Evolutionary genomics and divergence of Cacopsylla species with a special focus on the Apple Proliferation Vectors: Cacopsylla melanoneura and C. picta

Evolutionary genomics and divergence of Cacopsylla species with a special focus on the Apple Proliferation Vectors: Cacopsylla melanoneura and C. picta | 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 Research Article Evolutionary genomics and divergence of Cacopsylla species with a special focus on the Apple Proliferation Vectors: Cacopsylla melanoneura and C. picta Lapo Ragionieri, Liliya Štarhová Serbina, Erika Corretto, James M. Howie, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7518317/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 19 Mar, 2026 Read the published version in BMC Genomics → Version 1 posted 10 You are reading this latest preprint version Abstract Background The psyllid genus Cacopsylla includes several species that act as vectors for phytoplasma-associated diseases affecting plantations across Europe. Among them, Cacopsylla melanoneura and Cacopsylla picta are the primary vectors of ‘ Candidatus Phytoplasma mali’, the phloem-restricted bacterium responsible for Apple Proliferation disease in Europe. To explore whether vector competence in these species reflects shared ancestry or independent evolution, we assembled mitochondrial and draft nuclear genomes of Italian populations of C. melanoneura and C. picta and reconstructed time-calibrated phylogenies using 13 mitochondrial protein-coding genes from 12 Cacopsylla species. Results Phylogenetic analyses revealed two major Cacopsylla clades (Clade I and II) whose divergence times range from the Early Miocene (18.4 MYA; 95% HPD: 10.8–27.5) to the Middle Miocene (12.7 MYA; 95% HPD: 9.7–16.0). Both C. melanoneura and C. picta are within Clade I, which is predominantly composed of univoltine species that overwinter on conifers. Within this clade, Cacopsylla melanoneura is more closely related to the plum psyllid Cacopsylla pruni than to the apple-associated C. picta and Cacopsylla mali , the latter belonging to Clade II. Draft nuclear genomes revealed significant differences in size (438 Mb in C. melanoneura vs. 631 Mb in C. picta ), largely attributed to repetitive elements. Comparative analyses of repetitive elements across Cacopsylla species revealed a recent expansion of transposable elements, particularly LINE elements, which were slightly more abundant in Clade I and contributed to the larger genome size observed in C. picta . Conclusions Collectively, our findings provide the first genomic resources for C. melanoneura , C. picta , and several other phytoplasma-vectoring Cacopsylla species. We established a robust mitogenomic phylogeny with divergence estimated for this genus showing the presence of two clades with the representatives predominantly associated with different overwintering strategies. Our results further indicate that vectorial capacity in Cacopsylla reflects an independent evolutionary trajectory rather than a shared ancestral origin. This evolutionary framework advances our understanding of the biology and origin of vector competence in this agriculturally important group. Psylloidea Genome assembly Mitochondrial genes Time-calibrated phylogeny Transposable elements Apple Proliferations Life history traits Figures Figure 1 Figure 2 BACKGROUND Psyllids (Hemiptera: Psylloidea) are a group of phytophagous insects comprising ~ 4,000 described species belonging to seven families [ 1 ]. They are members of Sternorrhyncha, a suborder which includes several other well studied plant pathogen vectors such as aphids (Aphidoidea), whiteflies (Aleyrodoidea) and scale insects (Coccoidea) [ 1 , 2 ]. The genus Cacopsylla (Psyllidae) includes a particularly high number of vectors of phytoplasma, a bacterium (Mollicutes) inhabiting the phloem and responsible for a variety of economically important tree and crop diseases [ 3 – 5 ] including European Stone Fruit Yellows, Pear Decline, and Apple Proliferation [ 5 , 6 ]. Phytoplasmas alter the plant’s cellular processes by interfering with its ability to transport nutrients and water. This results in weakened and malformed structures, as well as in significant yield reductions [ 4 – 6 ]. Apple Proliferation (AP) is an important disease affecting apple trees, associated with the phytoplasma ‘Candidatus Phytoplasma mali’ (hereafter, ‘ Ca . P. mali’; for a review see Janik et al. [ 6 ]). Distinctive symptoms include characteristic shoots with a “witches” broom” appearance and fruits of reduced size and quality [ 7 ]. Because infected trees cannot be cured, they must be eradicated, leading to significant yield losses [ 6 , 8 , 9 ]. The AP is primarily transmitted by Cacopsylla picta , which acts as the main vector in most European countries [ 10 – 12 ], and by Cacopsylla melanoneura , which is the main vector in the areas of Northwestern Italy where C. picta is absent [ 10 , 13 , 14 ]. Due to variation in vector capabilities of these two psyllids, various environmental and genetic factors are expected to influence the rate of acquisition and transmission of ‘ Ca. P. mali’. These factors include the infectious status of the host tree and the genetics of the psyllid vector [ 12 , 15 ], the insect’s endosymbionts [ 16 ] and the phytoplasma itself [ 15 ]. Cacopsylla , like most other psyllid species, are host specific, with closely related psyllids tending to associate with related host plant lineages [ 17 , 18 ]. In temperate regions, many psyllid species migrate from their deciduous host plants to conifers, where they overwinter as adults or eggs [ 19 ]. In contrast, psyllids in tropical and southern temperate regions are often associated with evergreen hosts and tend to remain on the same plant throughout the year, completing several generations [ 19 ]. Intriguingly, some Cacopsylla species can develop on multiple related host plants (i.e. Rosaceae), forming genetically distinct groups with differing fitness levels. This is exemplified by C. melanoneura , which appears to have at least two genetically distinct populations, associated either with apple trees or hawthorn [ 20 ]. The timing of Cacopsylla diversification has not yet been inferred using time-calibrated phylogenies, leaving the genus's evolutionary history, particularly its historical biogeography and host-plant associations, poorly understood. To date, a Neighbor-Joining analysis based on partial cytochrome oxidase I (COI) gene sequences provided weak support for most deep clades, including those containing the AP vectors C. melanoneura and C. picta , or other Cacopsylla species like C. mali and C. pruni [ 21 ]. A more recent phylogeny, based on whole mitochondrial genomes that included several Cacopsylla species, was not time-calibrated and omitted both C. melanoneura and C. picta , limiting its utility for resolving the evolutionary relationships among key vectors of ‘Ca. P. mali’. [ 22 ]. Genomic information for these two species, and psyllids more broadly, remains limited, with existing studies focusing mainly on mitochondrial genomes [ 23 ]. These studies suggest the existence of two distinct clades, which distinguish species with differences in overwintering behaviour [ 24 ], although the diversification, including at the genetic and genomic level, is not yet established. A comprehensive understanding of a species evolutionary history requires investigating the evolution of the nuclear genome, which is shaped by various molecular mechanisms such as different classes of mutations, gene duplications, recombination, and horizontal gene transfer. In many species one major component involved in genome evolution and adaptation is represented by transposable elements [ 25 ]. Transposable elements (TEs) are mobile DNA sequences that can significantly influence the genome structure and its functions. In insects, the proportion of the genome occupied by TEs varies widely, reaching up to 60% in some species such as the migratory locust [ 26 ]. Although TE activity can have potentially deleterious effects on gene regulation, increasing evidence suggests that TEs also drive genomic innovation and can confer selective advantages to the host [ 27 ]. Comparative studies have revealed both similarities and differences in TE family diversity and abundance among insect genomes. Notably, significant variation in TE activity has been observed even among closely related species [ 28 ]. For example, within the order Hemiptera, contrasting TE profiles have been reported. In Homalodisca vitripennis (Hemiptera, Cicadellidae), LINEs and DNA transposons show a distinct divergence distribution, while SINEs and LTR elements are poorly represented. This pattern contrasts sharply with that of the pea aphid Acyrthosiphon pisum (Hemiptera, Aphididae), where SINEs dominate the TE content, and LINEs and LTRs are virtually absent. To overcome the limited genomic resources available for Cacopsylla species, we present newly assembled mitochondrial genomes and draft nuclear genome nuclear assemblies of C. melanoneura and C. picta . The mitochondrial genomes, together with publicly available data from other Cacopsylla species, were used to reconstruct a robust, time-calibrated phylogeny of the genus, including several vector species with different host plant preferences. In parallel, we provide the first nuclear genome assemblies of C. melanoneura and C. picta and use them to investigate the role of repetitive elements in psyllid genome evolution. Given the established involvement of repetitive elements in adaptive evolution and gene regulation, we also performed a comparative analysis across multiple Cacopsylla species, with a particular focus on the AP vector species C. melanoneura and C. picta , to identify lineage-specific traits potentially associated with the accumulation of recently active TEs. METHODS Psyllid collection, DNA extraction, library preparation and sequencing Individuals of C. melanoneura and C. picta were collected in 2015 from natural populations in Northeastern Italy, from Laimburg (South Tyrol) and Bosentino (Trentino), and preserved at -20°C in 90% ethanol. Total DNA extraction was carried out using two different protocols. For C. melanoneura , DNA was extracted using the Macherey-Nagel NucleoSpin Tissue Kit (Macherey-Nagel) from two individual specimens and one pool of six individuals. Three paired-end libraries (PE290, PE310, and PE700) were constructed from these samples using, representing different fragment sizes ( Table S1 ). For C. picta , an enhanced DNA extraction protocol was used, involving overnight lysis with DTT and extraction with the KingFisher Cell and Tissue DNA Kit (Thermo Fisher Scientific). Two paired-end libraries (PE510 and PE750) were prepared from the extracted single individuals ( Table S1 ). All five libraries were sequenced on the Illumina HiSeq 2000 platform with a 251 bp insert size (PRJNA1312285). This yielded 57.9, 59.4, and 75.3 Gb of raw data for C. melanoneura , corresponding to genome coverages of 131×, 135×, and 137×, respectively. For C. picta , sequencing produced 121.5 and 74.9 Gb of raw data, with corresponding coverages of 192× and 119×. Nuclear genome size estimation in Cacopsylla species Prior to the de novo assembly, the genome sizes of C. melanoneura ( Table S2 ) and C. picta ( Table S2 ) were estimated using a k-mer analysis of the raw reads of library PE700 and PE510, respectively, using Jellyfish v2.2.6 [ 29 ], GenomeScope v1.0 ( k = 17) [ 30 ] and SGA preqc ( k = 31) [ 31 ]. Additionally, using this approach we also estimated the genome size of C. burckhardti (PRJNA927338) and C. jukyungi (PRJNA927338), for which raw data with sufficient coverage are publicly available. Assembly of the nuclear genomes of C. melanoneura and C. picta Adapter sequences were removed and reads were trimmed in the Trim Galore ! wrapper ( http://www.bioinformatics.babraham.ac.uk/projects/trim_galore/ ) using Cutadapt [ 32 ]. Overlapping reads from the shorter fragment libraries were merged using FLASH [ 33 ], after which reads were filtered in GEM-mapper [ 34 ] (with up to 2% mismatches) against a contamination database including phiX, Univec sequences, E. coli, Cacopsylla coccinea mitochondrion complete genome (accession number NC_027087.1) and 17 contaminant species’ genomes (detected independently for each Cacopsylla species, using with Kraken v0.10.5 [ 35 ] as present in ≥ 0.03% of the reads, see Table S3 ). The C. melanoneura genome was assembled de novo using overlapping read-pairs from the PE700 library (detected with FLASH ) using DISCOVAR de novo (experimental release v.51885) with default options [ 36 , 37 ], after discarding all read-pairs shorter than 200 bp. Circular lines were discarded, and the DISCOVAR contigs were scaffolded with BESST v2.2.5 [ 38 ] using processed reads from all three PE libraries (PE290, PE310 and PE700) with the option "--separate_repeats” and discarding all contigs classified as repeats. Mis-assemblies were removed as in [ 39 , 40 ], using reads from all PE libraries, after introducing breaks at genomic intervals calculated to have negative consistency scores. This resulted in shorter but more reliable scaffolds, which were then broken again into contigs. Then contig assembly was “unchaffed” by filtering out those shorter than the read length (250 bp), thus only retaining sequences long enough to contain at least a partial exon (251–500 bp). Finally, the filtered contigs were re-scaffolded in BESST v2.2.5 yielding a final draft assembly ( Table S4 ). The C. picta genome was assembled with a modified version of the C. melanoneura pipeline. Overlapping read-pairs from library PE510 were assembled with DISCOVAR de novo [ 36 , 37 ], discarding both read-pairs shorter than 200 bp and circular lines. The DISCOVAR contigs were collapsed with Redundans [ 41 ] to reduce heterozygous haplotypes and repeats, thus accounting for high fragmentation. Redundans contigs were scaffolded with BESST v2.2.5 [ 38 ] using both PE libraries with the “-- separate_repeats ” option, yielding the final assembly draft ( Table S5 ). Estimates of genomic completeness were obtained for each genome using two methods. KAT [ 42 ] compared k-mers in the pre-processed reads (libraires PE290, PE310, PE700 for C. melanoneura , PE510 for C. picta ) with those in the final genomes to estimate sequence completeness. To assess genome assembly quality, we used BUSCO v5.8.3 [ 43 ], which estimates the completeness of genomic data based on the presence and universal single-copy orthologs (OrthoDB database odb12). Repetitive element annotation and comparisons The expected sample heterozygosity and genomic repetitiveness were estimated in GenomeScope v1.0 [ 30 ] ( Table S2 ). We then conducted a comparative analysis of abundances, sequence length and genome percentage for multiple repetitive element classes, including retroelements (LINEs, SINEs, LTRs), DNA transposons, and interspersed repeats (sRNAs, DNA satellites, simple repeats) using RepeatMasker [ 44 ], by mapping masked reads to a RepeatMasker Combined Database (Dfam_Consensus-20181026, RepBase-20181026) with RMBlastn v2.6.0+ (command: RepeatMasker scaffold.fa -species arthropoda -pa 3 ). In addition, RepeatModeler2 [ 45 ] with the option "–LTRStruct" was used to identify dispersed transposable elements. Subsequently, RepeatMasker was used to identify and mask interspersed repeats in the nuclear draft assemblies of C. melanoneura and C. picta , using the RepeatModeler2 library option. Additionally, we identified satellites and putative satellites in the raw reads and included them in RepeatModeler2 families for use in a RepeatExplorer2 analysis. Briefly, the pipeline was run to characterize the repeatome [ 46 , 47 ], including the TAREAN analysis within the Galaxy portal ( https://repeatexplorer-elixir.cerit-sc.cz ). For this, we randomly selected a total of 2,000,000 paired reads. Default options were selected, except that we set computing time to “long”, applied a filtration of the most abundant repeats, and set the threshold of the analysis to 0.001%. Besides C. melanoneura and C. picta presented here, no nuclear genome assemblies are available for other Cacopsylla species. For some other species, sequencing reads are publicly available ( Tables S6 ). To analyse the genomic content and compare nuclear repeats across Cacopsylla species, we used dnaPipeTE ( https://github.com/clemgoub/dnaPipeTE ) , a tool optimized for repeatome analysis from low-coverage sequencing data [ 48 ] that uses raw reads as input. Before analysis, we removed reads matching to mitochondrial DNA, known symbionts and contaminants. Repeat annotation was performed using the Dfam-RepeatMasker.lib database for Arthropoda, which included 6,828 entries as of May 2025. Repeat landscapes were generated using the dnaPTlandscape.sh script from the dnaPT_utils package ( https://github.com/clemgoub/dnaPT_utils ), with the -S and -U options enabled to visualize only repeat superfamilies and to exclude unclassified elements. Assembly of the mitochondrial genomes of C. melanoneura and C. picta Mitochondrial genomes of C. melanoneura (PX243765) and C. picta (PX243766) were assembled and circularised in the MitoZ pipeline [ 49 ] operated in a Singularity container [ 50 ] using Illumina raw read libraries PE290 and PE750, respectively. Mitogenomes were annotated in MITOS [ 51 ] and MITOS2 [ 52 ], a consensus annotation manually compiled, and the genomes visualised with annotations, GC content and coverages in MitoZ [ 49 ]. Mitochondrial phylogeny and divergence time estimation To test the phylogenetic placement of C. melanoneura and C. picta within the Cacopsylla genus, we conducted phylogenetic analyses using Bayesian inference (BI) in BEAST v2.7.5 [ 53 , 54 ] and maximum likelihood (ML) in IQ-TREE v1.6.12 [ 55 ]. The best-fit partitioning schemes and substitution models for subsequent phylogenetic analyses were predicted with ModelFinder [ 55 ] implemented in IQ-TREE release 2.1.4b [ 55 ]. We repeated the analyses using three datasets: amino acid sequences, the corresponding nucleotide (codon) sequences, and nucleotide sequences with the third codon position excluded. The mitochondrial sequences of 13 protein coding genes (PCGs) from 12 Cacopsylla species, eight psyllids from other families, two aphids and two white flies ( Table S6 ) were aligned using the MAFFT-L-INS-I algorithm [ 56 ] and concatenated using catsequences 1.3 ( https://zenodo.org/record/4409153#.YmJYT35Byot ). The optimal substitution model for each partition of the BI analyses was determined using the model-averaging approach implemented in OBAMA [ 53 ] with all substitution models enabled for the amino acid data, and the bModelTest packages [ 57 ] for the nucleotide data. The BI analyses of 100 million MCMC generations, with trees sampled every 1,000 generations, were run on the CIPRES platform [ 58 ] using BEAST [ 53 ]. Random starting trees were assigned to each partition. Divergence time estimation was conducted using the Most Recent Common Ancestor (MRCA) approach, incorporating various calibration points using BEAUTi [ 53 ] under an Optimized Relaxed Clock model. A time constraint derived from the posterior estimate of Li et al. , [ 59 ] was applied to the split between Psylloidea and its sister clade (Aleyrodoidea + Aphidoidea) set at 269 MYA and modeled as a normal prior distribution (mean = 269, S = 5.9). Outgroup taxa from Aleyrodoidea and Aphidoidea were represented by Aleurodicus dugesii + Bemisia tabaci and Aphis gossypii + Myzus persicae , respectively. To calibrate the Psylloidea crown node, we used the Eocene fossil Eogyropsylla paveloctogenarius (Aphalaridae; 41.3–47.8 MYA), the oldest known representative of Psylloidea s.str. [ 60 ]. The youngest age (41.3 MYA) was applied as a soft minimum using a log-normal prior (M = 3.67, S = 0.32, offset = 41.3), with Lanthanaphalara mira , an extant member of the same family, used to define the calibrated node. An additional calibration was applied to a tribal-level node within the family Liviidae (Paurocephalini), using the Early Miocene fossil Melanastera casca (20.4–13.8 MYA), a congener of the extant M. paucipunctata [ 61 ]. The youngest age (13.8 MYA) was treated as a soft minimum, implemented as a log-normal prior (M = 3.3, S = 0.39, offset = 13.8). To select the tree prior (Yule vs . birth–death models), we performed a marginal likelihood estimation (MLE) using Tracer [ 62 , 63 ] The marginal likelihood of both priors was calculated with 1,000 path steps, running chains for 1 million generations, and sampling log likelihood every 1,000 cycles. This analysis was conducted using BEAST v1.10.4 [ 64 ]. We calculated the Bayes factor (BF) as twice the natural logarithm (2lnBF) with respect to the highest-likelihood model, considering BF values > 10 as significantly favouring one model over another. The remaining prior parameters for both Yule and birth-death models were kept unchanged. The results were evaluated in Tracer v1.7.1 [ 62 ], using the effective sampling size (ESS > 200) criterion, and the first 30% of samples were discarded as burn-in. The tree files were then combined using LogCombiner v2.4.5, and the parameter values were annotated to the Maximum Clade Credibility (MCC) tree using TreeAnnotator v2.4.5. Nodal support was assessed by posterior probabilities (PP). ML and BI trees were visualized using FigTree v1.4.4 ( https://github.com/rambaut/figtree ). All figures were edited in GIMP 2.10.38. RESULTS Nuclear genomes of C. melanoneura and C. picta Based on raw sequencing reads, C. melanoneura has an estimated genome size of 438.67 Mb, while C. picta has a larger genome with 632.08 Mb ( Table S2 ). The other species with sufficient and public available raw reads data showed intermediate genome sizes: 528.10 Mb for C. jukyungi and 549.12 Mb for C. burckhardti . The final assembly of the C. melanoneura genome yielded a 688 Mb sequence, in a total of 678,097 contigs and 483,574 scaffolds with N50 values of 1.53 kb and 3.93 kb, respectively ( Table S2 ). The assembled genome size was thus inflated relative to a priori estimates of 438.7–473.8 Mb ( Table S2 ). The BUSCO completeness analysis revealed 32.9% of genes recovered as complete (of which 4.6% were duplicates), 31.4% as fragmented and 35.7% missed ( Fig. S1 ). As expected by using data from a pool of inthividuals, this genome appears to be highly heterozygous (2.51%) and repetitive (estimated at 57.28%) a considerable number of k -mers were missed in the heterozygous and homozygous regions, and several artificial duplications and repeats emerged due to the non-perfect collapsing of haplotypes. The