Contrasting epigenetics of Ixodes scapularis populations

Contrasting epigenetics of Ixodes scapularis populations | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Contrasting epigenetics of Ixodes scapularis populations Stephanie Guzman-Valencia, Jacob Cassens, Perot Saelao, Abagail Leal, and 15 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7762123/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract Hard ticks are a source of public health concern, in part due to their ability to inhabit different environmental regions, which increases human encounters. In the United States (US), blacklegged ticks ( Ixodes scapularis Say), the primary vector of Lyme disease, exhibit various phenotypes depending on their geographic origin (i.e. northern and southern US ticks). Although genetics may partially explain how blacklegged tick populations acclimate to different environmental conditions across the US, epigenetics may also contribute to their success. Epigenetic mechanisms, such as DNA methylation, might modulate gene expression allowing for rapid adaptation. To gain insight into the potential contribution of DNA methylation, an Enzyme-Linked Immunosorbent Assay (ELISA) was utilized to evaluate differences in DNA methylation levels between blacklegged ticks collected from Minnesota (northern region) and Texas (southern region). DNA methylation profiles from both populations were characterized using bisulfite and nanopore sequencing. Our results revealed significant variability in methylation levels between the southern and northern tick populations and a highly variable relative expression of DNA methyltransferases and demethylases. Overall, northern blacklegged ticks exhibited a reduction in DNA methylation compared to southern ticks. Basic proline-rich protein, sortilin-related receptor, and peptidase M20 domain-containing protein 2-like are among the genes that exhibit a depletion in DNA methylation. Our findings revealed that blacklegged tick populations possess distinctive DNA methylation profiles, which may contribute to their phenotypic plasticity across the US. This study aims to pave the way for future research into the potential molecular mechanisms that allow ticks to successfully acclimatize to their present habitat. Biological sciences/Ecology Earth and environmental sciences/Ecology Biological sciences/Genetics Biological sciences/Molecular biology Biological sciences/Zoology DNA methylation epigenetics ticks DNA methyltransferases Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Lyme disease (LD) is the most prevalent vector-borne disease in the United States (US), with 500,000 estimated cases each year [1–3] and an estimated economic burden of approximately $ 968 million annually [4]. In the eastern US, LD is primarily transmitted by the blacklegged tick, Ixodes scapularis Say. This tick is a three-host tick, capable of transmitting and harboring a wide array of pathogenic microorganisms, including Borrelia burgdorferi (the main causative agent of Lyme disease), Anaplasma phagocytophilum , and Babesia microti [5–7]. Blacklegged ticks can be co-infected with various pathogens simultaneously, which represents a risk for co-infections through the transmission of multiple pathogens in a single bite [8,9]. The lack of efficient tick control methods [3,10], ongoing geographic expansion of tick populations [11–13], and their ability to carry multiple zoonotic pathogens [5–7,9,14,15] collectively contribute to the growing health concern posed by this tick species. Blacklegged ticks have been reported throughout much of the eastern and upper midwestern US [13]. Interestingly, the incidence of pathogens associated with blacklegged ticks shows a disproportionate distribution, with higher transmission rates in northern than in southern states [13,16]. Initially, this variation was attributed to hypothesized differences in vector competence between two presumably different Ixodes species ( Ixodes dammini [found in the northern US] and I. scapularis [found in the southern US]). Nevertheless, mating experiments and phylogenetic analyses determined that these were conspecific populations, resulting in their synonymization to I. scapularis [17–19]. Ticks from southern and northern regions exhibit differences in seasonal activity [20], infection rate [21], host association [22], and host-seeking behavior [23,24]. Specifically, in the southern regions, immature blacklegged ticks display a preference for feeding on B. burgdorferi incompetent reptiles, whereas northern ticks predominantly favor B. burgdorferi competent mammalian hosts, such as the white-footed mouse ( Peromyscus leucopus ) [22]. The divergence in host association may also drive differences in questing behavior, with southern immature life stages maintaining a lower questing height, often remaining beneath the leaf litter. In contrast, northern immatures are more commonly found above the leaf litter, actively searching for hosts [23,25]. These variations in host-seeking behavior and host preference may partially explain the differences in nymphal infection prevalence and tick-borne pathogen transmission between the southeastern and northern US regions [22–24]. However, the genetic and molecular mechanisms that contribute to the observed phenotypic differences among blacklegged ticks from these two different geographic locations remain to be determined. DNA methylation has been documented in the genome of blacklegged tick cell lines (IDE2, IDE8, and ISE18) [26] and is suspected to drive phenotypic plasticity in arthropods [27]. Further, recent assembly and annotation of the I. scapularis genome revealed the presence of epigenetic clusters (polycomb and trithorax group proteins) known to regulate transcription [28]. Whether DNA methylation plays a role in blacklegged tick adaptation to environmental conditions, e.g., temperature, remains unknown [29–31]. Given the potential link between DNA methylation and tick phenotypic plasticity, we investigated i) global DNA methylation levels, ii) differentially methylated regions (DMRs), and iii) the relative expression of DNA methylating and demethylating enzymes in two blacklegged tick populations, one representing northern [Minnesota] and one southern [Texas] US. Given that these populations experience different ecological conditions, we hypothesized that blacklegged ticks from the north and south differ in the level of 5-methylcytosine (5-mC) methylation within their genomes, and that these differences are concentrated at specific loci. The aim of this study was to determine whether differences in DNA methylation correspond to geographic origin, specifically testing southern and northern blacklegged tick populations. Our results confirmed that ticks collected from Minnesota (MN) and Texas (TX) present distinct 5-mC