores, were chosen. Primers were only selected if the linear regression coefficient (R2) was ≥0.99 and the efficiency percentage was 90%–110%. For dsRNA primers, sequences were restricted to amplicon sizes between 200 and 450 bp, a GC% of 50%, and the lowest self and any scores. dsRNA primer sequences included a T7 promoter sequence (TAATACGACTCACTATAGGG) (Table 2) for compatibility with the MEGAscript RNAi Kit (Invitrogen, Waltham, MD, USA). Double-stranded green fluorescent protein (dsGFP) was selected as a negative control as it is not present in insects and cannot interfere with gene expression. Water was used as a second negative control for mortality analysis.

2.2. dsRNA Synthesis

Total RNA was extracted from adult RAB using the Trizol reagent (Life Technologies, Carlsbad, CA, USA), followed by gel electrophoresis and Nanodrop spectrometry (Thermo Fisher Scientific Inc., Waltham, MA, USA) to verify RNA integrity. cDNA (500 ng of RNA as template) was synthesized using SuperScript III Reverse Transcriptase (Invitrogen, Waltham, MA, USA), following the manufacturer’s protocol. Using RAB specific primers designed to target hsp, shi, and iap, PCR was performed at 94 °C for 30 s, followed by (94 °C for 30 s, 60 °C for 1 min, and 68 °C for 1 min) × 30 cycles, and a final extension step of 68 °C for 5 min. PCR templates were purified using a QIAquick PCR purification kit (Qiagen, Germantown, MD, USA), then synthesized into dsRNA using the MEGAscript RNAi kit (ThermoFisher, Waltham, MA, USA). The quality and quantity of dsRNA were assessed by gel electrophoresis and nanodrop spectrometry. dsRNA was dried at 37 °C using a Vacufuge Plus (Eppendorf, Hamburg, Germany) and resuspended in 0.5% sucrose solution containing blue tracking dye before use in bioassays.

2.3. Insects and dsRNA Treatments

Adult beetles used for reference gene analysis were collected from Broward County, FL, USA in October 2021 in compliance with institutional, national, and international guidelines and IUCN provisions. Adult beetles used for mortality and gene expression assays were collected from Alachua County, FL, USA, in August and September 2022, again in compliance with guidelines. Beetles were immediately shipped to the University of Kentucky, Lexington, KY, USA, and starved for 24 h before being used in experiments. Beetles used for reference gene assessment were placed under experimental conditions that included temperature, photoperiod, and dsRNA sensitivity (n = 7). To evaluate gene stability based on temperature, beetles were maintained at 20 °C and 25 °C for 72 h. To evaluate gene stability based on photoperiod, beetles were placed in total darkness or constant light for 72 h. To evaluate dsRNA sensitivity, beetles were exposed to 10 μg, based on success in other studies [29,45], dsGFP, + sucrose (0.5%) or a sucrose solution (0.5%) alone colored with a blue tracking dye [29,31]. The anterior end of each individual beetle was placed into a 10 μL micropipette tip containing 0.75 μL of the treatment, and using surface tension the solution was drawn up to submerge the insect up to the pronotum, taking care to not interfere with spiracles and oxygen intake. To prevent beetle movement, a second micropipette tip was placed behind the beetle (Figure 1). Micropipette tips containing beetles were oriented vertically in a Petri dish (100 × 15 mm) layered with moistened KimWipes (Kimtech, Neenah, WI, USA) for 24 h, after which they were removed and maintained in a Petri dish containing moistened KimWipes for an additional 72 h. Thus, each experimental beetle was subject to environmental conditions for 72 h following exposure, after which they were placed immediately into Trizol reagent to maximize RNA yield. Beetles evaluated for mortality (n = 21–28 per treatment) were administered treatments (dsHSP, dsSHI, dsIAP, dsGFP, and water) as described above and were maintained at room temperature and monitored every 24 h for mortality for 13 days. Mortality data was analyzed using a linear mixed effects model followed by a type III ANOVA (R statistical software Version 2023.3.1.446, Vienna, Austria). Tukey’s Honest Significant Difference (Tukey’s HSD) post hoc test was performed to identify the effects of treatments on beetle survival.

