Coconut Rhinoceros Beetle mitochondrial genomes assessment refines understanding of its Pacific invasions

Coconut Rhinoceros Beetle mitochondrial genomes assessment refines understanding of its Pacific invasions | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Coconut Rhinoceros Beetle mitochondrial genomes assessment refines understanding of its Pacific invasions Wee Tek Tay, Angel David Popa-Baez, Demi Yi-Chun Cho, Rahul Rane, and 21 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7796543/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 10 You are reading this latest preprint version Abstract We used draft mitochondrial genomes (mitogenomes) to explore introduction histories of the destructive coconut rhinoceros beetle (CRB, Oryctes rhinoceros L.) throughout the Pacific and its native range, focusing on re-evaluating the relationship between members of the CRB-G haplotype grouping ( sensu Marshall et al. 2017 ) as previously assessed by the partial mtCOI (mitochondrial DNA cytochrome oxidase subunit I ) gene. Mitogenome analyses that included historical CRB collections confirmed the 2007 invasive CRB population in Guam was found only in Guam, while there was a detection of a second novel CRB mitogenome, suggesting a new recent introduction(s) into Guam. Further, mitogenome analyses linked: Palau CRB with Indonesia and Philippines native range populations; Papua New Guinea and Solomon Islands CRB with native range Malaysia CRB; Marshall Islands CRB with Solomon Islands CRB; and Samoa and Fiji CRB with Sri Lanka. We therefore provided evidence of historical and current CRB hitchhiking pathways between various native and introduced locations. The results build upon the previous partial mtCOI marker framework to improve the resolution of diversity present within CRB. This study also highlights a need to implement new CRB population nomenclatures based on full mitochondrial DNA genomes. Biological sciences/Ecology Earth and environmental sciences/Ecology Biological sciences/Evolution Biological sciences/Genetics biosecurity CRB-G metagenomic Oryctes rhinoceros incursion Figures Figure 1 Figure 2 Figure 3 Figure 4 INTRODUCTION Accurate species identification and knowledge of the genetic diversity of alien invasive species are critical to the understanding of actual and potential introduction pathways. They enable identification of potential biosecurity hotspots (Rane et al. 2023 ; Tay et al. 2023) and allow factors underpinning continuous and emerging spread patterns to be identified. Spread through behavioural, environmental, and climatic factors, as well as natural migration abilities, has long underpinned distributions of exotic species (e.g., desert locust Schistocerca gregaria (Kennedy 1951 ; Lorenz 2009), blue-tongue virus vector Culicoides midges species (Murray 1987 ; Murray and Kirkland 1995 ;Eagles et al. 2012 ), and various lepidoptera species including the monarch butterfly (Reppert and de Roode 2018 ) and Helicoverpa species (Fitt 1996 ; Paula-Moraes et al. 2024 )). Increasingly, however, global trade, has been shown to be the overarching factor driving the spread of exotic alien species (De Barro et al. 2011; Lopez-da-Silva et al. 2014; Tay et al. 2016 ; Elfekih et al. 2018 ; Jones et al. 2019 ; Arnemann et al. 2019; Moore et al. 2016 ). In arthropods, various mitochondrial DNA gene regions, especially the partial cytochrome oxidase subunit I ( mtCOI ) gene, have long been used as the DNA marker to assist with species identification as well as initial investigative effort of genetic diversity within the species. However, such single markers provide limited insight into the genetic diversity of invasive species, and thus present limitations around the utility of these assessments for the likes of pathway analysis. Advances in whole genome sequencing technology and the associated rapidly decreasing sequencing costs now provide comprehensive data into not only population genetic diversity and structure that can be used to assess introduction histories, but also genes important for adaptation and for resistance to current and potential control agents. Studies comparing partial mtCOI versus whole genome sequence data have provided vastly different understandings of real-world situations. These can be seen in the recent global spread of the fall armyworm (FAW) Spodoptera frugiperda (e.g., Goergen et al. 2016 ; Cock et al. 2017 ; Nagoshi et al. 2018 vs. Tay et al. 2022b ; Rane et al. 2023 ; Schlume et al. 2021), and population expansion of the invasive cotton bollworm Helicoverpa armigera in Brazil (e.g., Mastrangelo et al. 2014 ; Leite et al. 2014 cf . Tay et al. 2013 , Anderson et al. 2016 ). For FAW, initial partial analyses of the mtCOI gene suggested that the spread of this noctuid pest moth was due to a single or limited introductions into western Africa, followed by rapid eastward spread across the African continent, Asia, Oceania, and the Pacific (e.g., Goergen et al. 2016 ; Day et al. 2017 ). However, subsequent whole mitochondrial genome analyses as well as nuclear SNP loci analyses, showed that multiple introductions underpinned the rapid and widespread detections of this exotic invasive species (Kennis et al. 2022; Tay et al. 2022, Tay et al. 2023; Rane et al. 2023 ). For the cotton bollworm, the assessment of multiple loci (e.g., mt DNA partial genes, EPIC-PCR nuclear markers; genome-wide SNP loci), as well as combining simulation analyses with the partial mtCOI gene data demonstrated that multiple introduction pathways, especially from the Old World into the southern and north-eastern regions of Brazil, were responsible for its rapid spread in the Americas (Tay et al, 2013 ; Anderson et al. 2016 ; Arnemann et al. 2018 ), contrary to the proposed local population expansion scenario from a single location, based on the partial mtCOI gene alone (Leite et al. 2014 ; Mastrangelo et al. 2014 ). The coconut rhinoceros beetle (CRB), Oryctes rhinoceros L. (Scarabaeidae, Dynastinae), is an invasive pest that has become of significant concern due to its destructive impact on coconut palm ( Cocos nucifera ) across the Pacific and Indian Ocean (Lever 1969 ; Bedford 1980 ; Mansfield et al. 2024 ). O. rhinoceros is also an important pest on other economically and ecologically important palm species (Bedford 1980 ; Paudel et al. 2021 ; Che Hussian et al. 2025 ; OISC 2025), and is also known to attack agricultural crops including bananas, sugarcane (Gressitt 1953 ), maize (Manikandan and Rengalakshmi 2024 ), and pineapple (Nasution et al. 2024 ; Paudel et al. 2022 ). This coleopteran pest is believed to be native to South/Southeast Asia (SEA), extending from India, Sri Lanka, across to Vietnam, Thailand, Malaysia, Singapore, Indonesia, the Philippines, and also southern China (Lever 1969 ). Since the start of 1900’s, the CRB has dispersed to many locations outside of its native range, causing significant damage, especially within the Pacific (Lever 1969 ; Bedford 1980 ; Paudel et al. 2021 ). The species continues to be reported from new locations, with recent confirmation including Vanuatu in 2019 (Butler 2019 ; see also Paudel 2023), multiple Hawaiian islands (HDOA 2024), the Marshall Islands (The Marshall Islands Journal 2023 ) and Mexico (Jackson et al. 2022 ). Numerous and continuous pre-border interceptions of CRB in various countries (Hoffmann et al. 2024 ) indicate frequent movement of CRB in global trade. Adding to concerns associated with the renewed spread of CRB in the Pacific is also the reported resistance to an important biological control agent, the double stranded DNA Oryctes rhinoceros Nudivirus (OrNV) (Huger 1966 ) in some native (Zalesny et al. 1970) and introduced (Moore 2008; Marshall et al. 2017 ; see also review by Paudel et al. 2022 ) populations. OrNV has been used as a biological control agent for over 50 years to manage CRB (Bedford 1980 , 1986 , 2013 ; Gopal et al. 2001 ; Paudel et al. 2021 ). It was first isolated from CRB in Malaysia (Huger 1966 ; Huger 2005 ), and first introduced as a biological control agent in Samoa (Zelazny 1977 , 1979 ; Bradford 1980; Huger 2005 ), achieving great success at suppressing the nation’s CRB populations. It was subsequently introduced to various Pacific Island nations (Gorick 1980 ; Bedford 1986 ; see also review by Paudel et al. 2021 ) and on the Maldives in the Indian Ocean. It was also used to target the related O. monoceros species (Zelazny et al. 1992 ; Lomer 1986 ), but with lower efficacy. However, in recent years reduced OrNV control efficacies of CRB were reported in the Pacific, combined with failed attempts to establish infection in CRB from Guam (Moore 2008, 2017; Marshall et al. 2017 ; Paudel et al. 2021 ). Analysis of partial mtCOI sequences found the CRB that had invaded Guam to be genetically distinct from previous historical invasions into the Pacific (e.g., Polynesia), with this mtCOI signature identified initially in Guam specimens and subsequently detected in CRB from elsewhere in the Pacific, including in Palau, Hawaii, Solomon Islands, Papua New Guinea, New Caledonia, Vanuatu (Paudel et al. 2023 ; Marshall et al. 2017 , 2023 ; Reil et al. 2018 ; Etebari et al. 2021 ; Tanaka et al. 2021 ), and in its native range such as Indonesia, Malaysia, and Philippines (see Marshall et al. 2017 ; Reil et al. 2018 ; Etebari 2021; Anggrainni et al. 2023). Laboratory trials on CRB from Guam (Marshall et al. 2017 ; Moore 2018 ) failed to establish infection with the OrNV isolates tested. This, together with observations from other new CRB outbreak locations (Marshall, pers comm) and the unique partial mtCOI DNA marker signature, led to the suggestion that members of the CRB-G haplotype grouping ( sensu Marshall et al. 2017 ) possessed a level of resistance to at least some of the commonly used OrNV biocontrol isolates previously released in the Pacific (Marshall et al. 2017 ). Extensive genomic research has since been undertaken by numerous research teams on OrNV isolates and CRB attempting to identify genomic regions in either OrNV or CRB affecting OrNV susceptibility. These efforts included genome sequencing of the OrNV (Wang et al. 2011; Etebari et al. 2020 ; Kurnia et al. 2021 ; Tanaka et al. 2021 , Weston et al. 2023 ) and genome sequencing of CRB as well as transcriptomic analysis (Etebari et al. 2020 , 2021 ; Reil et al. 2018 ; Filipovic et al. 2021). Research to-date has not found any reason for the apparent resistance to some OrNV isolates observed in various CRB populations. The detection of OrNV in Solomon Islands CRB-G variants (as defined by the partial mtCOI gene marker), and other locations with mixtures of CRB variants (Tanaka et al. 2021 ; Etebari et al. 2021 ; Anggriani et al. 2023) further confounded understanding of these newly reported CRB invasions. Initial multi-marker analysis using whole mitochondrial genome sequence data on a limited number of CRB individuals identified additional mitochondrial genes with genetic differences within the CRB-G grouping ( sensu Marshall et al. 2017 ). The additional markers identified for Guam specimens were absent from CRB in Palau and the Solomon Islands, suggesting that the introduction of CRB to these two Pacific Island nations was from a different source population to that from which the Guam introduction was derived (Tay et al. 2024b ). Linking historical samples with genomic studies of contemporary samples is crucial to our understanding and our ability to provide robust interpretations of invasion biology (e.g., Tay et al. 2012 ; 2017 ; Elfekih et al. 2018 ; Kunz et al. 2019 ). In this study, we used full mitochondrial DNA genomes to explore the relationship of CRB throughout the Pacific and its native range, with a particular focus on CRB-G as defined by prior partial mtCOI assessments ( sensu Marshall et al. 2017 ). CRB samples were obtained partly from new collections made specifically for this study, but also from historic collections used in prior publications (Marshall et al. 2017 ; Reil et al. 2018 ) to allow direct comparison with published results. We detail the implications of our findings for the understanding of CRB spread throughout the Pacific, and its management prospects, ultimately improving the understanding of the spread of CRB into the Pacific. Additionally, the genome resources generated can subsequently contribute to research in CRB native range countries (e.g., Philippines, Sri Lanka) especially where coconut represents an important economic source. METHODS Samples We assessed 263 CRB from 19 countries (Table 1 ; Table S1). Historical CRB samples (extracted gut tissue DNA) were obtained from a subset used in Marshall et al. ( 2017 ) and in Reil et al. ( 2018 ), as well as from newly collected CRB (both adults attracted to pheromone lures or light traps and larvae from breeding sites) (Table 1 ; Table S1). Following dissection, gut tissues were placed in 100% ethanol and stored at -20˚C with fresh ethanol replaced every 24 hours for two days. CRB from India, Sri Lanka, Thailand, Malaysia, Singapore, Indonesia, Philippines, China (Hainan), and Taiwan were considered to be from the native range, whereas those from Papua New Guinea, Solomon Islands, Palau, Fiji, Japan, Guam, Hawaii, Rota, Marshall Islands, and Samoa were from the introduced range. Whole genome sequencing (WGS) Genomic DNA (gDNA) from individual CRB gut tissue was extracted using the Qiagen Blood and Tissue DNA extraction kit (Duesseldorf, Germany) following the manufacturer’s suggested protocol. Extracted gDNA was eluted in 200 µL EB and kept at -18˚C until required for WGS. The quantity of the extracted gDNA was assessed using Qubit 2.0 prior to sending samples to either the Australian Genome Resource Facility (AGRF) in Melbourne, Australia, to AZENTA Life Sciences in China, or to BRF at the Australian National University in Canberra, Australia, for WGS library construction and then WGS. All samples were assumed to have a genome size of approximately 350 Mbp, and the WGS data returned an average of 25x coverage, 150 bp paired-end reads/sample for all samples except for the four Marshall Islands CRB specimens which had an average of 8x coverage. Confirmation, characterisation and analysis of CRB mitogenome haplotypes We assembled individual mitogenomes of all 263 CRB samples to reconstruct CRB female (i.e., maternal) movement history to better understand the phylogenetic