profiles. By creating a methylation gradient among tick populations, we combined this information with genetic markers to predict the vectorial potential of blacklegged tick populations. Results The percentage of 5-methylcytosine (%5-mC) varies among Ixodes scapularis populations across different years and geographical regions Previous studies have identified distinct genetic differences between northern and southern blacklegged ticks [32,33]. To assess whether variation between these populations also includes disparities in the level of DNA methylation, we quantified the level of 5-mC in MN and TX blacklegged tick populations using ELISA assays. Our preliminary results showed significant variation in methylation levels between ticks from MN and TX, with MN ticks displaying higher methylation levels than TX ticks (p = 0.0015). Nevertheless, due to the few ticks tested, these experiments were repeated to confirm the results. We performed further testing using ticks collected in 2021 and 2022 to determine whether these variations were replicable. We observed high variability in %5-mC between groups during two distinct years (Supplementary Fig. S1 ). Notably, no significant differences were found between MN and TX ticks collected in Spring 2021 (p = 0.8490) (Fig. 1 a, Supplementary Fig. S1 ). However, significant variation in the %5-mC was observed between MN and TX ticks collected in Spring 2022, using unpaired two-sided t-test (2022; t (30) = 4.568, p < 0.0001) (Fig. 1 B). Moreover, within each location, alterations in methylation levels were observed between tick sexes (Supplementary Fig. S1 ). Yet, males from MN displayed higher %5-mC in their genome, regardless of season or collection year (Fig. 1 c, Supplementary Fig. S1 e, f). Identification of genes encoding the enzymes putatively associated with DNA methylation homeostasis in blacklegged tick Currently, the genes encoding DNA methyltransferases (DNMTs) and thymine DNA glycosylase (TDG) within the genome of the blacklegged tick have been annotated using gene prediction [34]. To confirm the identity of DNMTs and demethylases of this species, we conducted a homology search using PSI-BLAST with human and mouse homologs. These species were chosen as they possess a complete set of DNMTs, unlike other arthropods, such as Drosophila , which possess only one DNA methylation enzyme (homolog of DNMT2) [26]. We identified a complete set of homologs for three DNMTs, along with the ten-eleven translocation (TET) 3 and TDG enzymes, known to modulate demethylation. The top homologous proteins found in the I. scapularis genome exhibited identity percentages ranging from 57.5 to 42.0%, when compared to the human homologs, and query coverage between 99 − 32% (Table 1 ). Table 1 Blacklegged tick DNA methyltransferases and demethylases identified by PSI-BLAST. Protein Organism Best Hit I. scapularis accession number Query cover (%) E-value Percentage of Identity (%) Size protein (aa) DNMT1 Homo sapiens DNA (cytosine-5)-methyltransferase PliMCI XP_029831274 76 0.0 57.50 1,363 DNMT2 Homo sapiens tRNA (cytosine(38)-C(5))-methyltransferase [ I. scapularis ] XP_029848442 99 6e-91 42.09 361 DNMT3A Homo sapiens DNA (cytosine-5)-methyltransferase 3A isoform X1 [ I. scapularis ] XP_040064066 44 7e-96 48.03 363 TDG Mus musculus G/T mismatch-specific thymine DNA glycosylase [ I. scapularis ] XP_029824608 57 1e-78 55.97 705 TET3 Homo sapiens uncharacterized protein LOC8042599 isoform X1 XP_029838410 34 1e-118 48.34 2,116 uncharacterized protein LOC8042599 isoform X2 XP_040075936 36 9ee-119 48.34 2,090 uncharacterized protein LOC8042599 isoform X3 XP_040075937 34 1e-118 48.34 2,062 uncharacterized protein LOC8042599 isoform X4 XP_040075938 34 8e-119 48.34 2,036 uncharacterized protein LOC8042599 isoform X5 XP_029838415 32 2e-119 48.34 1,767 uncharacterized protein LOC8042599 isoform X6 XP_040360312 32 2-e-119 48.34 1,713 To validate that the identified genes encode homologs to these enzymes, the presence of conserved domains within each putative blacklegged tick homolog was confirmed using the normal mode in SMART [35]. A potential homologous DNMT1 from the blacklegged tick, abbreviated as IscDNMT1, encoded a full-length protein of 1,363 amino acids, displaying four distinct domains: (1) the replication foci domain (DNMT1-RFD) facilitating methylation at the correct residue (positions 160–293); (2) a zinc-finger domain (zf-CXXC) that binds to an unmethylated CpG site (positions 396–442); (3) two consecutive bromo adjacent homology domains (BAH) typical of DNMT1 (positions 513–642 and 694–863) associated with DNA (cytosine-5) methyltransferases; and (4) the DNA methylase domain (c-5 cytosine-specific DNA methylase) responsible for methylating the fifth carbon of cytosine in DNA and producing the modification C5-methylcytosine (positions 902-1,355; Fig. 2 a). On the other hand, IscDNMT2 encoded a 361 amino acid polypeptide, and IscDNMT3 exhibited a full-length chain of 363 amino acids, both displaying a unique DNA methylase domain in their polypeptide sequences at positions 19–357 and 58–235, respectively (Fig. 2 b, c). In the case of IscTET3, this demethylase consisted of six isoforms ranging in length from 1,713 to 2,116 amino acids (Table 1 ). Each isoform features an oxygenase domain (Tet_JBP) responsible for catalyzing the conversion of 5-mC into 5-hydroxymethylcytosine (5hmC), followed by subsequent 5-formylcytosine (5fC) and 5-carboxylcytosine (5caC). The Tet_JBP domain is consistently positioned at the end of the sequences alongside a DNA binding domain (PBD/zf-CXXC), which is absent in isoforms X5 and X6 (Fig. 2 d, Supplementary Fig S2 ). IscTDG encoded a protein of 705 amino acids with three primary domains: (1) SCOP d1lsha3 domain, serving an unknown function, located at position 71–111, (2) three DNA binding domains (AT hooks) positioned at 158–170, 188–200, and 509–521, and (3) an Uracil-DNA glycosylase domain (UDG), a member of DNA repair enzymes responsible for actively removing products generated by TET at position 247–440 (Fig. 2 e). DNMT1 was differentially expressed among blacklegged tick adults collected in Texas and Minnesota To investigate whether the differences in methylation levels correlate with variations in methylase and de-methylase expression, we used qRT-PCR to study the relative expression of blacklegged tick DNA methyltransferases and demethylases that differ between populations in MN and TX. Three experimental replicate qRT-PCRs were conducted for each enzyme. The relative expression of all enzymes was normalized to actin as a reference gene. Comparisons were made between locations and sexes. The relative expression of the other DNMT2, DNMT3, and the two demethylases varied greatly between experiments (Supplementary Fig. S3), showing no discernible pattern. On the other hand, females from