2.4. Gene Expression

To determine the optimal concentration to evaluate treatments and to ensure primers met parameters (R2 ≥ 0.99 and efficiency percentage 90%–110%), qPCR was performed on a 5-fold dilution of water and cDNA (starting at a 1:5 dilution). Single melt curves were analyzed to ensure primer dimers or non-specific products were not present. Individuals used for reference gene assessment (n = 7) were exposed to experimental temperature, photoperiod, and dsRNA exposure conditions for 72 h; individuals evaluated for gene silencing (n = 3–5) were exposed to dsHSP, dsSHI, dsIAP, and dsGFP for 24 h and then maintained for 48 h or 72 h before being placed into Trizol. After exposure to treatments, all beetles were macerated, and total RNA was extracted using Trizol reagent, precipitated in isopropanol, and washed once with 75% ethanol before being resuspended in nuclease free water. Nanodrop spectrometry was used to ensure RNA integrity. To evaluate reference gene stability, cDNA was synthesized with 331.1 ng total RNA/cDNA reaction. cDNA from each individual beetle was diluted to 1:5 (cDNA:water), and qPCR was performed to measure gene expression. Three technical replicates were run for each of the biological samples per treatment, and each plate contained a no template control for each primer. Expression was determined for each reference and target gene using the Ct (cycle threshold) value. Reference gene stability was analyzed using RefFinder [50], an online tool that combines GeNorm [51], NormFinder [52], BestKeeper [53], and the delta-CT method [54] to produce a final comprehensive ranking of gene stability. Relative gene expression was analyzed using the 2−∆∆Ct method [55], and extreme outliers were removed using an interquartile range (IQR) analysis (values above Q3 + 3 × IQR or below Q1 − 3 × IQR). Expression of target genes in treatment beetles (dsHSP, dsSHI, dsIAP) was compared to dsGFP-fed (control) beetles. Significance between control (dsGFP) and treatment beetles was measured using a Student’s one-tailed t-test.

3. Results

3.1. Reference Gene Stability

Across all treatments, 28s was most highly expressed with Ct values ranging from 14.4 to 25.1 (Figure 2); this was followed by 18s and 16s. The greatest range of expression was observed in 16s. Of all genes analyzed, the least expressed were ef1α and act.
Across experimental conditions, relative candidate gene expression levels were consistent (Figure 3). The highest levels of gene expression across conditions were observed in 28s, and the lowest expression was observed in act.
RefFinder combines four algorithms, including GeNorm, NormFinder, Bestkeeper, and delta-CT, to create a comprehensive stability ranking of the candidate reference genes. GeNorm uses a gene expression stability value (M) to determine stability with lower values indicating greater stability, and an M value <1.5 is required to consider a gene stable. Of the genes tested 28s, ef1α, and act met criteria with 28s at 1.33, and ef1α and act being equally expressed at 0.82 (Figure 4a). NormFinder uses a stability value (SV) to determine the stability ranking of candidate genes and stability is indicated by SV > 1. Candidate genes including eflα, act, 18s, and 16s met the threshold; 28s did not (Figure 4b). BestKeeper ranks candidate gene stability based on standard deviation (SD), with a SD < 1 considered to be more stable. Candidate genes including ef1α, act, and 16s met the threshold; 28s and 18s did not (Figure 4c). The delta-CT method also uses SD to determine stability, with a lower value indicating more stability. According to the delta-CT method, 28s and ef1α were most stable while 16s and 18s were least stable (Figure 4d).
Using geometric mean values, RefFinder ranked 28s as most stably expressed, followed by ef1α, act, 18s, and 16s (Table 3). Of these, ef1α and act were selected as reference genes as they meet the criteria for all four algorithms (GeNorm, NormFinder, BestKeeper, and delta-CT) and have similar relative gene expression levels (Figure 3), allowing them to be more applicable when evaluating future target genes. Gene expression was normalized across individuals using ef1α and act as reference genes.