relationships of reported CRB-G populations in the native range of Indonesia, Philippines, Malaysia, and Taiwan with those reported from its introduced Pacific Island countries (Marshall et al. 2017 ; 2021; Paudel et al. 2021 ). To do this, we used our assembled draft mitogenome of an original Guam CRB individual (Guam_AgR_04-Or5; see Fig. 1 ) provided by AgResearch New Zealand as a representative reference mitochondrial genome (mitogenome) within the CRB-G (clade I) haplotype grouping. All mitogenomes were assessed against MT457815 (Filipović et al. 2021 ) to infer our assembly quality. We imported the forward raw sequence reads (150 bp) of individual CRB into Geneious Prime (Version 2022.2.2) (Biomatters Ltd., Auckland) for mitogenome assembly using the ‘Map to Reference’ option of the Geneious Mapper program and by selecting the ‘Low Sensitivity/Fastest’ option for the Sensitivity field, and with no fine-tuning. The overall high sequence coverage of each CRB sample (average 70.44 million pair-end reads/CRB sample; range 57.98 million reads – 92.24 million reads) enabled this low sensitive/fastest assembly option to be selected that also allowed for time and CPU optimisation. Assembly of arthropod mitogenome’s A-T rich region is typically challenging, especially based on short-read whole genome sequence data, due to the low complexity nature of this genomic region (e.g., Walsh et al. 2019 ; Behere et al. 2016 ; Behere et al. 2019 ; Tay et al. 2014 ; Tay et al. 2022d ). This issue also applies to CRB (Filipović et al. 2021 ) for which the long-read sequencing approach is better suited. Therefore, we excluded the A-T rich region of the mitogenomes for all subsequent analyses. For annotations, assembled draft mitogenomes were imported to Mitos (Bernt et al. 2013 ) and annotated selecting invertebrate genetic code, and output .bed files were imported back to Geneious Prime for visualisation and fine-tuning (i.e., adjustments to ensure all 13 protein coding genes (PCGs) from each mitogenome had identical lengths across all individuals, and where appropriate all started with a methionine residue and had a stop codon). All our assembled draft mitogenomes are available from CSIRO’s Data Access Repository (Tay et al. 2024a ). Phylogenetic analysis We aligned all assembled CRB mitogenomes using the MAFFT v7.450 program (Katoh et al. 2002 ; Katoh and Standley 2013 ) within Geneious Prime v22.2.2 using default parameters (Algorithm: Auto; Scoring matrix: 200PAM / K = 2; Gap open penalty: 1.53; Offset value: 0.123). Following trimming of non-coding gene regions (i.e., all 22 tRNA genes, both rRNA genes, and the A-T rich region) a 11,113 bp concatenated sequence was left that consisted of the 13 protein coding mitochondrial genes (see Tay et al. 2024a Supplemental Data 1). Inference of phylogenetic relationship was through IQ-tree (Trifinopoulos et al. 2016 ) in the W-IQ-TREE Web Service. Branch node support was inferred from 1,000 replications using UFBoot (Minh et al. 2013 ), with the 13 protein coding genes partitioned (see Tay et al. 2024 Supplemental Data 2) to enable optimisation of individual base substitution models for each gene. Visualisation and manipulation of the IQ-tree inferred tree topologies were done using Dendroscope 3 (Hudson et al. 2007 ). Nucleotide diversity estimates, population differentiation, and mitogenome haplotype network Mitogenome haplotypes from concatenation of the 13 Protein Coding Genes (PCGs; 11,133bp) from individual CRB mitogenomes were processed using FaBOX 1.61 (Villesen 2007 ) to identify unique mitogenome haplotypes for pairwise nucleotide distance estimates ( p -dist) performed in Geneious Prime, before imported into DnaSP 6.12.03 (Rozas et al. 2017 ) to estimate the degree of nucleotide polymorphism (i.e., nucleotide diversity; π) within the CRB populations. Tajima’s D (Tajima 1989 ) and Li and Fu’s test statistics (Fu and Li 1993 , 1997) were performed to identify signatures of either population expansion/purifying selection or decrease in population size/balancing selection, separately for the native range and introduced range populations. To estimate population differentiation incorporating mutations between mitogenome haplotypes, Analysis of Molecular Variance (AMOVA) was also performed within PopART (Leight and Bryant 2015) by grouping CRB from the native range versus those from the introduced range. To estimate the evolutionary distance (i.e., genetic differentiation) between all pairs of mitogenome haplotypes and to ascertain if populations were significantly differentiated according to their assumed origins, we calculated Φ ST by grouping native range populations, as well as by grouping populations based on their assumed shared introduction origins. Genetic differentiation enabled native range populations to be grouped as: (i) South Asia (India + Sri Lanka); (ii) Indonesia; (iii) Philippines; and (iv) Southeast Asia (SEA) that included Singapore, Malaysia, Thailand, and Hainan China (i.e., due to the south China CRB native range being in proximity to, e.g., CRB from Thailand). Populations with putatively shared introduced origins were grouped as follows: Introduced ‘Sri Lanka’ (i.e., Route 1: Fiji + Samoa), Introduced ‘Philippines/Taiwan’ (i.e., Route 2: Japan + Palau + Guam + Rota + Hawaii), and introduced ‘Malaysia’ (i.e., Route 3: Papua New Guinea + Solomon Islands + Marshall Islands). A haplotype network on all mitogenome haplotypes was constructed using the TCS statistical parsimony method (Templeton et al. 1992 ) within PopART (Leight and Bryant 2015) to visualise relationships between individual at the population level. The haplotype network was processed using Microsoft PowerPoint for Mac Version 16.79.2. We employed Genepop version 4.8.3 (Raymond and Rousset 1995 ; Rousset 2008 ) sub-options 3 and 4 for genotypic differentiation to assess population genetic structure, with the null hypothesis being that haplotypes were drawn from the same distribution in all populations. Pairwise F ST values were estimated using a “weighted” analysis of variance, as described by Cockerham ( 1973 ) and Weir and Cockerham ( 1984 ). Statistical significance of all paired F ST estimates involved an unbiased estimate of the P -value using a log-likelihood ratio (G) based exact test, with the rejection zone defined by the sum of probabilities of having a G value equal to or higher than the observed value. Principal Component Analysis To investigate genetic variation and population structure, we performed Principal Component Analysis (PCA) on mitogenome single nucleotide polymorphisms (SNPs) data from the 13 PCGs using the “adegenet” package in R (Jombart and Ahmed 2011 ), incorporating the sampling site metadata. PCA on genetic structure was illustrated through interactive scatter plots in two and three dimensions, utilizing “ggplot2” (Wickham 2016 ) and “plotly” for visualization. This methodology provided an insightful view of the genetic variation patterns within and across populations. RESULTS Draft CRB mitogenomes The annotated assembled mitogenomes of the 263 CRB individuals analysed all possessed the same number of coding sequences (CDS) including 13 PCGs, 22 tRNA genes, and 2 rRNA genes, with no gene re-arrangements detected when compared to the previously published CRB full mitochondrial genome assembled via the PacBio long-read sequencing platform (GenBank Accessions: MT457815; Filipović et al. 2021). The PCG sequences were concatenated and aligned, resulting in identification of 72 mitogenome haplotypes among these CRB samples (Tay et al. 2024a; Table S1). Small pairwise nucleotide distance ( p -dist) estimates between these 72 mitogenome haplotypes across the 13 PCG concatenated sequence length provided support that these were all from the same species ( p -dist.: 0–1%, data not shown). With the exception of four contemporary Guam CRB samples (i.e., GuamDoA-03, 04, 05, 18; red boxed individuals in Fig. 1), all historical Guam CRB mitogenomes (i.e., samples reported in Marshall et al. (2017), Riel et al. (2018)) and the remainder of the contemporary Guam samples (‘GuamDoA’ sample code; Fig. 1; Table S1; Tay et al. 2024a) were 100% identical across the CDS (A-T rich region excluded), but were different (99.5% pairwise sequence identity) from the Solomon Islands mitogenome (GenBank Accession: MT457815; Filipović et al. 2021); thereby clearly differentiating further mitogenome haplotype divisions that all share the partial mtCOI marker for the CRB-G (Clade I) grouping. Phylogenetic analysis The phylogeny from the 13 concatenated PCGs (Fig. 1; Tay et al. 2024a) provided strong evidence to support that further diversity existed within the CRB populations across the introduced ranges. Unexpectedly, CRB from Guam formed two clades: one that comprised almost all individuals, including all historical individuals from Marshall et al. (2017) (i.e., CRB-G; Fig. 1, Table 1, Table S1), and a second clade that comprised of only four individuals recently (September 2022) collected near Guam Ports of Entry (see Fig. 1, individuals in red dotted line box), suggesting that these individuals originated from a separate introduction. Palau individuals were predominantly associated with specimens from eastern Indonesia, Philippines, and Taiwan. Japan individuals also clustered with Philippines and Taiwan individuals. The clade that contained Hawaii CRB individuals also included individuals from Japan, Rota, Philippines, and Taiwan. The main Solomon Islands cluster included a Papua New Guinea (PNG) individual and all four Marshall Islands CRB, whereas four Solomon Islands individuals clustered together with three Malaysian individuals in the branch that also had CRB specimens from Sri Lanka. This Sri Lanka cluster also included individual CRB specimens from India and China. Finally, five individuals from Malaysia and the two Singapore individuals formed a cluster of their own with significant (87%-100%; Fig. 1) branch node that included Thailand and southern China individuals, reflecting their close geographic proximity. Nucleotide diversity estimates AMOVA results (Table 2) showed that when populations (based on country of collection) were grouped by their native vs. introduced range assignments, the within-population genetic variation was not statistically significant (43.3%, Φ CT : 0.03139, P = 0.247). Between-population variation accounted for most genetic variation (53.6%, Φ SC : 0.55316, P < 0.01), including a small but significant difference between native vs. introduced range groups (3.1%, Φ ST : 0.56719, P < 0.01). Further grouping of native range populations by putative population boundaries, and introduced range populations by their putative shared origins, showed that highest variation existed at the between-groups level (51.3%, Φ ST : 0.58419, P < 0.01), among populations had the least (i.e., most similar level) genetic variation, and supported the grouped introduced populations have similar genetic variation by their inferred shared origins (7.2%, Φ SC : 0.14847, P = 0.149). Genetic variation was also high at the within populations level, suggesting that individuals within grouped populations are significant differentiated (41.2%, Φ CT : 0.51253, P < 0.01) (Table 2). Estimated average nucleotide diversity (π ± variance; Table 3) of the introduced and native range populations was overall low at 0.00235 ± 0.0000001 and 0.00216 ± 0.00024, respectively. Tajima’s D estimates indicated an overall weak, but statistically non-significant, excess of rare alleles across the introduced populations, with the exception of the Hawaii population that exhibited the signature of population growth or recent population expansion. However, purifying selection (i.e., background selection to reduce genetic diversity) at the target locus could also result in the significant negative Tajima’s D value. The Fu and Li’s test statistics, which is more sensitive at detecting population demographic changes over shorter times (Ramírez-Soriano et al. 2008), similarly detected signatures of population expansion in the Hawaii population, but also in the Solomon Islands CRB population. Small sample sizes for PNG and Rota, as well as the lack of haplotype diversity in the Marshall Islands prevented detection of signatures of population demographic differences among CRB from those locations. Despite limited spatial sampling within countries such that many CRB samples were collected from the same site, across the native range populations we detected a significantly negative Tajima’s D value suggesting purifying selection and genetic signatures of population growth and/or migration. Specifically, we detected a statistically significant negative Tajima’s D as well as Li and Fu’s D and F values in the Indonesian population, as well as for the Li and Fu’s values for the China population, which suggests strong background selection is shaping the genomic diversity in these populations (Cvijović et al. 2018). Conversely, various introduced range populations (e.g., Palau, Solomon Islands, and Samoa) and some native range populations (i.e., Malaysia and Singapore) had positive but statistically non-significant Tajima’s D values as well as Li and Fu’s test statistic values, suggesting these populations experienced weak balancing selection (i.e., multiple alleles being actively maintained in the population) that reflected either a recent bottle neck or contraction. However, population substructure, such as likely present in Malaysia CRB, could also result in the positive values detected. The exception was the significant Li and Fu’s test statistic values for the Solomon Islands CRB samples, which likely consisted of individuals founded from different parts of the native range (i.e., from Malaysia and Philippines, see PCA results section), and potentially reflected maintenance of genetic variation over the short period. Mitogenome haplotype network The mitogenome haplotype network (Fig. 2) showed that > 10 mutations typically separated various native range populations, such as for Indonesia, Malaysia/Singapore/Thailand/China, Philippines/Taiwan, and Sri Lanka (including India). Notably, Malaysia had a population distinct (i.e., Malaysia/PNG/Solomon Islands cluster) to the Malaysia/Singapore/Thailand/China cluster. Taken as a whole, native range populations of CRB appeared to exhibit mitogenome sub-structures. The network