TX showed a significantly increased expression of DNMT1 when compared to females from MN (Fig. 3 ; p = 0.0008). These females also presented notably higher levels of DNMT1 expression when compared to males from both regions (Fig. 3 ; TX p = 0.0184, and MN p < 0.0001). In contrast, no significant changes in expression were found between males from MN and TX (p = 0.2359). Hyper- and hypomethylated genes potentially associated with regional adaptation in Minnesota ticks We utilized whole genome bisulfite sequencing (WGBS) and nanopore sequencing to analyze 5-mC, primarily in the CpG context, the most prevalent form of DNA methylation in arthropods [36–38]. DMRs were identified in genes and putative promoter regions. Five to six samples per location were subjected to bisulfite sequencing (three replicates for each sex except for males from MN that only had two replicates). Each sample contained five to six ticks categorized by sex. The average bisulfite conversion rate was 99.69%. The mean number of raw sequences obtained from pooled females and males was 220,369,976 for MN and 332,314,072 for TX. After quality control, the mean number of sequences was 218,315,030 (30.85 GB) for MN and 329,009,097 (46.475 GB) for TX (Supplementary Table S1 ). These reads were then mapped to the reference genome (NCBI, ASM1692078v2). There was an average mapping efficiency of 13.2% for MN and 16.6% for TX, with an CpG coverage around 24.6X and 21.3X for MN and TX, respectively, ensuring reliable alignments (Supplementary Table S2 , S3). For nanopore sequencing, the mean number of raw sequences obtained was 17,259,423 (29.58 GB) and 9,431,732 (25.88 GB) for individual adult females from MN and TX. Mapped sequences achieved efficiencies of 97.93% and 98.20% with CpG coverage of 11.53X and 10.83X for MN and TX, respectively (Supplementary Table S4). To characterize the DNA methylation in the MN and TX populations, we examined DNA methylation levels in distinct contexts using WGBS, a method that has previously been used in ticks [36]. Genome-wide bisulfite sequencing revealed that the 5-mC in the CpG context was the most abundant, with an average of 11.12% for MN ticks and 14.01% for TX ticks (Fig. 4 a). Additionally, TX females exhibited statistically higher levels of 5-mC in the CpG context compared to TX males, MN females, and MN males; while TX males had higher CpG 5-mC compared to MN males and females (Fig. 4 b, p < 0.0051). Notably, TX ticks exhibited increased levels of 5-mC compared to MN ticks (Fig. 4 a; t (9) = 4.682, p = 0.0011). The next most common context was CHH, showing 4.42% and 4.31%. This was followed by CHG with 3.48% and 3.51% in MN and TX. However, no meaningful variation in DNA methylation was observed among populations in any of these contexts (Supplementary Table S2 , Supplementary Fig. S4a, b; CHH p = 0.4460 and CHG p = 0.5760). Additionally, pooled females and males from WGBS were used for comparative analysis to identify differentially methylated genes in CpG sites among both blacklegged tick populations. Two distinct clusters were identified according to correlation distance method that coincides with principal component analysis (Fig. 4 c, Supplementary Fig. S4c), indicating methylation profile variations between MN and TX blacklegged tick populations. Noteworthy, in this later analysis, the CpG methylation profiles from TX ticks were more distinct from each other, especially TX2 and TX3, which correspond to females from the same geographic location in Texas (Supplementary Fig. S4c). Furthermore, differentially methylated CpG sites were identified in MN and TX populations, with the most abundant genes being hypomethylated bases (Fig. 5 ), i.e., blacklegged ticks from TX showed greater methylation differences in genic regions compared to MN ticks. A total of 431 and 3565 hyper- and hypomethylated sites (associated with 11 and 163 genes), respectively, were identified in the analysis comparing MN to TX ticks (Fig. 6 , Table S5, S6). Many of these sites are distributed across the largest scaffolds, such as NW_024609883.1 and NW_024609839.1. Nanopore sequencing revealed an opposite trend, where female ticks from MN showed greater methylation in genic regions than female ticks from TX. Ultimately, nanopore sequencing validated the site-specific DMRs in genes identified by WGBS, notably three genes (XM_029973219.3, XM_029971324.3, XM_040219496.1) with hypermethylation signatures in TX organisms (Supplementary Table S6, S7). In total, nanopore sequencing identified 114 genic DMRs between these two populations of blacklegged ticks, with 63 of these DMRs corresponding to unique protein-coding genes (Supplementary Table S7, S8, Supplementary Fig. S5). Variation between blacklegged tick in the north and south may result from epigenetic and genetic differentiation [39,40]. This latter mechanism can be tracked by examining single nucleotide variation [39]; therefore, we explored variable sites in males and females from both locations using WGS. Females and males from both locations were assigned to one population for this analysis. The mean of raw sequences was 333,465,834 bases (33.47 GB) and decreased to 333,465,831 (32.52 GB) after quality control. Filtered sequences were then mapped to the reference genome (NCBI, ASM1692078v2) with a mean percentage of mapped reads of 97.51% (Supplementary Table S9). In total, 143,654,820 variable sites were detected from WGS from MN and TX ticks together, and after being filtered out, the total SNPs were 19,799,421 (Supplementary Table S10). The SNPs were checked against the cytosines identified as differentially methylated to correct for genetic changes that may have been previously identified as differentially methylated bases (DMBs). This led to the elimination of six DMBs as they were SNPs modifications and of LOC8034183 from the final hypomethylated list. No DMBs were removed from the hypermethylated list because no overlaps with SNPs were found. Promoter methylation in this tick species was analyzed from the differentially methylated sites. A total of 9 hypermethylated and 5 hypomethylated candidate promoter regions were found in MN compared to TX ticks. These hypermethylated sites were found in the promoter areas of genes encoding a histone H3, small subunit, and 5.8S ribosomal RNA. On the contrary, hypomethylated residues within promoters were found in genes encoding transmembrane protein 50A and protein-cysteine N-palmitoyltransferase Rasp (Supplementary Table S11). Overrepresented Gene Ontology (GO) terms in hypomethylated genes To infer the potential impact of the variability in methylation on the biology and vector competency of this tick species, we performed enrichment analysis based on GO, protein and molecular function, and pathways. Hypomethylated genes were overrepresented in 68 GO terms