3.2. RAB Mortality

There was significant mortality of beetles after exposure to dsRNAs (dsHSP, dsSHI, dsIAP) (F4,124 = 28.6, p < 0.001). Replicate (F2,2 = 0.09, p > 0.05) and treatment by day (F48,124 = 1.11, p > 0.05) were not significant. Tukey’s HSD demonstrated that mortality of all dsRNA treatments was significantly higher than the dsGFP and water controls (p < 0.0001). There were no significant differences in mortality between treatments (p > 0.05). Relative to control beetles, temporal differences in mortality were significant for dsHSP-treated beetles on day 11 (p < 0.05) (Figure 5). Differences were significant for dsSHI-treated beetles on days 8, 11, and 12 (p < 0.05) and for dsIAP-treated beetles on days 7, 10, and 11 (p < 0.05) (Figure 5). Mortality was marginally significant for dsHSP on day 7, dsSHI on days 9 and 10, and dsIAP on day 12 (p > 0.05).

3.3. Gene Expression

After 48 h of exposure to dsHSP, the hsp gene showed a significant 28% reduction in expression in comparison to dsGFP-treated control beetles (p = 0.03, df = 8; Figure 6a); after 72 h there was a significant 41% decrease (p = 0.03, df = 8; Figure 6b). A significant 28% reduction in gene expression was observed in shi after 48 h of exposure (p = 0.03, df = 7; Figure 6c), and after 72 h there was a 56% reduction in expression (p = 0.002, df = 7; Figure 6d). Contrary to expectations, the iap gene showed significant upregulation of 19% and 20%, respectively, after 48 h (p = 0.02, df = 7; Figure 6e) and after 72 h (p = 0.04, df = 7; Figure 6f). Significant downregulation in gene expression was observed in hsp and shi after 48 and 72 h of exposure to dsRNAs, corroborating with significant mortality.