analysis results also support a scenario that introduced populations throughout the Pacific had multiple introduction origins. For example, CRB from Palau appeared to have originated from both Indonesia and Philippines due to similarities with these two native range populations. Many of the recently reported introduced range outbreak populations appeared to share closer evolutionary relationships with specimens collected from Philippines and Taiwan, forming a central cluster with low mutation steps (i.e., 1–3 steps) between network branches. Fiji and Samoa clustered with Sri Lanka (i.e., South Asia group), away from the Southeast Asia native range group, whereas a subset of Papua New Guinea and Solomon Islands CRB clustered with a population from Malaysia. F st estimates Non-significant population differentiation between Malaysia/Singapore, China/Malaysia/Thailand suggested gene flow (i.e., exchange of individuals) across this region (Table 4), bearing in mind the small sample size from, e.g., Singapore (n = 2), and its low but significant F st estimates with China (n = 5) and Thailand. Non-significant F st estimates between the introduced Hawaii CRB population and the Philippines and Taiwan native range populations, but also with introduced range populations from Japan, Marshall Islands, and Rota suggested these populations shared some gene flow but likely also their shared closer evolutionary relationships with native range Philippines and Taiwan populations. Significant F st estimates were found for the Guam population against all other populations except for Rota (n = 2) and Japan (n = 4), suggesting that the Guam population had limited exchange of individuals with our introduced range locations. The detection of an additional Guam clade (i.e., Fig. 1, GuamDoA-03, 04, 05, 18) could potentially contribute to the two non-significant F st estimates with Japan and Rota. Despite analyses showing the close evolutionary relationships between CRB from Fiji, Samoa, and Sri Lanka, significant F st were detected between these three populations, suggesting potentially limited exchange of individuals among introduced range locations after the original introduction events. CRB mitogenome PCA Principal Component Analysis (PCA) of mitogenome SNPs (from the 13 PCGs) identified distinct sub-cluster diversity within the high-level native range grouping for both South Asia (i.e., Sri Lanka, Sri Lanka + India) and Southeast Asia (Philippines/Taiwan, Malaysia/Singapore/Thailand/China, Malaysia, and Indonesia) (Fig. 3). The Palau specimens clustered with both native Indonesia and Philippines/Taiwan sub-clusters. A subset of specimens from both PNG and Solomon Islands clustered with a Malaysia native range group that was distinct from the South Asia and southeast Asia native range groups that also included Malaysian CRB specimens. Several CRB from invaded Pacific Island countries (Guam, Hawaii, Japan, Marshall Islands, Palau, PNG, Rota, Solomon Islands) formed a cluster with the native range Philippines/Taiwan sub-cluster. CRB from invaded Samoa and Fiji, but also from native ranges of Malaysia and China, were associated with three separate sub-clusters of Sri Lanka/India native CRB populations. DISCUSSION This study, based on a whole genome sequencing (WGS) approach of the mitochondria genome, represents the most comprehensive survey of both native and introduced CRB populations undertaken to date, and provides deeper insights to genetic diversity and differentiation of this pest from the maternal (i.e., mitochondrial) lineage perspectives. Based on the 13 PCGs concatenated nucleotide sequence and linking recently collected samples with the historical CRB samples of Marshall et al. ( 2017 ) and Reil et al. ( 2018 ), these results demonstrate a much richer diversity of CRB than has been shown to date, especially in native populations, and highlight the limitations of defining CRB using only a single partial mtCOI molecular marker (Tay et al. 2024b ). From the mitogenome (i.e., maternal lineage) perspective, and based on surveys of the 10 introduced populations, there is no evidence for: (i) Guam as a key CRB dispersal point (i.e., as a ‘bridge head’ location; Lombaert et al. 2010 ) from which CRB spread into other Pacific Islands including Hawaii, Papua New Guinea, Solomon Islands, Palau and Yap (e.g., Tsatsia et al. 2018 ; Datt et al. 2020 ; Valaqo et al. 2017); (ii) nor evidence of a common maternal lineage of a native founder population that subsequently dispersed to Guam and other Pacific locations with the CRB-G haplotype grouping ( sensu Marshall et al. 2017 ) populations (e.g., Reil et al. 2018 ; Etebari et al. 2021 ; Tanaka et al. 2022); (iii) and no evidence of multiple native range populations being directly related with the unique Guam maternal lineage (e.g., Etebari et al. 2021 ; Anggraini et al. 2023 ) and most other exotic range populations. This CRB mitogenome analysis also identified a second mitogenome haplotype representing a separate introduction event of CRB into Guam. There is a low likelihood that some of the CRB individuals analysed by Marshall et al. ( 2017 ) and Reil et al. ( 2018 ) included individuals that belonged to this separate introduction event, but this was not detected through analyses of the partial mtCOI gene region. However, because some of our individuals with a different origin were recently collected at a Guam Port (Table S1), they were likely to represent a new introduction event associated with the pest’s propensity to be accidentally transported (Hoffmann et al. 2024 ). This work has further highlighted the value of whole genome sequencing approach, while also reiterating the importance of using multiple genetic markers (e.g., Tay et al. 2024b ) together with the inclusion of both introduced and native range sourced specimens to understand invasion pathway histories. Increasingly, mitogenome haplotypes including the use of concatenated PCGs from highly invasive arthropod species, have provided evidence to show genetic and demographic differentiation among the native and introduced populations (e.g., the fall armyworm Spodoptera frugiperda , Tay et al. 2022; the cotton bollworm Helicoverpa armigera , Anderson et al. 2016 ; Phthorimaea ( Tuta ) absoluta , Li et al. 2022 ; Magalhaes et al. 2025 ). As reported in Tay et al. ( 2024b ), which utilised limited samples, this study further demonstrated that by including specimens from the native range, mitogenome haplotypes for the CRB (i) improved demographic signatures (ii) explained the mtCOI versus nuclear DNA SNP loci discrepancy for the presence or absence of population movements from Guam to other Pacific islands; (iii) better linked introduced populations with their putative native ranges (Figs. 2 , 3 ); and (iv) provided evidence of genetic differentiation (Tables 2 , 3 ). For example, historically, the origin of Samoan CRB was reported to be from Sri Lanka simply due to horticultural trade movements of rubber seedlings containing CRB larvae (Doane 1913 ; Catley 1969; Lever 1969 ; Bedford 1980 ). This Sri Lankan population origin report is now explicitly supported, by our genomic evidence that showed close maternal lineage relationships between Sri Lankan and Samoan CRB. To further improve understanding of CRB invasion origins into the Pacific will require more comprehensive sampling of CRB from both the native range and other Pacific Island nations including e.g., Vanuatu, Saipan, American Samoa, New Caledonia, Tonga, as well as increasing sample sizes especially in countries such as PNG. Combining our mitogenome haplotype results with previous population genomic findings (Reil et al. 2018 ; Etebari et al. 2021 ) enables strong assessment of our understanding of CRB Pacific Island dispersals (Fig. 4 ). Our work has clearly found separate maternal origins of the Guam and Hawaii populations (Fig. 1 ), but with both being closely related to the Philippines/Taiwan native population cluster (Figs. 2 and 3 ). That Guam and Hawaii CRB do not appear to share a direct invasion history is consistent with inference of separate lineages based on nuclear genome analysis (Reil et al. 2018 ). The Palau CRB population exhibited distinct Indonesia and Philippines CRB mitogenome signatures (Figs. 1 – 3 ), and is in agreement with nuclear SNP loci analyses of Reil et al. ( 2018 ) that also identified Philippines and Indonesia as likely origins of CRB into Palau. Although low CRB sample sizes from Marshall Islands, PNG, and Rota were analysed, CRB individuals between PNG and its neighbouring Solomon Islands likely had genetic exchange based on both nuclear (Etebari et al. 2021 ), and our mitochondrial genome analyses, with both having an original linkage back to Malaysia (Fig. 3 ). Similarly, Samoa CRB shared demographic history with Fiji which was supported by nuclear loci analysis (Etebari et al. 2021 ). Nuclear loci (Reil et al. 2018 ) and our mitogenomes support shared demographic signatures between Hainan (China) and Thailand CRB populations, and our mitogenome analysis further grouped some of the Malaysian and Singapore CRB individuals with both Hainan and Thailand populations (Fig. 3 ). We also recognise some limitations of our study. Our mitochondrial genome results will require further support from nuclear gene analysis because our CRB samples included introduced range populations previously not analysed by Reil et al. ( 2018 ) and Etebari et al. ( 2021 ), and from other locations that have not been included in studies using either mitochondrial or nuclear genome analyses. Importantly, the spread of CRB could potentially involve males which would not be detected via the mitochondrial genome analysis. This is an important consideration that requires urgent follow-up, especially if the reported resistance to OrNV biocontrol isolates within (at least some) members of the CRB-G haplotype grouping ( sensu Marshall et al. 2017 ) involved interactions between the nuclear as well as the viral genome. Effective management of invasive insect pests benefits from an identification nomenclature based on whole genomic analyses and with adequate sampling of populations from native and introduced ranges. Such a naming system, which is increasingly enabled by next and third-generation sequencing technologies, enables analysis of underlying genetic diversity, with implications for understanding of invasive spread, adaptation, and resistance to control agents. In this study, analyses based on multiple genes from draft whole mitogenomes has especially shown the native CRB populations analysed to strongly correlate to geographic origins such as those as from Indonesia, Philippines/Taiwan, Malaysia/Singapore, and Sri Lanka, which lends further support to previous work that surmised on origins (e.g., Doane 1913 ; Catley 1969; Marshall et al. 2017 ; Reil et al. 2018 ). This has also facilitated identification and tracking of invasive populations, extending what was possible before. Indeed, the mitochondrial genome resources reported in this study could potentially serve as the starting point of a more robust and phylogeographically informative CRB-naming system (e.g., introduced clade 1, introduced clade 2, native clade 1, native clade 2, etc.). However, we were unable to define such a naming scheme at present, in parts, due to our incomplete sampling of both native and introduced populations, and further because the invasion process of the CRB is on-going (Hoffmann et al. 2024 ). Beyond these issues, a definitive system will also need to incorporate data from whole genome resequencing analyses that will further provide finer grain insights into the genetic makeups of introduced populations underpinned by idiosyncratic population establishment processes. Acknowledgements and Funding Information Indonesian CRB samples were provided with Republic of Indonesia Ministry of Agriculture, Agricultural Quarantine Agency Permit numbers: 2021.1.2005.0.K13.E.00003 No. 4299301 and 2022.1.2005.0.K12.E.00002 No. 5896762). The Philippines CRB samples were gathered under the Gratuitous Permit DENR8-GP No. 2022-02 (10 January 2022) provided by the Department of Environment and Natural Resources 8 of the Republic of the Philippines and conducted under the VSU-IP 2021-10 (BIO-CAMP) and VSU-IP 2022-2 (CRB) projects. Singapore CRB samples were generously provided by Izaan Muhammad Izzan Bin Istijab (Plant Science & Health, Horticulture & Community Division, National Parks Board Singapore). This project was funded by the DFAT Administered (aid) Simple Grant Agreement 77092. We thank Tristan Armstrong (DFAT), Geoff Bedford (Macquarie University), Mr Gibson Susumu (SPC, Fiji), Tanya Robinson (New Zealand Ministry of Foreign Affairs & Trade), Silva DPM (Crop Protection Division, Coconut Research Institute, Bandirippuwa, Lunuwila,61150, Sri Lanka), Sivapragasam Annamalai (CABI Associate), and Alison Watson (Head of the Secretariate of ASEAN FAW Action Plan) for helpful discussions during the course of this project. Declarations CONFLICT OF INTEREST The authors declared no conflict of interest Author Contribution Manuscript preparation and writing of the main text: Wee Tek Tay, Angel David Popa-Baez, Rahul Rane, Andy Bachler, Glenn Dulla, Alex Gofton, Justine Millado, Michael Melzer, Jelfina Alouw, Sean Marshall, Harshani Dilrukshika, Karl Gordon, Ben Hoffmann.Sample collection and logistics: Juniaty Sambiran, Jelfina Alouw, Justine Millado, Ben Hoffmann, Francis Tastsia, Jacob Yombai, Chris Dahl, Tanu Toomata, Pueata Tanielu, Harshani Dilrukshika, Muhammad Faheem, Leon Court, Michael Melzer, Andrea Blas.Laboratory work: Juniaty Sambiran, Meldy Hosang, Jacob Yombai, Justine Millado, Michael Melzer, Timothy Hogarty, Demi Yi-Chun Cho, Leon Court, Muhammad Faheem, Andrea Blas, Wee Tek Tay.Data Analysis: Rahul Rane, Wee Tek Tay, Angel David Popa-Baez, Andy Bachler, Alex Gofton, Meldy Hosang, Muhammad Faheem, Andrea Blas, Karl Gordon.All authors contributed to the review of various manuscript drafts. Acknowledgement Indonesian CRB samples were provided with Republic of Indonesia Ministry of Agriculture, Agricultural Quarantine Agency Permit numbers: 2021.1.2005.0.K13.E.00003 No. 4299301 and 2022.1.2005.0.K12.E.00002 No. 5896762). The Philippines CRB samples were gathered under the Gratuitous Permit DENR8-GP No. 2022-02 (10 January 2022) provided by the Department of Environment and Natural Resources 8 of the Republic of the Philippines and conducted under the VSU-IP 2021-10 (BIO-CAMP) and VSU-IP 2022-2 (CRB) projects. Singapore CRB samples were generously provided by Izaan Muhammad Izzan Bin Istijab (Plant Science & Health, Horticulture & Community Division, National Parks Board Singapore). This project was funded by the DFAT Administered (aid) Simple Grant Agreement 77092. We thank Tristan Armstrong (DFAT), Geoff Bedford (Macquarie University), Mr Gibson Susumu (SPC, Fiji), Tanya Robinson (New Zealand Ministry of Foreign Affairs & Trade), Silva DPM (Crop Protection Division, Coconut Research Institute, Bandirippuwa, Lunuwila,61150, Sri Lanka), Sivapragasam Annamalai (CABI Associate), and Alison Watson (Head of the Secretariate of ASEAN FAW Action Plan) for helpful discussions during the course of this project. Data Availability Assembled draft mitochondrial DNA genome sequence data can be accessed from the CSIRO Data Access Portal (CSIRO DAP) [https://data.csiro.au/collection/csiro:62248](https:/data.csiro.au/collection/csiro:62248) . References Anderson, C. J., Tay, W. T., McGaughran, A., Gordon, K. & Walsh, T. K. Population structure and gene flow in the global pest, Helicoverpa armigera . Mol. Ecol. 25 (21), 5296–5311 (2016). Anderson, C. J. et al. Hybridization and gene flow in the mega-pest lineage of moth, Helicoverpa . 