associated with purine nucleotide catabolic process (GO:0006195), rho protein signal transduction (GO:0007266), homophilic cell adhesion via plasma membrane adhesion molecules (GO:0007156), axon guidance (GO:0007411), import into cell (GO:0098657), synaptic vesicle (GO:0008021), axon (GO:0030424), intracellular non-membrane-bounded organelle (GO:0043232), cell periphery (GO:0071944), and kinase activity (GO:0016301) (Supplementary Table S12-S14,Supplementary Fig. S6). Three types of proteins were overrepresented in those genes, including non-receptor serine/threonine protein kinase (PC00167) and RNA metabolism protein (PC00031) (Supplementary Table S15, Supplementary Fig. S7). No enrichment of hypomethylated genes was identified in pathways. Similarly, a lack of significant enrichment was associated with hypermethylated genes. Discussion Examining the genetic composition of blacklegged ticks across their geographical range in the US provides critical insight into the genetic basis that may underline distinctive biological characteristics and behaviors. This may potentially affect pathogen transmission and the prevalence of disease transmission in these regions. Previous studies have leveraged population genetic analyses to describe the contributions of evolutionary forces in shaping genetic heterogeneity [39,41]. Yet, whether epigenetic divergence occurs within tick populations is unknown. In ticks, DNA methylation may represent an alternative fine scale modulatory response to fluctuating environmental conditions, such as rapid thermal acclimatization and/or adaptation to local ecological niches [36,42]. Our study characterized differences in DNA methylation between two blacklegged tick populations in the US (MN and TX), uncovering global methylation signatures, differentially methylated genic regions, and expression variation of genes encoding enzymes involved in the homeostasis of DNA methylation. Epigenetic mechanisms, particularly DNA methylation catalyzed by DNMTs, have been associated with arthropod phenotypic plasticity in response to environmental cues. Environmental stressors, such as extreme temperatures, can cause fluctuations in the expression levels of DNMTs [30,31]. Blacklegged tick populations are exposed to considerable variation in environmental conditions that may impose disparate constraints on fundamental biological processes and require unique molecular responses. In other hard tick species, transient exposure to cold increased the expression of DNA methyltransferases [42], suggesting that these enzymes contribute to winter survival in ticks. Although the enzymes involved in DNA methylation establishment (DNMT3) and maintenance (DNMT1) have been reported in hard tick species, including the blacklegged tick [26,36,42–44] these studies did not identify other enzymes required for DNA methylation homeostasis, such as demethylases. Our result showed that the blacklegged tick genome possesses a complete set of DNA methylation machinery, including demethylases, TET, and TDG, indicating that methylation is a coordinated and dynamic process in blacklegged ticks. In addition to identifying the components of the methylation machinery, we found significant differences in the expression level of DNMT1 (Supplementary Fig. S3). This indicates that blacklegged tick populations may diverge in their ability to maintain DNA methylation profiles. Notably, TX females exhibited higher relative expression of DNMT1 than males of the same location (Fig. 3 ). Intersex disparities in DNMT1 expression levels have been recorded in another arthropod, the mealybug (Hemiptera: Pseudococcidae). In this case, mealybug females showed higher DNMT1 expression levels than males, suggesting that DNA methylation maintenance enzymes may contribute to sex-specific methylation patterns and sexual differentiation [45]. Sexual dimorphism is morphologically apparent in blacklegged ticks, where females are generally larger and possess a smaller scutum than males [11]. However, since the current blacklegged tick genome is from a single female, we could not determine whether variations in methylation patterns exist among females and males. Thus, further research is required to assess the role of IscDNMT1 and DNA methylation in blacklegged tick sexual differentiation. The remaining enzymes showed considerable variation in relative expression levels without any consistent trend, which might reflect the wide range of global 5-mC levels uncovered in blacklegged tick genomes. Nevertheless, global 5-mC methylation in blacklegged tick genomes was consistent with levels reported in other chelicerate species, including ticks [26,36]. Nwanade et al. [36] reported approximately 3% 5-mC levels in CpG contexts of lab breeding H. longicornis females; however, laboratory reared ticks raised under controlled settings might not accurately reflect the suite of abiotic and biotic stressors shaping DNA methylation in natural tick populations. Using multiple molecular approaches, we discovered consistent differences in DNA methylation levels between MN and TX ticks, suggesting either (1) a northern population with higher levels of DNA methylation supported by ELISA and nanopore sequencing, or (2) lower levels of methylation in MN compared to TX ticks supported by WGBS. Bisulfite sequencing identified 5-mC based on conversion of non-methylated cytosine to uracil by sodium bisulfite treatment followed by PCR amplification, and ultimately, the change of modified cytosine to thymine. Subsequently, converted DNA sequencing is carried out using next-generation sequencing for short reads [46]. Although both technologies offer high efficiency (> 90%) and accuracy in base calling (Q20), bisulfite sequencing has limitations. For instance, it cannot differentiate between early demethylation products such as 5-hydroxymethylcytosine (5-hmC) and 5mC, leading to an overestimation of methylated cytosine levels [46,47]. This limitation may contribute to our varying results. However, it is important to emphasize that the heterogeneity in sample size and years of sample collection could also significantly influence the results. For example, WGBS sequencing was performed on pools of males or females, while nanopore sequencing used a single female. As such, our WGBS data presents consensus methylated regions between the sexes and multiple individual ticks, which might eliminate regions present in nanopore sequencing. These DMRs detected by nanopore sequencing may be individual specific and thus not detected in other ticks. Despite this, three differentially methylated genes, basic proline-rich, sortilin-related receptor, and peptidase M20 domain-containing protein 2-like, were shared across these two sequencing methods, which were hypermethylated in TX ticks. These genes may be associated with local