assembled C. picta genome was larger, with 739.04 Mb and shows contig and scaffold N50s of 2.24 Kb and 6.3 Kb respectively ( Table S2; S5 ). The BUSCO completeness analysis indicated 30.1% of genes complete (of which 0.7% were duplicates), 33.1% fragmented (i.e. partial matches) and 36.8% missed. Because the genome was heterozygous (1.37%) and repetitive (estimated at 67.1%), there were some difficulties collapsing alleles in heterozygous regions and an excess of duplicated sequences in homozygous regions, although the effect on genome size inflation was weaker than in C. melanoneura . Although the genome size and repetitiveness seems to be porperties inherent to both genomes, the heterozygosity and efficiency in collapsing haplotypes can be explained by the larger number of individuals sequenced and simultaneously assembled in C. melanoneura. Mitochondrial genomes of C. melanoneura and C. picta The final assemblies of the C. melanoneura and C. picta mitogenome yielded 14,882 bp and 14,829 bp circular sequences, respectively, with 13 PCGs, 22 tRNAs and 2 rRNAs, as well as some control region and origin of L-strand replication elements (recovered in MITOS2 ) ( Fig. S2 ). The mitochondrial genome size of C. melanoneura presented here was almost identical to the one of specimens from Czech Republic (14,779 - 14,881 bp) [23], while the C. picta specimen of this study had a slightly larger mitochondrial genome compared to Czech individuals (14,801 and 14,802 bp) [23]. In general, variations in genome length among the investigated Cacopsylla species are consistently found in the control regions. The gene order and GC usage in both C. melanoneura and C. picta was identical to that observed across all known Cacopsylla species [22, 65–67] as well as most other psyllid species [22, 23]. Mitochondrial phylogeny and divergence time estimation of Cacopsylla We investigated the phylogenetic relationships of the newly sequenced samples of C. melanoneura and C. picta within the genus Cacopsylla . Our dataset comprised 13 PCGs obtained from whole-mitochondrial sequences across 12 Cacopsylla species and 12 outgroup taxa ( Table 1 and Table S6 ). To assess the robustness of our phylogenetic inference, we employed two analytical frameworks, Bayesian inference (BI) and maximum likelihood (ML), and analysed three data types: amino acid sequences (3,404 bp), nucleotide sequences including all codon positions (10,211 bp), and nucleotide sequences with the third codon position excluded, hereafter referred to as the nucleotide tree (6,809 bp). For the time-calibrated BI phylogenies, we assessed the fit of different tree priors by comparing marginal likelihood estimates (MLE) derived via stepping-stone sampling. The MLE values for the Yule and birth–death models were -106,096.04 and -106,088.62, respectively. The resulting Bayes Factor (BF = -7.42) favoured the birth–death model, which we therefore used in the final analyses. In general, the BI trees based on the amino acid dataset and the nucleotide dataset excluding the third codon position provided stronger support for both deep and internal branches suggesting that these values provide more reliable approximate estimates compared to the all-codon tree ( Fig. 1; S3, S4, S5 ). A notable difference in the all-codon tree, however, was the recovery of the outgroup family Liviidae as monophyletic, including Euphyllura phillyreae (Euphyllurinae) and three representatives of Liviinae ( Livia junci , Melanastera paucipunctata , Paurocephala sauteri ). In addition, the all-codon tree recovered a monophyletic grouping of C. coccinea and C. mali ( Fig. S3 ). The divergence time estimates from the amino acid tree were in general older compared to the nucleotide tree. In both trees, the crown diversification of Psylloidea was estimated to have occurred in the Paleocene–Eocene, at approximately 52.1 MYA (95% HPD: 45.7–70.2 MYA) based on the nucleotide dataset, or 62.3 MYA (95% HPD: 46.3–82.7 MYA) based on the amino acid dataset ( Fig. 1 ). These estimates are substantially older than the fossil prior minimum of 41.3 MYA. In the amino acid tree, the crown age of the genus Cacopsylla was estimated to be in the Early Miocene, at approximately ­­ (95% HPD: 10.8–27.5 MYA). In contrast, the nucleotide tree suggested a later divergence, placing the crown age of Cacopsylla in the Middle Miocene, at approximately 12.7 MYA (95% HPD: 9.7–16.0 MYA). Both the amino acid and nucleotide trees strongly supported (PP = 1.0) the presence of two major Cacopsylla clades: Clade I and Clade II (Fig. 1 and Fig. 2). All species within Cacopsylla Clade I (red branches) are associated with host plants from the family Rosaceae (Table 1; Fig. 2) . In all trees, C. melanoneura forms a clade with the plum psyllid C. pruni , with strong support in the amino acid tree (PP = 0.96) and in the nucleotide tree (PP = 1.0). The divergence between these two species was estimated at approximately 6.1–6.9 MYA (amino acid tree: 95% HPD: 2.4–11.8 MYA; nucleotide tree: 95% HPD: 3.9–8.3 MYA). This pair consistently clusters as a sister group to the pear psyllids C. burckhardti and C. pyrisuga , with strong support across both datasets (amino acid tree PP = 1.0; nucleotide tree PP = 0.99). In turn, C. picta forms a sister lineage to the above mentioned clades in both trees (PP = 1.0), with the split between C. picta and the most recent common ancestor (MRCA) of these species estimated at approximately 8.6–11.5 MYA, in the Late Miocene (amino acid tree: 95% HPD: 5.5–18.7 MYA; nucleotide tree: 95% HPD: 6.0–11.4 MYA). These results suggest independent evolutionary trajectories for the two main AP vector species in Europe, C. melanoneura and C. picta . The Cacopsylla species in Clade II (yellow branches) form a separate group, also including psyllids primarily associated with Rosaceae, along with single representatives from the families Lardizabalaceae and Rutaceae (Table 1) . The two European species associated with Pyrus , C. pyri and C. pyricola , cluster together with the Asian C. jukyungi , also associated with Pyrus , as sister species ( Fig. 2 ). These nodes exhibit strong support across all phylogenetic inference methods. In contrast, the phylogenetic relationships among C. citrisuga , C. coccinea , and C. mali remain unresolved and vary considerably among different phylogenetic reconstructions, likely due to incomplete taxon sampling. Interestingly, C. citrisuga and C. coccinea are Asian species that primarily reproduce on citrus and Akebia , respectively, while C. mali , found in Europe and North America, reproduces on apple trees. Notably, although it is the only species in this group associated with apple, C. mali is phylogenetically distant from C. melanoneura and C. picta and has never been recovered as their sister taxon. Another notable finding is that the divergence of the four pear-associated Cacopsylla species from the two clades, C. pyri / C. pyricola (Clade II) and C. burckhardti / C. pyrisuga (Clade I), represents the two most recent speciation events among the analysed taxa, estimated at around 4.7 MYA (amino acid tree: 95% HPD: 3.6–6.1 MYA; nucleotide tree: 95% HPD: 4.6–6.1 MYA). Similar to the results of the BI all-codon tree, the ML all-codon tree also recovered the family Liviidae as monophyletic, albeit with weak support ( Fig. S6 ). In contrast, both the BI and ML trees based on amino acid and third codon-excluded nucleotide datasets did not support the monophyly of Liviidae, while both major Cacopsylla clades ( Fig. S7 and S8 ) were strongly supported in all ML analyses (BS > 0.98), with internal branch support across Cacopsylla being generally lower than in the BI inferences. Repetitive element landscape diversity in Cacopsylla species TE composition was investigated using landscape plots that report the frequency and variability of the different TE families. In this analysis, sequence divergence of TE copies from their consensus sequence is shown on the X-axis, and their genomic proportion on the Y-axis. Peaks toward the left (low divergence) indicate more recent TE insertions, while those toward the right (high divergence) reflect older insertions. In C. mali and C. picta , prominent recent bursts of DNA and LINE elements support relatively recent TE bursts. In contrast, species like C. pruni and C. pyricola show older TEs expansions ( Fig. 2 ). The dominant TE classes vary across samples, indicating that different TE families drive genome changes in different species. ( Fig. 2 ). Specifically, in C. pyri , there is high recent TE activity, particularly in DNA and LINE elements, while in its sister species, C. pyricola , recent TE activity is lower and the TE landscape suggests older insertions. Cacopsylla jukyungi shows DNA and LTR elements dominant in recent bins, suggesting a likely recent expansion. In C. mali , there is a very pronounced peak of low divergent TE copies, supporting strong recent activity of DNA, LINE and RC elements. This is likely one of the highest recent TE activity profiles. In C. burckhardti , there is moderate to high recent TE activity, mostly driven by LTR, DNA and LINE elements. The sister species, C. pyrisuga , has a flatter and more right-shifted TE distribution, which suggests that TE activity has slowed down. C. melanoneura shows very active recent TE insertions, especially in DNA, LINE and LTR elements. The prominent peak at 0–2% divergence suggests a recent expansion event. In contrast, the sister species C. pruni shows low recent TE activity, with most insertions being older. The TE peak is broad and right-shifted, indicating a more stable TE landscape. Finally, C. picta has a sharp recent peak, especially in LINE and DNA elements, which is comparable to C. mali and C. melanoneura , making it one of the most dynamic genomes in this dataset. In summary, the species that show strong peaks at very low divergence values (0–2%), indicating ongoing or recent TE bursts, are C. mali from Clade II and all the species from Clade I, except C. pruni . The remaining species from Clade II and C. pruni show a broader peak indicating relatively low and moderate divergence values (~3–10%). TE content contributes to genome size in C. melanoneura and C. picta Given the substantial difference in estimated genome size between C. melanoneura and C. picta , we examined in more detail the contribution of repetitive elements to their genome size. Repetitive elements accounted for a moderate fraction of the assembled genome of both C. melanoneura , at 6.7%, and C. picta, at 12.2%. In both species, simple repeats were the most common element, followed by retroelements (LINEs, SINEs and LTRs), and DNA transposons ( Fig S9 ). This enrichment was consistent when considering total element count, length, and percentage of genome occupied. Focusing on comparative differences between species, simple repeats were more numerous and accounted for a larger proportion of the genome in C. picta compared to C. melanoneura ( Fig. S9 ). A similar pattern was observed for retroelements, which was driven by the relative abundances of LINE elements ( Fig. S9 ). Unclassified repetitive elements were also more common in C. picta . No notable differences in counts, length or percentage of genome occupied were found for SINE or LTR retroelements, sRNA or satellites, while DNA transposons were slightly more numerous in C. picta , although the percentage of genome occupied by these TEs was identical in the two species. Similar results were obtained using RepeatMasker with species-specific repeat libraries generated by RepeatModeler2 , where the main difference observed was in the proportion of masked bases, 52.95% in C. melanoneura and 60.86% in C. picta. Discrepancies between the two approaches were primarily due to differences in the proportion of unclassified repetitive elements in both species ( Fig. S9 ). Retroelements and DNA transposons in the draft genome of C. melanoneura and C. picta We further explored the genomic abundance in the draft genome assembly of both the retroelement and DNA transposon sub-classes. LINEs were the most abundant subclass in both C. melanoneura and C. picta , followed by SINEs and LTRs ( Fig. S9; S10 ). However, LINEs were more abundant in C. picta , while SINEs and LTRs were more common in C. melanoneura . Most of the difference in LINE content between the two species is associated to the much higher number of RTE/Bov-B elements in C. picta . On the other hand, the higher abundance of LTRs in C. melanoneura is mostly attributed to BEL/Pao and Gypsy/DIRS1 being more abundant in this species ( Fig. S10 ). We also note that Tcl-IS630-Pogo and hobo-activator were the most common DNA transposons in both C. melanoneura and C. picta , the latter hosting in particular almost twice as much hobo-activator than its related species ( Fig. S10 ). DISCUSSION Psyllids from the genus Cacopsylla are phytophagous insects with a wide range of host plants and include several vectors of plant pathogens. Although several Cacopsylla species are among the most important pests of various fruit trees, information on their evolutionary history, including their genetic and genomic makeup and evolution, remains scarce. We therefore conducted comparative genomic and phylogenetic analyses of Cacopsylla species, with a special focus on the two vectors of apple phytoplasma, ‘ Ca. P. mali’, C. melanoneura and C. picta . One specific aim was to assess whether their ability to transmit ‘ Ca. P. mali’ reflects a shared evolutionary origin or independent acquisition. For this purpose, we sequenced and assembled the nuclear and mitochondrial genomes of these species and, leveraging on publicly available data from other Cacopsylla and other psyllid species, reconstructed their phylogeny to trace their relationships with other vectors within Cacopsylla . The phylogenetic trees based on amino acid and nucleotide sequences of 12 psyllid species showed largely similar topologies, although divergence times were consistently estimated to be older when inferred from the amino acid data. In both the amino acid and nucleotide phylogenies, E. phillyreae from the subfamily Euphyllurinae was recovered as paraphyletic with respect to the other analysed Liviinae representatives. In contrast, the family Liviidae was recovered as monophyletic in the all-codon trees. A similar pattern was reported by Percy et al. [ 22 ], who found that Liviidae is not monophyletic in either their conserved codon or combined datasets. Nevertheless, our amino acid and nucleotide phylogenies recovered stronger support for both deep and internal clades compared to the all-codon trees, suggesting that codon composition and substitution saturation may affect the inferred topology. This contrasts with findings from Wang et al. 2023 [ 68 ], where excluding the third codon position from nuclear nucleotide datasets did not resolve compositional heterogeneity or correct the inferred topology. We estimated that Psylloidea started diversifying during the Paleocene–Eocene, approximately at 52.1 or 62.3 million years ago (MYA), with confidence intervals ranging from 46.3 to 82.7 Ma. These estimates are substantially younger than those reported in the large-scale Hemiptera phylogenies of Li et al. [ 59 ] that placed the crown diversification of Psylloidea at ~ 120 MYA during the Early Cretaceous, while [ 69 ] estimated it at ~ 220 MYA in the Late Triassic. This discrepancy may be explained by our inclusion of psyllid fossil calibrations, which constrained internal psyllid nodes, as well as our broader taxon sampling within Psylloidea. Our results are also consistent with paleontological evidence presented by [ 60 ] and Drohojowska et al. , [ 61 , 70 ], which suggested that, based on fossil evidence, extant psyllids could not have diversified earlier than the mid-Eocene Lutetian stage. Although our point estimates predate the Lutetian, the lower bound of the 95% HPD interval extends into this stage, making our divergence estimates more consistent with both paleontological and molecular evidence than previous studies. The crown divergence of the genus Cacopsylla was estimated to have occurred in the Early Miocene at 18.4 MYA (amino acid phylogeny) or in the Middle Miocene at 12.7 MYA (nucleotide phylogeny). These estimates are also in agreement with the fossil evidence of Cacopsylla dated to the Miocene [ 71 ]. Because the upper and lower bounds of the amino acid and nucleotide-based estimates also overlap, the approximate dating is reliable. Nevertheless, the amino-acid or nucleotide-based estimate is probably the closest estimate of the true time of divergence given its better alignment with the available fossil evidence. Our topologies across all trees consistently support a close relationship between C. melanoneura and C. pruni , the latter being the major vector of ‘ Ca. Phytoplasma prunorum’, the causal agent of European Stone Fruit Yellows [ 72 ]. Interestingly, both C. melanoneura and C. pruni may represent cryptic species complexes, comprising genetically distinct lineages that are morphologically nearly identical and lack diagnostic morphological characters to distinguish them. These lineages are generally associated with different host preferences and show considerable molecular divergence within each nominal species [ 20 , 24 , 73 , 74 ]. Crucially, across nearly all analyses, C. picta was consistently placed as a sister taxon to a clade comprising four other Rosaceae-associated species, C. melanoneura and C. pruni , as well as two pear psyllids C. burckhardti and C. pyrisuga . This pattern suggests that the two primary vectors of AP, C. melanoneura and C. picta , likely evolved their vector competence independently rather than inheriting it from a common ancestor. Furthermore, both AP vector species are even more distantly related to another apple psyllid C. mali , which has not been confirmed as a vector of ‘ Ca. P. mali’. Similarly, pear psyllids C. pyri and C. pyricola (Clade II), as well as C. burckhardti and C. pyrisuga (Clade I), are distributed across distinct phylogenetic clades, suggesting independent evolutionary origins of pear-associated lineages. While C. pyri and C. pyricola may have inherited vector competence from a common ancestor, the more distantly related C. pyrisuga likely acquired this trait through a separate evolutionary pathway. While Cacopsylla species do not cluster based on their capability to transmit phytoplasma or host preference, the two clades recovered in our study appear to differ in key biological traits. Cacopsylla Clade I consists of species which are strictly associated with Rosaceae. All species in this clade (( C. burckhardti + C. pyrisuga ) ( C. melanoneura + C. pruni ) C. picta )) are univoltine and migrate to conifers for overwintering (Table 1 ). This migratory behaviour may represent an adaptation to harsh environmental conditions and the seasonal unavailability of suitable phloem sources on deciduous hosts, serving as an overwintering strategy of many psyllid species in northern temperate regions [ 19 ]. In contrast, most species assigned to Clade II ( C. pyri , C. pyricola , C. jukyungi , C. citrisuga , C. mali ) overwinter on their host plants without migrating to conifers. Although the genetic basis and evolution of the migratory behaviour in psyllids remain unclear, our data suggest a potential correlation between phylogenetic structure and ecological traits. Moreover, all species belonging to Clade I are restricted to the family Rosaceae, whereas several species from Clade II are associated with other plant families, i.e. C. citrisuga develops on Rutaceae and C. coccinea on Lardizabalaceae. Additionally, Clade I contains only univoltine species, while various species belonging to Clade II are polyvoltine. This pattern is consistent with ecological strategies observed in psyllids from tropical and southern temperate regions, where the psyllid species richness is the highest and continuous host availability facilitates multiple generations per year [ 1 ]. Taken together, these observations suggest that life history traits, such as voltinism and overwintering strategy, might be linked to the phylogenetic structure within Cacopsylla , and may help trace the evolutionary transitions in host association and overwintering behaviour. However, broader taxon sampling and mitogenome sequencing across the genus are needed to confirm this hypothesis. We also investigated the repeatome to better understand the genomic processes shaping evolution in the Cacopsylla genus. We found that TEs dynamics vary widely across species, with lineage-specific patterns of accumulation and turnover likely contributing to genome evolution and adaptation. Species such as C. mali , C. melanoneura , C. picta and C. pyri show evidence of recent TE bursts, particularly of DNA transposons and LINE elements, suggesting ongoing genome re-modelling. In contrast, C. pruni , C. pyricola , and C. pyrisuga exhibit older and likely more stable TE landscapes. According to our phylogenetic analyses, Clade I and Clade II are similar in age, although Clade I may be slightly younger. Moreover, the two clades differ in life history traits that may influence TE activity (Table 1 ). Clade I species inhabit less stable environments and are univoltine and migratory, with seasonal movement to conifers for overwintering. In contrast, most Clade II species are mostly polyvoltine, with several of them occupying more stable environments (without seasonal changes), which may reduce the stressful conditions that promote TE activity [ 75 – 77 ]. Environment aside, polyvoltine species may accumulate TEs faster due to shorter generation times [ 78 ], while univoltine species may experience slower TE accumulation and stronger selection against harmful insertions and more stable epigenetic silencing [ 79 ]. Additionally, the presence of seasonal migration in some species may also lead to periods of genomic “silence” potentially affecting TE activity compared to species that undergo continuous generations on their host plants. For example, studies have shown that in some insect groups, TEs are differentially expressed during diapause versus active developmental stages. In the bee species Megachile rotundata and Osmia lignaria , TE expression varied significantly during diapause and in response to temperature stress, suggesting that environmental conditions and life stage transitions can modulate TE activity [ 80 ]. Similarly, in Drosophila montana , a cold-adapted fly species, specific TEs were found to be upregulated during diapause, implying a role in regulating genes associated with diapause and cold tolerance [ 81 ]. We further compared