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Possibility of resistance to a baculovirus in populations of the coconut rhinoceros beetle ( Oryctes rhinoceros ). Plant. Prot. Bull. FA0 (2), 77–82 (1989). Zelazny, B., Lolong, A. & Pattang, B. Oryctes rhinoceros (Coleoptera: Scarabaeidae) populations suppressed by a Baculovirus. J. Invertebr. Pathol. 59 , 61–68 (1992). Tables Tables are available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files floatimage1.png Table 1:263 CRB samples from native and introduced ranges used in whole genome sequencing for mitochondrial DNA genome and metagenomic assessments. Historical samples included samples previous reported in publications by both Marshall et al. (2017; ‘AgR’ code) and Reil et al. (2018; ‘MM’ code). Where available, details of regional location information and GPS coordinates are provided in Table S1. floatimage3.png Table 2: Analysis of Molecular Variance (AMOVA) of CRB populations (based on country of collection) from the introduced and native range based on 13 mitochondrial protein coding regions. floatimage4.png Table 3: Haplotype diversity ( h ) and nucleotide diversity (π) and their respective variance estimates for CRB from introduced and native ranges. See Table 1 for sample sizes and Table S1 for other collection data. Note the low sample sizes for Rota, PNG, and Singapore (n = 2 from each country). India and Sri Lanka samples were combined due to there being only a single sample from India. Values in parentheses for Malaysia indicate when Singapore (n = 2) and Malaysia samples were combined for the estimate. floatimage6.png Table 4: F st estimates of coconut rhinoceros beetle (CRB) populations from the introduced and native ranges based on 11,133 bp of 13 concatenated mitochondrial PCGs. Codes for populations are: China (CHN), Fiji (FJI), Guam (GUM), Hawaii (HNL), Indonesia (IDN), Japan (JPN), Malaysia (MYS), Marshall Islands (MHL), Palau (PLW), Papua New Guinea (PNG), Philippines (PHL), Rota (ROP), Samoa (WSM), Singapore (SGP), Solomon Islands (SLB), Sri Lanka (LKA), Taiwan (TWN), and Thailand (THA)., Sample sizes are indicated in parentheses. Significant F st values at P<0.05 are indicated by ‘*’; non-significant pairwise F st estimates are highlighted in green. Note that the Sri Lanka population included the one CRB individual from India. Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 23 Jan, 2026 Reviews received at journal 22 Jan, 2026 Reviews received at journal 17 Jan, 2026 Reviewers agreed at journal 02 Jan, 2026 Reviewers agreed at journal 02 Dec, 2025 Reviewers invited by journal 27 Nov, 2025 Editor invited by journal 18 Nov, 2025 Editor assigned by journal 10 Oct, 2025 Submission checks completed at journal 10 Oct, 2025 First submitted to journal 07 Oct, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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16:43:30","extension":"xml","order_by":19,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":201218,"visible":true,"origin":"","legend":"","description":"","filename":"90ee576eb0094a66b80d679c69bef7051structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7796543/v1/dc1bfa0c7b5c13dd7a141963.xml"},{"id":98427009,"identity":"e8d8c911-0f8a-44f7-8a0d-c0893aba3ebe","added_by":"auto","created_at":"2025-12-17 16:39:15","extension":"html","order_by":20,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":223510,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7796543/v1/ab02bd7431722611469ff8c8.html"},{"id":98072154,"identity":"1d50fc2d-8e48-4bac-bc6a-c87618411bf2","added_by":"auto","created_at":"2025-12-12 13:09:44","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1485557,"visible":true,"origin":"","legend":"\u003cp\u003ePhylogeny of 263 CRB individuals based on a 11,113 bp concatenated 13 mitochondrial protein coding gene sequence. CRB samples from the native range are from China, India, Indonesia, Malaysia, Philippines, Sri Lanka, Taiwan and Thailand. CRB samples from the introduced range are from Fiji, Guam, Hawaii, Japan, Marshall Islands Palau, Rota, Solomon Islands. Branch node support estimates are indicated for 74-86% (grey dots) and for 87-100% (red dots). Country origins of CRB individuals are colour coded.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7796543/v1/1bdad9a0cfb13028a4bccddf.jpeg"},{"id":98429710,"identity":"41c369ba-1ba5-460d-a96e-96e33301abf4","added_by":"auto","created_at":"2025-12-17 16:44:02","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":456356,"visible":true,"origin":"","legend":"\u003cp\u003eMitogenome haplotype network of the coconut rhinoceros beetle (CRB) samples showing number of base substitutions along network branches. Refer to Table S1 for CRB haplotype numbers and sample sizes. The countries that clusters of haplotypes belonged to are indicated.\u003c/p\u003e","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7796543/v1/fa6fe4e7bb163b4015aef340.jpeg"},{"id":98429670,"identity":"cb49112e-1321-44f8-80ae-ceefd1311e87","added_by":"auto","created_at":"2025-12-17 16:43:59","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":264236,"visible":true,"origin":"","legend":"\u003cp\u003ePrincipal Component Analysis (PCA) of mitogenome SNPs involving native and introduced range CRB populations. Country origins of populations are colour coded. Ellipses in dotted lines indicate putative population clusters.\u003c/p\u003e","description":"","filename":"floatimage7.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7796543/v1/9451839cf2b7da4383d5b153.jpeg"},{"id":98428665,"identity":"b83ff5fc-679f-49f4-b455-5d9017a68bf8","added_by":"auto","created_at":"2025-12-17 16:42:14","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":18517,"visible":true,"origin":"","legend":"\u003cp\u003eCRB populations from the native range (green markers) and the introduced range (red markers) analysed through whole mitogenome sequencing in this study with inferred directionality of movements between populations shown by orange dotted lines with arrows. Purple coloured ellipses indicate native populations that were clustered with strong bootstraps support estimates in the phylogeny (Fig. 1) and in the Principal Component Analysis (Fig. 3).\u003c/p\u003e","description":"","filename":"Onlinefloatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-7796543/v1/1e39f93bb8800f6dafee0327.png"},{"id":98774625,"identity":"b51bde72-16a9-40e2-9620-ff135e37d01b","added_by":"auto","created_at":"2025-12-22 12:06:02","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3326331,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7796543/v1/0ff1b259-fe4d-4527-b16f-479e0164c46d.pdf"},{"id":98429717,"identity":"053691b2-8a55-4853-bb7b-d0953f47cdca","added_by":"auto","created_at":"2025-12-17 16:44:02","extension":"png","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":143983,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTable 1:\u003c/strong\u003e263 CRB samples from native and introduced ranges used in whole genome sequencing for mitochondrial DNA genome and metagenomic assessments. Historical samples included samples previous reported in publications by both Marshall et al. (2017; ‘AgR’ code) and Reil et al. (2018; ‘MM’ code). Where available, details of regional location information and GPS coordinates are provided in Table S1.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7796543/v1/6317dae158de85114a87a37f.png"},{"id":98072168,"identity":"6d9455a1-a79d-4ba6-9ff5-92194a07fb0f","added_by":"auto","created_at":"2025-12-12 13:09:46","extension":"png","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":309983,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTable 2:\u003c/strong\u003e Analysis of Molecular Variance (AMOVA) of CRB populations (based on country of collection) from the introduced and native range based on 13 mitochondrial protein coding regions.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7796543/v1/9b4ae023f3f906f2316a89d4.png"},{"id":98428591,"identity":"e80ef21a-2db3-4114-ba51-e9ac11738c3e","added_by":"auto","created_at":"2025-12-17 16:42:10","extension":"png","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":108023,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTable 3:\u003c/strong\u003e Haplotype diversity (\u003cem\u003eh\u003c/em\u003e) and nucleotide diversity (π) and their respective variance estimates for CRB from introduced and native ranges. See Table 1 for sample sizes and Table S1 for other collection data. Note the low sample sizes for Rota, PNG, and Singapore (n = 2 from each country). India and Sri Lanka samples were combined due to there being only a single sample from India. Values in parentheses for Malaysia indicate when Singapore (n = 2) and Malaysia samples were combined for the estimate.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7796543/v1/9b47aab3f1f99e6978a84823.png"},{"id":98428559,"identity":"aa716f0e-750d-4503-9df0-dfe34fb30aef","added_by":"auto","created_at":"2025-12-17 16:42:08","extension":"png","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":101952,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTable 4:\u003c/strong\u003e \u003cem\u003eF\u003c/em\u003e\u003csub\u003est\u003c/sub\u003e estimates of coconut rhinoceros beetle (CRB) populations from the introduced and native ranges based on 11,133 bp of 13 concatenated mitochondrial PCGs. Codes for populations are: China (CHN), Fiji (FJI), Guam (GUM), Hawaii (HNL), Indonesia (IDN), Japan (JPN), Malaysia (MYS), Marshall Islands (MHL), Palau (PLW), Papua New Guinea (PNG), Philippines (PHL), Rota (ROP), Samoa (WSM), Singapore (SGP), Solomon Islands (SLB), Sri Lanka (LKA), Taiwan (TWN), and Thailand (THA).,\u0026nbsp; Sample sizes are indicated in parentheses. Significant \u003cem\u003eF\u003c/em\u003e\u003csub\u003est\u003c/sub\u003e values at P\u0026lt;0.05 are indicated by ‘*’; non-significant pairwise \u003cem\u003eF\u003c/em\u003e\u003csub\u003est\u003c/sub\u003e estimates are highlighted in green. Note that the Sri Lanka population included the one CRB individual from India.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7796543/v1/6da4d26233d8f83b407d9da8.png"}],"financialInterests":"No competing interests reported.","formattedTitle":"Coconut Rhinoceros Beetle mitochondrial genomes assessment refines understanding of its Pacific invasions","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eAccurate species identification and knowledge of the genetic diversity of alien invasive species are critical to the understanding of actual and potential introduction pathways. They enable identification of potential biosecurity hotspots (Rane et al. \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Tay et al. 2023) and allow factors underpinning continuous and emerging spread patterns to be identified. Spread through behavioural, environmental, and climatic factors, as well as natural migration abilities, has long underpinned distributions of exotic species (e.g., desert locust \u003cem\u003eSchistocerca gregaria\u003c/em\u003e (Kennedy \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e1951\u003c/span\u003e; Lorenz 2009), blue-tongue virus vector \u003cem\u003eCulicoides\u003c/em\u003e midges species (Murray \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e1987\u003c/span\u003e; Murray and Kirkland \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e1995\u003c/span\u003e;Eagles et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), and various lepidoptera species including the monarch butterfly (Reppert and de Roode \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) and \u003cem\u003eHelicoverpa\u003c/em\u003e species (Fitt \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; Paula-Moraes et al. \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e2024\u003c/span\u003e)). Increasingly, however, global trade, has been shown to be the overarching factor driving the spread of exotic alien species (De Barro et al. 2011; Lopez-da-Silva et al. 2014; Tay et al. \u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Elfekih et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Jones et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Arnemann et al. 2019; Moore et al. \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). In arthropods, various mitochondrial DNA gene regions, especially the partial \u003cem\u003ecytochrome oxidase subunit I\u003c/em\u003e (\u003cem\u003emtCOI\u003c/em\u003e) gene, have long been used as the DNA marker to assist with species identification as well as initial investigative effort of genetic diversity within the species. However, such single markers provide limited insight into the genetic diversity of invasive species, and thus present limitations around the utility of these assessments for the likes of pathway analysis. Advances in whole genome sequencing technology and the associated rapidly decreasing sequencing costs now provide comprehensive data into not only population genetic diversity and structure that can be used to assess introduction histories, but also genes important for adaptation and for resistance to current and potential control agents.