adaptation to specific ecological conditions that require their hypermethylation in Texas. For instances, basic proline-rich gene (XM_029973219.3), which, among other functions, facilitates digestion as a component of mammalian saliva [48,49]. Interestingly, this protein presents homology with a zinc finger protein in humans, ZNF608 (NP_001372550.1), which is also present in insects. Curiously, this transcriptional regulator is involved in sexual dimorphism in the broad-horned flour beetle ( Gnatocerus cornutus ) [50]. A second gene encodes a sortilin-related receptor (SORL1) (XM_029971324.3). In honeybees ( Apis mellifera) , SORL1 is expressed in the brains of worker bees in response to ecdysone-regulated foraging behavior [51]. A third gene, peptidase M20 domain-containing protein 2-like (XM_040219496.1), it is also known as Xaa-Arg dipeptidase in humans, and has been identified in hard ticks [52]. However, the specific function of these genes in tick biology has not been defined. Other hypomethylated genes likely associated with regional adaptation were identified within the WGBS dataset. These genes included those encoding a serine/threonine-protein kinase pim-1-like (XM_040208937.1), two metalloproteases, one cubilin-like (XM_042292858.1), a venom metalloproteinase antarease-like TtrivMP_A (XM_040212634.1) and proline-rich protein (XM_040216711.3), which may serves as a cryoprotectant in insects [53] and plants [54], and a mitogen-activated kinase (XM_029987871.4). However, the function of these proteins in response to abiotic factors has not been experimentally tested. Moreover, cis-regulatory elements, such as promoters, and epigenetic modifications coordinate to regulate the spatiotemporal expression of transcriptional programs in arthropods [55], yet their contribution to modulating gene expression in blacklegged ticks remains unknown. We identified hyper- and hypomethylated CpG sites in MN ticks compared to TX ticks, falling within 14 putative promoter regions of the tick genome. For instance, possible promoter regions of histone genes were found to be highly methylated in MN relative to TX. A second mechanism by which DNA methylation may affect gene regulation is through CpG islands and island shores, which are stretches of DNA with high densities of CpG bases. These islands can be methylated, leading to gene silencing, especially during imprinting [56]. Nevertheless, whether methylation of promoter regions or CpG islands in ticks results in inhibition or induction of gene expression remains to be determined. Notably, variations in DNA methylation, either depletion or addition, have been recorded as a response to distinct climatic conditions experienced in unique geographical locations by disparate populations of the same species [40,57]. Our study provides the first report, to our knowledge, of the expression levels of enzymes involved in DNA methylation homeostasis, global DNA methylation level differences, and differentially methylated genomic regions among blacklegged tick populations from contrasting geographic regions in the US. Beside the genetic mechanism such as pleiotropy and epistasis, epigenetic mechanisms provide an individual with the ability to modify its morphology, physiology, and behavior in response to environmental stimuli, known as phenotypic flexibility [58–62]. Given that ticks have a complex life cycle with prolonged off-host periods that expose them to experience several environmental stressors, ticks are under variable selective pressures to respond to external fluctuating stimuli. As such, it is highly plausible that epigenetic factors influence tick activity, biology, and potentially vectorial capacity. Although not all stimuli have an effect in the epigenetic landscape of organisms [60], contrasting hot weather [30,63], host preference [64,65], photoperiod [38] and winter temperatures [36,40] may lead to the non-uniformity in methylation patterns found between MN and TX ticks. Our study has several limitations, including differences in ages between ticks, variance in collection years, and the limited number of tick samples used for nanopore sequencing. Yet, our study serves as an initial resource for future research to build upon by experimentally evaluating the role of epigenetic modifications in tick biology. Methods 2.1 Tick collections Questing adult blacklegged tick were collected from distinct locations in MN and TX (Supplementary Table S16) between 2016–2023, except for 2018 and 2020 when collection was not performed. Females and males were collected from the vegetation along trails with tick drags (BioQuip, Rancho Dominguez, CA, US) and placed in 100% ethanol or RNAlater (Invitrogen, Waltham, MA, US). Collected ticks were immediately stored at -80°C until DNA and RNA isolation was carried out. Only unfed adults were used for these experiments. Immature I. scapularis stages are rarely collected from the vegetation in the south [66,67] and, we did not collect any during our study period. Further, methylation from the bloodmeal within engorged ticks may affect our results and maintaining ticks at laboratory conditions until molting may also affect their methylation patterns; therefore, we decided to perform these analyses on unfed adult ticks collected from the field only. While we recognized that pathogens might exert epigenetic control [68–70], the influence of pathogen infections on DNA methylation remains unclear and warrants further investigation in future studies. 2.2 Quantification of 5-Methylcystosine (5-mC) levels in blacklegged tick Ticks were removed from the storage solution and washed three times with 1 ml 1x Phosphate Buffered Saline (PBS). They were then separated by sex into different groups, depending on the downstream procedure as described below. Preliminary measurements of 5-mC levels were performed using DNA from ticks collected in Chippewa National Forest, Camp Ripley and Saint Croix State Park, MN and Harris County, TX in 2017 (Supplementary Table S16). Methylation levels were measured with MethylFlash Global DNA Methylation (5-mC) ELISA Easy Kit [Colorimetric] (Epigentek, Farmingdale, NY, US). All following assays were performed using adult ticks collected from 2021–2022 from MN and TX (Supplementary Table S16). DNA was isolated using the Quick-DNA/RNA Microprep Plus kit (Zymo Research Corporation). DNA isolation was performed according to the manufacturer indications with the following modifications: 200 µL of the lysis buffer was used to homogenize the ticks using a Fisherbrand RNase-free disposable pestle (Fisher Scientific, Waltham, MA, US) and 30 µL of DNA/RNase free water for the final elution of DNA. DNA concentration and integrity were assessed with a NanoQuant Infinite M200PRO (Tecan Group Ltd., Mannedorf, Switzerland) with the i-control 1.12 software and stored at -80°C until use. The DNA cytosine methylation in the blacklegged tick was measured using the 5-mC ELISA kit (Zymo Research Corporation), according to the manufacturer’s instructions. In brief, 100 ng of DNA were denatured at 98°C for 5 minutes and applied to each well. 5-mC was detected using a mouse anti-5-methylcytosine monoclonal antibody (clone 7D21; Zymo Research Corporation) and an HRP-labeled secondary antibody. Samples were assessed in duplicates. Each assay included a standard curve with known 5-mC percentages to determine the methylation levels in the samples. Change in color, which reflects the presence of 5-mC, was quantified using a NanoQuant Infinite M200PRO (Tecan Group Ltd.) with Magellan 7.1 with an absorbance of 450 nm. The %5-mC was calculated using a standard curve. Statistical differences in the 5-mC level were determined using an unpaired two-tailed t-test in GraphPad Prism 9.2.0 (GraphPad Software, San Diego, CA, US). Differences in 5-mC levels were compared using geographic location and sex as variables. 2.3 Characterization of 5-mC patterns in Texas and Minnesota blacklegged tick populations using WGBS DNA was isolated from three groups of pooled ticks (five to six ticks), separated by sex and location, using the Quick-DNA/RNA Microprep Plus kit (Zymo Research) following the manufacturer directions with a few modifications. Briefly, ticks were crushed in 400 µL of lysis buffer using Fisherbrand RNase-free disposable pestles (Fisher Scientific) and eluted with a final volume of 50 µL of DNA/RNase free water per sample. DNA from three groups of female and male ticks were submitted to GENEWIZ (South Plainfield, NJ, US) on dry ice for WGBS. DNA quality was assessed in a Qubit 2.0 Fluorometer (Life Technologies, Carlsbad, CA, US) to detect DNA concentration and possible RNA contamination. Samples with RNA contamination were RNAse treated before building libraries. Bisulfite conversion, library preparation and sequencing were also conducted by the company mentioned above. In brief, Bisulfite treatment was performed with the EZ DNA Methylation Gold Kit (Zymo Research). DNA was fragmented with Covaris (PerKinElmer Covaris, Woburn, MA, US) and library preparation was performed using the Accel-NGS Methyl-Seq kit (Swift Biosciences, Ann Arbor, MI, US). A ~ 0.5% unmethylated lambda DNA spike-in was used as a bisulfite conversion rate control and for downstream bioinformatics. Sequencing libraries were validated using the Agilent Tapestation 4200 (Agilent Technologies, Palo Alto, CA, US) and quantified by Qubit 2.0 fluorometer as well as by quantitative real-time PCR (Applied Biosystem, Carlsbad, CA, US). Finally, sequencing libraries were multiplexed and sequenced on the Illumina HiSeq instrument (4000 or equivalent) according to manufacturer’s instructions. The samples were sequenced using a 2x150 Paired End (PE) configuration. The information and accession number for each sequence is provided in Supplementary Table S17. To identify changes in DNA methylation sites between populations, WGBS data were quality filtered and trimmed using Trim Galore v0.6.10 using the default setting [71]. Filtered bisulfite reads were mapped to the reference genome (NCBI, ASM1692078v2; [28]) using bowtie2 v2.5.3, followed by deduplication and methylated cytosine calling implemented in Bismark v0.24.2 [72]. Hyper/hypomethylated sites were processed by Methylkit package v1.28.0 implemented in R v4.3.3 [73] with a q-value cutoff at 0.01 and the minimum difference in the methylation levels was set to 25 percentage value. DMBs were compared with gene annotation (NCBI, ASM1692078v2). Genes with at least one hypo or hypermethylated site were considered as a hyper- or hypomethylated gene. Methylkit and circlize v0.4.16 packages [74] were used to visualize and map chromosome-wide differentially methylated region distribution and associated with feature annotations in the WGBS datasets. To ensure that observed disparities in methylation between the MN and TX blacklegged tick populations were due to epigenetic rather than genetic variation, WGS sequences (Supplementary Table S17) from males and females of this tick collected in 2021 from Lake Elmo Park Reserve, Minnesota and Big Thicket State Park, Texas were used to filter out variable sites that overlap methylated cytosine in CpG context following the Rahman and Lozier approach [40]. DNA was extracted from single ticks and prepared for Illumina sequencing. Individuals were homogenized in 1.5 mL tubes in liquid nitrogen baths with liquid nitrogen-cooled pestles. DNA was isolated using the E.Z.N.A. Insect DNA Kit (Omega Bio-tek, Inc., Norcross, GA, US). Following isolation, genomic DNA was evaluated using a NanoDrop 2000 Spectrophotometer (Thermo Fisher Scientific, Waltham, MA, US). Illumina libraries were prepared using the FS DNA Library Prep Kit and NEBNext Multiplex Oligos for Illumina (New England Biolabs, Ipswich, MA, US). Size selection and cleanup were performed with SPRIselect beads (Beckman Coulter, Inc., Brea, CA, US). The prepared libraries were sequenced at the USDA-ARS Veterinary Pest Genetics Research Unit in Kerrville, Texas, on a NextSeq 2000 system with a P3 flow cell and a 200-cycle reagent cartridge (Illumina, Inc., San Diego, CA, US). To identify variable sites such as single nucleotide polymorphisms (SNPs), raw sequences were trimmed and filtered out using bbduk v39.11 [75]. Trimmed reads were subsequently mapped to the I. scapularis reference genome (NCBI, ASM1692078v2) using the BWA-MEM algorithm from BWA v07.17 [76]. The sequence alignment map (SAM) files were then converted to binary format and sorted by coordinates using SAMtools v1.19.2 [77]. Mark duplication and the index of binary alignment map (BAM) files were conducted with Picard v3.2.0 [78]. The output files were used for SNP identification with FreeBayes v1.3.8 [79]. To simplify data interpretation and mitigate potential sequencing artifacts that could introduce errors downstream [80,81], the initial variable site set was further refined using VCFtools v0.1.16 [82]. This process involved removing indels, non-biallelic SNPs, sites with low read depth, quality score Q ≥ 20, and minor allele counts ≥ 2. Additionally, SNPs with excessive coverage were excluded from the final VCF file, utilizing VCFtools along with AWK v5.1.0 (https://www.gnu.org/software/gawk/manual/gawk.html#Manual-History), as outlined by Rahman and Lozier[40] [https://github.com/steph166/contrastingEpigenetics-]. SNPs were compared to hyper- and hypomethylated genes using the GenomicRanges package [83] in R v4.3.3. Any differentially methylated genes overlapping with the SNP site were excluded from the final list. Additionally, putative promoter regions in blacklegged tick were analyzed for variation in 5-mC levels, which might influence gene expression [84,85]. Thus, DMBs were examined in search of hyper- and hypomethylated promoter regions. Putative promoter regions in this tick species were defined as those located within 2000 bp upstream of the transcription starting site (TSS) [86–88]. A new column titled “promoter” was incorporated into the gene information set, containing the beginning of each potential promoter region and the start location gene at the end of the potential region. Subsequently, differentially methylated genes previously identified were merged with gene information (GenesLocations), using “scaffold name” as a common column between the two datasets. Candidate differentially methylated promoter regions were identified based on where methylated site ≥ promoter start and < promoter end using the IF function in Excel. 