the TEs in the shallow genome assemblies of C. melanoneura and C. picta . The primary finding was that simple repeats, LINE-class retrotransposons, and unclassified repeats were approximately twice as abundant in the genome of C. picta compared to C. melanoneura . The analysis of retroelements and DNA transposons revealed that these classes significantly contributed to the genome size differences between the two species. Retroelements such as RTE/Bov-B subclass were especially overrepresented in C. picta . In contrast, C. melanoneura had a greater proportion of non-assigned LINEs, although this did not affect the overall retroelement composition. Overall, while the composition of element types was broadly conserved, C. picta consistently exhibited a higher abundance of most repeat types. Transposable elements may contribute to genomic variability and regulatory plasticity that may facilitate resistance to chemical contaminants such as pesticides, primarily through gene upregulation, loss of function, and alternative splicing. Among TE types, LINEs have been shown in Drosophila melanogaster to alter the splicing and regulation of genes involved in insecticide resistance, conferring resistance to DDT and other insecticides [ 82 , 83 ]. Similarly, in Helicoverpa armigera , several TE families, including LINEs, have been identified near detoxification genes, supporting the association between TE activity and gene regulation [ 84 , 85 ]. Similarly, in the whitefly Bemisia tabaci , multiple TE insertions were reported, including six linked to known insecticide resistance genes, suggesting a role in both resistance and genome evolution [ 86 ]. In the aphid Myzus persicae , TEs contribute to resistance by disrupting a dominant susceptibility allele, enabling the expression of a recessive resistance allele [ 87 ]. These studies demonstrate how TEs can drive adaptation under environmental and genetic stressors highlighting a potential role of TEs in the adaptation of agriculturally important pest species such as C. picta and C. melanoneura on pesticides. Conclusions Cacopsylla is a diverse genus of phytophagous insects which includes several important vectors of phytoplasma, such as Apple Proliferation (AP), a serious threat to agriculture. Using a time-calibrated phylogenetic approach, we estimated the crown divergence of this genus between the Early Miocene (~ 18.4 MYA) and the Middle Miocene (~ 12.7 MYA). Within Cacopsylla , two major clades were identified, largely differentiated by their overwintering strategies and voltinism, ecological traits that might reflect adaptations to environmental changes over the past 10 million years. Interestingly, although C. melanoneura and C. picta are the only Cacopsylla species known to be vector of ‘ Ca. Phytoplasma mali’ and both develop on apple trees, we found them to be phylogenetically distantly related. The divergence of C. picta from the most recent common ancestor of C. melanoneura was estimated to have occurred between 8.6 and 11.5 MYA, during the Late Miocene. These findings reinforce the hypothesis that these two species vectoring AP phytoplasma vectoring species followed independent evolutionary trajectories and likely acquired the ability to transmit ‘ Ca. P. mali’ independently. Furthermore, C. mali , another apple-associated psyllid that is not a confirmed vector of ‘ Ca. P. mali’, was found to belong to distinct clade and was never recovered as a sister taxon to either C. melanoneura or C. picta . Based on the current results, it is not possible to clearly identify the ancestral clade, although Clade I appears relatively younger than Clade II. Finally, our analyses of transposable elements suggest that life history traits, such as host preference, overwintering strategy and voltinism, may influence recent genome rearrangements. These patterns are more pronounced in the representatives from the generally univoltine and overwintering Clade I, supporting the idea that some repetitive elements may play functional roles in seasonal migration, ecological adaptation, pathogen transmission and potentially in the evolution of pesticide resistance. Future studies are needed to clarify how transposable element dynamics, and the expansion of repetitive sequences shape genomic plasticity and resilience in these agriculturally important pests. Abbreviations AP – Apple Proliferation BF – Bayes Factor BI – Bayesian Inference BS – Bootstrap COI – Cytochrome c Oxidase Subunit I ESS – Effective Sampling Size HPD – Highest Posterior Density LINEs – Long Interspersed Nuclear Elements LTRs – Long Terminal Repeats MCC – Maximum Clade Credibility ML – Maximum Likelihood MLE – Marginal Likelihood Estimation MRCA – Most Recent Common Ancestor MYA – Million Years Ago PCGs – Protein-Coding Genes PP – Posterior Probabilities RC- Rolling Circle Transposon SINEs – Short Interspersed Nuclear Elements TEs – Transposable Elements Declarations ETHICS APPROVAL AND CONSENT TO PARTICIPATE Not applicable CONSENT FOR PUBLICATION Not applicable AVAILABILITY OF DATA AND MATERIALS NCBI BIO PROJECT: PRJNA1312285 COMPETING INTERESTS The authors declare that they have no competing interests FUNDING This work was supported by a joint project funded by the province of Bolzano-Bozen and the Austrian Science Fund FWF (project I4639-B) to Hannes Schuler and Christian Stauffer, by a joint project of the province of Bolzano-Bozen and the Luxembourg National Research Fund FNR to Hannes Schuler and by a cofounded Fondazione Edmund Mach/APOT (project SCOPAZZI) to Omar Rota Stabelli, Guanfranco Anfora and Lino Ometto ACKNOWLEDGMENTS We are very grateful to Daniel Burckhardt for his critical comments and suggestions. AUTHORS’ CONTRIBUTIONS LR, LŠS, EK, JMH, GA, CS, LO, ORS, and HS conceived and designed the study. HS, CS, GA and ORS secured the funding. EC and LO coordinated the sequencing. FC and TA assembled the nuclear genomes. JMH assembled the mitochondrial genomes with input from NZ. LŠS performed the phylogenetic analyses with input from ORS and JMH. LR and LO performed the transposable elements analyses. LR, LŠS, EC and JMH wrote the paper with contribution from all authors. All authors discussed the results and approved the article. References Burckhardt D, Ouvrard D, Percy DM. An updated classification of the jumping plant-lice (Hemiptera: Psylloidea) integrating molecular and morphological evidence. Eur J Taxon. 2021;736:137–82. https://doi.org/10.5852/ejt.2021.736.1257. Li D, Zhang C, Tong Z, Su D, Zhang G, Zhang S, et al. Transcriptome response comparison between vector and non-vector aphids after feeding on virus-infected wheat plants. BMC Genomics. 2020;21:638. https://doi.org/10.1186/s12864-020-07057-0. Jarausch B, Jarausch W. Psyllid Vectors and their Control. In: Weintraub PG, Jones P, editors. Phytoplasmas: Genomes, Plant Hosts and Vectors. Wallingford, UK: CAB International; 2010. Rao GP, Bertaccini A, Fiore N, Liefting LW. Phytoplasmas: Plant Pathogenic Bacteria - I: Characterisation and Epidemiology of Phytoplasma - Associated Diseases. 2018. Seemüller E, Schneider B. “Candidatus Phytoplasma mali”, “ Candidatus Phytoplasma pyri” and “ Candidatus Phytoplasma prunorum”, the causal agents of apple proliferation, pear decline and European stone fruit yellows, respectively. Int J Syst Evol Microbiol. 2004;54 Pt 4:1217–26. https://doi.org/10.1099/ijs.0.02823-0. Janik K, Barthel D, Oppedisano T, Anfora G. Apple Proliferation: A Joint Review. 2020. Seemüller E, Carraro L, Jarausch W, Schneider B. CHAPTER 14: Apple Proliferation Phytoplasma. In: Hadidi A, Barba M, Candresse T, Jelkmann W, editors. Virus and Virus-Like Diseases of Pome and Stone Fruits. APS Publications; 2011. p. 67–73. https://doi.org/10.1094/9780890545010.014. Tedeschi R, Jarausch B, Delic D, Weintraub PG. Actual distribution of fruit tree and grapevine phytoplasma diseases and their vectors in Europe and neighboring regions. Phytopathogenic Mollicutes. 2013;3:3–4. Bertaccini A. COST Action FA0807 Phytoplasmas and phytoplasma disease management: how to reduce their economic impact. 2014. Fischnaller S, Parth M, Messner M, al et. Occurrence of different Cacopsylla species in apple orchards in South Tyrol (Italy) and detection of apple proliferation phytoplasma in Cacopsylla melanoneura and Cacopsylla picta . Cicadina. 2017;17:37–51. Jarausch B, Fuchs A, Schwind N, Krczal G, Jarausch W. Cacopsylla picta as most important vector for “ Candidatus Phytoplasma mali” in Germany and neighbouring regions. Bull Insectology. 2007;60:189–90. Oppedisano T, Panassiti B, Pedrazzoli F, Mittelberger C, Bianchedi PL, Angeli G, et al. Importance of psyllids’ life stage in the epidemiology of apple proliferation phytoplasma. J Pest Sci (2004). 2020;93:49–61. https://doi.org/10.1007/s10340-019-01130-8. Tedeschi R, Baldessari M, Mazzoni V, Trona F, Angeli G. Population dynamics of Cacopsylla melanoneura (Hemiptera: Psyllidae) in northeast Italy and its role in the apple proliferation epidemiology in apple orchards. J Econ Entomol. 2012;105:322–8. https://doi.org/10.1603/ec11237. Candian V, Monti M, Tedeschi R. Temporal dynamics of “Ca. Phytoplasma mali” load in the insect vector Cacopsylla melanoneura . Insects. 2020;11. https://doi.org/10.3390/insects11090592. Corretto E, Trenti M, Starhova Serbina L, Howie JM, Dittmer J, Kerschbamer C, et al. Multiple factors driving the acquisition efficiency of apple proliferation phytoplasma in Cacopsylla melanoneura . J Pest Sci (2004). 2024;97:1299–314. https://doi.org/10.1007/s10340-023-01699-1. Schuler H, Dittmer J, Borruso L, Galli J, Fischnaller S, Anfora G, et al. Investigating the microbial community of Cacopsylla spp. as potential factor in vector competence of phytoplasma. Environ Microbiol. 2022;24:4771–86. https://doi.org/10.1111/1462-2920.16138. Ouvrard D, Chalise P, Percy DM. Host-plant leaps versus host-plant shuffle: a global survey reveals contrasting patterns in an oligophagous insect group (Hemiptera, Psylloidea). Syst Biodivers. 2015;13:434–54. https://doi.org/10.1080/14772000.2015.1046969. Burckhardt D, Ouvrard D, Queiroz D, Percy D. Psyllid Host-Plants (Hemiptera: Psylloidea): Resolving a Semantic Problem. Florida Entomologist. 2014;97:242–6. https://doi.org/10.1653/024.097.0132. Hodkinson ID. Life cycle variation and adaptation in jumping plant lice (Insecta: Hemiptera: Psylloidea): a global synthesis. J Nat Hist. 2009;43:65–179. https://doi.org/10.1080/00222930802354167. Malagnini V, Pedrazzoli F, Papetti C, Cainelli C, Zasso R, Gualandri V, et al. Ecological and genetic differences between Cacopsylla melanoneura (Hemiptera, Psyllidae) populations reveal species host plant preference. PLoS One. 2013;8:e69663–e69663. https://doi.org/10.1371/journal.pone.0069663. Oettl S, Schlink K. Molecular identification of two vector species, Cacopsylla melanoneura and Cacopsylla picta (Hemiptera: Psyllidae), of Apple Proliferation disease and further common psyllids of Northern Italy. J Econ Entomol. 2015;108:2174–83. https://doi.org/10.1093/jee/tov204. Percy DM, Crampton‐Platt A, Sveinsson S, Lemmon AR, Lemmon EM, Ouvrard D, et al. Resolving the psyllid tree of life: phylogenomic analyses of the superfamily Psylloidea (Hemiptera). Syst Entomol. 2018;43:762–76. https://doi.org/10.1111/syen.12302. Šafářová D, Zrníková E, Holušová K, Ouředníčková J, Starý M, Navrátil M. Molecular Characterization of Mitogenome of Cacopsylla picta and Cacopsylla melanoneura , Two Vector Species of ‘Candidatus Phytoplasma mali.’ Agronomy. 2023;13:2210. https://doi.org/10.3390/agronomy13092210. Corretto E, Štarhová Serbina L, Dittmer J, Michalik A, Schuler H. Evolutionary dynamics of obligate endosymbiosis in the psyllid genus Cacopsylla . Commun Biol. 2025. Bourque G, Burns KH, Gehring M, Gorbunova V, Seluanov A, Hammell M, et al. Ten things you should know about transposable elements. Genome Biol. 2018;19:199. https://doi.org/10.1186/s13059-018-1577-z. Wang X, Fang X, Yang P, Jiang X, Jiang F, Zhao D, et al. The locust genome provides insight into swarm formation and long-distance flight. Nat Commun. 2014;5:2957. https://doi.org/10.1038/ncomms3957. Makałowski W, Gotea V, Pande A, Makałowska I. Transposable Elements: classification, identification, and their use as a tool for comparative genomics. 2019. p. 177–207. https://doi.org/10.1007/978-1-4939-9074-0_6. Petersen M, Armisén D, Gibbs RA, Hering L, Khila A, Mayer G, et al. Diversity and evolution of the transposable element repertoire in arthropods with particular reference to insects. BMC Ecol Evol. 2019;19:11. https://doi.org/10.1186/s12862-018-1324-9. Marcais G, Kingsford C. A fast, lock-free approach for efficient parallel counting of occurrences of k-mers. Bioinformatics. 2011;27:764–70. https://doi.org/10.1093/bioinformatics/btr011. Vurture GW, Sedlazeck FJ, Nattestad M, Underwood CJ, Fang H, Gurtowski J, et al. GenomeScope: fast reference-free genome profiling from short reads. Bioinformatics. 2017;33:2202–4. https://doi.org/10.1093/bioinformatics/btx153. Simpson JT. Exploring genome characteristics and sequence quality without a reference. Bioinformatics. 2014;30:1228–35. https://doi.org/10.1093/bioinformatics/btu023. Martin M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J. 2011;17. https://doi.org/10.14806/ej.17.1.200. Magoc T, Salzberg SL. FLASH: fast length adjustment of short reads to improve genome assemblies. Bioinformatics. 2011;27:2957–63. https://doi.org/10.1093/bioinformatics/btr507. Marco-Sola S, Sammeth M, Guigo R, Ribeca P. The GEM mapper: fast, accurate and versatile alignment by filtration. Nat Methods. 2012. https://doi.org/10.1038/nmeth.2221. Wood D, Salzberg S. Kraken: ultrafast metagenomic sequence classification using exact alignments. Genome Biol. 2014;15:R46–R46. Weisenfeld NI, Kumar V, Shah P, Church DM, Jaffe DB. Direct determination of diploid genome sequences. Genome Res. 2017;27:757–67. https://doi.org/10.1101/gr.214874.116. Weisenfeld NI, Yin S, Sharpe T, Lau B, Hegarty R, Holmes L, et al. Comprehensive variation discovery in single human genomes. Nat Genet. 2014;46:1350–5. https://doi.org/10.1038/ng.3121. Sahlin K, Vezzi F, Nystedt B, Lundeberg J, Arvestad L. BESST - Efficient scaffolding of large fragmented assemblies. BMC Bioinformatics. 2014;15:281. https://doi.org/10.1186/1471-2105-15-281. Cruz F, Julca I, Gomez-Garrido J, Loska D, Marcet-Houben M, Cano E, et al. Genome sequence of the olive tree, Olea europaea . Gigascience. 2016;5:29. https://doi.org/10.1186/s13742-016-0134-5. Puerma E, Orengo DJ, Cruz F, Gomez-Garrido J, Librado P, Salguero D, et al. The high-quality genome sequence of the oceanic island endemic species Drosophila guanche reveals signals of adaptive evolution in genes related to flight and genome stability. Genome Biol Evol. 2018;10:1956–69. https://doi.org/10.1093/gbe/evy135. Pryszcz LP, Gabaldon T. Redundans: an assembly pipeline for highly heterozygous genomes. Nucleic Acids Res. 2016;44. https://doi.org/10.1093/nar/gkw294. Mapleson D, Garcia Accinelli G, Kettleborough G, Wright J, Clavijo BJ. KAT: a K-mer analysis toolkit to quality control NGS datasets and genome assemblies. Bioinformatics. 2017;33:574–6. https://doi.org/10.1093/bioinformatics/btw663. Simão FA, Waterhouse RM, Ioannidis P, Kriventseva E V, Zdobnov EM. BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs. Bioinformatics. 2015;31. https://doi.org/10.1093/bioinformatics/btv351. Smit AFA, Hubley R, Green P. RepeatMasker Open. Flynn JM, Hubley R, Goubert C, Rosen J, Clark AG, Feschotte C, et al. RepeatModeler2 for automated genomic discovery of transposable element families. Proceedings of the National Academy of Sciences. 2020;117:9451–7. https://doi.org/10.1073/pnas.1921046117. Novák P, Neumann P, Macas J. Graph-based clustering and characterization of repetitive sequences in next-generation sequencing data. BMC Bioinformatics. 2010;11:378. https://doi.org/10.1186/1471-2105-11-378. Novák P, Neumann P, Pech J, Steinhaisl J, Macas J. RepeatExplorer: a Galaxy-based web server for genome-wide characterization of eukaryotic repetitive elements from next-generation sequence reads. Bioinformatics. 2013;29:792–3. https://doi.org/10.1093/bioinformatics/btt054. Goubert C. Assembly-Free Detection and Quantification of Transposable Elements with dnaPipeTE. 2023. p. 25–43. https://doi.org/10.1007/978-1-0716-2883-6_2. Meng G, Li Y, Yang C, Liu S. MitoZ: a toolkit for animal mitochondrial genome assembly, annotation and visualization. Nucleic Acids Res. 2019;47:e63–e63. https://doi.org/10.1093/nar/gkz173. Kurtzer GM, Sochat V, Bauer MW. Singularity: Scientific containers for mobility of compute. PLoS One. 2017;12:e0177459–e0177459. https://doi.org/10.1371/journal.pone.0177459. Bernt M, Donath A, Juhling F, Externbrink F, Florentz C, Fritzsch G, et al. MITOS: improved de novo metazoan mitochondrial genome annotation. Mol Phylogenet Evol. 2013;69:313–9. https://doi.org/10.1016/j.ympev.2012.08.023. Donath A, Juhling F, Al-Arab M, Bernhart SH, Reinhardt F, Stadler PF, et al. Improved annotation of protein-coding genes boundaries in metazoan mitochondrial genomes. Nucleic Acids Res. 2019;47:10543–52. https://doi.org/10.1093/nar/gkz833. Bouckaert R, Vaughan TG, Barido-Sottani J, Duchene S, Fourment M, Gavryushkina A, et al. BEAST 2.5: An advanced software platform for Bayesian evolutionary analysis. PLoS Comput Biol. 2019;15:e1006650–e1006650. https://doi.org/10.1371/journal.pcbi.1006650. Drummond AJ, Rambaut A. BEAST: Bayesian evolutionary analysis by sampling trees. BMC Evol Biol. 2007;7:214. https://doi.org/10.1186/1471-2148-7-214. Minh BQ, Schmidt HA, Chernomor O, Schrempf D, Woodhams MD, von Haeseler A, et al. IQ-TREE 2: new models and efficient methods for phylogenetic inference in the genomic era. Mol Biol Evol. 2020;37:1530–4. https://doi.org/10.1093/molbev/msaa015. Katoh K, Standley DM. MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability. Mol Biol Evol. 2013;30:772–80. https://doi.org/10.1093/molbev/mst010. Bouckaert RR, Drummond AJ. bModelTest: Bayesian phylogenetic site model averaging and model comparison. BMC Evol Biol. 2017;17:42. https://doi.org/10.1186/s12862-017-0890-6. Miller MA, Schwartz T, Hoover P, Yoshimoto K, Sivagnanam S, Majumdar A. The CIPRES workbench. In: Proceedings of the 2015 XSEDE Conference on Scientific Advancements Enabled by Enhanced Cyberinfrastructure - XSEDE ’15. New York, New York, USA: ACM Press; 2015. p. 1–8. https://doi.org/10.1145/2792745.2792784. Li H, Leavengood Jr. JM, Chapman EG, Burkhardt D, Song F, Jiang P, et al. Mitochondrial phylogenomics of Hemiptera reveals adaptive innovations driving the diversification of true bugs. Proc Biol Sci. 2017;284. https://doi.org/10.1098/rspb.2017.1223. Ouvrard DBDGD. The oldest jumping plant-louse (Insecta: Hemiptera: Sternorrhyncha) with comments on the classification and nomenclature of the Palaeogene Psylloidea. Acta Musei Moraviae, Scientiae biologicae (Brno). 2013;98:21–33. Burckhardt D, Drohojowska J, Štarhová Serbina L, Malenovský I. First record of jumping plant lice of the family Liviidae (Hemiptera, Sternorrhyncha, Psylloidea) from Dominican amber. Neues Jahrbuch für Geologie und Paläontologie - Abhandlungen Band . 2024;:215–27. Baele G, Lemey P, Bedford T, Rambaut A, Suchard MA, Alekseyenko A V. improving the accuracy of demographic and molecular clock model comparison while accommodating phylogenetic uncertainty. Mol Biol Evol. 2012;29:2157–67. https://doi.org/10.1093/molbev/mss084. Xie W, Lewis PO, Fan Y, Kuo L, Chen M-H. improving marginal likelihood estimation for bayesian phylogenetic model selection. Syst Biol. 2011;60:150–60. https://doi.org/10.1093/sysbio/syq085. Suchard MA, Lemey P, Baele G, Ayres DL, Drummond AJ, Rambaut A. Bayesian phylogenetic and phylodynamic data integration using BEAST 1.10. Virus Evol. 2018;4. https://doi.org/10.1093/ve/vey016. Jo E, Cho G. The complete mitochondrial genome of Cacopsylla burckhardti (Hemiptera, Psylloidea, Psyllidae). Biodivers Data J. 2022;10:e85094–e85094. https://doi.org/10.3897/BDJ.10.e85094. Que S, Yu L, Xin T, Zou Z, Hu L, Xia B. Complete mitochondrial genome of Cacopsylla coccinae (Hemiptera: Psyllidae). Mitochondrial DNA A DNA Mapp Seq Anal. 2016;27:3169–70. https://doi.org/10.3109/19401736.2015.1007319. Wang Y, Cen Y, He Y, Wu Y, Huang S, Lu J. The first complete mitochondrial genome sequence of Cacopsylla citrisuga (Yang & Li), a new insect vector of Huanglongbing in Yunnan Province, China. Mitochondrial DNA B Resour. 2021;6:575–7. https://doi.org/10.1080/23802359.2021.1875908. Wang W, Dong Z, Du Z, Wu P. Genome-scale approach to reconstructing the phylogenetic tree of psyllids (superfamily Psylloidea) with account of systematic bias. Mol Phylogenet Evol. 2023;189:107924. https://doi.org/10.1016/j.ympev.2023.107924. Johnson KP, Dietrich CH, Friedrich F, Beutel RG, Wipfler B, Peters RS, et al. Phylogenomics and the evolution of hemipteroid insects. 2018;115. https://doi.org/10.5061/dryad.t4f4g85. Drohojowska J, Węgierek P, Solórzano Kraemer MM. First Psylloidea (Hemiptera: Sternorrhyncha) in Miocene Mexican amber. Palaontol Z. 2016;90:185–8. https://doi.org/10.1007/s12542-016-0290-z. Zhang T, Luo X, Yao Y, Ren D. A new fossil psyllid, Cacopsylla trigona sp. nov. (Hemiptera: Psylloidea: Psyllidae), from the Miocene of China. Palaeoentomology. 2019;2:413–7. https://doi.org/10.11646/palaeoentomology.2.5.2. Steffek R, Follak S, Sauvion N, Labonne G, MacLeod A. Distribution of ‘ Candidatus Phytoplasma prunorum’ and its vector Cacopsylla pruni in European fruit‐growing areas: a review. EPPO Bulletin. 2012;42:191–202. https://doi.org/10.1111/epp.2567. Peccoud J, Labonne G, Sauvion N. Molecular Test to Assign Individuals within the Cacopsylla pruni Complex. PLoS One. 2013;8:e72454. https://doi.org/10.1371/journal.pone.0072454. Sauvion N, Peccoud J, Meynard C, Ouvrard D. Occurrence data for the two cryptic species of Cacopsylla pruni (Hemiptera: Psylloidea). Biodivers Data J. 2021;9. https://doi.org/10.3897/BDJ.9.e68860. Milyaeva PA, Kukushkina I V., Kim AI, Nefedova LN. Stress Induced Activation of LTR Retrotransposons in the Drosophila melanogaster Genome. Life. 2023;13:2272. https://doi.org/10.3390/life13122272. de Oliveira DS, Rosa MT, Vieira C, Loreto ELS. Oxidative and radiation stress induces transposable element transcription in Drosophila melanogaster . J Evol Biol. 2021;34:628–38. https://doi.org/10.1111/jeb.13762. Kneuss E, Munafò M, Eastwood EL, Deumer U-S, Preall JB, Hannon GJ, et al. Specialization of the Drosophila nuclear export family protein Nxf3 for piRNA precursor export. Genes Dev. 2019;33:1208–20. https://doi.org/10.1101/gad.328690.119. Lawlor MA, Ellison CE. Evolutionary dynamics between transposable elements and their host genomes: mechanisms of suppression and escape. Curr Opin Genet Dev. 2023;82:102092. https://doi.org/10.1016/j.gde.2023.102092. Slotkin RK, Martienssen R. Transposable elements and the epigenetic regulation of the genome. Nat Rev Genet. 