\u003c/p\u003e\u003cp\u003eStudies comparing partial \u003cem\u003emtCOI\u003c/em\u003e versus whole genome sequence data have provided vastly different understandings of real-world situations. These can be seen in the recent global spread of the fall armyworm (FAW) \u003cem\u003eSpodoptera frugiperda\u003c/em\u003e (e.g., Goergen et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Cock et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Nagoshi et al. \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2018\u003c/span\u003e vs. Tay et al. \u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e2022b\u003c/span\u003e; Rane et al. \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Schlume et al. 2021), and population expansion of the invasive cotton bollworm \u003cem\u003eHelicoverpa armigera\u003c/em\u003e in Brazil (e.g., Mastrangelo et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Leite et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2014\u003c/span\u003e \u003cem\u003ecf\u003c/em\u003e. Tay et al. \u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e2013\u003c/span\u003e, Anderson et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). For FAW, initial partial analyses of the \u003cem\u003emtCOI\u003c/em\u003e gene suggested that the spread of this noctuid pest moth was due to a single or limited introductions into western Africa, followed by rapid eastward spread across the African continent, Asia, Oceania, and the Pacific (e.g., Goergen et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Day et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). However, subsequent whole mitochondrial genome analyses as well as nuclear SNP loci analyses, showed that multiple introductions underpinned the rapid and widespread detections of this exotic invasive species (Kennis et al. 2022; Tay et al. 2022, Tay et al. 2023; Rane et al. \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). For the cotton bollworm, the assessment of multiple loci (e.g., \u003cem\u003emt\u003c/em\u003eDNA partial genes, EPIC-PCR nuclear markers; genome-wide SNP loci), as well as combining simulation analyses with the partial \u003cem\u003emtCOI\u003c/em\u003e gene data demonstrated that multiple introduction pathways, especially from the Old World into the southern and north-eastern regions of Brazil, were responsible for its rapid spread in the Americas (Tay et al, \u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Anderson et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Arnemann et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), contrary to the proposed local population expansion scenario from a single location, based on the partial \u003cem\u003emtCOI\u003c/em\u003e gene alone (Leite et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Mastrangelo et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe coconut rhinoceros beetle (CRB), \u003cem\u003eOryctes rhinoceros\u003c/em\u003e L. (Scarabaeidae, Dynastinae), is an invasive pest that has become of significant concern due to its destructive impact on coconut palm (\u003cem\u003eCocos nucifera\u003c/em\u003e) across the Pacific and Indian Ocean (Lever \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e1969\u003c/span\u003e; Bedford \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1980\u003c/span\u003e; Mansfield et al. \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). \u003cem\u003eO. rhinoceros\u003c/em\u003e is also an important pest on other economically and ecologically important palm species (Bedford \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1980\u003c/span\u003e; Paudel et al. \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Che Hussian et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; OISC 2025), and is also known to attack agricultural crops including bananas, sugarcane (Gressitt \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e1953\u003c/span\u003e), maize (Manikandan and Rengalakshmi \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), and pineapple (Nasution et al. \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Paudel et al. \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). This coleopteran pest is believed to be native to South/Southeast Asia (SEA), extending from India, Sri Lanka, across to Vietnam, Thailand, Malaysia, Singapore, Indonesia, the Philippines, and also southern China (Lever \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e1969\u003c/span\u003e). Since the start of 1900\u0026rsquo;s, the CRB has dispersed to many locations outside of its native range, causing significant damage, especially within the Pacific (Lever \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e1969\u003c/span\u003e; Bedford \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1980\u003c/span\u003e; Paudel et al. \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The species continues to be reported from new locations, with recent confirmation including Vanuatu in 2019 (Butler \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; see also Paudel 2023), multiple Hawaiian islands (HDOA 2024), the Marshall Islands (The Marshall Islands Journal \u003cspan citationid=\"CR105\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) and Mexico (Jackson et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Numerous and continuous pre-border interceptions of CRB in various countries (Hoffmann et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) indicate frequent movement of CRB in global trade.\u003c/p\u003e\u003cp\u003eAdding to concerns associated with the renewed spread of CRB in the Pacific is also the reported resistance to an important biological control agent, the double stranded DNA \u003cem\u003eOryctes rhinoceros\u003c/em\u003e Nudivirus (OrNV) (Huger \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e1966\u003c/span\u003e) in some native (Zalesny et al. 1970) and introduced (Moore 2008; Marshall et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; see also review by Paudel et al. \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) populations. OrNV has been used as a biological control agent for over 50 years to manage CRB (Bedford \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1980\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1986\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Gopal et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Paudel et al. \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). It was first isolated from CRB in Malaysia (Huger \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e1966\u003c/span\u003e; Huger \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), and first introduced as a biological control agent in Samoa (Zelazny \u003cspan citationid=\"CR118\" class=\"CitationRef\"\u003e1977\u003c/span\u003e, \u003cspan citationid=\"CR119\" class=\"CitationRef\"\u003e1979\u003c/span\u003e; Bradford 1980; Huger \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), achieving great success at suppressing the nation\u0026rsquo;s CRB populations. It was subsequently introduced to various Pacific Island nations (Gorick \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e1980\u003c/span\u003e; Bedford \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1986\u003c/span\u003e; see also review by Paudel et al. \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and on the Maldives in the Indian Ocean. It was also used to target the related \u003cem\u003eO. monoceros\u003c/em\u003e species (Zelazny et al. \u003cspan citationid=\"CR121\" class=\"CitationRef\"\u003e1992\u003c/span\u003e; Lomer \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e1986\u003c/span\u003e), but with lower efficacy. However, in recent years reduced OrNV control efficacies of CRB were reported in the Pacific, combined with failed attempts to establish infection in CRB from Guam (Moore 2008, 2017; Marshall et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Paudel et al. \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAnalysis of partial \u003cem\u003emtCOI\u003c/em\u003e sequences found the CRB that had invaded Guam to be genetically distinct from previous historical invasions into the Pacific (e.g., Polynesia), with this \u003cem\u003emtCOI\u003c/em\u003e signature identified initially in Guam specimens and subsequently detected in CRB from elsewhere in the Pacific, including in Palau, Hawaii, Solomon Islands, Papua New Guinea, New Caledonia, Vanuatu (Paudel et al. \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Marshall et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2017\u003c/span\u003e, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Reil et al. \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Etebari et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Tanaka et al. \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), and in its native range such as Indonesia, Malaysia, and Philippines (see Marshall et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Reil et al. \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Etebari 2021; Anggrainni et al. 2023). Laboratory trials on CRB from Guam (Marshall et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Moore \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) failed to establish infection with the OrNV isolates tested. This, together with observations from other new CRB outbreak locations (Marshall, pers comm) and the unique partial \u003cem\u003emtCOI\u003c/em\u003e DNA marker signature, led to the suggestion that members of the CRB-G haplotype grouping (\u003cem\u003esensu\u003c/em\u003e Marshall et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) possessed a level of resistance to at least some of the commonly used OrNV biocontrol isolates previously released in the Pacific (Marshall et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eExtensive genomic research has since been undertaken by numerous research teams on OrNV isolates and CRB attempting to identify genomic regions in either OrNV or CRB affecting OrNV susceptibility. These efforts included genome sequencing of the OrNV (Wang et al. 2011; Etebari et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Kurnia et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Tanaka et al. \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, Weston et al. \u003cspan citationid=\"CR114\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) and genome sequencing of CRB as well as transcriptomic analysis (Etebari et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Reil et al. \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Filipovic et al. 2021). Research to-date has not found any reason for the apparent resistance to some OrNV isolates observed in various CRB populations. The detection of OrNV in Solomon Islands CRB-G variants (as defined by the partial \u003cem\u003emtCOI\u003c/em\u003e gene marker), and other locations with mixtures of CRB variants (Tanaka et al. \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Etebari et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Anggriani et al. 2023) further confounded understanding of these newly reported CRB invasions. Initial multi-marker analysis using whole mitochondrial genome sequence data on a limited number of CRB individuals identified additional mitochondrial genes with genetic differences within the CRB-G grouping (\u003cem\u003esensu\u003c/em\u003e Marshall et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The additional markers identified for Guam specimens were absent from CRB in Palau and the Solomon Islands, suggesting that the introduction of CRB to these two Pacific Island nations was from a different source population to that from which the Guam introduction was derived (Tay et al. \u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e2024b\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eLinking historical samples with genomic studies of contemporary samples is crucial to our understanding and our ability to provide robust interpretations of invasion biology (e.g., Tay et al. \u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; \u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Elfekih et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Kunz et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). In this study, we used full mitochondrial DNA genomes to explore the relationship of CRB throughout the Pacific and its native range, with a particular focus on CRB-G as defined by prior partial \u003cem\u003emtCOI\u003c/em\u003e assessments (\u003cem\u003esensu\u003c/em\u003e Marshall et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). CRB samples were obtained partly from new collections made specifically for this study, but also from historic collections used in prior publications (Marshall et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Reil et al. \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) to allow direct comparison with published results. We detail the implications of our findings for the understanding of CRB spread throughout the Pacific, and its management prospects, ultimately improving the understanding of the spread of CRB into the Pacific. Additionally, the genome resources generated can subsequently contribute to research in CRB native range countries (e.g., Philippines, Sri Lanka) especially where coconut represents an important economic source.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003eSamples\u003c/h2\u003e\n \u003cp\u003eWe assessed 263 CRB from 19 countries (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e; Table S1). Historical CRB samples (extracted gut tissue DNA) were obtained from a subset used in Marshall et al. (\u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e) and in Reil et al. (\u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e), as well as from newly collected CRB (both adults attracted to pheromone lures or light traps and larvae from breeding sites) (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e; Table S1). Following dissection, gut tissues were placed in 100% ethanol and stored at -20˚C with fresh ethanol replaced every 24 hours for two days. CRB from India, Sri Lanka, Thailand, Malaysia, Singapore, Indonesia, Philippines, China (Hainan), and Taiwan were considered to be from the native range, whereas those from Papua New Guinea, Solomon Islands, Palau, Fiji, Japan, Guam, Hawaii, Rota, Marshall Islands, and Samoa were from the introduced range.