2.4 Gene ontology associated with hyper- and hypomethylated genes in blacklegged tick populations Gene ontology and pathway analyses were conducted for hyper- and hypomethylated genes identified in MN ticks in comparison to TX ticks, using the Panther Classification System v19.0 [89,90]. The statistical overrepresentation test was selected for the analysis, with Fisher’s test employed as the default statistical method. 2.5 DNA isolation and nanopore sequencing Blacklegged ticks collected from Carlos Avery Wildlife Management Area, MN and Beech woods trail, Big Thicket State Park, TX in 2023 [41] were morphologically identified using keys from Kierans and Clifford [91] and Cooley and Kohls [92]. Ticks were rinsed with molecular grade water and transferred to DNA/RNA shield until DNA extraction. DNA was extracted using a Qiagen MagAttract kit (Qiagen, Germantown, MD, US) according to the manufacturer’s instructions, with a final elution step extended to 1 hour at 37°C. DNA was sheared by 20 passes through a standard 30-gauge insulin syringe. Library prep was performed with an SQK-LSK-114 native ligation sequencing kit (ONT, Oxford, United Kingdom). Sequencing was performed on a P2 Solo instrument and base called using Nvidia 4090 GPUs. Sequencing was performed over three days with nuclease flush and library reload every 24 hours. Individual adult females were used for sequencing of blacklegged ticks from MN and TX. 2.6 Characterization of 5-mC patterns in Texas and Minnesota I. scapularis populations using Oxford Nanopore Technologies Nanopore sequencing is a single-molecule sequencing platform that leverages electrical currents across nanopores embedded in a flow cell to detect individual nucleotides of a DNA fragment as they pass through the nanopores. The change in electrical current is determined by the molecular weight of the passing nucleotide, which is deciphered through a bioinformatic process called base calling. Methylated bases possess unique molecular weights and can be detected natively. We implemented nanopore sequencing as an alternative method to validate the global 5-mC methylation levels and DMRs observed with WGBS. Raw data from all runs were base called together using Dorado v0.8.1 with the “super accuracy” model dna_r10.4.1_e8.2_400bps_supv4.2.0. Base modifications were called simultaneously using the Dorado flag —modified-bases 5mC_5hmC. Read quality was assessed using Nanoq v0.10.0 [93]. Global DNA methylation and hydroxymethylation (5-mC and 5hmC) at cytosine-guanine dinucleotides (CpGs) were identified using modified base information stored in the initial base calling output files for two female individual blacklegged ticks (MN and TX, respectively) [94]. The two blacklegged tick individual output files were concatenated and aligned to the PalLabHiFi assembly using Minimap2 v2.28 [95]. The resulting mapped BAM files containing modified base information were converted to bedMethyl format using Modkit v0.4.1 [96], and global 5-mC and 5hmC percentages were calculated using AWK v5.3. Differential methylation analyses were performed according to Flack et al. [94]. Count filtering, tiling into 100 bp windows, and differential methylation analysis were performed with MethylKit v1.30.0 [73]. Windows were considered DMRs if they had at least 10 CpGs, a mean absolute difference in methylation ≥ 50%⁠, and a Benjamini–Hochberg-adjusted P-value of ⁠0.05 [97]. CpG sites are locations on a DNA strand where a cytosine is directly followed by a guanine nucleotide, connected by a phosphate bond. The cytosine within the CpG dinucleotide context can be methylated. DMRs were annotated by identifying the nearest gene with BedTools [98]. DMRs identified between individuals were visualized with karyotypeR v1.30.0 [99]. 2.7 Identification of demethylation and methylation enzymes homologous in blacklegged tick populations. DNA methylation is carried out by a group of enzymes that add a methyl group onto the 5th carbon in cytosine, DNMTs, which are traditionally named DNMT1, DNMT2, and DNMT3 [56,100]. Demethylation in the genome is regulated by TET dioxygenases and TDG [85]. To establish whether these enzymes are present in the genome of the blacklegged tick, we used the protein sequences of Homo sapiens DNMT1 (AAI26228.1), DNMT2 (CAG29312.1), DNMT3a (AAH23612.1), and TET3 (NP_001274420.1) to identify homologs. Additionally, Mus musculus TDG (NP_766140.2) was used. Homologs were determined by Position-Specific Iterative (PSI)-BLAST search (NCBI, NIH, Bethesda, MD, US). The identity of the homologs was corroborated by confirming the presence of conserved domains within the proteins, using SMART v9 [35]. The Expasy Translate Tool (Swiss Institute of Bioinformatics, Lausanne, Switzerland; [101]) was used to discard any non-protein coding sequence and identify the mRNA coding sequence for each enzyme, except TET3, for which several isoforms were identified. Trimmed sequences were used to design oligos using the Geneious Prime v2021.2 (Biomatters Inc, Auckland, New Zealand) and OligoAnalyzer Tool in IDT (Integrated DNA Technology Inc, Coralville, IA, US; [102]). In the case of DNMT3 and TDG, probes were designed using the PrimerQuest Tool. In the case of TET3, all isoform sequences were aligned in Geneious Prime v.2021.2 to locate a conserved region among all isoforms and primers were designed using this region (see Supplementary Fig. S8). To ascertain the expression of these enzymes in both populations of blacklegged ticks, RNA from individual ticks was purified from the lysate flow-through of the purified DNA from the ticks used in our 5-mC quantification experiments described above. RNA was isolated using the Quick-DNA/RNA Microprep Plus kit (Zymo Research), according to the manufacturer’s indications. RNA was eluted with 30 µl of DNA/RNase free water. cDNA was synthesized from the mRNA isolated from ticks collected from either MN or TX, using the Verso cDNA Synthesis Kit (Thermo Scientific), following the manufacturer’s protocols. Amplicons were amplified using GoTaq Flexi DNA Polymerase (Promega Corporation, Madison, WI) with the following thermal cycling conditions: one cycle of 95°C for 3 minutes, followed by 95°C for 60 s, 52–55°C for 60 s, and 72°C for 30 s per 34 cycles, and a final extension at 72°C for 5 minutes. To verify the identity of the amplicons, PCR products were purified using QIAquick PCR purification kit (Qiagen), according to the manufacturer’s instructions. Purified PCR products were submitted to EtonBio (Eton Bioscience, Inc., San Diego, CA, US) for Sanger sequencing. The sequence identity was confirmed by BLAST and deposited in NCBI (Supplementary Table S18). 