2007;8:272–85. https://doi.org/10.1038/nrg2072. Signor S, Yocum G, Bowsher J. Life stage and the environment as effectors of transposable element activity in two bee species. J Insect Physiol. 2022;137:104361. https://doi.org/10.1016/j.jinsphys.2022.104361. Tahami MS, Vargas-Chavez C, Poikela N, Coronado-Zamora M, González J, Kankare M. Transposable elements in Drosophila montana from harsh cold environments. Mob DNA. 2024;15:18. https://doi.org/10.1186/s13100-024-00328-7. Schmidt JM, Good RT, Appleton B, Sherrard J, Raymant GC, Bogwitz MR, et al. Copy number variation and transposable elements feature in recent, ongoing adaptation at the Cyp6g1 locus. PLoS Genet. 2010;6:e1000998. https://doi.org/10.1371/journal.pgen.1000998. Daborn PJ, Yen JL, Bogwitz MR, Le Goff G, Feil E, Jeffers S, et al. A Single P450 Allele Associated with Insecticide Resistance in Drosophila . Science (1979). 2002;297:2253–6. https://doi.org/10.1126/science.1074170. Klai K, Chénais B, Zidi M, Djebbi S, Caruso A, Denis F, et al. Screening of Helicoverpa armigera mobilome revealed transposable element insertions in insecticide resistance genes. Insects. 2020;11:879. https://doi.org/10.3390/insects11120879. Rahman M-M, Omoto C, Kim J. Genome-wide exploration of long non-coding RNAs of Helicoverpa armigera in response to pyrethroid insecticide resistance. Insects. 2024;15:146. https://doi.org/10.3390/insects15030146. Zidi M, Klai K, Confais J, Chénais B, Caruso A, Denis F, et al. Genome-wide screening of transposable elements in the whitefly, Bemisia tabaci (Hemiptera: Aleyrodidae), revealed insertions with potential insecticide resistance implications. Insects. 2022;13:396. https://doi.org/10.3390/insects13050396. Panini M, Chiesa O, Troczka BJ, Mallott M, Manicardi GC, Cassanelli S, et al. Transposon-mediated insertional mutagenesis unmasks recessive insecticide resistance in the aphid Myzus persicae . Proceedings of the National Academy of Sciences. 2021;118. https://doi.org/10.1073/pnas.2100559118. Table Table 1 is available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files SupportinginformationV6.docx SUPPLEMENTARY FIGURES Figure S1. BUSCO assessment results. Number of complete, fragmented and missing BUSCO orthologous genes in the C. melanoneura (Cmel) and C. picta (Cpic) assembled genomes. The analyis ias based on the odb12 databases for Arthrpopoda, Insecta and Hemiptera. Figure S2. Circular representations of complete Cacopsylla melanoneura and C. picta mitochondrial genomes. The position and orientation of the 13 PCG genes (green), 22 tRNA genes (red), 2 rRNA genes (orange), control region (blue) and origin of L-strand replication (pink) are shown. The inner circle displays GC bias and the outer circle displays coverage depth of the Illumina reads used mitochondrial genome assembly. Figure S3. Bayesian tree with nucleotides 123 Figure S4. Bayesian tree with amino acids Figure S5. Maximum likelihoods with all nucleotides Figure S6. Maximum likelihoods tree without 3d codon positions Figure S7. Maximum likelihoods tree with amino acids Figure S8. Maximum likelihoods tree with nucleotide 1 and 2. Figure S9 Bar plots showing the count frequency (a,b) and percentage of genome occupied by various classes of genomically interspersed repeats (c,d), including retroelements (SINE, LINE, LTR; a,c), DNA transposons, unclassified repetitive elements, sRNAs and satellites, and simple repeats, in Cacopsylla picta (dotted bars) and in C. melanoneura (solid bars (b,d). Figure S10. Bar plots showing count frequencies of specific genomically interspersed repetitive elements in Cacopsylla picta (dotted bars) and C. melanoneura (solid bars). Colours correspond to repetitive element classes. Retroelements of class SINE are in brown, of class LINE in ochre orange, and class LTR in salmon. DNA transposons are in slate grey. Table1V6.docx Cite Share Download PDF Status: Published Journal Publication published 19 Mar, 2026 Read the published version in BMC Genomics → Version 1 posted Editorial decision: Revision requested 09 Oct, 2025 Reviews received at journal 07 Oct, 2025 Reviews received at journal 06 Oct, 2025 Reviewers agreed at journal 24 Sep, 2025 Reviewers agreed at journal 20 Sep, 2025 Reviewers agreed at journal 13 Sep, 2025 Reviewers invited by journal 12 Sep, 2025 Editor assigned by journal 03 Sep, 2025 Submission checks completed at journal 03 Sep, 2025 First submitted to journal 02 Sep, 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7518317","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":510277812,"identity":"34fee438-287c-4a27-9b2e-480e491a5309","order_by":0,"name":"Lapo Ragionieri","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/klEQVRIie3RMWsCMRTA8SeFuARvfV30KzwRxOn8Kjky3KKdC4XrQeFusZ31W/gBHF5w6NI6H7SDLjeVYrcbOvQ8K4iQzIXmD4HwyI8EAuDz/cE6p42oFwNgF6CV1Xu0EnFJBidiNeJyEKW/Qztpv5ptaxWGT+1Hw1+rUbx8e8h2FYwSK5E3mqDUOpMbZeYlTpfvJid0PmwyROArLXBCa8k1KaIMyUWCjwO5P5JvxpgORLkINresw4YAo2oIO8mnJsXPSsgXMjPG/qKI8n5KeJ1aSBBMzXbPd+NePhvsK056nSIud9VtEthuAZAA6vgd55EdNKRu7Dri8/l8/7wfYbhRQFX/OMYAAAAASUVORK5CYII=","orcid":"","institution":"Free University of Bozen-Bolzano, Italy","correspondingAuthor":true,"prefix":"","firstName":"Lapo","middleName":"","lastName":"Ragionieri","suffix":""},{"id":510277813,"identity":"d6095db8-997d-48d3-9b61-44f9da6a7159","order_by":1,"name":"Liliya Štarhová Serbina","email":"","orcid":"","institution":"Leibniz Institute for Evolution and Biodiversity Science, Museum für Naturkunde","correspondingAuthor":false,"prefix":"","firstName":"Liliya","middleName":"Štarhová","lastName":"Serbina","suffix":""},{"id":510277814,"identity":"258996ab-2b3c-4a10-b67a-1bd4cb0f3057","order_by":2,"name":"Erika Corretto","email":"","orcid":"","institution":"Free University of Bozen-Bolzano, Italy","correspondingAuthor":false,"prefix":"","firstName":"Erika","middleName":"","lastName":"Corretto","suffix":""},{"id":510277815,"identity":"24b4acbb-6ca3-43ad-9006-9b6d06dca377","order_by":3,"name":"James M. Howie","email":"","orcid":"","institution":"BOKU University","correspondingAuthor":false,"prefix":"","firstName":"James","middleName":"M.","lastName":"Howie","suffix":""},{"id":510277816,"identity":"fb48b9e9-a338-4db0-bb8a-0ee210be5eea","order_by":4,"name":"Fernando Cruz","email":"","orcid":"","institution":"Centro Nacional de Análisis Genómico (CNAG)","correspondingAuthor":false,"prefix":"","firstName":"Fernando","middleName":"","lastName":"Cruz","suffix":""},{"id":510277817,"identity":"2aa7ae5f-a91f-4c7f-be4e-2520ae90cb9b","order_by":5,"name":"Tyler S. Alioto","email":"","orcid":"","institution":"Centro Nacional de Análisis Genómico (CNAG)","correspondingAuthor":false,"prefix":"","firstName":"Tyler","middleName":"S.","lastName":"Alioto","suffix":""},{"id":510277818,"identity":"7e28fd23-2992-44fe-b304-fe41029400f4","order_by":6,"name":"Nicola Zadra","email":"","orcid":"","institution":"University of Trento, Center Agriculture Food Environment (C3A)","correspondingAuthor":false,"prefix":"","firstName":"Nicola","middleName":"","lastName":"Zadra","suffix":""},{"id":510277819,"identity":"33ee0a6c-4bfa-4e54-94a8-a0ee9a73a850","order_by":7,"name":"Gianfranco Anfora","email":"","orcid":"","institution":"University of Trento, Center Agriculture Food Environment (C3A)","correspondingAuthor":false,"prefix":"","firstName":"Gianfranco","middleName":"","lastName":"Anfora","suffix":""},{"id":510277820,"identity":"3329dcad-e308-4030-9fd3-a5f88296ac53","order_by":8,"name":"Christian Stauffer","email":"","orcid":"","institution":"BOKU University","correspondingAuthor":false,"prefix":"","firstName":"Christian","middleName":"","lastName":"Stauffer","suffix":""},{"id":510277821,"identity":"211c443c-0870-4180-9def-faa14aca0bd4","order_by":9,"name":"Lino Ometto","email":"","orcid":"","institution":"University of Pavia","correspondingAuthor":false,"prefix":"","firstName":"Lino","middleName":"","lastName":"Ometto","suffix":""},{"id":510277822,"identity":"d3e37278-e7a8-4ee9-93b3-96915122ebee","order_by":10,"name":"Omar Rota-Stabelli","email":"","orcid":"","institution":"University of Trento, Center Agriculture Food Environment (C3A)","correspondingAuthor":false,"prefix":"","firstName":"Omar","middleName":"","lastName":"Rota-Stabelli","suffix":""},{"id":510277823,"identity":"505a50f9-da20-4715-8f74-9ec45d970d17","order_by":11,"name":"Hannes Schuler","email":"","orcid":"","institution":"Free University of Bozen-Bolzano","correspondingAuthor":false,"prefix":"","firstName":"Hannes","middleName":"","lastName":"Schuler","suffix":""}],"badges":[],"createdAt":"2025-09-02 13:38:36","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7518317/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7518317/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12864-026-12622-0","type":"published","date":"2026-03-19T15:58:35+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":90795136,"identity":"e184115e-c82b-451b-9dd5-3d936256f6b1","added_by":"auto","created_at":"2025-09-08 08:52:40","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":160089,"visible":true,"origin":"","legend":"\u003cp\u003eTime-calibrated Bayesian phylogeny of 12 \u003cem\u003eCacopsylla\u003c/em\u003e species, based on 13 mitochondrial PCGs. Red branches correspond to Clade I and yellow branches to Clade II. The * refers to selected fossil records used for calibrations. Number at nodes correspond to posterior probabilities derived from amino acid dataset. Node divergence age estimates ±95% HPD are shown to be overlapping based on nucleotide third codon removed phylogeny.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-7518317/v1/19e5a1b717b1cb342f9c1303.png"},{"id":90795139,"identity":"055ac2b2-5282-4663-bf1a-598f89372b49","added_by":"auto","created_at":"2025-09-08 08:52:40","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1328016,"visible":true,"origin":"","legend":"\u003cp\u003eSubtree with dated phylogeny of \u003cem\u003eCacopsylla\u003c/em\u003especies with repeat landscape plots. (A) Subtree from Figure 1. Icons of the leafless tree and the conifer indicate differences in overwintering behaviour (non-migrating and migrating), whereas icons of different fruits represent the most agriculturally important host plants for each species. (B) landscapes divergence in TEs, the X-axis of each plot reflects how much a TE has diverged from its consensus sequence, with low divergence suggesting younger TEs (peaks on the left), while high divergence indicates ancient insertions (broad right-shifted distributions). The Y-axis represents the genomic proportion of the genome occupied by TEs at each divergence level. The large fraction of unclassified elements was omitted for these plots to focus only on annotated elements.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-7518317/v1/196910ade750aa29428324ef.png"},{"id":105224137,"identity":"f9bd5481-f134-47b9-a3c6-0d36380cbdca","added_by":"auto","created_at":"2026-03-23 16:12:39","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3097473,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7518317/v1/1fe194d2-8877-441e-aaf8-6aa084deb7c7.pdf"},{"id":90795143,"identity":"18b33ee1-5983-4dcb-971b-267e0557f20c","added_by":"auto","created_at":"2025-09-08 08:52:40","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1380613,"visible":true,"origin":"","legend":"\u003cp\u003eSUPPLEMENTARY FIGURES\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure S1\u003c/strong\u003e. BUSCO assessment results. Number of complete, fragmented and missing BUSCO orthologous genes in the \u003cem\u003eC. melanoneura \u003c/em\u003e(Cmel) and \u003cem\u003eC. picta \u003c/em\u003e(Cpic) assembled genomes. The analyis ias based on the odb12 databases for Arthrpopoda, Insecta and Hemiptera.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure S2\u003c/strong\u003e. Circular representations of complete \u003cem\u003eCacopsylla melanoneura\u003c/em\u003e and \u003cem\u003eC. picta\u003c/em\u003e mitochondrial genomes. The position and orientation of the 13 PCG genes (green), 22 tRNA genes (red), 2 rRNA genes (orange), control region (blue) and origin of L-strand replication (pink) are shown. The inner circle displays GC bias and the outer circle displays coverage depth of the Illumina reads used mitochondrial genome assembly.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure S3\u003c/strong\u003e. Bayesian tree with nucleotides 123\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure S4\u003c/strong\u003e. Bayesian tree with amino acids\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure S5\u003c/strong\u003e. Maximum likelihoods with all nucleotides\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure S6\u003c/strong\u003e. Maximum likelihoods tree without 3d codon positions\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure S7.\u003c/strong\u003e Maximum likelihoods tree with amino acids\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure S8\u003c/strong\u003e. Maximum likelihoods tree with nucleotide 1 and 2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure S9\u003c/strong\u003e Bar plots showing the count frequency (a,b) and percentage of genome occupied by various classes of genomically interspersed repeats (c,d), including retroelements (SINE, LINE, LTR; a,c), DNA transposons, unclassified repetitive elements, sRNAs and satellites, and simple repeats, in \u003cem\u003eCacopsylla picta\u003c/em\u003e (dotted bars) and in \u003cem\u003eC. melanoneura\u003c/em\u003e (solid bars (b,d).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure S10\u003c/strong\u003e. Bar plots showing count frequencies of specific genomically interspersed repetitive elements in \u003cem\u003eCacopsylla picta\u003c/em\u003e (dotted bars) and \u003cem\u003eC. melanoneura\u003c/em\u003e(solid bars). Colours correspond to repetitive element classes. Retroelements of class SINE are in brown, of class LINE in ochre orange, and class LTR in salmon. DNA transposons are in slate grey.\u003c/p\u003e","description":"","filename":"SupportinginformationV6.docx","url":"https://assets-eu.researchsquare.com/files/rs-7518317/v1/ea166f17234bb2a935861b0f.docx"},{"id":90795135,"identity":"b5471d90-22bd-4a26-a331-945762edb92e","added_by":"auto","created_at":"2025-09-08 08:52:40","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":22866,"visible":true,"origin":"","legend":"","description":"","filename":"Table1V6.docx","url":"https://assets-eu.researchsquare.com/files/rs-7518317/v1/735a1289d6f9861283431b0c.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Evolutionary genomics and divergence of Cacopsylla species with a special focus on the Apple Proliferation Vectors: Cacopsylla melanoneura and C. picta","fulltext":[{"header":"BACKGROUND","content":"\u003cp\u003ePsyllids (Hemiptera: Psylloidea) are a group of phytophagous insects comprising\u0026thinsp;~\u0026thinsp;4,000 described species belonging to seven families [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. They are members of Sternorrhyncha, a suborder which includes several other well studied plant pathogen vectors such as aphids (Aphidoidea), whiteflies (Aleyrodoidea) and scale insects (Coccoidea) [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The genus \u003cem\u003eCacopsylla\u003c/em\u003e (Psyllidae) includes a particularly high number of vectors of phytoplasma, a bacterium (Mollicutes) inhabiting the phloem and responsible for a variety of economically important tree and crop diseases [\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] including European Stone Fruit Yellows, Pear Decline, and Apple Proliferation [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Phytoplasmas alter the plant\u0026rsquo;s cellular processes by interfering with its ability to transport nutrients and water. This results in weakened and malformed structures, as well as in significant yield reductions [\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eApple Proliferation (AP) is an important disease affecting apple trees, associated with the phytoplasma \u003cem\u003e\u0026lsquo;Candidatus\u003c/em\u003e Phytoplasma mali\u0026rsquo; (hereafter, \u0026lsquo;\u003cem\u003eCa\u003c/em\u003e. P. mali\u0026rsquo;; for a review see Janik et al. [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]). Distinctive symptoms include characteristic shoots with a \u0026ldquo;witches\u0026rdquo; broom\u0026rdquo; appearance and fruits of reduced size and quality [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Because infected trees cannot be cured, they must be eradicated, leading to significant yield losses [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The AP is primarily transmitted by \u003cem\u003eCacopsylla picta\u003c/em\u003e, which acts as the main vector in most European countries [\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], and by \u003cem\u003eCacopsylla melanoneura\u003c/em\u003e, which is the main vector in the areas of Northwestern Italy where \u003cem\u003eC. picta\u003c/em\u003e is absent [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Due to variation in vector capabilities of these two psyllids, various environmental and genetic factors are expected to influence the rate of acquisition and transmission of \u0026lsquo;\u003cem\u003eCa.\u003c/em\u003e P. mali\u0026rsquo;. These factors include the infectious status of the host tree and the genetics of the psyllid vector [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], the insect\u0026rsquo;s endosymbionts [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] and the phytoplasma itself [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cem\u003eCacopsylla\u003c/em\u003e, like most other psyllid species, are host specific, with closely related psyllids tending to associate with related host plant lineages [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. In temperate regions, many psyllid species migrate from their deciduous host plants to conifers, where they overwinter as adults or eggs [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. In contrast, psyllids in tropical and southern temperate regions are often associated with evergreen hosts and tend to remain on the same plant throughout the year, completing several generations [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Intriguingly, some \u003cem\u003eCacopsylla\u003c/em\u003e species can develop on multiple related host plants (i.e. Rosaceae), forming genetically distinct groups with differing fitness levels. This is exemplified by \u003cem\u003eC. melanoneura\u003c/em\u003e, which appears to have at least two genetically distinct populations, associated either with apple trees or hawthorn [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe timing of \u003cem\u003eCacopsylla\u003c/em\u003e diversification has not yet been inferred using time-calibrated phylogenies, leaving the genus's evolutionary history, particularly its historical biogeography and host-plant associations, poorly understood. To date, a Neighbor-Joining analysis based on partial \u003cem\u003ecytochrome oxidase I\u003c/em\u003e (COI) gene sequences provided weak support for most deep clades, including those containing the AP vectors \u003cem\u003eC. melanoneura\u003c/em\u003e and \u003cem\u003eC. picta\u003c/em\u003e, or other \u003cem\u003eCacopsylla\u003c/em\u003e species like \u003cem\u003eC. mali\u003c/em\u003e and \u003cem\u003eC. pruni\u003c/em\u003e [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. A more recent phylogeny, based on whole mitochondrial genomes that included several \u003cem\u003eCacopsylla\u003c/em\u003e species, was not time-calibrated and omitted both \u003cem\u003eC. melanoneura\u003c/em\u003e and \u003cem\u003eC. picta\u003c/em\u003e, limiting its utility for resolving the evolutionary relationships among key vectors of \u003cem\u003e\u0026lsquo;Ca.\u003c/em\u003e P. mali\u0026rsquo;. [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Genomic information for these two species, and psyllids more broadly, remains limited, with existing studies focusing mainly on mitochondrial genomes [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. These studies suggest the existence of two distinct clades, which distinguish species with differences in overwintering behaviour [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], although the diversification, including at the genetic and genomic level, is not yet established.\u003c/p\u003e\u003cp\u003eA comprehensive understanding of a species evolutionary history requires investigating the evolution of the nuclear genome, which is shaped by various molecular mechanisms such as different classes of mutations, gene duplications, recombination, and horizontal gene transfer. In many species one major component involved in genome evolution and adaptation is represented by transposable elements [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Transposable elements (TEs) are mobile DNA sequences that can significantly influence the genome structure and its functions. In insects, the proportion of the genome occupied by TEs varies widely, reaching up to 60% in some species such as the migratory locust [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Although TE activity can have potentially deleterious effects on gene regulation, increasing evidence suggests that TEs also drive genomic innovation and can confer selective advantages to the host [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Comparative studies have revealed both similarities and differences in TE family diversity and abundance among insect genomes. Notably, significant variation in TE activity has been observed even among closely related species [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. For example, within the order Hemiptera, contrasting TE profiles have been reported. In \u003cem\u003eHomalodisca vitripennis\u003c/em\u003e (Hemiptera, Cicadellidae), LINEs and DNA transposons show a distinct divergence distribution, while SINEs and LTR elements are poorly represented. This pattern contrasts sharply with that of the pea aphid \u003cem\u003eAcyrthosiphon pisum\u003c/em\u003e (Hemiptera, Aphididae), where SINEs dominate the TE content, and LINEs and LTRs are virtually absent.