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eWhole genome sequencing (WGS)\u003c/h3\u003e\n\u003cp\u003eGenomic DNA (gDNA) from individual CRB gut tissue was extracted using the Qiagen Blood and Tissue DNA extraction kit (Duesseldorf, Germany) following the manufacturer\u0026rsquo;s suggested protocol. Extracted gDNA was eluted in 200 \u0026micro;L EB and kept at -18˚C until required for WGS. The quantity of the extracted gDNA was assessed using Qubit 2.0 prior to sending samples to either the Australian Genome Resource Facility (AGRF) in Melbourne, Australia, to AZENTA Life Sciences in China, or to BRF at the Australian National University in Canberra, Australia, for WGS library construction and then WGS. All samples were assumed to have a genome size of approximately 350 Mbp, and the WGS data returned an average of 25x coverage, 150 bp paired-end reads/sample for all samples except for the four Marshall Islands CRB specimens which had an average of 8x coverage.\u003c/p\u003e\n\u003ch3\u003eConfirmation, characterisation and analysis of CRB mitogenome haplotypes\u003c/h3\u003e\n\u003cp\u003eWe assembled individual mitogenomes of all 263 CRB samples to reconstruct CRB female (i.e., maternal) movement history to better understand the phylogenetic relationships of reported CRB-G populations in the native range of Indonesia, Philippines, Malaysia, and Taiwan with those reported from its introduced Pacific Island countries (Marshall et al. \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e; 2021; Paudel et al. \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). To do this, we used our assembled draft mitogenome of an original Guam CRB individual (Guam_AgR_04-Or5; see Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e) provided by AgResearch New Zealand as a representative reference mitochondrial genome (mitogenome) within the CRB-G (clade I) haplotype grouping. All mitogenomes were assessed against MT457815 (Filipović et al. \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e) to infer our assembly quality.\u003c/p\u003e\n\u003cp\u003eWe imported the forward raw sequence reads (150 bp) of individual CRB into Geneious Prime (Version 2022.2.2) (Biomatters Ltd., Auckland) for mitogenome assembly using the \u0026lsquo;Map to Reference\u0026rsquo; option of the Geneious Mapper program and by selecting the \u0026lsquo;Low Sensitivity/Fastest\u0026rsquo; option for the Sensitivity field, and with no fine-tuning. The overall high sequence coverage of each CRB sample (average 70.44 million pair-end reads/CRB sample; range 57.98 million reads \u0026ndash; 92.24 million reads) enabled this low sensitive/fastest assembly option to be selected that also allowed for time and CPU optimisation. Assembly of arthropod mitogenome\u0026rsquo;s A-T rich region is typically challenging, especially based on short-read whole genome sequence data, due to the low complexity nature of this genomic region (e.g., Walsh et al. \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e; Behere et al. \u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e; Behere et al. \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e; Tay et al. \u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e; Tay et al. \u003cspan class=\"CitationRef\"\u003e2022d\u003c/span\u003e). This issue also applies to CRB (Filipović et al. \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e) for which the long-read sequencing approach is better suited. Therefore, we excluded the A-T rich region of the mitogenomes for all subsequent analyses. For annotations, assembled draft mitogenomes were imported to Mitos (Bernt et al. \u003cspan class=\"CitationRef\"\u003e2013\u003c/span\u003e) and annotated selecting invertebrate genetic code, and output .bed files were imported back to Geneious Prime for visualisation and fine-tuning (i.e., adjustments to ensure all 13 protein coding genes (PCGs) from each mitogenome had identical lengths across all individuals, and where appropriate all started with a methionine residue and had a stop codon). All our assembled draft mitogenomes are available from CSIRO\u0026rsquo;s Data Access Repository (Tay et al. \u003cspan class=\"CitationRef\"\u003e2024a\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003ePhylogenetic analysis\u003c/h3\u003e\n\u003cp\u003eWe aligned all assembled CRB mitogenomes using the MAFFT v7.450 program (Katoh et al. \u003cspan class=\"CitationRef\"\u003e2002\u003c/span\u003e; Katoh and Standley \u003cspan class=\"CitationRef\"\u003e2013\u003c/span\u003e) within Geneious Prime v22.2.2 using default parameters (Algorithm: Auto; Scoring matrix: 200PAM / K\u0026thinsp;=\u0026thinsp;2; Gap open penalty: 1.53; Offset value: 0.123). Following trimming of non-coding gene regions (i.e., all 22 tRNA genes, both rRNA genes, and the A-T rich region) a 11,113 bp concatenated sequence was left that consisted of the 13 protein coding mitochondrial genes (see Tay et al. \u003cspan class=\"CitationRef\"\u003e2024a\u003c/span\u003eSupplemental Data 1). Inference of phylogenetic relationship was through IQ-tree (Trifinopoulos et al. \u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e) in the W-IQ-TREE Web Service. Branch node support was inferred from 1,000 replications using UFBoot (Minh et al. \u003cspan class=\"CitationRef\"\u003e2013\u003c/span\u003e), with the 13 protein coding genes partitioned (see Tay et al. 2024 Supplemental Data 2) to enable optimisation of individual base substitution models for each gene. Visualisation and manipulation of the IQ-tree inferred tree topologies were done using Dendroscope 3 (Hudson et al. \u003cspan class=\"CitationRef\"\u003e2007\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eNucleotide diversity estimates, population differentiation, and mitogenome haplotype network\u003c/h3\u003e\n\u003cp\u003eMitogenome haplotypes from concatenation of the 13 Protein Coding Genes (PCGs; 11,133bp) from individual CRB mitogenomes were processed using FaBOX 1.61 (Villesen \u003cspan class=\"CitationRef\"\u003e2007\u003c/span\u003e) to identify unique mitogenome haplotypes for pairwise nucleotide distance estimates (\u003cem\u003ep\u003c/em\u003e-dist) performed in Geneious Prime, before imported into DnaSP 6.12.03 (Rozas et al. \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e) to estimate the degree of nucleotide polymorphism (i.e., nucleotide diversity; \u0026pi;) within the CRB populations. Tajima\u0026rsquo;s D (Tajima \u003cspan class=\"CitationRef\"\u003e1989\u003c/span\u003e) and Li and Fu\u0026rsquo;s test statistics (Fu and Li \u003cspan class=\"CitationRef\"\u003e1993\u003c/span\u003e, 1997) were performed to identify signatures of either population expansion/purifying selection or decrease in population size/balancing selection, separately for the native range and introduced range populations.\u003c/p\u003e\n\u003cp\u003eTo estimate population differentiation incorporating mutations between mitogenome haplotypes, Analysis of Molecular Variance (AMOVA) was also performed within PopART (Leight and Bryant 2015) by grouping CRB from the native range versus those from the introduced range. To estimate the evolutionary distance (i.e., genetic differentiation) between all pairs of mitogenome haplotypes and to ascertain if populations were significantly differentiated according to their assumed origins, we calculated \u0026Phi;\u003csub\u003eST\u003c/sub\u003e by grouping native range populations, as well as by grouping populations based on their assumed shared introduction origins. Genetic differentiation enabled native range populations to be grouped as: (i) South Asia (India\u0026thinsp;+\u0026thinsp;Sri Lanka); (ii) Indonesia; (iii) Philippines; and (iv) Southeast Asia (SEA) that included Singapore, Malaysia, Thailand, and Hainan China (i.e., due to the south China CRB native range being in proximity to, e.g., CRB from Thailand). Populations with putatively shared introduced origins were grouped as follows: Introduced \u0026lsquo;Sri Lanka\u0026rsquo; (i.e., Route 1: Fiji\u0026thinsp;+\u0026thinsp;Samoa), Introduced \u0026lsquo;Philippines/Taiwan\u0026rsquo; (i.e., Route 2: Japan\u0026thinsp;+\u0026thinsp;Palau\u0026thinsp;+\u0026thinsp;Guam\u0026thinsp;+\u0026thinsp;Rota\u0026thinsp;+\u0026thinsp;Hawaii), and introduced \u0026lsquo;Malaysia\u0026rsquo; (i.e., Route 3: Papua New Guinea\u0026thinsp;+\u0026thinsp;Solomon Islands\u0026thinsp;+\u0026thinsp;Marshall Islands). A haplotype network on all mitogenome haplotypes was constructed using the TCS statistical parsimony method (Templeton et al. \u003cspan class=\"CitationRef\"\u003e1992\u003c/span\u003e) within PopART (Leight and Bryant 2015) to visualise relationships between individual at the population level. The haplotype network was processed using Microsoft PowerPoint for Mac Version 16.79.2.\u003c/p\u003e\n\u003cp\u003eWe employed Genepop version 4.8.3 (Raymond and Rousset \u003cspan class=\"CitationRef\"\u003e1995\u003c/span\u003e; Rousset \u003cspan class=\"CitationRef\"\u003e2008\u003c/span\u003e) sub-options 3 and 4 for genotypic differentiation to assess population genetic structure, with the null hypothesis being that haplotypes were drawn from the same distribution in all populations. Pairwise \u003cem\u003eF\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e values were estimated using a \u0026ldquo;weighted\u0026rdquo; analysis of variance, as described by Cockerham (\u003cspan class=\"CitationRef\"\u003e1973\u003c/span\u003e) and Weir and Cockerham (\u003cspan class=\"CitationRef\"\u003e1984\u003c/span\u003e). Statistical significance of all paired \u003cem\u003eF\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e estimates involved an unbiased estimate of the \u003cem\u003eP\u003c/em\u003e-value using a log-likelihood ratio (G) based exact test, with the rejection zone defined by the sum of probabilities of having a G value equal to or higher than the observed value.\u003c/p\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003ePrincipal Component Analysis\u003c/h2\u003e\n \u003cp\u003eTo investigate genetic variation and population structure, we performed Principal Component Analysis (PCA) on mitogenome single nucleotide polymorphisms (SNPs) data from the 13 PCGs using the \u0026ldquo;adegenet\u0026rdquo; package in R (Jombart and Ahmed \u003cspan class=\"CitationRef\"\u003e2011\u003c/span\u003e), incorporating the sampling site metadata. PCA on genetic structure was illustrated through interactive scatter plots in two and three dimensions, utilizing \u0026ldquo;ggplot2\u0026rdquo; (Wickham \u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e) and \u0026ldquo;plotly\u0026rdquo; for visualization. This methodology provided an insightful view of the genetic variation patterns within and across populations.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec10\"\u003e\n \u003ch2\u003eDraft CRB mitogenomes\u003c/h2\u003e\n \u003cp\u003eThe annotated assembled mitogenomes of the 263 CRB individuals analysed all possessed the same number of coding sequences (CDS) including 13 PCGs, 22 tRNA genes, and 2 rRNA genes, with no gene re-arrangements detected when compared to the previously published CRB full mitochondrial genome assembled via the PacBio long-read sequencing platform (GenBank Accessions: MT457815; Filipović et al. 2021). The PCG sequences were concatenated and aligned, resulting in identification of 72 mitogenome haplotypes among these CRB samples (Tay et al. 2024a; Table S1). Small pairwise nucleotide distance (\u003cem\u003ep\u003c/em\u003e-dist) estimates between these 72 mitogenome haplotypes across the 13 PCG concatenated sequence length provided support that these were all from the same species (\u003cem\u003ep\u003c/em\u003e-dist.: 0\u0026ndash;1%, data not shown). With the exception of four contemporary Guam CRB samples (i.e., GuamDoA-03, 04, 05, 18; red boxed individuals in Fig. 1), all historical Guam CRB mitogenomes (i.e., samples reported in Marshall et al. (2017), Riel et al. (2018)) and the remainder of the contemporary Guam samples (\u0026lsquo;GuamDoA\u0026rsquo; sample code; Fig. 1; Table S1; Tay et al. 2024a) were 100% identical across the CDS (A-T rich region excluded), but were different (99.5% pairwise sequence identity) from the Solomon Islands mitogenome (GenBank Accession: MT457815; Filipović et al. 2021); thereby clearly differentiating further mitogenome haplotype divisions that all share the partial \u003cem\u003emtCOI\u003c/em\u003e marker for the CRB-G (Clade I) grouping.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\"\u003e\n \u003ch2\u003ePhylogenetic analysis\u003c/h2\u003e\n \u003cp\u003eThe phylogeny from the 13 concatenated PCGs (Fig.\u0026nbsp;1; Tay et al. 2024a) provided strong evidence to support that further diversity existed within the CRB populations across the introduced ranges. Unexpectedly, CRB from Guam formed two clades: one that comprised almost all individuals, including all historical individuals from Marshall et al. (2017) (i.e., CRB-G; Fig.\u0026nbsp;1, Table\u0026nbsp;1, Table S1), and a second clade that comprised of only four individuals recently (September 2022) collected near Guam Ports of Entry (see Fig.\u0026nbsp;1, individuals in red dotted line box), suggesting that these individuals originated from a separate introduction. Palau individuals were predominantly associated with specimens from eastern Indonesia, Philippines, and Taiwan. Japan individuals also clustered with Philippines and Taiwan individuals. The clade that contained Hawaii CRB individuals also included individuals from Japan, Rota, Philippines, and Taiwan. The main Solomon Islands cluster included a Papua New Guinea (PNG) individual and all four Marshall Islands CRB, whereas four Solomon Islands individuals clustered together with three Malaysian individuals in the branch that also had CRB specimens from Sri Lanka. This Sri Lanka cluster also included individual CRB specimens from India and China. Finally, five individuals from Malaysia and the two Singapore individuals formed a cluster of their own with significant (87%-100%; Fig.\u0026nbsp;1) branch node that included Thailand and southern China individuals, reflecting their close geographic proximity.