4. Discussion

Here we identify stably expressed reference genes and document an RNAi-induced response in the non-native, invasive RAB, vector of the lethal laurel wilt disease, following oral ingestion of RAB-specific dsRNAs. This is the first published study to establish reference genes for gene expression analysis in this species. Establishment of reliable reference genes is essential for minimizing variability between samples and enhancing the accuracy of expression quantification [56,57]. Using multiple reference genes improves analytic rigor by accounting for variation across experimental treatments [58].
There is ample literature describing coleopteran gene selection to assess the feasibility of RNAi as a pest management strategy. In the Colorado potato beetle, Leptinotarsa decemlineata Say (Chrysomelidae), nine housekeeping genes were evaluated for stability and subsequent utility as reference genes in gene expression studies, including translation elongation factor 1α (ef1α) [59]. Similarly, in the chrysomelid western corn rootworm, Diabrotica virgifera virgifera Leconte, five candidate genes, again including elongation factor -1α (ef1α), were evaluated using multiple algorithms to determine relative expression and stability [60]. Based on these and other studies, ef1α has been a reliable component of RNAi-induced gene silencing proofs of concept for pest management. In our study, we selected ef1α and act as reference genes because they demonstrate comparable levels of expression and are stable; the comprehensive ranking produced by RefFinder ranked these as second and third, respectively. Gene stability across photoperiod and temperature conditions supports their utility under varying conditions, and there are numerous examples of their use in coleopterans, including for forest pests such as the southern pine beetle (Scolytinae) [29] and the emerald ash borer (Buprestidae) [44]. However, additional validation is needed to assess stability across beetle populations and across host plants, where genetic variation may influence gene expression and therefore RNAi efficacy as a pest management tool.
Target gene selection for tree pests has primarily focused on a limited number of conserved genes that have demonstrated relatively high and consistent efficacy within Coleoptera, though responses can still vary among species. In RAB, oral ingestion of dsRNAs targeting hsp and shi led to a significant downregulation at 48 and 72 h post-exposure, followed by subsequent mortality. Ingestion of dsHSP and dsSHI induces similar mortality and gene expression effects across multiple Scolytinae, including the southern and mountain pine beetles [28,29] and the six-spined ips [31].
RAB mortality also occurred following oral ingestion of dsIAP, but contrary to expectations, it was accompanied by a significant and unexpected upregulation of the iap gene and no detectable silencing. Similar paradoxical expression has been reported elsewhere. Upregulation of shi following dsSHI exposure was observed in another Scolytinae, I. calligraphus, despite high mortality [31] and has also been observed in Bactrocera dorsalis [61], suggesting upregulation across diverse insect taxa. Gene upregulation has also been documented in mammalian RNAi studies [62], indicating the widespread nature of this response, which clearly merits further investigation. Numerous factors could play a role, including the target site within the gene [63], interactions with regulatory elements that influence transcription, potentially leading to gene activation [62], compensatory and immune-associated responses [64], or high dsRNA concentrations [65]. The length and amount of dsRNAs can trigger different pathways leading to an increased inflammatory or immune response [66]. Additional studies are needed to evaluate dose-dependent responses to determine if the observed iap upregulation is driven by dsRNA concentration, seasonal variation, or host plant, all of which could play a role in efficacy and therefore in the feasibility of RNAi deployment.
Beyond targeting survival of the beetle vector, RNAi could be refocused to disrupt other components of the invasive LWD complex. Olfaction is critical for beetle host location and recognition [67], so silencing genes associated with olfactory reception could impair host-finding behavior and arrest disease spread. RNAi technology has shown promise influencing this aspect of beetle biology in other species [68]. Manipulation of the RNAi pathway could also target the fungal pathogen responsible for laurel wilt disease [69,70]. Although H. lauricola is an obligate nutritional symbiont of RAB, the fungus has been found associated with other arthropods, both internally and phoretically [24,71,72,73]. Because of fungal presence beyond the association with RAB, developing RNAi technology focusing on the fungus itself may be a more effective route for LWD management incorporating RNAi technology.
RNAi is considered species-specific, and this specificity has been demonstrated with multiple forest pest-specific dsRNAs [45,60,74,75,76], but congeneric effects have been documented [77,78]. Rather than being problematic, however, they point to the potential for designing dsRNAs that target multiple ambrosia beetle species or multiple coleopteran vectors, potentially limiting H. lauricola spread and reducing disease impacts. This would be especially attractive in highly managed orchard systems. Environmental persistence of RAB-specific dsRNAs must also be considered; however, research indicates that dsRNAs degrade rapidly in the environment [38,39], allowing this management approach to be applied as needed without long-term environmental accumulation.
Developing scalable dsRNA delivery strategies must also be prioritized. Successful in planta uptake and translocation of exogenous dsRNAs have been demonstrated in both conifer [79] and deciduous species [80,81] via root drenches [82], foliar sprays [83], and stem applications [27,84,85], suggesting that season-long, single tree protection is feasible. Large-scale RNAi delivery schemes for forest-wide protection remain challenging, yet innovative approaches such as fungi transformed to carry the pest-specific dsRNA construct or trees engineered to express pest-specific dsRNAs have potential [86].
Current management approaches have failed to contain the spread of LWD [21,22,87], highlighting an urgent need for novel strategies. However, widespread acceptance of emerging biotechnologies by stakeholders and end users is essential to enable use of RNAi and other innovative tools for managing our natural resources that are threatened by multiple stressors. Developing these emerging technologies could substantially contribute to the mitigation of LWD and other invading pest complexes, safeguarding our forests.

5. Conclusions

Management of laurel wilt disease and its primary vector, the redbay ambrosia beetle, is problematic. The insect is cryptic, the disease complex is spreading, trees are dying, and innovative approaches are badly needed. RNA interference (RNAi) technology is a highly precise, ecologically sound, non-chemical mechanism for modulating gene expression and inducing insect mortality. Although RNAi technology in forests is in its infancy, here we demonstrate its potential for suppressing the vector of an aggressive insect–pathogen complex. RNAi technology shows promise, and advancing molecularly based strategies for pest suppression constitutes a critical step toward managing invasive insect pests and pathogens sustainably and enhancing forest health under escalating biotic and abiotic pressures.

Author Contributions

M.C.K.: Visualization, Methodology, Investigation, Formal analysis, Writing—original draft. L.K.R.: Project administration, Funding acquisition, Conceptualization, Analysis, Writing—review and editing. All authors have read and agreed to the published version of the manuscript.