\u003c/p\u003e\u003cp\u003eTo overcome the limited genomic resources available for \u003cem\u003eCacopsylla\u003c/em\u003e species, we present newly assembled mitochondrial genomes and draft nuclear genome nuclear assemblies of \u003cem\u003eC. melanoneura\u003c/em\u003e and \u003cem\u003eC. picta\u003c/em\u003e. The mitochondrial genomes, together with publicly available data from other \u003cem\u003eCacopsylla\u003c/em\u003e species, were used to reconstruct a robust, time-calibrated phylogeny of the genus, including several vector species with different host plant preferences. In parallel, we provide the first nuclear genome assemblies of \u003cem\u003eC. melanoneura\u003c/em\u003e and \u003cem\u003eC. picta\u003c/em\u003e and use them to investigate the role of repetitive elements in psyllid genome evolution. Given the established involvement of repetitive elements in adaptive evolution and gene regulation, we also performed a comparative analysis across multiple \u003cem\u003eCacopsylla\u003c/em\u003e species, with a particular focus on the AP vector species \u003cem\u003eC. melanoneura\u003c/em\u003e and \u003cem\u003eC. picta\u003c/em\u003e, to identify lineage-specific traits potentially associated with the accumulation of recently active TEs.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003ePsyllid collection, DNA extraction, library preparation and sequencing\u003c/h2\u003e\u003cp\u003eIndividuals of \u003cem\u003eC. melanoneura\u003c/em\u003e and \u003cem\u003eC. picta\u003c/em\u003e were collected in 2015 from natural populations in Northeastern Italy, from Laimburg (South Tyrol) and Bosentino (Trentino), and preserved at -20\u0026deg;C in 90% ethanol. Total DNA extraction was carried out using two different protocols. For \u003cem\u003eC. melanoneura\u003c/em\u003e, DNA was extracted using the Macherey-Nagel NucleoSpin Tissue Kit (Macherey-Nagel) from two individual specimens and one pool of six individuals. Three paired-end libraries (PE290, PE310, and PE700) were constructed from these samples using, representing different fragment sizes (\u003cb\u003eTable \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e). For \u003cem\u003eC. picta\u003c/em\u003e, an enhanced DNA extraction protocol was used, involving overnight lysis with DTT and extraction with the KingFisher Cell and Tissue DNA Kit (Thermo Fisher Scientific). Two paired-end libraries (PE510 and PE750) were prepared from the extracted single individuals (\u003cb\u003eTable \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e).\u003c/p\u003e\u003cp\u003eAll five libraries were sequenced on the Illumina HiSeq 2000 platform with a 251 bp insert size (PRJNA1312285). This yielded 57.9, 59.4, and 75.3 Gb of raw data for \u003cem\u003eC. melanoneura\u003c/em\u003e, corresponding to genome coverages of 131\u0026times;, 135\u0026times;, and 137\u0026times;, respectively. For \u003cem\u003eC. picta\u003c/em\u003e, sequencing produced 121.5 and 74.9 Gb of raw data, with corresponding coverages of 192\u0026times; and 119\u0026times;.\u003c/p\u003e\u003cp\u003e\u003cb\u003eNuclear genome size estimation in\u003c/b\u003e \u003cb\u003eCacopsylla\u003c/b\u003e \u003cb\u003especies\u003c/b\u003e\u003c/p\u003e\u003cp\u003ePrior to the \u003cem\u003ede novo\u003c/em\u003e assembly, the genome sizes of \u003cem\u003eC. melanoneura\u003c/em\u003e (\u003cb\u003eTable S2\u003c/b\u003e) and \u003cem\u003eC. picta\u003c/em\u003e (\u003cb\u003eTable S2\u003c/b\u003e) were estimated using a k-mer analysis of the raw reads of library PE700 and PE510, respectively, using \u003cem\u003eJellyfish\u003c/em\u003e v2.2.6 [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], \u003cem\u003eGenomeScope\u003c/em\u003e v1.0 (\u003cem\u003ek\u003c/em\u003e\u0026thinsp;=\u0026thinsp;17) [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e] and \u003cem\u003eSGA preqc\u003c/em\u003e (\u003cem\u003ek\u003c/em\u003e\u0026thinsp;=\u0026thinsp;31) [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Additionally, using this approach we also estimated the genome size of \u003cem\u003eC. burckhardti\u003c/em\u003e (PRJNA927338) and \u003cem\u003eC. jukyungi\u003c/em\u003e (PRJNA927338), for which raw data with sufficient coverage are publicly available.\u003c/p\u003e\u003cp\u003e\u003cb\u003eAssembly of the nuclear genomes of\u003c/b\u003e \u003cb\u003eC. melanoneura\u003c/b\u003e \u003cb\u003eand\u003c/b\u003e \u003cb\u003eC. picta\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAdapter sequences were removed and reads were trimmed in the \u003cem\u003eTrim Galore\u003c/em\u003e! wrapper (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.bioinformatics.babraham.ac.uk/projects/trim_galore/\u003c/span\u003e\u003cspan address=\"http://www.bioinformatics.babraham.ac.uk/projects/trim_galore/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) using \u003cem\u003eCutadapt\u003c/em\u003e [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Overlapping reads from the shorter fragment libraries were merged using \u003cem\u003eFLASH\u003c/em\u003e [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], after which reads were filtered in \u003cem\u003eGEM-mapper\u003c/em\u003e [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] (with up to 2% mismatches) against a contamination database including phiX, Univec sequences, \u003cem\u003eE. coli, Cacopsylla coccinea\u003c/em\u003e mitochondrion complete genome (accession number NC_027087.1) and 17 contaminant species\u0026rsquo; genomes (detected independently for each \u003cem\u003eCacopsylla\u003c/em\u003e species, using with \u003cem\u003eKraken\u003c/em\u003e v0.10.5 [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] as present in \u0026ge;\u0026thinsp;0.03% of the reads, see \u003cb\u003eTable S3\u003c/b\u003e).\u003c/p\u003e\u003cp\u003eThe \u003cem\u003eC. melanoneura\u003c/em\u003e genome was assembled \u003cem\u003ede novo\u003c/em\u003e using overlapping read-pairs from the PE700 library (detected with \u003cem\u003eFLASH\u003c/em\u003e) using \u003cem\u003eDISCOVAR de novo\u003c/em\u003e (experimental release v.51885) with default options [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], after discarding all read-pairs shorter than 200 bp. Circular lines were discarded, and the \u003cem\u003eDISCOVAR\u003c/em\u003e contigs were scaffolded with \u003cem\u003eBESST\u003c/em\u003e v2.2.5 [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] using processed reads from all three PE libraries (PE290, PE310 and PE700) with the option \u003cem\u003e\"--separate_repeats\u0026rdquo;\u003c/em\u003e and discarding all contigs classified as repeats. Mis-assemblies were removed as in [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e], using reads from all PE libraries, after introducing breaks at genomic intervals calculated to have negative consistency scores. This resulted in shorter but more reliable scaffolds, which were then broken again into contigs. Then contig assembly was \u0026ldquo;unchaffed\u0026rdquo; by filtering out those shorter than the read length (250 bp), thus only retaining sequences long enough to contain at least a partial exon (251\u0026ndash;500 bp). Finally, the filtered contigs were re-scaffolded in \u003cem\u003eBESST\u003c/em\u003e v2.2.5 yielding a final draft assembly (\u003cb\u003eTable S4\u003c/b\u003e).\u003c/p\u003e\u003cp\u003eThe \u003cem\u003eC. picta\u003c/em\u003e genome was assembled with a modified version of the \u003cem\u003eC. melanoneura\u003c/em\u003e pipeline. Overlapping read-pairs from library PE510 were assembled with \u003cem\u003eDISCOVAR de novo\u003c/em\u003e [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], discarding both read-pairs shorter than 200 bp and circular lines. The \u003cem\u003eDISCOVAR\u003c/em\u003e contigs were collapsed with \u003cem\u003eRedundans\u003c/em\u003e [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e] to reduce heterozygous haplotypes and repeats, thus accounting for high fragmentation. \u003cem\u003eRedundans\u003c/em\u003e contigs were scaffolded with \u003cem\u003eBESST\u003c/em\u003e v2.2.5 [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] using both PE libraries with the \u0026ldquo;--\u003cem\u003eseparate_repeats\u003c/em\u003e\u0026rdquo; option, yielding the final assembly draft (\u003cb\u003eTable S5\u003c/b\u003e).\u003c/p\u003e\u003cp\u003eEstimates of genomic completeness were obtained for each genome using two methods. \u003cem\u003eKAT\u003c/em\u003e [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e] compared k-mers in the pre-processed reads (libraires PE290, PE310, PE700 for \u003cem\u003eC. melanoneura\u003c/em\u003e, PE510 for \u003cem\u003eC. picta\u003c/em\u003e) with those in the final genomes to estimate sequence completeness. To assess genome assembly quality, we used \u003cem\u003eBUSCO\u003c/em\u003e v5.8.3 [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e], which estimates the completeness of genomic data based on the presence and universal single-copy orthologs (OrthoDB database odb12).\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eRepetitive element annotation and comparisons\u003c/h3\u003e\n\u003cp\u003eThe expected sample heterozygosity and genomic repetitiveness were estimated in \u003cem\u003eGenomeScope\u003c/em\u003e v1.0 [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e] (\u003cb\u003eTable S2\u003c/b\u003e). We then conducted a comparative analysis of abundances, sequence length and genome percentage for multiple repetitive element classes, including retroelements (LINEs, SINEs, LTRs), DNA transposons, and interspersed repeats (sRNAs, DNA satellites, simple repeats) using \u003cem\u003eRepeatMasker\u003c/em\u003e [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e], by mapping masked reads to a \u003cem\u003eRepeatMasker\u003c/em\u003e Combined Database (Dfam_Consensus-20181026, RepBase-20181026) with \u003cem\u003eRMBlastn\u003c/em\u003e v2.6.0+ (command: \u003cem\u003eRepeatMasker scaffold.fa -species arthropoda -pa 3\u003c/em\u003e). In addition, \u003cem\u003eRepeatModeler2\u003c/em\u003e [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e] with the option \"\u0026ndash;LTRStruct\" was used to identify dispersed transposable elements. Subsequently, \u003cem\u003eRepeatMasker\u003c/em\u003e was used to identify and mask interspersed repeats in the nuclear draft assemblies of \u003cem\u003eC. melanoneura\u003c/em\u003e and \u003cem\u003eC. picta\u003c/em\u003e, using the \u003cem\u003eRepeatModeler2\u003c/em\u003e library option. Additionally, we identified satellites and putative satellites in the raw reads and included them in \u003cem\u003eRepeatModeler2\u003c/em\u003e families for use in a \u003cem\u003eRepeatExplorer2\u003c/em\u003e analysis. Briefly, the pipeline was run to characterize the repeatome [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e], including the \u003cem\u003eTAREAN\u003c/em\u003e analysis within the \u003cem\u003eGalaxy\u003c/em\u003e portal (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://repeatexplorer-elixir.cerit-sc.cz\u003c/span\u003e\u003cspan address=\"https://repeatexplorer-elixir.cerit-sc.cz\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). For this, we randomly selected a total of 2,000,000 paired reads. Default options were selected, except that we set computing time to \u0026ldquo;long\u0026rdquo;, applied a filtration of the most abundant repeats, and set the threshold of the analysis to 0.001%.\u003c/p\u003e\u003cp\u003eBesides \u003cem\u003eC. melanoneura\u003c/em\u003e and \u003cem\u003eC. picta\u003c/em\u003e presented here, no nuclear genome assemblies are available for other \u003cem\u003eCacopsylla\u003c/em\u003e species. For some other species, sequencing reads are publicly available (\u003cb\u003eTables S6\u003c/b\u003e). To analyse the genomic content and compare nuclear repeats across \u003cem\u003eCacopsylla\u003c/em\u003e species, we used \u003cem\u003ednaPipeTE\u003c/em\u003e (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/clemgoub/dnaPipeTE\u003c/span\u003e\u003cspan address=\"https://github.com/clemgoub/dnaPipeTE\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e)\u003c/span\u003e, a tool optimized for repeatome analysis from low-coverage sequencing data [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e] that uses raw reads as input. Before analysis, we removed reads matching to mitochondrial DNA, known symbionts and contaminants. Repeat annotation was performed using the Dfam-RepeatMasker.lib database for Arthropoda, which included 6,828 entries as of May 2025. Repeat landscapes were generated using the dnaPTlandscape.sh script from the dnaPT_utils package (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/clemgoub/dnaPT_utils\u003c/span\u003e\u003cspan address=\"https://github.com/clemgoub/dnaPT_utils\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), with the -S and -U options enabled to visualize only repeat superfamilies and to exclude unclassified elements.\u003c/p\u003e\u003cp\u003e\u003cb\u003eAssembly of the mitochondrial genomes of\u003c/b\u003e \u003cb\u003eC. melanoneura\u003c/b\u003e \u003cb\u003eand\u003c/b\u003e \u003cb\u003eC. picta\u003c/b\u003e\u003c/p\u003e\u003cp\u003eMitochondrial genomes of \u003cem\u003eC. melanoneura\u003c/em\u003e (PX243765) and \u003cem\u003eC. picta\u003c/em\u003e (PX243766) were assembled and circularised in the \u003cem\u003eMitoZ\u003c/em\u003e pipeline [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e] operated in a \u003cem\u003eSingularity\u003c/em\u003e container [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e] using Illumina raw read libraries PE290 and PE750, respectively. Mitogenomes were annotated in \u003cem\u003eMITOS\u003c/em\u003e [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e] and \u003cem\u003eMITOS2\u003c/em\u003e [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e], a consensus annotation manually compiled, and the genomes visualised with annotations, GC content and coverages in \u003cem\u003eMitoZ\u003c/em\u003e [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eMitochondrial phylogeny and divergence time estimation\u003c/h3\u003e\n\u003cp\u003eTo test the phylogenetic placement of \u003cem\u003eC. melanoneura\u003c/em\u003e and \u003cem\u003eC. picta\u003c/em\u003e within the \u003cem\u003eCacopsylla\u003c/em\u003e genus, we conducted phylogenetic analyses using Bayesian inference (BI) in \u003cem\u003eBEAST\u003c/em\u003e v2.7.5 [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e] and maximum likelihood (ML) in \u003cem\u003eIQ-TREE\u003c/em\u003e v1.6.12 [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. The best-fit partitioning schemes and substitution models for subsequent phylogenetic analyses were predicted with \u003cem\u003eModelFinder\u003c/em\u003e [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e] implemented in \u003cem\u003eIQ-TREE\u003c/em\u003e release 2.1.4b [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. We repeated the analyses using three datasets: amino acid sequences, the corresponding nucleotide (codon) sequences, and nucleotide sequences with the third codon position excluded. The mitochondrial sequences of 13 protein coding genes (PCGs) from 12 \u003cem\u003eCacopsylla\u003c/em\u003e species, eight psyllids from other families, two aphids and two white flies (\u003cb\u003eTable S6\u003c/b\u003e) were aligned using the MAFFT-L-INS-I algorithm [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e] and concatenated using catsequences 1.3 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://zenodo.org/record/4409153#.YmJYT35Byot\u003c/span\u003e\u003cspan address=\"https://zenodo.org/record/4409153#.YmJYT35Byot\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe optimal substitution model for each partition of the BI analyses was determined using the model-averaging approach implemented in OBAMA [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e] with all substitution models enabled for the amino acid data, and the bModelTest packages [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e] for the nucleotide data. The BI analyses of 100\u0026nbsp;million MCMC generations, with trees sampled every 1,000 generations, were run on the CIPRES platform [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e] using BEAST [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. Random starting trees were assigned to each partition. Divergence time estimation was conducted using the Most Recent Common Ancestor (MRCA) approach, incorporating various calibration points using \u003cem\u003eBEAUTi\u003c/em\u003e [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e] under an Optimized Relaxed Clock model. A time constraint derived from the posterior estimate of Li \u003cem\u003eet al.\u003c/em\u003e, [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e] was applied to the split between Psylloidea and its sister clade (Aleyrodoidea\u0026thinsp;+\u0026thinsp;Aphidoidea) set at 269 MYA and modeled as a normal prior distribution (mean\u0026thinsp;=\u0026thinsp;269, S\u0026thinsp;=\u0026thinsp;5.9). Outgroup taxa from Aleyrodoidea and Aphidoidea were represented by \u003cem\u003eAleurodicus dugesii\u003c/em\u003e\u0026thinsp;+\u0026thinsp;\u003cem\u003eBemisia tabaci\u003c/em\u003e and \u003cem\u003eAphis gossypii\u003c/em\u003e\u0026thinsp;+\u0026thinsp;\u003cem\u003eMyzus persicae\u003c/em\u003e, respectively. To calibrate the Psylloidea crown node, we used the Eocene fossil \u003cem\u003eEogyropsylla paveloctogenarius\u003c/em\u003e (Aphalaridae; 41.3\u0026ndash;47.8 MYA), the oldest known representative of Psylloidea s.str. [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. The youngest age (41.3 MYA) was applied as a soft minimum using a log-normal prior (M\u0026thinsp;=\u0026thinsp;3.67, S\u0026thinsp;=\u0026thinsp;0.32, offset\u0026thinsp;=\u0026thinsp;41.3), with \u003cem\u003eLanthanaphalara mira\u003c/em\u003e, an extant member of the same family, used to define the calibrated node. An additional calibration was applied to a tribal-level node within the family Liviidae (Paurocephalini), using the Early Miocene fossil \u003cem\u003eMelanastera casca\u003c/em\u003e (20.4\u0026ndash;13.8 MYA), a congener of the extant \u003cem\u003eM. paucipunctata\u003c/em\u003e [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. The youngest age (13.8 MYA) was treated as a soft minimum, implemented as a log-normal prior (M\u0026thinsp;=\u0026thinsp;3.3, S\u0026thinsp;=\u0026thinsp;0.39, offset\u0026thinsp;=\u0026thinsp;13.8).\u003c/p\u003e\u003cp\u003eTo select the tree prior (Yule \u003cem\u003evs\u003c/em\u003e. birth\u0026ndash;death models), we performed a marginal likelihood estimation (MLE) using \u003cem\u003eTracer\u003c/em\u003e [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e] The marginal likelihood of both priors was calculated with 1,000 path steps, running chains for 1\u0026nbsp;million generations, and sampling log likelihood every 1,000 cycles. This analysis was conducted using \u003cem\u003eBEAST\u003c/em\u003e v1.10.4 [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. We calculated the Bayes factor (BF) as twice the natural logarithm (2lnBF) with respect to the highest-likelihood model, considering BF values\u0026thinsp;\u0026gt;\u0026thinsp;10 as significantly favouring one model over another. The remaining prior parameters for both Yule and birth-death models were kept unchanged. The results were evaluated in \u003cem\u003eTracer\u003c/em\u003e v1.7.1 [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e], using the effective sampling size (ESS\u0026thinsp;\u0026gt;\u0026thinsp;200) criterion, and the first 30% of samples were discarded as burn-in. The tree files were then combined using \u003cem\u003eLogCombiner\u003c/em\u003e v2.4.5, and the parameter values were annotated to the Maximum Clade Credibility (MCC) tree using \u003cem\u003eTreeAnnotator\u003c/em\u003e v2.4.5. Nodal support was assessed by posterior probabilities (PP).\u003c/p\u003e\u003cp\u003eML and BI trees were visualized using \u003cem\u003eFigTree\u003c/em\u003e v1.4.4 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/rambaut/figtree\u003c/span\u003e\u003cspan address=\"https://github.com/rambaut/figtree\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). All figures were edited in \u003cem\u003eGIMP\u003c/em\u003e 2.10.38.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003e\u003cstrong\u003eNuclear genomes of \u003cem\u003eC. melanoneura and C. picta\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBased on raw sequencing reads, \u003cem\u003eC. melanoneura\u003c/em\u003e has an estimated genome size of 438.67 Mb, while \u003cem\u003eC. picta\u003c/em\u003e has a larger genome with 632.08 Mb (\u003cstrong\u003eTable S2\u003c/strong\u003e). The other species with sufficient and public available raw reads data showed intermediate genome sizes: 528.10 Mb for \u003cem\u003eC. jukyungi\u003c/em\u003e and 549.12 Mb for \u003cem\u003eC. burckhardti\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003eThe final assembly of the \u003cem\u003eC. melanoneura\u003c/em\u003e genome yielded a 688 Mb sequence, in a total of 678,097 contigs and 483,574 scaffolds with N50 values of 1.53 kb and 3.93 kb, respectively (\u003cstrong\u003eTable S2\u003c/strong\u003e). The assembled genome size was thus inflated relative to \u003cem\u003ea priori\u003c/em\u003e estimates of 438.7\u0026ndash;473.8 Mb (\u003cstrong\u003eTable S2\u003c/strong\u003e). The BUSCO completeness analysis revealed 32.9% of genes recovered as complete (of which 4.6% were duplicates), 31.4% as fragmented and 35.7% missed (\u003cstrong\u003eFig. S1\u003c/strong\u003e). As expected by using data from a pool of inthividuals, this genome appears to be highly heterozygous (2.51%) and repetitive (estimated at 57.28%) a considerable number of \u003cem\u003ek\u003c/em\u003e-mers were missed in the heterozygous and homozygous regions, and several artificial duplications and repeats emerged due to the non-perfect collapsing of haplotypes.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe assembled \u003cem\u003eC. picta\u003c/em\u003e genome was larger, with 739.04 Mb and shows contig and scaffold N50s of 2.24 Kb and 6.3 Kb respectively (\u003cstrong\u003eTable S2; S5\u003c/strong\u003e). The BUSCO completeness analysis indicated 30.1% of genes complete (of which 0.7% were duplicates), 33.1% fragmented (i.e. partial matches) and 36.8% missed. Because the genome was heterozygous (1.37%) and repetitive (estimated at 67.1%), there were some difficulties collapsing alleles in heterozygous regions and an excess of duplicated sequences in homozygous regions, although the effect on genome size inflation was weaker than in \u003cem\u003eC. melanoneura\u003c/em\u003e. Although the genome size and repetitiveness seems to be porperties inherent to both genomes, the heterozygosity and efficiency in collapsing haplotypes can be explained by the larger number of individuals sequenced and simultaneously assembled in C. melanoneura.