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\"\u003e\n \u003ch2\u003eNucleotide diversity estimates\u003c/h2\u003e\n \u003cp\u003eAMOVA results (Table\u0026nbsp;2) showed that when populations (based on country of collection) were grouped by their native vs. introduced range assignments, the within-population genetic variation was not statistically significant (43.3%, \u0026Phi;\u003csub\u003eCT\u003c/sub\u003e: 0.03139, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.247). Between-population variation accounted for most genetic variation (53.6%, \u0026Phi;\u003csub\u003eSC\u003c/sub\u003e: 0.55316, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), including a small but significant difference between native vs. introduced range groups (3.1%, \u0026Phi;\u003csub\u003eST\u003c/sub\u003e: 0.56719, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Further grouping of native range populations by putative population boundaries, and introduced range populations by their putative shared origins, showed that highest variation existed at the between-groups level (51.3%, \u0026Phi;\u003csub\u003eST\u003c/sub\u003e: 0.58419, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), among populations had the least (i.e., most similar level) genetic variation, and supported the grouped introduced populations have similar genetic variation by their inferred shared origins (7.2%, \u0026Phi;\u003csub\u003eSC\u003c/sub\u003e: 0.14847, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.149). Genetic variation was also high at the within populations level, suggesting that individuals within grouped populations are significant differentiated (41.2%, \u0026Phi;\u003csub\u003eCT\u003c/sub\u003e: 0.51253, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (Table\u0026nbsp;2).\u003c/p\u003e\n \u003cp\u003eEstimated average nucleotide diversity (\u0026pi;\u0026thinsp;\u0026plusmn;\u0026thinsp;variance; Table\u0026nbsp;3) of the introduced and native range populations was overall low at 0.00235\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0000001 and 0.00216\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00024, respectively. Tajima\u0026rsquo;s D estimates indicated an overall weak, but statistically non-significant, excess of rare alleles across the introduced populations, with the exception of the Hawaii population that exhibited the signature of population growth or recent population expansion. However, purifying selection (i.e., background selection to reduce genetic diversity) at the target locus could also result in the significant negative Tajima\u0026rsquo;s D value. The Fu and Li\u0026rsquo;s test statistics, which is more sensitive at detecting population demographic changes over shorter times (Ram\u0026iacute;rez-Soriano et al. 2008), similarly detected signatures of population expansion in the Hawaii population, but also in the Solomon Islands CRB population. Small sample sizes for PNG and Rota, as well as the lack of haplotype diversity in the Marshall Islands prevented detection of signatures of population demographic differences among CRB from those locations.\u003c/p\u003e\n \u003cp\u003eDespite limited spatial sampling within countries such that many CRB samples were collected from the same site, across the native range populations we detected a significantly negative Tajima\u0026rsquo;s D value suggesting purifying selection and genetic signatures of population growth and/or migration. Specifically, we detected a statistically significant negative Tajima\u0026rsquo;s D as well as Li and Fu\u0026rsquo;s D and F values in the Indonesian population, as well as for the Li and Fu\u0026rsquo;s values for the China population, which suggests strong background selection is shaping the genomic diversity in these populations (Cvijović et al. 2018). Conversely, various introduced range populations (e.g., Palau, Solomon Islands, and Samoa) and some native range populations (i.e., Malaysia and Singapore) had positive but statistically non-significant Tajima\u0026rsquo;s D values as well as Li and Fu\u0026rsquo;s test statistic values, suggesting these populations experienced weak balancing selection (i.e., multiple alleles being actively maintained in the population) that reflected either a recent bottle neck or contraction. However, population substructure, such as likely present in Malaysia CRB, could also result in the positive values detected. The exception was the significant Li and Fu\u0026rsquo;s test statistic values for the Solomon Islands CRB samples, which likely consisted of individuals founded from different parts of the native range (i.e., from Malaysia and Philippines, see PCA results section), and potentially reflected maintenance of genetic variation over the short period.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\"\u003e\n \u003ch2\u003eMitogenome haplotype network\u003c/h2\u003e\n \u003cp\u003eThe mitogenome haplotype network (Fig.\u0026nbsp;2) showed that \u0026gt;\u0026thinsp;10 mutations typically separated various native range populations, such as for Indonesia, Malaysia/Singapore/Thailand/China, Philippines/Taiwan, and Sri Lanka (including India). Notably, Malaysia had a population distinct (i.e., Malaysia/PNG/Solomon Islands cluster) to the Malaysia/Singapore/Thailand/China cluster. Taken as a whole, native range populations of CRB appeared to exhibit mitogenome sub-structures. The network analysis results also support a scenario that introduced populations throughout the Pacific had multiple introduction origins. For example, CRB from Palau appeared to have originated from both Indonesia and Philippines due to similarities with these two native range populations. Many of the recently reported introduced range outbreak populations appeared to share closer evolutionary relationships with specimens collected from Philippines and Taiwan, forming a central cluster with low mutation steps (i.e., 1\u0026ndash;3 steps) between network branches. Fiji and Samoa clustered with Sri Lanka (i.e., South Asia group), away from the Southeast Asia native range group, whereas a subset of Papua New Guinea and Solomon Islands CRB clustered with a population from Malaysia.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\"\u003e\n \u003ch2\u003eF\u003csub\u003est\u003c/sub\u003e estimates\u003c/h2\u003e\n \u003cp\u003eNon-significant population differentiation between Malaysia/Singapore, China/Malaysia/Thailand suggested gene flow (i.e., exchange of individuals) across this region (Table 4), bearing in mind the small sample size from, e.g., Singapore (n\u0026thinsp;=\u0026thinsp;2), and its low but significant \u003cem\u003eF\u003c/em\u003e\u003csub\u003est\u003c/sub\u003e estimates with China (n\u0026thinsp;=\u0026thinsp;5) and Thailand. Non-significant \u003cem\u003eF\u003c/em\u003e\u003csub\u003est\u003c/sub\u003e estimates between the introduced Hawaii CRB population and the Philippines and Taiwan native range populations, but also with introduced range populations from Japan, Marshall Islands, and Rota suggested these populations shared some gene flow but likely also their shared closer evolutionary relationships with native range Philippines and Taiwan populations. Significant \u003cem\u003eF\u003c/em\u003e\u003csub\u003est\u003c/sub\u003e estimates were found for the Guam population against all other populations except for Rota (n\u0026thinsp;=\u0026thinsp;2) and Japan (n\u0026thinsp;=\u0026thinsp;4), suggesting that the Guam population had limited exchange of individuals with our introduced range locations. The detection of an additional Guam clade (i.e., Fig. 1, GuamDoA-03, 04, 05, 18) could potentially contribute to the two non-significant \u003cem\u003eF\u003c/em\u003e\u003csub\u003est\u003c/sub\u003e estimates with Japan and Rota. Despite analyses showing the close evolutionary relationships between CRB from Fiji, Samoa, and Sri Lanka, significant \u003cem\u003eF\u003c/em\u003e\u003csub\u003est\u003c/sub\u003e were detected between these three populations, suggesting potentially limited exchange of individuals among introduced range locations after the original introduction events.\u003c/p\u003e\n\u003cdiv id=\"Sec15\"\u003e\n \u003ch2\u003eCRB mitogenome PCA\u003c/h2\u003e\n \u003cp\u003ePrincipal Component Analysis (PCA) of mitogenome SNPs (from the 13 PCGs) identified distinct sub-cluster diversity within the high-level native range grouping for both South Asia (i.e., Sri Lanka, Sri Lanka\u0026thinsp;+\u0026thinsp;India) and Southeast Asia (Philippines/Taiwan, Malaysia/Singapore/Thailand/China, Malaysia, and Indonesia) (Fig.\u0026nbsp;3). The Palau specimens clustered with both native Indonesia and Philippines/Taiwan sub-clusters. A subset of specimens from both PNG and Solomon Islands clustered with a Malaysia native range group that was distinct from the South Asia and southeast Asia native range groups that also included Malaysian CRB specimens. Several CRB from invaded Pacific Island countries (Guam, Hawaii, Japan, Marshall Islands, Palau, PNG, Rota, Solomon Islands) formed a cluster with the native range Philippines/Taiwan sub-cluster. CRB from invaded Samoa and Fiji, but also from native ranges of Malaysia and China, were associated with three separate sub-clusters of Sri Lanka/India native CRB populations.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis study, based on a whole genome sequencing (WGS) approach of the mitochondria genome, represents the most comprehensive survey of both native and introduced CRB populations undertaken to date, and provides deeper insights to genetic diversity and differentiation of this pest from the maternal (i.e., mitochondrial) lineage perspectives. Based on the 13 PCGs concatenated nucleotide sequence and linking recently collected samples with the historical CRB samples of Marshall et al. (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and Reil et al. (\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), these results demonstrate a much richer diversity of CRB than has been shown to date, especially in native populations, and highlight the limitations of defining CRB using only a single partial \u003cem\u003emtCOI\u003c/em\u003e molecular marker (Tay et al. \u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e2024b\u003c/span\u003e). From the mitogenome (i.e., maternal lineage) perspective, and based on surveys of the 10 introduced populations, there is no evidence for: (i) Guam as a key CRB dispersal point (i.e., as a \u0026lsquo;bridge head\u0026rsquo; location; Lombaert et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) from which CRB spread into other Pacific Islands including Hawaii, Papua New Guinea, Solomon Islands, Palau and Yap (e.g., Tsatsia et al. \u003cspan citationid=\"CR106\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Datt et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Valaqo et al. 2017); (ii) nor evidence of a common maternal lineage of a native founder population that subsequently dispersed to Guam and other Pacific locations with the CRB-G haplotype grouping (\u003cem\u003esensu\u003c/em\u003e Marshall et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) populations (e.g., Reil et al. \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Etebari et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Tanaka et al. 2022); (iii) and no evidence of multiple native range populations being directly related with the unique Guam maternal lineage (e.g., Etebari et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Anggraini et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) and most other exotic range populations.\u003c/p\u003e\u003cp\u003eThis CRB mitogenome analysis also identified a second mitogenome haplotype representing a separate introduction event of CRB into Guam. There is a low likelihood that some of the CRB individuals analysed by Marshall et al. (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and Reil et al. (\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) included individuals that belonged to this separate introduction event, but this was not detected through analyses of the partial \u003cem\u003emtCOI\u003c/em\u003e gene region. However, because some of our individuals with a different origin were recently collected at a Guam Port (Table S1), they were likely to represent a new introduction event associated with the pest\u0026rsquo;s propensity to be accidentally transported (Hoffmann et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). This work has further highlighted the value of whole genome sequencing approach, while also reiterating the importance of using multiple genetic markers (e.g., Tay et al. \u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e2024b\u003c/span\u003e) together with the inclusion of both introduced and native range sourced specimens to understand invasion pathway histories.\u003c/p\u003e\u003cp\u003eIncreasingly, mitogenome haplotypes including the use of concatenated PCGs from highly invasive arthropod species, have provided evidence to show genetic and demographic differentiation among the native and introduced populations (e.g., the fall armyworm \u003cem\u003eSpodoptera frugiperda\u003c/em\u003e, Tay et al. 2022; the cotton bollworm \u003cem\u003eHelicoverpa armigera\u003c/em\u003e, Anderson et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; \u003cem\u003ePhthorimaea\u003c/em\u003e (\u003cem\u003eTuta\u003c/em\u003e) \u003cem\u003eabsoluta\u003c/em\u003e, Li et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Magalhaes et al. \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). As reported in Tay et al. (\u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e2024b\u003c/span\u003e), which utilised limited samples, this study further demonstrated that by including specimens from the native range, mitogenome haplotypes for the CRB (i) improved demographic signatures (ii) explained the \u003cem\u003emtCOI\u003c/em\u003e versus nuclear DNA SNP loci discrepancy for the presence or absence of population movements from Guam to other Pacific islands; (iii) better linked introduced populations with their putative native ranges (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e); and (iv) provided evidence of genetic differentiation (Tables\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). For example, historically, the origin of Samoan CRB was reported to be from Sri Lanka simply due to horticultural trade movements of rubber seedlings containing CRB larvae (Doane \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e1913\u003c/span\u003e; Catley 1969; Lever \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e1969\u003c/span\u003e; Bedford \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1980\u003c/span\u003e). This Sri Lankan population origin report is now explicitly supported, by our genomic evidence that showed close maternal lineage relationships between Sri Lankan and Samoan CRB. To further improve understanding of CRB invasion origins into the Pacific will require more comprehensive sampling of CRB from both the native range and other Pacific Island nations including e.g., Vanuatu, Saipan, American Samoa, New Caledonia, Tonga, as well as increasing sample sizes especially in countries such as PNG.