Funding

This publication is from the Kentucky Agricultural Experiment Station and is published with the approval of the director. This work was supported through the USDA Forest Health Research and Education Center and through funds provided by USDA APHIS AP20PPQS&T00C0032, USDA Forest Service Southern Research Station 23-JV-11330160-070, 24-JV-11330160-108, the University of Kentucky, and the Kentucky Agricultural Experiment Station under McIntire-Stennis 2351197000.

Data Availability Statement

Data is available through Harvard Dataverse at https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/BRJVCY accessed 1 October 2021.

Acknowledgments

The authors thank Jeffery Eickwort, Florida Forest Service, and Paul Kendra, USDA ARS, for assistance in obtaining beetles. Tyler Dreaden, USDA Forest Service, provided invaluable insight into experimental design. Beth Kyre, Mary Wallace, Zach Bragg, and Flávia Pampolini assisted in the laboratory.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Adult RAB are exposed to dsRNA treatment using a 10 μL micropipette tip. A second micropipette tip prevents beetle movement.
Figure 1. Adult RAB are exposed to dsRNA treatment using a 10 μL micropipette tip. A second micropipette tip prevents beetle movement.
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Forests 16 01577 g002
Figure 2. Candidate reference gene Ct values across all treatments. Boxes encompass the 25th to the 75th percentiles, and whiskers represent 1.5 times the interquartile range. Outliers are indicated by dots.
Figure 2. Candidate reference gene Ct values across all treatments. Boxes encompass the 25th to the 75th percentiles, and whiskers represent 1.5 times the interquartile range. Outliers are indicated by dots.
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Forests 16 01577 g003
Figure 3. Candidate reference gene average Ct values across experimental conditions that include (a) photoperiod, (b) temperature, and (c) dsRNA exposure. Maximum and minimum Ct values are represented by error bars.
Figure 3. Candidate reference gene average Ct values across experimental conditions that include (a) photoperiod, (b) temperature, and (c) dsRNA exposure. Maximum and minimum Ct values are represented by error bars.
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Forests 16 01577 g004
Figure 4. Reference gene stability rankings across four algorithms, including (a) GeNorm, (b) NormFinder, (c) BestKeeper, and (d) the delta-CT method.
Figure 4. Reference gene stability rankings across four algorithms, including (a) GeNorm, (b) NormFinder, (c) BestKeeper, and (d) the delta-CT method.
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Forests 16 01577 g005
Figure 5. Beetle mortality up to 13 days after exposure to 10 μg of dsRNAs (dsHSP, dsSHI, dsIAP) and negative controls (dsGFP and water). Significant temporal differences in mortality relative to controls for beetles fed dsHSP (■), dsSHI (●), and dsIAP (◆).
Figure 5. Beetle mortality up to 13 days after exposure to 10 μg of dsRNAs (dsHSP, dsSHI, dsIAP) and negative controls (dsGFP and water). Significant temporal differences in mortality relative to controls for beetles fed dsHSP (■), dsSHI (●), and dsIAP (◆).
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Figure 6. Relative mRNA levels in beetles treated with 10 μg of dsRNA (dsHSP, dsSHI, dsIAP) relative to the negative control, dsGFP, after 48 h (a,c,e) and 72 h (b,d,f). Significance is indicated by an asterisk (*).
Figure 6. Relative mRNA levels in beetles treated with 10 μg of dsRNA (dsHSP, dsSHI, dsIAP) relative to the negative control, dsGFP, after 48 h (a,c,e) and 72 h (b,d,f). Significance is indicated by an asterisk (*).