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMitochondrial genomes of \u003cem\u003eC. melanoneura\u003c/em\u003e and \u003cem\u003eC. picta\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe final assemblies of the \u003cem\u003eC. melanoneura\u003c/em\u003e and \u003cem\u003eC. picta\u003c/em\u003e mitogenome yielded 14,882 bp and 14,829 bp circular sequences, respectively, with 13 PCGs, 22 tRNAs and 2 rRNAs, as well as some control region and origin of L-strand replication elements (recovered in \u003cem\u003eMITOS2\u003c/em\u003e) (\u003cstrong\u003eFig. S2\u003c/strong\u003e). The mitochondrial genome size of \u003cem\u003eC. melanoneura\u003c/em\u003e presented here was almost identical to the one of specimens from Czech Republic (14,779 - 14,881 bp) [23], while the \u003cem\u003eC. picta\u003c/em\u003e specimen of this study had a slightly larger mitochondrial genome compared to Czech individuals (14,801 and 14,802 bp) [23]. In general, variations in genome length among the investigated \u003cem\u003eCacopsylla\u003c/em\u003e species are consistently found in the control regions. The gene order and GC usage in both \u003cem\u003eC. melanoneura\u003c/em\u003e and \u003cem\u003eC. picta\u003c/em\u003e was identical to that observed across all known \u003cem\u003eCacopsylla\u0026nbsp;\u003c/em\u003especies [22, 65\u0026ndash;67]\u003cem\u003e\u0026nbsp;\u003c/em\u003eas well as most other psyllid species [22, 23]. \u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMitochondrial phylogeny and divergence time estimation of \u003cem\u003eCacopsylla\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe investigated the phylogenetic relationships of the newly sequenced samples of \u003cem\u003eC. melanoneura\u003c/em\u003e and \u003cem\u003eC. picta\u003c/em\u003e within the genus \u003cem\u003eCacopsylla\u003c/em\u003e. Our dataset comprised 13 PCGs obtained from whole-mitochondrial sequences across 12 \u003cem\u003eCacopsylla\u003c/em\u003e species and 12 outgroup taxa (\u003cstrong\u003eTable 1 and Table S6\u003c/strong\u003e). To assess the robustness of our phylogenetic inference, we employed two analytical frameworks, Bayesian inference (BI) and maximum likelihood (ML), and analysed three data types: amino acid sequences (3,404 bp), nucleotide sequences including all codon positions (10,211 bp), and nucleotide sequences with the third codon position excluded, hereafter referred to as the nucleotide tree (6,809 bp).\u003c/p\u003e\n\u003cp\u003eFor the time-calibrated BI phylogenies, we assessed the fit of different tree priors by comparing marginal likelihood estimates (MLE) derived via stepping-stone sampling. The MLE values for the Yule and birth\u0026ndash;death models were -106,096.04 and -106,088.62, respectively. The resulting Bayes Factor (BF = -7.42) favoured the birth\u0026ndash;death model, which we therefore used in the final analyses.\u003c/p\u003e\n\u003cp\u003eIn general, the BI trees based on the amino acid dataset and the nucleotide dataset excluding the third codon position provided stronger support for both deep and internal branches suggesting that these values provide more reliable approximate estimates compared to the all-codon tree (\u003cstrong\u003eFig. 1; S3, S4, S5\u003c/strong\u003e). A notable difference in the all-codon tree, however, was the recovery of the outgroup family Liviidae as monophyletic, including \u003cem\u003eEuphyllura phillyreae\u003c/em\u003e (Euphyllurinae) and three representatives of Liviinae (\u003cem\u003eLivia junci\u003c/em\u003e, \u003cem\u003eMelanastera paucipunctata\u003c/em\u003e, \u003cem\u003ePaurocephala sauteri\u003c/em\u003e). In addition, the all-codon tree recovered a monophyletic grouping of \u003cem\u003eC. coccinea\u003c/em\u003e and \u003cem\u003eC. mali\u0026nbsp;\u003c/em\u003e(\u003cstrong\u003eFig. S3\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003eThe divergence time estimates from the amino acid tree were in general older compared to the nucleotide tree. In both trees, the crown diversification of Psylloidea was estimated to have occurred in the Paleocene\u0026ndash;Eocene, at approximately 52.1 MYA (95% HPD: 45.7\u0026ndash;70.2 MYA) based on the nucleotide dataset, or 62.3 MYA (95% HPD: 46.3\u0026ndash;82.7 MYA) based on the amino acid dataset (\u003cstrong\u003eFig. 1\u003c/strong\u003e). These estimates are substantially older than the fossil prior minimum of 41.3 MYA. In the amino acid tree, the crown age of the genus \u003cem\u003eCacopsylla\u003c/em\u003e was estimated to be in the Early Miocene, at approximately \u0026shy;\u0026shy; (95% HPD: 10.8\u0026ndash;27.5 MYA). In contrast, the nucleotide tree suggested a later divergence, placing the crown age of \u003cem\u003eCacopsylla\u003c/em\u003e in the Middle Miocene, at approximately 12.7 MYA (95% HPD: 9.7\u0026ndash;16.0 MYA). Both the amino acid and nucleotide trees strongly supported (PP = 1.0) the presence of two major \u003cem\u003eCacopsylla\u003c/em\u003e clades: Clade I and Clade II \u003cstrong\u003e(Fig. 1 and Fig. 2).\u0026nbsp;\u003c/strong\u003eAll species within \u003cem\u003eCacopsylla\u003c/em\u003e Clade I (red branches) are associated with host plants from the family Rosaceae \u003cstrong\u003e(Table 1; Fig. 2)\u003c/strong\u003e.\u003cs\u003e\u0026nbsp;\u003c/s\u003eIn all trees, \u003cem\u003eC. melanoneura\u003c/em\u003e forms a clade with the plum psyllid \u003cem\u003eC. pruni\u003c/em\u003e, with strong support in the amino acid tree (PP = 0.96) and in the nucleotide tree (PP = 1.0). The divergence between these two species was estimated at approximately 6.1\u0026ndash;6.9 MYA (amino acid tree: 95% HPD: 2.4\u0026ndash;11.8 MYA; nucleotide tree: 95% HPD: 3.9\u0026ndash;8.3 MYA). This pair consistently clusters as a sister group to the pear psyllids \u003cem\u003eC. burckhardti\u003c/em\u003e and \u003cem\u003eC. pyrisuga\u003c/em\u003e, with strong support across both datasets (amino acid tree PP = 1.0; nucleotide tree PP = 0.99). In turn, \u003cem\u003eC. picta\u003c/em\u003e forms a sister lineage to the above mentioned clades in both trees (PP = 1.0), with the split between \u003cem\u003eC. picta\u003c/em\u003e and the most recent common ancestor (MRCA) of these species estimated at approximately 8.6\u0026ndash;11.5 MYA, in the Late Miocene (amino acid tree: 95% HPD: 5.5\u0026ndash;18.7 MYA; nucleotide tree: 95% HPD: 6.0\u0026ndash;11.4 MYA). These results suggest independent evolutionary trajectories for the two main AP vector species in Europe, \u003cem\u003eC. melanoneura\u003c/em\u003e and \u003cem\u003eC. picta\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003eThe \u003cem\u003eCacopsylla\u003c/em\u003e species in Clade II (yellow branches) form a separate group, also including psyllids primarily associated with Rosaceae, along with single representatives from the families Lardizabalaceae and Rutaceae \u003cstrong\u003e(Table 1)\u003c/strong\u003e. The two European species associated with \u003cem\u003ePyrus\u003c/em\u003e, \u003cem\u003eC. pyri\u003c/em\u003e and \u003cem\u003eC. pyricola\u003c/em\u003e, cluster together with the Asian \u003cem\u003eC. jukyungi\u003c/em\u003e, also associated with \u003cem\u003ePyrus\u003c/em\u003e, as sister species (\u003cstrong\u003eFig. 2\u003c/strong\u003e). These nodes exhibit strong support across all phylogenetic inference methods. In contrast, the phylogenetic relationships among \u003cem\u003eC. citrisuga\u003c/em\u003e, \u003cem\u003eC. coccinea\u003c/em\u003e, and \u003cem\u003eC. mali\u003c/em\u003e remain unresolved and vary considerably among different phylogenetic reconstructions, likely due to incomplete taxon sampling. Interestingly, \u003cem\u003eC. citrisuga\u003c/em\u003e and \u003cem\u003eC. coccinea\u003c/em\u003e are Asian species that primarily reproduce on citrus and \u003cem\u003eAkebia\u003c/em\u003e, respectively, while \u003cem\u003eC. mali\u003c/em\u003e, found in Europe and North America, reproduces on apple trees. Notably, although it is the only species in this group associated with apple, \u003cem\u003eC. mali\u003c/em\u003e is phylogenetically distant from \u003cem\u003eC. melanoneura\u003c/em\u003e and \u003cem\u003eC. picta\u003c/em\u003e and has never been recovered as their sister taxon.\u003c/p\u003e\n\u003cp\u003eAnother notable finding is that the divergence of the four pear-associated \u003cem\u003eCacopsylla\u003c/em\u003e species from the two clades, \u003cem\u003eC. pyri\u003c/em\u003e / \u003cem\u003eC. pyricola\u003c/em\u003e (Clade II) and \u003cem\u003eC. burckhardti\u003c/em\u003e / \u003cem\u003eC. pyrisuga\u003c/em\u003e (Clade I), represents the two most recent speciation events among the analysed taxa, estimated at around 4.7 MYA (amino acid tree: 95% HPD: 3.6\u0026ndash;6.1 MYA; nucleotide tree: 95% HPD: 4.6\u0026ndash;6.1 MYA). Similar to the results of the BI all-codon tree, the ML all-codon tree also recovered the family Liviidae as monophyletic, albeit with weak support (\u003cstrong\u003eFig. S6\u003c/strong\u003e). In contrast, both the BI and ML trees based on amino acid and third codon-excluded nucleotide datasets did not support the monophyly of Liviidae, while both major \u003cem\u003eCacopsylla\u003c/em\u003e clades (\u003cstrong\u003eFig. S7 and S8\u003c/strong\u003e) were strongly supported in all ML analyses (BS \u0026gt; 0.98), with internal branch support across \u003cem\u003eCacopsylla\u003c/em\u003e being generally lower than in the BI inferences.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRepetitive element landscape diversity in \u003cem\u003eCacopsylla\u003c/em\u003e species\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTE composition was investigated using landscape plots that report the frequency and variability of the different TE families. In this analysis, sequence divergence of TE copies from their consensus sequence is shown on the X-axis, and their genomic proportion on the Y-axis. Peaks toward the left (low divergence) indicate more recent TE insertions, while those toward the right (high divergence) reflect older insertions. In \u003cem\u003eC. mali\u003c/em\u003e and \u003cem\u003eC. picta\u003c/em\u003e, prominent recent bursts of DNA and LINE elements support relatively recent TE bursts. In contrast, species like \u003cem\u003eC. pruni\u003c/em\u003e and \u003cem\u003eC. pyricola\u003c/em\u003e show older TEs expansions (\u003cstrong\u003eFig. 2\u003c/strong\u003e). The dominant TE classes vary across samples, indicating that different TE families drive genome changes in different species. (\u003cstrong\u003eFig. 2\u003c/strong\u003e). Specifically, in \u003cem\u003eC. pyri\u003c/em\u003e, there is high recent TE activity, particularly in DNA and LINE elements, while in its sister species, \u003cem\u003eC. pyricola\u003c/em\u003e, recent TE activity is lower and the TE landscape suggests older insertions. \u003cem\u003eCacopsylla jukyungi\u003c/em\u003e shows DNA and LTR elements dominant in recent bins, suggesting a likely recent expansion. In \u003cem\u003eC. mali\u003c/em\u003e, there is a very pronounced peak of low divergent TE copies, supporting strong recent activity of DNA, LINE and RC elements. This is likely one of the highest recent TE activity profiles. In \u003cem\u003eC. burckhardti\u003c/em\u003e, there is moderate to high recent TE activity, mostly driven by LTR, DNA and LINE elements. The sister species, \u003cem\u003eC. pyrisuga\u003c/em\u003e, has a flatter and more right-shifted TE distribution, which suggests that TE activity has slowed down. \u003cem\u003eC. melanoneura\u003c/em\u003e shows very active recent TE insertions, especially in DNA, LINE and LTR elements. The prominent peak at 0\u0026ndash;2% divergence suggests a recent expansion event. In contrast, the sister species \u003cem\u003eC. pruni\u003c/em\u003e shows low recent TE activity, with most insertions being older. The TE peak is broad and right-shifted, indicating a more stable TE landscape. Finally, \u003cem\u003eC. picta\u003c/em\u003e has a sharp recent peak, especially in LINE and DNA elements, which is comparable to \u003cem\u003eC. mali\u003c/em\u003e and \u003cem\u003eC. melanoneura\u003c/em\u003e, making it one of the most dynamic genomes in this dataset. In summary, the species that show strong peaks at very low divergence values (0\u0026ndash;2%), indicating ongoing or recent TE bursts, are \u003cem\u003eC. mali\u003c/em\u003e from Clade II and all the species from Clade I, except \u003cem\u003eC. pruni\u003c/em\u003e. The remaining species from Clade II and \u003cem\u003eC. pruni\u003c/em\u003e show a broader peak indicating relatively low and moderate divergence values (~3\u0026ndash;10%). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTE content contributes to genome size in \u003cem\u003eC. melanoneura\u003c/em\u003e and \u003cem\u003eC. picta\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGiven the substantial difference in estimated genome size between \u003cem\u003eC. melanoneura\u0026nbsp;\u003c/em\u003eand \u003cem\u003eC. picta\u003c/em\u003e, we examined in more detail the contribution of repetitive elements to their genome size. Repetitive elements accounted for a moderate fraction of the assembled genome of both \u003cem\u003eC. melanoneura\u003c/em\u003e, at 6.7%, and \u003cem\u003eC. picta,\u003c/em\u003e at 12.2%. In both species, simple repeats were the most common element, followed by retroelements (LINEs, SINEs and LTRs), and DNA transposons (\u003cstrong\u003eFig S9\u003c/strong\u003e). This enrichment was consistent when considering total element count, length, and percentage of genome occupied. Focusing on comparative differences between species, simple repeats were more numerous and accounted for a larger proportion of the genome in \u003cem\u003eC. picta\u003c/em\u003e compared to \u003cem\u003eC. melanoneura\u003c/em\u003e (\u003cstrong\u003eFig. S9\u003c/strong\u003e). A similar pattern was observed for retroelements, which was driven by the relative abundances of LINE elements (\u003cstrong\u003eFig. S9\u003c/strong\u003e). Unclassified repetitive elements were also more common in \u003cem\u003eC. picta\u003c/em\u003e. No notable differences in counts, length or percentage of genome occupied were found for SINE or LTR retroelements, sRNA or satellites, while DNA transposons were slightly more numerous in \u003cem\u003eC. picta\u003c/em\u003e, although the percentage of genome occupied by these TEs was identical in the two species. Similar results were obtained using \u003cem\u003eRepeatMasker\u003c/em\u003e with species-specific repeat libraries generated by \u003cem\u003eRepeatModeler2\u003c/em\u003e,\u003cs\u003e\u0026nbsp;\u003c/s\u003ewhere the main difference observed was in the proportion of masked bases, 52.95% in \u003cem\u003eC. melanoneura\u003c/em\u003e and 60.86% in \u003cem\u003eC. picta.\u003c/em\u003e Discrepancies between the two approaches were primarily due to differences in the proportion of unclassified repetitive elements in both species (\u003cstrong\u003eFig. S9\u003c/strong\u003e).\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRetroelements and DNA transposons in the draft genome of \u003cem\u003eC. melanoneura\u003c/em\u003e and \u003cem\u003eC. picta\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe further explored the genomic abundance in the draft genome assembly of both the retroelement and DNA transposon sub-classes. LINEs were the most abundant subclass in both \u003cem\u003eC. melanoneura\u0026nbsp;\u003c/em\u003eand \u003cem\u003eC. picta\u003c/em\u003e, followed by SINEs and LTRs (\u003cstrong\u003eFig. S9; S10\u003c/strong\u003e). However, LINEs were more abundant in \u003cem\u003eC. picta\u003c/em\u003e, while SINEs and LTRs were more common in \u003cem\u003eC. melanoneura\u003c/em\u003e. Most of the difference in LINE content between the two species is associated to the much higher number of \u003cem\u003eRTE/Bov-B\u003c/em\u003e elements in \u003cem\u003eC. picta\u003c/em\u003e. On the other hand, the higher abundance of LTRs in \u003cem\u003eC. melanoneura\u003c/em\u003e is mostly attributed to BEL/Pao and \u003cem\u003eGypsy/DIRS1\u0026nbsp;\u003c/em\u003ebeing more abundant in this species (\u003cstrong\u003eFig. S10\u003c/strong\u003e). We also note that \u003cem\u003eTcl-IS630-Pogo\u003c/em\u003e and \u003cem\u003ehobo-activator\u003c/em\u003e were the most common DNA transposons in both \u003cem\u003eC. melanoneura\u0026nbsp;\u003c/em\u003eand \u003cem\u003eC. picta\u003c/em\u003e, the latter hosting in particular almost twice as much \u003cem\u003ehobo-activator\u003c/em\u003e than its related species (\u003cstrong\u003eFig. S10\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003ePsyllids from the genus \u003cem\u003eCacopsylla\u003c/em\u003e are phytophagous insects with a wide range of host plants and include several vectors of plant pathogens. Although several \u003cem\u003eCacopsylla\u003c/em\u003e species are among the most important pests of various fruit trees, information on their evolutionary history, including their genetic and genomic makeup and evolution, remains scarce. We therefore conducted comparative genomic and phylogenetic analyses of \u003cem\u003eCacopsylla\u003c/em\u003e species, with a special focus on the two vectors of apple phytoplasma, \u0026lsquo;\u003cem\u003eCa.\u003c/em\u003e P. mali\u0026rsquo;, \u003cem\u003eC. melanoneura\u003c/em\u003e and \u003cem\u003eC. picta\u003c/em\u003e. One specific aim was to assess whether their ability to transmit \u0026lsquo;\u003cem\u003eCa.\u003c/em\u003e P. mali\u0026rsquo; reflects a shared evolutionary origin or independent acquisition. For this purpose, we sequenced and assembled the nuclear and mitochondrial genomes of these species and, leveraging on publicly available data from other \u003cem\u003eCacopsylla\u003c/em\u003e and other psyllid species, reconstructed their phylogeny to trace their relationships with other vectors within \u003cem\u003eCacopsylla\u003c/em\u003e.\u003c/p\u003e\u003cp\u003eThe phylogenetic trees based on amino acid and nucleotide sequences of 12 psyllid species showed largely similar topologies, although divergence times were consistently estimated to be older when inferred from the amino acid data. In both the amino acid and nucleotide phylogenies, \u003cem\u003eE. phillyreae\u003c/em\u003e from the subfamily Euphyllurinae was recovered as paraphyletic with respect to the other analysed Liviinae representatives. In contrast, the family Liviidae was recovered as monophyletic in the all-codon trees. A similar pattern was reported by Percy et al. [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], who found that Liviidae is not monophyletic in either their conserved codon or combined datasets. Nevertheless, our amino acid and nucleotide phylogenies recovered stronger support for both deep and internal clades compared to the all-codon trees, suggesting that codon composition and substitution saturation may affect the inferred topology. This contrasts with findings from Wang et al. 2023 [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e], where excluding the third codon position from nuclear nucleotide datasets did not resolve compositional heterogeneity or correct the inferred topology. We estimated that Psylloidea started diversifying during the Paleocene\u0026ndash;Eocene, approximately at 52.1 or 62.3\u0026nbsp;million years ago (MYA), with confidence intervals ranging from 46.3 to 82.7 Ma. These estimates are substantially younger than those reported in the large-scale Hemiptera phylogenies of Li et al. [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e] that placed the crown diversification of Psylloidea at ~\u0026thinsp;120 MYA during the Early Cretaceous, while [\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e] estimated it at ~\u0026thinsp;220 MYA in the Late Triassic. This discrepancy may be explained by our inclusion of psyllid fossil calibrations, which constrained internal psyllid nodes, as well as our broader taxon sampling within Psylloidea. Our results are also consistent with paleontological evidence presented by [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e] and Drohojowska \u003cem\u003eet al.\u003c/em\u003e, [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e], which suggested that, based on fossil evidence, extant psyllids could not have diversified earlier than the mid-Eocene Lutetian stage. Although our point estimates predate the Lutetian, the lower bound of the 95% HPD interval extends into this stage, making our divergence estimates more consistent with both paleontological and molecular evidence than previous studies.\u003c/p\u003e\u003cp\u003eThe crown divergence of the genus \u003cem\u003eCacopsylla\u003c/em\u003e was estimated to have occurred in the Early Miocene at 18.4 MYA (amino acid phylogeny) or in the Middle Miocene at 12.7 MYA (nucleotide phylogeny). These estimates are also in agreement with the fossil evidence of \u003cem\u003eCacopsylla\u003c/em\u003e dated to the Miocene [\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e]. Because the upper and lower bounds of the amino acid and nucleotide-based estimates also overlap, the approximate dating is reliable. Nevertheless, the amino-acid or nucleotide-based estimate is probably the closest estimate of the true time of divergence given its better alignment with the available fossil evidence. Our topologies across all trees consistently support a close relationship between \u003cem\u003eC. melanoneura\u003c/em\u003e and \u003cem\u003eC. pruni\u003c/em\u003e, the latter being the major vector of \u0026lsquo;\u003cem\u003eCa.\u003c/em\u003e Phytoplasma prunorum\u0026rsquo;, the causal agent of European Stone Fruit Yellows [\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e]. Interestingly, both \u003cem\u003eC. melanoneura\u003c/em\u003e and \u003cem\u003eC. pruni\u003c/em\u003e may represent cryptic species complexes, comprising genetically distinct lineages that are morphologically nearly identical and lack diagnostic morphological characters to distinguish them. These lineages are generally associated with different host preferences and show considerable molecular divergence within each nominal species [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e, \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eCrucially, across nearly all analyses, \u003cem\u003eC. picta\u003c/em\u003e was consistently placed as a sister taxon to a clade comprising four other Rosaceae-associated species, \u003cem\u003eC. melanoneura\u003c/em\u003e and \u003cem\u003eC. pruni\u003c/em\u003e, as well as two pear psyllids \u003cem\u003eC. burckhardti\u003c/em\u003e and \u003cem\u003eC. pyrisuga\u003c/em\u003e. This pattern suggests that the two primary vectors of AP, \u003cem\u003eC. melanoneura\u003c/em\u003e and \u003cem\u003eC. picta\u003c/em\u003e, likely evolved their vector competence independently rather than inheriting it from a common ancestor. Furthermore, both AP vector species are even more distantly related to another apple psyllid \u003cem\u003eC. mali\u003c/em\u003e, which has not been confirmed as a vector of \u0026lsquo;\u003cem\u003eCa.