\u003c/p\u003e\u003cp\u003eCombining our mitogenome haplotype results with previous population genomic findings (Reil et al. \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Etebari et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) enables strong assessment of our understanding of CRB Pacific Island dispersals (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Our work has clearly found separate maternal origins of the Guam and Hawaii populations (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), but with both being closely related to the Philippines/Taiwan native population cluster (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). That Guam and Hawaii CRB do not appear to share a direct invasion history is consistent with inference of separate lineages based on nuclear genome analysis (Reil et al. \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The Palau CRB population exhibited distinct Indonesia and Philippines CRB mitogenome signatures (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), and is in agreement with nuclear SNP loci analyses of Reil et al. (\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) that also identified Philippines and Indonesia as likely origins of CRB into Palau. Although low CRB sample sizes from Marshall Islands, PNG, and Rota were analysed, CRB individuals between PNG and its neighbouring Solomon Islands likely had genetic exchange based on both nuclear (Etebari et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), and our mitochondrial genome analyses, with both having an original linkage back to Malaysia (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Similarly, Samoa CRB shared demographic history with Fiji which was supported by nuclear loci analysis (Etebari et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Nuclear loci (Reil et al. \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) and our mitogenomes support shared demographic signatures between Hainan (China) and Thailand CRB populations, and our mitogenome analysis further grouped some of the Malaysian and Singapore CRB individuals with both Hainan and Thailand populations (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eWe also recognise some limitations of our study. Our mitochondrial genome results will require further support from nuclear gene analysis because our CRB samples included introduced range populations previously not analysed by Reil et al. (\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) and Etebari et al. (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), and from other locations that have not been included in studies using either mitochondrial or nuclear genome analyses. Importantly, the spread of CRB could potentially involve males which would not be detected via the mitochondrial genome analysis. This is an important consideration that requires urgent follow-up, especially if the reported resistance to OrNV biocontrol isolates within (at least some) members of the CRB-G haplotype grouping (\u003cem\u003esensu\u003c/em\u003e Marshall et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) involved interactions between the nuclear as well as the viral genome.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eEffective management of invasive insect pests benefits from an identification nomenclature based on whole genomic analyses and with adequate sampling of populations from native and introduced ranges. Such a naming system, which is increasingly enabled by next and third-generation sequencing technologies, enables analysis of underlying genetic diversity, with implications for understanding of invasive spread, adaptation, and resistance to control agents. In this study, analyses based on multiple genes from draft whole mitogenomes has especially shown the native CRB populations analysed to strongly correlate to geographic origins such as those as from Indonesia, Philippines/Taiwan, Malaysia/Singapore, and Sri Lanka, which lends further support to previous work that surmised on origins (e.g., Doane \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e1913\u003c/span\u003e; Catley 1969; Marshall et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Reil et al. \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). This has also facilitated identification and tracking of invasive populations, extending what was possible before. Indeed, the mitochondrial genome resources reported in this study could potentially serve as the starting point of a more robust and phylogeographically informative CRB-naming system (e.g., introduced clade 1, introduced clade 2, native clade 1, native clade 2, etc.). However, we were unable to define such a naming scheme at present, in parts, due to our incomplete sampling of both native and introduced populations, and further because the invasion process of the CRB is on-going (Hoffmann et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Beyond these issues, a definitive system will also need to incorporate data from whole genome resequencing analyses that will further provide finer grain insights into the genetic makeups of introduced populations underpinned by idiosyncratic population establishment processes.\u003c/p\u003e\u003cp\u003e\u003cb\u003eAcknowledgements and Funding Information\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIndonesian CRB samples were provided with Republic of Indonesia Ministry of Agriculture, Agricultural Quarantine Agency Permit numbers: 2021.1.2005.0.K13.E.00003 No. 4299301 and 2022.1.2005.0.K12.E.00002 No. 5896762). The Philippines CRB samples were gathered under the Gratuitous Permit DENR8-GP No. 2022-02 (10 January 2022) provided by the Department of Environment and Natural Resources 8 of the Republic of the Philippines and conducted under the VSU-IP 2021-10 (BIO-CAMP) and VSU-IP 2022-2 (CRB) projects. Singapore CRB samples were generously provided by Izaan Muhammad Izzan Bin Istijab (Plant Science \u0026amp; Health, Horticulture \u0026amp; Community Division, National Parks Board Singapore). This project was funded by the DFAT Administered (aid) Simple Grant Agreement 77092. We thank Tristan Armstrong (DFAT), Geoff Bedford (Macquarie University), Mr Gibson Susumu (SPC, Fiji), Tanya Robinson (New Zealand Ministry of Foreign Affairs \u0026amp; Trade), Silva DPM (Crop Protection Division, Coconut Research Institute, Bandirippuwa, Lunuwila,61150, Sri Lanka), Sivapragasam Annamalai (CABI Associate), and Alison Watson (Head of the Secretariate of ASEAN FAW Action Plan) for helpful discussions during the course of this project.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eCONFLICT OF INTEREST\u003c/h2\u003e\u003cp\u003eThe authors declared no conflict of interest\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eManuscript preparation and writing of the main text: Wee Tek Tay, Angel David Popa-Baez, Rahul Rane, Andy Bachler, Glenn Dulla, Alex Gofton, Justine Millado, Michael Melzer, Jelfina Alouw, Sean Marshall, Harshani Dilrukshika, Karl Gordon, Ben Hoffmann.Sample collection and logistics: Juniaty Sambiran, Jelfina Alouw, Justine Millado, Ben Hoffmann, Francis Tastsia, Jacob Yombai, Chris Dahl, Tanu Toomata, Pueata Tanielu, Harshani Dilrukshika, Muhammad Faheem, Leon Court, Michael Melzer, Andrea Blas.Laboratory work: Juniaty Sambiran, Meldy Hosang, Jacob Yombai, Justine Millado, Michael Melzer, Timothy Hogarty, Demi Yi-Chun Cho, Leon Court, Muhammad Faheem, Andrea Blas, Wee Tek Tay.Data Analysis: Rahul Rane, Wee Tek Tay, Angel David Popa-Baez, Andy Bachler, Alex Gofton, Meldy Hosang, Muhammad Faheem, Andrea Blas, Karl Gordon.All authors contributed to the review of various manuscript drafts.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eIndonesian CRB samples were provided with Republic of Indonesia Ministry of Agriculture, Agricultural Quarantine Agency Permit numbers: 2021.1.2005.0.K13.E.00003 No. 4299301 and 2022.1.2005.0.K12.E.00002 No. 5896762). The Philippines CRB samples were gathered under the Gratuitous Permit DENR8-GP No. 2022-02 (10 January 2022) provided by the Department of Environment and Natural Resources 8 of the Republic of the Philippines and conducted under the VSU-IP 2021-10 (BIO-CAMP) and VSU-IP 2022-2 (CRB) projects. Singapore CRB samples were generously provided by Izaan Muhammad Izzan Bin Istijab (Plant Science \u0026amp; Health, Horticulture \u0026amp; Community Division, National Parks Board Singapore). This project was funded by the DFAT Administered (aid) Simple Grant Agreement 77092. We thank Tristan Armstrong (DFAT), Geoff Bedford (Macquarie University), Mr Gibson Susumu (SPC, Fiji), Tanya Robinson (New Zealand Ministry of Foreign Affairs \u0026amp; Trade), Silva DPM (Crop Protection Division, Coconut Research Institute, Bandirippuwa, Lunuwila,61150, Sri Lanka), Sivapragasam Annamalai (CABI Associate), and Alison Watson (Head of the Secretariate of ASEAN FAW Action Plan) for helpful discussions during the course of this project.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eAssembled draft mitochondrial DNA genome sequence data can be accessed from the CSIRO Data Access Portal (CSIRO DAP) [https://data.csiro.au/collection/csiro:62248](https:/data.csiro.au/collection/csiro:62248) .\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAnderson, C. J., Tay, W. T., McGaughran, A., Gordon, K. \u0026amp; Walsh, T. K. 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Possibility of resistance to a baculovirus in populations of the coconut rhinoceros beetle (\u003cem\u003eOryctes rhinoceros\u003c/em\u003e). \u003cem\u003ePlant. Prot. Bull.\u003c/em\u003e \u003cb\u003eFA0\u003c/b\u003e (2), 77\u0026ndash;82 (1989).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZelazny, B., Lolong, A. \u0026amp; Pattang, B. \u003cem\u003eOryctes rhinoceros\u003c/em\u003e (Coleoptera: Scarabaeidae) populations suppressed by a Baculovirus. \u003cem\u003eJ. Invertebr. Pathol.\u003c/em\u003e \u003cb\u003e59\u003c/b\u003e, 61\u0026ndash;68 (1992).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":true,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"biosecurity, CRB-G, metagenomic, Oryctes rhinoceros, incursion","lastPublishedDoi":"10.21203/rs.3.rs-7796543/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7796543/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eWe used draft mitochondrial genomes (mitogenomes) to explore introduction histories of the destructive coconut rhinoceros beetle (CRB, \u003cem\u003eOryctes rhinoceros\u003c/em\u003e L.) throughout the Pacific and its native range, focusing on re-evaluating the relationship between members of the CRB-G haplotype grouping (\u003cem\u003esensu\u003c/em\u003e Marshall et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) as previously assessed by the partial \u003cem\u003emtCOI\u003c/em\u003e (mitochondrial DNA \u003cem\u003ecytochrome oxidase subunit I\u003c/em\u003e) gene. Mitogenome analyses that included historical CRB collections confirmed the 2007 invasive CRB population in Guam was found only in Guam, while there was a detection of a second novel CRB mitogenome, suggesting a new recent introduction(s) into Guam. Further, mitogenome analyses linked: Palau CRB with Indonesia and Philippines native range populations; Papua New Guinea and Solomon Islands CRB with native range Malaysia CRB; Marshall Islands CRB with Solomon Islands CRB; and Samoa and Fiji CRB with Sri Lanka. We therefore provided evidence of historical and current CRB hitchhiking pathways between various native and introduced locations. The results build upon the previous partial \u003cem\u003emtCOI\u003c/em\u003e marker framework to improve the resolution of diversity present within CRB. This study also highlights a need to implement new CRB population nomenclatures based on full mitochondrial DNA genomes.\u003c/p\u003e","manuscriptTitle":"Coconut Rhinoceros Beetle mitochondrial genomes assessment refines understanding of its Pacific invasions","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-12 13:09:39","doi":"10.21203/rs.3.rs-7796543/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-01-23T08:41:21+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-22T11:48:03+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-18T02:44:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"220895156724434164146131879135417905863","date":"2026-01-02T07:45:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"71604996914696815048327270589707199601","date":"2025-12-03T03:30:06+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-11-27T16:40:32+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-11-18T08:18:32+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-10T08:16:36+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-10T08:15:00+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-10-07T06:43:40+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c9f79676-325d-4239-abb3-8469eef51200","owner":[],"postedDate":"December 12th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[{"id":59332787,"name":"Biological sciences/Ecology"},{"id":59332788,"name":"Earth and environmental sciences/Ecology"},{"id":59332789,"name":"Biological sciences/Evolution"},{"id":59332790,"name":"Biological sciences/Genetics"}],"tags":[],"updatedAt":"2026-01-23T08:54:00+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-12 13:09:39","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7796543","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7796543","identity":"rs-7796543","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}