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Table 1. qPCR primer sequences, amplicon size in base pairs, R2 correlation coefficient, and percent primer efficiency.
Table 1. qPCR primer sequences, amplicon size in base pairs, R2 correlation coefficient, and percent primer efficiency.
Gene NamePrimersAmplicon (bp)R2E(%)
28s ribosomal RNA
(28s)		F - CGTCTCGTCATTCGTACGTG
R - ACGAGTCGAACGCTCCTAAA		1070.997109
Elongation factor-1 alpha
(ef1a)		F - CTCGGCCTTCAATTTATCCA
R - CATCGACAAACGTACCATCG		1000.990105
Actin
(act)		F - CCAGACGCGTATAAGGACAAA
R - CCCAAGGCCAACAGAGAAA		1040.994104
18s ribosomal RNA
(18s)		F - GTTTTCGGAACACCGAGGTA1020.99293
R - GCTTCTGTCCGTCTTTCGAC
16s ribosomal RNA
(16s)		F - GCGACCTCGATGTTGGATTA1000.99897
R - GCCGGTCTAAACTCAGATCAT
Heat shock protein
(hsp)		F - CCAAGGATGGAGAACGATTAG1000.99795
R - CGTCTTCCAATCAACCTCTT
Shibire
(shi)		F - AGATGGGTACTGTGGGATCT1070.99294
R - TCCTGGTCTGTTGGGAATTG
Inhibitor of apoptosis
(iap)		F - GTGATGGCTCGGCATAGAAA1000.99691
R - CAGGGCTGGTGGATGTTATT
Table 2. dsRNA primer sequences including the T7 promoter sequence (in bold) and amplicon size in base pairs.
Table 2. dsRNA primer sequences including the T7 promoter sequence (in bold) and amplicon size in base pairs.
GenePrimer SequencesAmplicon
hspF:TAATACGACTCACTATAGGGGTGATTGCAGGGTTGAATGTG419
R:TAATACGACTCACTATAGGGCTGGCTCTAGTGATCTTGGAATAG
shiF:TAATACGACTCACTATAGGGGACATGGCGTTTGAAGCAATAG420
R:TAATACGACTCACTATAGGGGGAAGTGAGGACAAACCAGTAG
iapF:TAATACGACTCACTATAGGGTGGTCAAAGGGCAGGATTT399
R:TAATACGACTCACTATAGGGGTTTGGAAGCGTGGTCAATG
gfpF:TAATACGACTCACTATAGGGCGATGCCACCTACGGCAA288
R:TAATACGACTCACTATAGGGTGTCGCCCTCGAACTTCA
Table 3. Stability ranking for five candidate reference genes by web-based tool RefFinder, which combines GeNorm, NormFinder, BestKeeper, and delta-CT to create a comprehensive ranking. M: gene expression stability; SV: stability value; SD: standard deviation; GM: geometric mean; R: ranking.
Table 3. Stability ranking for five candidate reference genes by web-based tool RefFinder, which combines GeNorm, NormFinder, BestKeeper, and delta-CT to create a comprehensive ranking. M: gene expression stability; SV: stability value; SD: standard deviation; GM: geometric mean; R: ranking.
GeNormNormFinderBestKeeperdelta-CTComprehensive
GeneMRSVRSDRSDRGMR
28s1.3320.4710.9321.6411.571
ef1a0.8211.3721.0941.85222
act0.8211.5941.1151.9932.783
18s1.9141.6450.6812.0853.344
16s1.7931.6731.073243.465
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Knutsen, M.C.; Rieske, L.K. Reference Gene Identification and RNAi-Induced Gene Silencing in the Redbay Ambrosia Beetle (Xyleborus glabratus), Vector of Laurel Wilt Disease. Forests 2025, 16, 1577. https://doi.org/10.3390/f16101577

AMA Style

Knutsen MC, Rieske LK. Reference Gene Identification and RNAi-Induced Gene Silencing in the Redbay Ambrosia Beetle (Xyleborus glabratus), Vector of Laurel Wilt Disease. Forests. 2025; 16(10):1577. https://doi.org/10.3390/f16101577

Chicago/Turabian Style

Knutsen, Morgan C., and Lynne K. Rieske. 2025. "Reference Gene Identification and RNAi-Induced Gene Silencing in the Redbay Ambrosia Beetle (Xyleborus glabratus), Vector of Laurel Wilt Disease" Forests 16, no. 10: 1577. https://doi.org/10.3390/f16101577

APA Style

Knutsen, M. C., & Rieske, L. K. (2025). Reference Gene Identification and RNAi-Induced Gene Silencing in the Redbay Ambrosia Beetle (Xyleborus glabratus), Vector of Laurel Wilt Disease. Forests, 16(10), 1577. https://doi.org/10.3390/f16101577

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