\u003c/em\u003e P. mali\u0026rsquo;. Similarly, pear psyllids \u003cem\u003eC. pyri\u003c/em\u003e and \u003cem\u003eC. pyricola\u003c/em\u003e (Clade II), as well as \u003cem\u003eC. burckhardti\u003c/em\u003e and \u003cem\u003eC. pyrisuga\u003c/em\u003e (Clade I), are distributed across distinct phylogenetic clades, suggesting independent evolutionary origins of pear-associated lineages. While \u003cem\u003eC. pyri\u003c/em\u003e and \u003cem\u003eC. pyricola\u003c/em\u003e may have inherited vector competence from a common ancestor, the more distantly related \u003cem\u003eC. pyrisuga\u003c/em\u003e likely acquired this trait through a separate evolutionary pathway.\u003c/p\u003e\u003cp\u003eWhile \u003cem\u003eCacopsylla\u003c/em\u003e species do not cluster based on their capability to transmit phytoplasma or host preference, the two clades recovered in our study appear to differ in key biological traits. \u003cem\u003eCacopsylla\u003c/em\u003e Clade I consists of species which are strictly associated with Rosaceae. All species in this clade ((\u003cem\u003eC. burckhardti\u003c/em\u003e\u0026thinsp;+\u0026thinsp;\u003cem\u003eC. pyrisuga\u003c/em\u003e) (\u003cem\u003eC. melanoneura\u003c/em\u003e\u0026thinsp;+\u0026thinsp;\u003cem\u003eC. pruni\u003c/em\u003e) \u003cem\u003eC. picta\u003c/em\u003e)) are univoltine and migrate to conifers for overwintering (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). This migratory behaviour may represent an adaptation to harsh environmental conditions and the seasonal unavailability of suitable phloem sources on deciduous hosts, serving as an overwintering strategy of many psyllid species in northern temperate regions [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. In contrast, most species assigned to Clade II (\u003cem\u003eC. pyri\u003c/em\u003e, \u003cem\u003eC. pyricola\u003c/em\u003e, \u003cem\u003eC. jukyungi\u003c/em\u003e, \u003cem\u003eC. citrisuga\u003c/em\u003e, \u003cem\u003eC. mali\u003c/em\u003e) overwinter on their host plants without migrating to conifers. Although the genetic basis and evolution of the migratory behaviour in psyllids remain unclear, our data suggest a potential correlation between phylogenetic structure and ecological traits. Moreover, all species belonging to Clade I are restricted to the family Rosaceae, whereas several species from Clade II are associated with other plant families, i.e. \u003cem\u003eC. citrisuga\u003c/em\u003e develops on Rutaceae and \u003cem\u003eC. coccinea\u003c/em\u003e on Lardizabalaceae. Additionally, Clade I contains only univoltine species, while various species belonging to Clade II are polyvoltine. This pattern is consistent with ecological strategies observed in psyllids from tropical and southern temperate regions, where the psyllid species richness is the highest and continuous host availability facilitates multiple generations per year [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Taken together, these observations suggest that life history traits, such as voltinism and overwintering strategy, might be linked to the phylogenetic structure within \u003cem\u003eCacopsylla\u003c/em\u003e, and may help trace the evolutionary transitions in host association and overwintering behaviour. However, broader taxon sampling and mitogenome sequencing across the genus are needed to confirm this hypothesis.\u003c/p\u003e\u003cp\u003eWe also investigated the repeatome to better understand the genomic processes shaping evolution in the \u003cem\u003eCacopsylla\u003c/em\u003e genus. We found that TEs dynamics vary widely across species, with lineage-specific patterns of accumulation and turnover likely contributing to genome evolution and adaptation. Species such as \u003cem\u003eC. mali\u003c/em\u003e, \u003cem\u003eC. melanoneura\u003c/em\u003e, \u003cem\u003eC. picta\u003c/em\u003e and \u003cem\u003eC. pyri\u003c/em\u003e show evidence of recent TE bursts, particularly of DNA transposons and LINE elements, suggesting ongoing genome re-modelling. In contrast, \u003cem\u003eC. pruni\u003c/em\u003e, \u003cem\u003eC. pyricola\u003c/em\u003e, and \u003cem\u003eC. pyrisuga\u003c/em\u003e exhibit older and likely more stable TE landscapes. According to our phylogenetic analyses, Clade I and Clade II are similar in age, although Clade I may be slightly younger. Moreover, the two clades differ in life history traits that may influence TE activity (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Clade I species inhabit less stable environments and are univoltine and migratory, with seasonal movement to conifers for overwintering. In contrast, most Clade II species are mostly polyvoltine, with several of them occupying more stable environments (without seasonal changes), which may reduce the stressful conditions that promote TE activity [\u003cspan additionalcitationids=\"CR76\" citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e]. Environment aside, polyvoltine species may accumulate TEs faster due to shorter generation times [\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e], while univoltine species may experience slower TE accumulation and stronger selection against harmful insertions and more stable epigenetic silencing [\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e]. Additionally, the presence of seasonal migration in some species may also lead to periods of genomic \u0026ldquo;silence\u0026rdquo; potentially affecting TE activity compared to species that undergo continuous generations on their host plants. For example, studies have shown that in some insect groups, TEs are differentially expressed during diapause versus active developmental stages. In the bee species \u003cem\u003eMegachile rotundata\u003c/em\u003e and \u003cem\u003eOsmia lignaria\u003c/em\u003e, TE expression varied significantly during diapause and in response to temperature stress, suggesting that environmental conditions and life stage transitions can modulate TE activity [\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e]. Similarly, in \u003cem\u003eDrosophila montana\u003c/em\u003e, a cold-adapted fly species, specific TEs were found to be upregulated during diapause, implying a role in regulating genes associated with diapause and cold tolerance [\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eWe further compared the TEs in the shallow genome assemblies of \u003cem\u003eC. melanoneura\u003c/em\u003e and \u003cem\u003eC. picta\u003c/em\u003e. The primary finding was that simple repeats, LINE-class retrotransposons, and unclassified repeats were approximately twice as abundant in the genome of \u003cem\u003eC. picta\u003c/em\u003e compared to \u003cem\u003eC. melanoneura\u003c/em\u003e. The analysis of retroelements and DNA transposons revealed that these classes significantly contributed to the genome size differences between the two species. Retroelements such as RTE/Bov-B subclass were especially overrepresented in \u003cem\u003eC. picta\u003c/em\u003e. In contrast, \u003cem\u003eC. melanoneura\u003c/em\u003e had a greater proportion of non-assigned LINEs, although this did not affect the overall retroelement composition. Overall, while the composition of element types was broadly conserved, \u003cem\u003eC. picta\u003c/em\u003e consistently exhibited a higher abundance of most repeat types.\u003c/p\u003e\u003cp\u003eTransposable elements may contribute to genomic variability and regulatory plasticity that may facilitate resistance to chemical contaminants such as pesticides, primarily through gene upregulation, loss of function, and alternative splicing. Among TE types, LINEs have been shown in \u003cem\u003eDrosophila melanogaster\u003c/em\u003e to alter the splicing and regulation of genes involved in insecticide resistance, conferring resistance to DDT and other insecticides [\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e, \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e]. Similarly, in \u003cem\u003eHelicoverpa armigera\u003c/em\u003e, several TE families, including LINEs, have been identified near detoxification genes, supporting the association between TE activity and gene regulation [\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e, \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e]. Similarly, in the whitefly \u003cem\u003eBemisia tabaci\u003c/em\u003e, multiple TE insertions were reported, including six linked to known insecticide resistance genes, suggesting a role in both resistance and genome evolution [\u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e]. In the aphid \u003cem\u003eMyzus persicae\u003c/em\u003e, TEs contribute to resistance by disrupting a dominant susceptibility allele, enabling the expression of a recessive resistance allele [\u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e]. These studies demonstrate how TEs can drive adaptation under environmental and genetic stressors highlighting a potential role of TEs in the adaptation of agriculturally important pest species such as \u003cem\u003eC. picta\u003c/em\u003e and \u003cem\u003eC. melanoneura\u003c/em\u003e on pesticides.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003e\u003cem\u003eCacopsylla\u003c/em\u003e is a diverse genus of phytophagous insects which includes several important vectors of phytoplasma, such as Apple Proliferation (AP), a serious threat to agriculture. Using a time-calibrated phylogenetic approach, we estimated the crown divergence of this genus between the Early Miocene (~\u0026thinsp;18.4 MYA) and the Middle Miocene (~\u0026thinsp;12.7 MYA). Within \u003cem\u003eCacopsylla\u003c/em\u003e, two major clades were identified, largely differentiated by their overwintering strategies and voltinism, ecological traits that might reflect adaptations to environmental changes over the past 10\u0026nbsp;million years. Interestingly, although \u003cem\u003eC. melanoneura\u003c/em\u003e and \u003cem\u003eC. picta\u003c/em\u003e are the only \u003cem\u003eCacopsylla\u003c/em\u003e species known to be vector of \u0026lsquo;\u003cem\u003eCa.\u003c/em\u003e Phytoplasma mali\u0026rsquo; and both develop on apple trees, we found them to be phylogenetically distantly related. The divergence of \u003cem\u003eC. picta\u003c/em\u003e from the most recent common ancestor of \u003cem\u003eC. melanoneura\u003c/em\u003e was estimated to have occurred between 8.6 and 11.5 MYA, during the Late Miocene. These findings reinforce the hypothesis that these two species vectoring AP phytoplasma vectoring species followed independent evolutionary trajectories and likely acquired the ability to transmit \u0026lsquo;\u003cem\u003eCa.\u003c/em\u003e P. mali\u0026rsquo; independently. Furthermore, \u003cem\u003eC. mali\u003c/em\u003e, another apple-associated psyllid that is not a confirmed vector of \u0026lsquo;\u003cem\u003eCa.\u003c/em\u003e P. mali\u0026rsquo;, was found to belong to distinct clade and was never recovered as a sister taxon to either \u003cem\u003eC. melanoneura\u003c/em\u003e or \u003cem\u003eC. picta\u003c/em\u003e. Based on the current results, it is not possible to clearly identify the ancestral clade, although Clade I appears relatively younger than Clade II. Finally, our analyses of transposable elements suggest that life history traits, such as host preference, overwintering strategy and voltinism, may influence recent genome rearrangements. These patterns are more pronounced in the representatives from the generally univoltine and overwintering Clade I, supporting the idea that some repetitive elements may play functional roles in seasonal migration, ecological adaptation, pathogen transmission and potentially in the evolution of pesticide resistance. Future studies are needed to clarify how transposable element dynamics, and the expansion of repetitive sequences shape genomic plasticity and resilience in these agriculturally important pests.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cul type=\"disc\"\u003e\n \u003cli\u003eAP \u0026ndash; Apple Proliferation\u003c/li\u003e\n \u003cli\u003eBF \u0026ndash; Bayes Factor\u003c/li\u003e\n \u003cli\u003eBI \u0026ndash; Bayesian Inference\u003c/li\u003e\n \u003cli\u003eBS \u0026ndash; Bootstrap\u003c/li\u003e\n \u003cli\u003eCOI \u0026ndash; Cytochrome c Oxidase Subunit I\u003c/li\u003e\n \u003cli\u003eESS \u0026ndash; Effective Sampling Size\u003c/li\u003e\n \u003cli\u003eHPD \u0026ndash; Highest Posterior Density\u003c/li\u003e\n \u003cli\u003eLINEs \u0026ndash; Long Interspersed Nuclear Elements\u003c/li\u003e\n \u003cli\u003eLTRs \u0026ndash; Long Terminal Repeats\u003c/li\u003e\n \u003cli\u003eMCC \u0026ndash; Maximum Clade Credibility\u003c/li\u003e\n \u003cli\u003eML \u0026ndash; Maximum Likelihood\u003c/li\u003e\n \u003cli\u003eMLE \u0026ndash; Marginal Likelihood Estimation\u003c/li\u003e\n \u003cli\u003eMRCA \u0026ndash; Most Recent Common Ancestor\u003c/li\u003e\n \u003cli\u003eMYA \u0026ndash; Million Years Ago\u003c/li\u003e\n \u003cli\u003ePCGs \u0026ndash; Protein-Coding Genes\u003c/li\u003e\n \u003cli\u003ePP \u0026ndash; Posterior Probabilities\u003c/li\u003e\n \u003cli\u003eRC- Rolling Circle Transposon\u003c/li\u003e\n \u003cli\u003eSINEs \u0026ndash; Short Interspersed Nuclear Elements\u003c/li\u003e\n \u003cli\u003eTEs \u0026ndash; Transposable Elements\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Declarations","content":"\u003cp\u003eETHICS APPROVAL AND CONSENT TO PARTICIPATE\u003c/p\u003e\n\u003cp\u003eNot applicable\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCONSENT FOR PUBLICATION\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003eAVAILABILITY OF DATA AND MATERIALS\u003c/p\u003e\n\u003cp\u003eNCBI BIO PROJECT: PRJNA1312285\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCOMPETING INTERESTS\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests\u003c/p\u003e\n\u003cp\u003eFUNDING \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis work was supported by a joint project funded by the province of Bolzano-Bozen and the Austrian Science Fund FWF (project I4639-B) to Hannes Schuler and Christian Stauffer, by a joint project of the province of Bolzano-Bozen and the Luxembourg National Research Fund FNR to Hannes Schuler and by a cofounded Fondazione Edmund Mach/APOT (project SCOPAZZI) to Omar Rota Stabelli, Guanfranco Anfora and Lino Ometto\u003c/p\u003e\n\u003cp\u003eACKNOWLEDGMENTS\u003c/p\u003e\n\u003cp\u003eWe are very grateful to Daniel Burckhardt for his critical comments and suggestions. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAUTHORS\u0026rsquo; CONTRIBUTIONS\u003c/p\u003e\n\u003cp\u003eLR, L\u0026Scaron;S, EK, JMH, GA, CS, LO, ORS, and HS conceived and designed the study. HS, CS, GA and ORS secured the funding. EC and LO coordinated the sequencing. FC and TA assembled the nuclear genomes. JMH assembled the mitochondrial genomes with input from NZ. L\u0026Scaron;S performed the phylogenetic analyses with input from ORS and JMH. LR and LO performed the transposable elements analyses. LR, L\u0026Scaron;S, EC and JMH wrote the paper with contribution from all authors. All authors discussed the results and approved the article. \u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBurckhardt D, Ouvrard D, Percy DM. An updated classification of the jumping plant-lice (Hemiptera: Psylloidea) integrating molecular and morphological evidence. Eur J Taxon. 2021;736:137\u0026ndash;82. https://doi.org/10.5852/ejt.2021.736.1257.\u003c/li\u003e\n\u003cli\u003eLi D, Zhang C, Tong Z, Su D, Zhang G, Zhang S, et al. Transcriptome response comparison between vector and non-vector aphids after feeding on virus-infected wheat plants. BMC Genomics. 2020;21:638. https://doi.org/10.1186/s12864-020-07057-0.\u003c/li\u003e\n\u003cli\u003eJarausch B, Jarausch W. Psyllid Vectors and their Control. In: Weintraub PG, Jones P, editors. Phytoplasmas: Genomes, Plant Hosts and Vectors. Wallingford, UK: CAB International; 2010.\u003c/li\u003e\n\u003cli\u003eRao GP, Bertaccini A, Fiore N, Liefting LW. Phytoplasmas: Plant Pathogenic Bacteria - I: Characterisation and Epidemiology of Phytoplasma - Associated Diseases. 2018.\u003c/li\u003e\n\u003cli\u003eSeem\u0026uuml;ller E, Schneider B. \u0026ldquo;Candidatus Phytoplasma mali\u0026rdquo;, \u0026ldquo;\u003cem\u003eCandidatus\u003c/em\u003e Phytoplasma pyri\u0026rdquo; and \u0026ldquo;\u003cem\u003eCandidatus\u003c/em\u003e Phytoplasma prunorum\u0026rdquo;, the causal agents of apple proliferation, pear decline and European stone fruit yellows, respectively. Int J Syst Evol Microbiol. 2004;54 Pt 4:1217\u0026ndash;26. https://doi.org/10.1099/ijs.0.02823-0.\u003c/li\u003e\n\u003cli\u003eJanik K, Barthel D, Oppedisano T, Anfora G. Apple Proliferation: A Joint Review. 2020.\u003c/li\u003e\n\u003cli\u003eSeem\u0026uuml;ller E, Carraro L, Jarausch W, Schneider B. CHAPTER 14: Apple Proliferation Phytoplasma. In: Hadidi A, Barba M, Candresse T, Jelkmann W, editors. Virus and Virus-Like Diseases of Pome and Stone Fruits. APS Publications; 2011. p. 67\u0026ndash;73. https://doi.org/10.1094/9780890545010.014.\u003c/li\u003e\n\u003cli\u003eTedeschi R, Jarausch B, Delic D, Weintraub PG. Actual distribution of fruit tree and grapevine phytoplasma diseases and their vectors in Europe and neighboring regions. Phytopathogenic Mollicutes. 2013;3:3\u0026ndash;4.\u003c/li\u003e\n\u003cli\u003eBertaccini A. COST Action FA0807 Phytoplasmas and phytoplasma disease management: how to reduce their economic impact. 2014.\u003c/li\u003e\n\u003cli\u003eFischnaller S, Parth M, Messner M, al et. Occurrence of different \u003cem\u003eCacopsylla\u003c/em\u003e species in apple orchards in South Tyrol (Italy) and detection of apple proliferation phytoplasma in \u003cem\u003eCacopsylla\u003c/em\u003e \u003cem\u003emelanoneura\u003c/em\u003e and \u003cem\u003eCacopsylla picta\u003c/em\u003e. Cicadina. 2017;17:37\u0026ndash;51.\u003c/li\u003e\n\u003cli\u003eJarausch B, Fuchs A, Schwind N, Krczal G, Jarausch W. \u003cem\u003eCacopsylla picta\u003c/em\u003e as most important vector for \u0026ldquo;\u003cem\u003eCandidatus\u003c/em\u003e Phytoplasma mali\u0026rdquo; in Germany and neighbouring regions. Bull Insectology. 2007;60:189\u0026ndash;90.\u003c/li\u003e\n\u003cli\u003eOppedisano T, Panassiti B, Pedrazzoli F, Mittelberger C, Bianchedi PL, Angeli G, et al. Importance of psyllids\u0026rsquo; life stage in the epidemiology of apple proliferation phytoplasma. J Pest Sci (2004). 2020;93:49\u0026ndash;61. https://doi.org/10.1007/s10340-019-01130-8.\u003c/li\u003e\n\u003cli\u003eTedeschi R, Baldessari M, Mazzoni V, Trona F, Angeli G. Population dynamics of \u003cem\u003eCacopsylla melanoneura\u003c/em\u003e (Hemiptera: Psyllidae) in northeast Italy and its role in the apple proliferation epidemiology in apple orchards. J Econ Entomol. 2012;105:322\u0026ndash;8. https://doi.org/10.1603/ec11237.\u003c/li\u003e\n\u003cli\u003eCandian V, Monti M, Tedeschi R. Temporal dynamics of \u0026ldquo;Ca. Phytoplasma mali\u0026rdquo; load in the insect vector \u003cem\u003eCacopsylla melanoneura\u003c/em\u003e. Insects. 2020;11. https://doi.org/10.3390/insects11090592.\u003c/li\u003e\n\u003cli\u003eCorretto E, Trenti M, Starhova Serbina L, Howie JM, Dittmer J, Kerschbamer C, et al. Multiple factors driving the acquisition efficiency of apple proliferation phytoplasma in \u003cem\u003eCacopsylla melanoneura\u003c/em\u003e. J Pest Sci (2004). 2024;97:1299\u0026ndash;314. https://doi.org/10.1007/s10340-023-01699-1.\u003c/li\u003e\n\u003cli\u003eSchuler H, Dittmer J, Borruso L, Galli J, Fischnaller S, Anfora G, et al. Investigating the microbial community of \u003cem\u003eCacopsylla\u003c/em\u003e spp. as potential factor in vector competence of phytoplasma. Environ Microbiol. 2022;24:4771\u0026ndash;86. https://doi.org/10.1111/1462-2920.16138.\u003c/li\u003e\n\u003cli\u003eOuvrard D, Chalise P, Percy DM. Host-plant leaps versus host-plant shuffle: a global survey reveals contrasting patterns in an oligophagous insect group (Hemiptera, Psylloidea). Syst Biodivers. 2015;13:434\u0026ndash;54. https://doi.org/10.1080/14772000.2015.1046969.\u003c/li\u003e\n\u003cli\u003eBurckhardt D, Ouvrard D, Queiroz D, Percy D. Psyllid Host-Plants (Hemiptera: Psylloidea): Resolving a Semantic Problem. Florida Entomologist. 2014;97:242\u0026ndash;6. https://doi.org/10.1653/024.097.0132.\u003c/li\u003e\n\u003cli\u003eHodkinson ID. Life cycle variation and adaptation in jumping plant lice (Insecta: Hemiptera: Psylloidea): a global synthesis. J Nat Hist. 2009;43:65\u0026ndash;179. https://doi.org/10.1080/00222930802354167.\u003c/li\u003e\n\u003cli\u003eMalagnini V, Pedrazzoli F, Papetti C, Cainelli C, Zasso R, Gualandri V, et al. Ecological and genetic differences between \u003cem\u003eCacopsylla melanoneura\u003c/em\u003e (Hemiptera, Psyllidae) populations reveal species host plant preference. PLoS One. 2013;8:e69663\u0026ndash;e69663. https://doi.org/10.1371/journal.pone.0069663.\u003c/li\u003e\n\u003cli\u003eOettl S, Schlink K. Molecular identification of two vector species, \u003cem\u003eCacopsylla melanoneura\u003c/em\u003e and \u003cem\u003eCacopsylla picta\u003c/em\u003e (Hemiptera: Psyllidae), of Apple Proliferation disease and further common psyllids of Northern Italy. J Econ Entomol. 2015;108:2174\u0026ndash;83. https://doi.org/10.1093/jee/tov204.\u003c/li\u003e\n\u003cli\u003ePercy DM, Crampton‐Platt A, Sveinsson S, Lemmon AR, Lemmon EM, Ouvrard D, et al. Resolving the psyllid tree of life: phylogenomic analyses of the superfamily Psylloidea (Hemiptera). Syst Entomol. 2018;43:762\u0026ndash;76. https://doi.org/10.1111/syen.12302.\u003c/li\u003e\n\u003cli\u003e\u0026Scaron;af\u0026aacute;řov\u0026aacute; D, Zrn\u0026iacute;kov\u0026aacute; E, Holu\u0026scaron;ov\u0026aacute; K, Ouředn\u0026iacute;čkov\u0026aacute; J, Star\u0026yacute; M, Navr\u0026aacute;til M. Molecular Characterization of Mitogenome of \u003cem\u003eCacopsylla picta\u003c/em\u003e and \u003cem\u003eCacopsylla melanoneura\u003c/em\u003e, Two Vector Species of \u0026lsquo;Candidatus Phytoplasma mali.\u0026rsquo; Agronomy. 2023;13:2210. https://doi.org/10.3390/agronomy13092210.\u003c/li\u003e\n\u003cli\u003eCorretto E, \u0026Scaron;tarhov\u0026aacute; Serbina L, Dittmer J, Michalik A, Schuler H. Evolutionary dynamics of obligate endosymbiosis in the psyllid genus \u003cem\u003eCacopsylla\u003c/em\u003e. Commun Biol. 2025.\u003c/li\u003e\n\u003cli\u003eBourque G, Burns KH, Gehring M, Gorbunova V, Seluanov A, Hammell M, et al. Ten things you should know about transposable elements. Genome Biol. 2018;19:199. https://doi.org/10.1186/s13059-018-1577-z.\u003c/li\u003e\n\u003cli\u003eWang X, Fang X, Yang P, Jiang X, Jiang F, Zhao D, et al. The locust genome provides insight into swarm formation and long-distance flight. Nat Commun. 2014;5:2957. https://doi.org/10.1038/ncomms3957.\u003c/li\u003e\n\u003cli\u003eMakałowski W, Gotea V, Pande A, Makałowska I. Transposable Elements: classification, identification, and their use as a tool for comparative genomics. 2019. p. 177\u0026ndash;207. https://doi.org/10.1007/978-1-4939-9074-0_6.\u003c/li\u003e\n\u003cli\u003ePetersen M, Armis\u0026eacute;n D, Gibbs RA, Hering L, Khila A, Mayer G, et al. Diversity and evolution of the transposable element repertoire in arthropods with particular reference to insects. BMC Ecol Evol. 2019;19:11. https://doi.org/10.1186/s12862-018-1324-9.\u003c/li\u003e\n\u003cli\u003eMarcais G, Kingsford C. A fast, lock-free approach for efficient parallel counting of occurrences of k-mers. Bioinformatics. 2011;27:764\u0026ndash;70. https://doi.org/10.1093/bioinformatics/btr011.\u003c/li\u003e\n\u003cli\u003eVurture GW, Sedlazeck FJ, Nattestad M, Underwood CJ, Fang H, Gurtowski J, et al. GenomeScope: fast reference-free genome profiling from short reads. Bioinformatics. 2017;33:2202\u0026ndash;4. https://doi.org/10.1093/bioinformatics/btx153.\u003c/li\u003e\n\u003cli\u003eSimpson JT. Exploring genome characteristics and sequence quality without a reference. Bioinformatics. 2014;30:1228\u0026ndash;35. https://doi.org/10.1093/bioinformatics/btu023.\u003c/li\u003e\n\u003cli\u003eMartin M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J. 2011;17. https://doi.org/10.14806/ej.17.1.200.\u003c/li\u003e\n\u003cli\u003eMagoc T, Salzberg SL. FLASH: fast length adjustment of short reads to improve genome assemblies. Bioinformatics. 2011;27:2957\u0026ndash;63. https://doi.org/10.1093/bioinformatics/btr507.\u003c/li\u003e\n\u003cli\u003eMarco-Sola S, Sammeth M, Guigo R, Ribeca P. The GEM mapper: fast, accurate and versatile alignment by filtration. Nat Methods. 2012. https://doi.org/10.1038/nmeth.2221.\u003c/li\u003e\n\u003cli\u003eWood D, Salzberg S. Kraken: ultrafast metagenomic sequence classification using exact alignments. Genome Biol. 2014;15:R46\u0026ndash;R46.\u003c/li\u003e\n\u003cli\u003eWeisenfeld NI, Kumar V, Shah P, Church DM, Jaffe DB. Direct determination of diploid genome sequences. Genome Res. 2017;27:757\u0026ndash;67. https://doi.org/10.1101/gr.214874.116.\u003c/li\u003e\n\u003cli\u003eWeisenfeld NI, Yin S, Sharpe T, Lau B, Hegarty R, Holmes L, et al. Comprehensive variation discovery in single human genomes. Nat Genet. 2014;46:1350\u0026ndash;5. https://doi.org/10.1038/ng.3121.\u003c/li\u003e\n\u003cli\u003eSahlin K, Vezzi F, Nystedt B, Lundeberg J, Arvestad L. BESST - Efficient scaffolding of large fragmented assemblies. BMC Bioinformatics. 2014;15:281. https://doi.org/10.1186/1471-2105-15-281.\u003c/li\u003e\n\u003cli\u003eCruz F, Julca I, Gomez-Garrido J, Loska D, Marcet-Houben M, Cano E, et al. Genome sequence of the olive tree, \u003cem\u003eOlea europaea\u003c/em\u003e. Gigascience. 2016;5:29. https://doi.org/10.1186/s13742-016-0134-5.\u003c/li\u003e\n\u003cli\u003ePuerma E, Orengo DJ, Cruz F, Gomez-Garrido J, Librado P, Salguero D, et al. The high-quality genome sequence of the oceanic island endemic species Drosophila guanche reveals signals of adaptive evolution in genes related to flight and genome stability. Genome Biol Evol. 2018;10:1956\u0026ndash;69. https://doi.org/10.1093/gbe/evy135.\u003c/li\u003e\n\u003cli\u003ePryszcz LP, Gabaldon T. Redundans: an assembly pipeline for highly heterozygous genomes. Nucleic Acids Res. 2016;44. https://doi.org/10.1093/nar/gkw294.\u003c/li\u003e\n\u003cli\u003eMapleson D, Garcia Accinelli G, Kettleborough G, Wright J, Clavijo BJ. KAT: a K-mer analysis toolkit to quality control NGS datasets and genome assemblies. Bioinformatics. 2017;33:574\u0026ndash;6. https://doi.org/10.1093/bioinformatics/btw663.\u003c/li\u003e\n\u003cli\u003eSim\u0026atilde;o FA, Waterhouse RM, Ioannidis P, Kriventseva E V, Zdobnov EM. BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs. Bioinformatics. 2015;31. https://doi.org/10.1093/bioinformatics/btv351.\u003c/li\u003e\n\u003cli\u003eSmit AFA, Hubley R, Green P. RepeatMasker Open.\u003c/li\u003e\n\u003cli\u003eFlynn JM, Hubley R, Goubert C, Rosen J, Clark AG, Feschotte C, et al. RepeatModeler2 for automated genomic discovery of transposable element families. Proceedings of the National Academy of Sciences. 2020;117:9451\u0026ndash;7. https://doi.org/10.1073/pnas.1921046117.\u003c/li\u003e\n\u003cli\u003eNov\u0026aacute;k P, Neumann P, Macas J. Graph-based clustering and characterization of repetitive sequences in next-generation sequencing data. BMC Bioinformatics. 2010;11:378. https://doi.org/10.1186/1471-2105-11-378.\u003c/li\u003e\n\u003cli\u003eNov\u0026aacute;k P, Neumann P, Pech J, Steinhaisl J, Macas J. RepeatExplorer: a Galaxy-based web server for genome-wide characterization of eukaryotic repetitive elements from next-generation sequence reads. Bioinformatics. 2013;29:792\u0026ndash;3. https://doi.org/10.1093/bioinformatics/btt054.\u003c/li\u003e\n\u003cli\u003eGoubert C. Assembly-Free Detection and Quantification of Transposable Elements with dnaPipeTE. 2023. p. 25\u0026ndash;43. https://doi.org/10.1007/978-1-0716-2883-6_2.\u003c/li\u003e\n\u003cli\u003eMeng G, Li Y, Yang C, Liu S. MitoZ: a toolkit for animal mitochondrial genome assembly, annotation and visualization. Nucleic Acids Res. 2019;47:e63\u0026ndash;e63. https://doi.org/10.1093/nar/gkz173.\u003c/li\u003e\n\u003cli\u003eKurtzer GM, Sochat V, Bauer MW. Singularity: Scientific containers for mobility of compute. PLoS One. 2017;12:e0177459\u0026ndash;e0177459. https://doi.org/10.1371/journal.pone.0177459.\u003c/li\u003e\n\u003cli\u003eBernt M, Donath A, Juhling F, Externbrink F, Florentz C, Fritzsch G, et al. MITOS: improved \u003cem\u003ede novo\u003c/em\u003e metazoan mitochondrial genome annotation. Mol Phylogenet Evol. 2013;69:313\u0026ndash;9. https://doi.org/10.1016/j.ympev.2012.08.023.\u003c/li\u003e\n\u003cli\u003eDonath A, Juhling F, Al-Arab M, Bernhart SH, Reinhardt F, Stadler PF, et al. Improved annotation of protein-coding genes boundaries in metazoan mitochondrial genomes. Nucleic Acids Res. 2019;47:10543\u0026ndash;52. https://doi.org/10.1093/nar/gkz833.\u003c/li\u003e\n\u003cli\u003eBouckaert R, Vaughan TG, Barido-Sottani J, Duchene S, Fourment M, Gavryushkina A, et al. BEAST 2.5: An advanced software platform for Bayesian evolutionary analysis. PLoS Comput Biol. 2019;15:e1006650\u0026ndash;e1006650. https://doi.org/10.1371/journal.pcbi.1006650.\u003c/li\u003e\n\u003cli\u003eDrummond AJ, Rambaut A. BEAST: Bayesian evolutionary analysis by sampling trees. BMC Evol Biol. 2007;7:214. https://doi.org/10.1186/1471-2148-7-214.\u003c/li\u003e\n\u003cli\u003eMinh BQ, Schmidt HA, Chernomor O, Schrempf D, Woodhams MD, von Haeseler A, et al. IQ-TREE 2: new models and efficient methods for phylogenetic inference in the genomic era. Mol Biol Evol. 2020;37:1530\u0026ndash;4. https://doi.org/10.1093/molbev/msaa015.\u003c/li\u003e\n\u003cli\u003eKatoh K, Standley DM. MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability. Mol Biol Evol. 2013;30:772\u0026ndash;80. https://doi.org/10.1093/molbev/mst010.\u003c/li\u003e\n\u003cli\u003eBouckaert RR, Drummond AJ. bModelTest: Bayesian phylogenetic site model averaging and model comparison. BMC Evol Biol. 2017;17:42. https://doi.org/10.1186/s12862-017-0890-6.\u003c/li\u003e\n\u003cli\u003eMiller MA, Schwartz T, Hoover P, Yoshimoto K, Sivagnanam S, Majumdar A. The CIPRES workbench. In: Proceedings of the 2015 XSEDE Conference on Scientific Advancements Enabled by Enhanced Cyberinfrastructure - XSEDE \u0026rsquo;15. New York, New York, USA: ACM Press; 2015. p. 1\u0026ndash;8. https://doi.org/10.1145/2792745.2792784.\u003c/li\u003e\n\u003cli\u003eLi H, Leavengood Jr. JM, Chapman EG, Burkhardt D, Song F, Jiang P, et al. Mitochondrial phylogenomics of Hemiptera reveals adaptive innovations driving the diversification of true bugs. Proc Biol Sci. 2017;284. https://doi.org/10.1098/rspb.2017.1223.\u003c/li\u003e\n\u003cli\u003eOuvrard DBDGD. The oldest jumping plant-louse (Insecta: Hemiptera: Sternorrhyncha) with comments on the classification and nomenclature of the Palaeogene Psylloidea. Acta Musei Moraviae, Scientiae biologicae (Brno). 2013;98:21\u0026ndash;33.\u003c/li\u003e\n\u003cli\u003eBurckhardt D, Drohojowska J, \u0026Scaron;tarhov\u0026aacute; Serbina L, Malenovsk\u0026yacute; I. First record of jumping plant lice of the family Liviidae (Hemiptera, Sternorrhyncha, Psylloidea) from Dominican amber. Neues Jahrbuch f\u0026uuml;r Geologie und Pal\u0026auml;ontologie - Abhandlungen Band . 2024;:215\u0026ndash;27.\u003c/li\u003e\n\u003cli\u003eBaele G, Lemey P, Bedford T, Rambaut A, Suchard MA, Alekseyenko A V. improving the accuracy of demographic and molecular clock model comparison while accommodating phylogenetic uncertainty. Mol Biol Evol. 2012;29:2157\u0026ndash;67. https://doi.org/10.1093/molbev/mss084.\u003c/li\u003e\n\u003cli\u003eXie W, Lewis PO, Fan Y, Kuo L, Chen M-H. improving marginal likelihood estimation for bayesian phylogenetic model selection. Syst Biol. 2011;60:150\u0026ndash;60. https://doi.org/10.1093/sysbio/syq085.\u003c/li\u003e\n\u003cli\u003eSuchard MA, Lemey P, Baele G, Ayres DL, Drummond AJ, Rambaut A. Bayesian phylogenetic and phylodynamic data integration using BEAST 1.10. Virus Evol. 2018;4. https://doi.org/10.1093/ve/vey016.\u003c/li\u003e\n\u003cli\u003eJo E, Cho G. The complete mitochondrial genome of \u003cem\u003eCacopsylla burckhardti\u003c/em\u003e (Hemiptera, Psylloidea, Psyllidae). Biodivers Data J. 2022;10:e85094\u0026ndash;e85094. https://doi.org/10.3897/BDJ.10.e85094.\u003c/li\u003e\n\u003cli\u003eQue S, Yu L, Xin T, Zou Z, Hu L, Xia B. Complete mitochondrial genome of \u003cem\u003eCacopsylla coccinae\u003c/em\u003e (Hemiptera: Psyllidae). Mitochondrial DNA A DNA Mapp Seq Anal. 2016;27:3169\u0026ndash;70. https://doi.org/10.3109/19401736.2015.1007319.\u003c/li\u003e\n\u003cli\u003eWang Y, Cen Y, He Y, Wu Y, Huang S, Lu J. The first complete mitochondrial genome sequence of \u003cem\u003eCacopsylla citrisuga\u003c/em\u003e (Yang \u0026amp; Li), a new insect vector of Huanglongbing in Yunnan Province, China. Mitochondrial DNA B Resour. 2021;6:575\u0026ndash;7. https://doi.org/10.1080/23802359.2021.1875908.\u003c/li\u003e\n\u003cli\u003eWang W, Dong Z, Du Z, Wu P. Genome-scale approach to reconstructing the phylogenetic tree of psyllids (superfamily Psylloidea) with account of systematic bias. Mol Phylogenet Evol. 2023;189:107924. https://doi.org/10.1016/j.ympev.2023.107924.\u003c/li\u003e\n\u003cli\u003eJohnson KP, Dietrich CH, Friedrich F, Beutel RG, Wipfler B, Peters RS, et al. Phylogenomics and the evolution of hemipteroid insects. 2018;115. https://doi.org/10.5061/dryad.t4f4g85.\u003c/li\u003e\n\u003cli\u003eDrohojowska J, Węgierek P, Sol\u0026oacute;rzano Kraemer MM. First Psylloidea (Hemiptera: Sternorrhyncha) in Miocene Mexican amber. Palaontol Z. 2016;90:185\u0026ndash;8. https://doi.org/10.1007/s12542-016-0290-z.\u003c/li\u003e\n\u003cli\u003eZhang T, Luo X, Yao Y, Ren D. A new fossil psyllid, \u003cem\u003eCacopsylla trigona\u003c/em\u003e sp. nov. (Hemiptera: Psylloidea: Psyllidae), from the Miocene of China. Palaeoentomology. 2019;2:413\u0026ndash;7. https://doi.org/10.11646/palaeoentomology.2.5.2.\u003c/li\u003e\n\u003cli\u003eSteffek R, Follak S, Sauvion N, Labonne G, MacLeod A. Distribution of \u0026lsquo;\u003cem\u003eCandidatus \u003c/em\u003ePhytoplasma prunorum\u0026rsquo; and its vector \u003cem\u003eCacopsylla pruni \u003c/em\u003ein European fruit‐growing areas: a review. EPPO Bulletin. 2012;42:191\u0026ndash;202. https://doi.org/10.1111/epp.2567.\u003c/li\u003e\n\u003cli\u003ePeccoud J, Labonne G, Sauvion N. Molecular Test to Assign Individuals within the \u003cem\u003eCacopsylla pruni\u003c/em\u003e Complex. PLoS One. 2013;8:e72454. https://doi.org/10.1371/journal.pone.0072454.\u003c/li\u003e\n\u003cli\u003eSauvion N, Peccoud J, Meynard C, Ouvrard D. Occurrence data for the two cryptic species of \u003cem\u003eCacopsylla pruni\u003c/em\u003e (Hemiptera: Psylloidea). Biodivers Data J. 2021;9. https://doi.org/10.3897/BDJ.9.e68860.\u003c/li\u003e\n\u003cli\u003eMilyaeva PA, Kukushkina I V., Kim AI, Nefedova LN. Stress Induced Activation of LTR Retrotransposons in the \u003cem\u003eDrosophila melanogaster\u003c/em\u003e Genome. Life. 2023;13:2272. https://doi.org/10.3390/life13122272.\u003c/li\u003e\n\u003cli\u003ede Oliveira DS, Rosa MT, Vieira C, Loreto ELS. Oxidative and radiation stress induces transposable element transcription in \u003cem\u003eDrosophila melanogaster\u003c/em\u003e. J Evol Biol. 2021;34:628\u0026ndash;38. https://doi.org/10.1111/jeb.13762.\u003c/li\u003e\n\u003cli\u003eKneuss E, Munaf\u0026ograve; M, Eastwood EL, Deumer U-S, Preall JB, Hannon GJ, et al. Specialization of the \u003cem\u003eDrosophila\u003c/em\u003e nuclear export family protein Nxf3 for piRNA precursor export. Genes Dev. 2019;33:1208\u0026ndash;20. https://doi.org/10.1101/gad.328690.119.\u003c/li\u003e\n\u003cli\u003eLawlor MA, Ellison CE. Evolutionary dynamics between transposable elements and their host genomes: mechanisms of suppression and escape. Curr Opin Genet Dev. 2023;82:102092. https://doi.org/10.1016/j.gde.2023.102092.\u003c/li\u003e\n\u003cli\u003eSlotkin RK, Martienssen R. Transposable elements and the epigenetic regulation of the genome. Nat Rev Genet. 2007;8:272\u0026ndash;85. https://doi.org/10.1038/nrg2072.\u003c/li\u003e\n\u003cli\u003eSignor S, Yocum G, Bowsher J. Life stage and the environment as effectors of transposable element activity in two bee species. J Insect Physiol. 2022;137:104361. https://doi.org/10.1016/j.jinsphys.2022.104361.\u003c/li\u003e\n\u003cli\u003eTahami MS, Vargas-Chavez C, Poikela N, Coronado-Zamora M, Gonz\u0026aacute;lez J, Kankare M. Transposable elements in \u003cem\u003eDrosophila montana\u003c/em\u003e from harsh cold environments. Mob DNA. 2024;15:18. https://doi.org/10.1186/s13100-024-00328-7.\u003c/li\u003e\n\u003cli\u003eSchmidt JM, Good RT, Appleton B, Sherrard J, Raymant GC, Bogwitz MR, et al. Copy number variation and transposable elements feature in recent, ongoing adaptation at the Cyp6g1 locus. PLoS Genet. 2010;6:e1000998. https://doi.org/10.1371/journal.pgen.1000998.\u003c/li\u003e\n\u003cli\u003eDaborn PJ, Yen JL, Bogwitz MR, Le Goff G, Feil E, Jeffers S, et al. A Single P450 Allele Associated with Insecticide Resistance in \u003cem\u003eDrosophila\u003c/em\u003e. Science (1979). 2002;297:2253\u0026ndash;6. https://doi.org/10.1126/science.1074170.\u003c/li\u003e\n\u003cli\u003eKlai K, Ch\u0026eacute;nais B, Zidi M, Djebbi S, Caruso A, Denis F, et al. Screening of \u003cem\u003eHelicoverpa armigera\u003c/em\u003e mobilome revealed transposable element insertions in insecticide resistance genes. Insects. 2020;11:879. https://doi.org/10.3390/insects11120879.\u003c/li\u003e\n\u003cli\u003eRahman M-M, Omoto C, Kim J. Genome-wide exploration of long non-coding RNAs of \u003cem\u003eHelicoverpa armigera\u003c/em\u003e in response to pyrethroid insecticide resistance. Insects. 2024;15:146. https://doi.org/10.3390/insects15030146.\u003c/li\u003e\n\u003cli\u003eZidi M, Klai K, Confais J, Ch\u0026eacute;nais B, Caruso A, Denis F, et al. Genome-wide screening of transposable elements in the whitefly, \u003cem\u003eBemisia tabaci\u003c/em\u003e (Hemiptera: Aleyrodidae), revealed insertions with potential insecticide resistance implications. Insects. 2022;13:396. https://doi.org/10.3390/insects13050396.\u003c/li\u003e\n\u003cli\u003ePanini M, Chiesa O, Troczka BJ, Mallott M, Manicardi GC, Cassanelli S, et al. Transposon-mediated insertional mutagenesis unmasks recessive insecticide resistance in the aphid \u003cem\u003eMyzus persicae\u003c/em\u003e. Proceedings of the National Academy of Sciences. 2021;118. https://doi.org/10.1073/pnas.2100559118.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table","content":"\u003cp\u003eTable 1 is available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-genomics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"gics","sideBox":"Learn more about [BMC Genomics](http://bmcgenomics.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/gics","title":"BMC Genomics","twitterHandle":"#BMCGenomics","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Psylloidea, Genome assembly, Mitochondrial genes, Time-calibrated phylogeny, Transposable elements, Apple Proliferations, Life history traits","lastPublishedDoi":"10.21203/rs.3.rs-7518317/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7518317/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eThe psyllid genus \u003cem\u003eCacopsylla\u003c/em\u003e includes several species that act as vectors for phytoplasma-associated diseases affecting plantations across Europe. Among them, \u003cem\u003eCacopsylla melanoneura\u003c/em\u003e and \u003cem\u003eCacopsylla picta\u003c/em\u003e are the primary vectors of \u0026lsquo;\u003cem\u003eCandidatus\u003c/em\u003e Phytoplasma mali\u0026rsquo;, the phloem-restricted bacterium responsible for Apple Proliferation disease in Europe. To explore whether vector competence in these species reflects shared ancestry or independent evolution, we assembled mitochondrial and draft nuclear genomes of Italian populations of \u003cem\u003eC. melanoneura\u003c/em\u003e and \u003cem\u003eC. picta\u003c/em\u003e and reconstructed time-calibrated phylogenies using 13 mitochondrial protein-coding genes from 12 \u003cem\u003eCacopsylla\u003c/em\u003e species.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003ePhylogenetic analyses revealed two major \u003cem\u003eCacopsylla\u003c/em\u003e clades (Clade I and II) whose divergence times range from the Early Miocene (18.4 MYA; 95% HPD: 10.8\u0026ndash;27.5) to the Middle Miocene (12.7 MYA; 95% HPD: 9.7\u0026ndash;16.0). Both \u003cem\u003eC. melanoneura\u003c/em\u003e and \u003cem\u003eC. picta\u003c/em\u003e are within Clade I, which is predominantly composed of univoltine species that overwinter on conifers. Within this clade, \u003cem\u003eCacopsylla melanoneura\u003c/em\u003e is more closely related to the plum psyllid \u003cem\u003eCacopsylla pruni\u003c/em\u003e than to the apple-associated \u003cem\u003eC. picta\u003c/em\u003e and \u003cem\u003eCacopsylla mali\u003c/em\u003e, the latter belonging to Clade II. Draft nuclear genomes revealed significant differences in size (438 Mb in \u003cem\u003eC. melanoneura vs.\u003c/em\u003e 631 Mb in \u003cem\u003eC. picta\u003c/em\u003e), largely attributed to repetitive elements. Comparative analyses of repetitive elements across \u003cem\u003eCacopsylla\u003c/em\u003e species revealed a recent expansion of transposable elements, particularly LINE elements, which were slightly more abundant in Clade I and contributed to the larger genome size observed in \u003cem\u003eC. picta\u003c/em\u003e.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eCollectively, our findings provide the first genomic resources for \u003cem\u003eC. melanoneura\u003c/em\u003e, \u003cem\u003eC. picta\u003c/em\u003e, and several other phytoplasma-vectoring \u003cem\u003eCacopsylla\u003c/em\u003e species. We established a robust mitogenomic phylogeny with divergence estimated for this genus showing the presence of two clades with the representatives predominantly associated with different overwintering strategies. Our results further indicate that vectorial capacity in Cacopsylla reflects an independent evolutionary trajectory rather than a shared ancestral origin. This evolutionary framework advances our understanding of the biology and origin of vector competence in this agriculturally important group.\u003c/p\u003e","manuscriptTitle":"Evolutionary genomics and divergence of Cacopsylla species with a special focus on the Apple Proliferation Vectors: Cacopsylla melanoneura and C. picta","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-08 08:52:35","doi":"10.21203/rs.3.rs-7518317/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-09T05:18:47+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-07T16:32:42+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-06T13:23:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"80435290160239534802028994263620443697","date":"2025-09-24T15:52:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"176291106263952455909358352625333679725","date":"2025-09-20T13:07:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"337778187767630179728447456277485460285","date":"2025-09-13T05:25:13+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-12T18:59:21+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-03T12:22:26+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-03T12:22:03+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Genomics","date":"2025-09-02T13:35:31+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-genomics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"gics","sideBox":"Learn more about [BMC Genomics](http://bmcgenomics.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/gics","title":"BMC Genomics","twitterHandle":"#BMCGenomics","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"39bd4e11-9806-4569-ba1a-8307bf1daf09","owner":[],"postedDate":"September 8th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-03-23T16:09:20+00:00","versionOfRecord":{"articleIdentity":"rs-7518317","link":"https://doi.org/10.1186/s12864-026-12622-0","journal":{"identity":"bmc-genomics","isVorOnly":false,"title":"BMC Genomics"},"publishedOn":"2026-03-19 15:58:35","publishedOnDateReadable":"March 19th, 2026"},"versionCreatedAt":"2025-09-08 08:52:35","video":"","vorDoi":"10.1186/s12864-026-12622-0","vorDoiUrl":"https://doi.org/10.1186/s12864-026-12622-0","workflowStages":[]},"version":"v1","identity":"rs-7518317","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7518317","identity":"rs-7518317","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}