2.8 Measurement of DNA methylation and demethylation enzymes relative expression In other arthropod species, such as bees and ants, stimuli and memory formation can lead to the differential expression of DNMTs and TET [103,104]. Likewise, in ticks, cold temperatures can affect the expression of DNMTs [42]. To assess whether methylating and demethylating enzymes were differentially expressed in blacklegged tick populations, the primers listed in Supplementary Table S19 were used to assess the relative expression of DNMTs, TET, and TDG enzymes. The mRNA was normalized to 100 ng and used for cDNA synthesis as described above. The relative expression of DNMT1, DNMT2, and TET was evaluated using SyBR Green (Thermo Fisher Scientific, Carlsbad, CA, US), according to the manufacturer’s directions. However, DNMT3 and TDG were measured using TaqMan Fast Advanced Master Mix (Thermo Fisher Scientific), due to the presence of primer dimer and secondary products that could not be eliminated. All primers and probes are listed in Supplementary Table S19. All denaturing steps were performed at 95°C for 60 s and annealing temperature between 52–55°C for 60 s over 39 cycles (see Supplementary Table S19, S20 for details about reaction conditions). Fluorescence was recorded during the annealing step to evaluate amplification. The specificity of the primers was verified by adding a melting curve step in the SyBR Green assays. Three biological replicates were performed to evaluate the relative expression of each gene. For the DNMT1 gene, four replicates were performed to achieve a consensus. All reactions were performed in a CXF Opus 96 (Bio-Rad Laboratories Inc, Hercules, CA, US). The relative expression of methylation and demethylation enzymes was calculated using 2 −ΔCT method [105], using actin as a normalizing gene [106]. Significant differences in gene expression were evaluated using a Two-way ANOVA in GraphPad Prism 9.4.1 (GraphPad Software, San Diego, CA, US). Data availability Raw data from WGBS and WGS associated with this manuscript has been deposited in the National Center for Biotechnology Information (NCBI) under Bioproject number PRJNA1081399, and the nanopore raw reads can be found at https://datadryad.org/dataset/doi:10.5061/dryad.sbcc2frh8#citations. All code used for the analysis of the data, along with the raw output, is available in the public repository: https://github.com/steph166/contrastingEpigenetics-. Accession numbers, PCR and qPCR amplification conditions, WGBS, WGB, and nanopore statistics and results, as well as a full list of differentially methylated sites and enrichment analyses in putative promoters and genes, are available in the supplementary material associated with this manuscript. Declarations Competing interests The authors declare no competing interests. Funding This research was funded by the USDA National Institute of Food and Agriculture Hatch MultistateProject #TEX0-1-7714, Texas A&M University the T3: Triads for Transformation to AOC, USDA award 58-8042-7-070 and Texas A&M University insect vector to RFM, and by a grant provide by the Midwest Center for Occupational Health and Safety Pilot Projects Research Training Program to JC. AL and SO were supported by EFAS-REEU (grant no. 2016-67032- 25013). The funders did not play any role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. Author Contribution Conceptualization: AOC and JDO; Methodology: AOC, JDO, PS, MCG, and CF; Investigation: SGV, JC, PS, AL, EL, CH, BLG, CC, CW, SO, MT, TJ, NAM, and AOC; Formal analysis: SGV, JC, PS, CF, and AOC; Validation: SGV and JC; Resources: PS, TJ, RFM, DMT, JDO, and AOC; Visualization: SGV and JC; Writing – original draft preparation: SGV and JC; Writing – review and editing: PS, JC, BLG, MT, TJ, MCG, RFM, DMT, CF, JDO and AOC; Supervision: JDO, CF, and AOC; Project administration: JDO and AOC; Funding acquisition: JDO and AOC. Acknowledgement We thank Dr. Donald H. Bouyer at UTMB who kindly provided DNA for TX ticks to assess the preliminary measurement of 5-mC level. This article reports the results of research only. Mention of a proprietary product does not constitute an endorsement or a recommendation by the USDA for its use. The USDA is an equal opportunity provider and employer. References Centers for Disease Control and Prevention (CDC). 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13:10:48","extension":"xml","order_by":17,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":162869,"visible":true,"origin":"","legend":"","description":"","filename":"87b5cce875eb4137865305644a3c4f1b1structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7762123/v1/5ecc351d13fefb312f7ff785.xml"},{"id":93141005,"identity":"ed92460f-8fdb-4181-a6b2-b0b4a972361f","added_by":"auto","created_at":"2025-10-09 13:02:48","extension":"html","order_by":18,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":179796,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7762123/v1/dfcd1857932e10489aec8b8e.html"},{"id":93140986,"identity":"e3b20bd5-a1e7-49d3-94f3-158a08495ee6","added_by":"auto","created_at":"2025-10-09 13:02:47","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":25475,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePercentage variations of 5-mC between blacklegged ticks collected over a span of 2 years.\u003c/strong\u003eComparison of the methylation percentage variations in cytosine residues among MN and TX ticks collected in (a) 2021 and (b) 2022 [both sexes combined]. (c) Represents the dissimilarities in cytosine methylation among MN versus TX tick males collected in 2021. Significant differences were evaluated with an unpaired two-sided t-test. The error bars represent the mean ± SEM of the two variables. Asterisks indicated significant variability between samples. Abbreviations= MN: Minnesota, TX: Texas, and percentage of 5-mC: %5-mC. Representative figures from four experiments are shown. N1= number of MN ticks and N2= number of TX ticks used for comparison. The results from all experimental replicates are provided in Supplementary Fig. S1.\u003c/p\u003e","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7762123/v1/6730988840f2649b2f463f19.png"},{"id":93142074,"identity":"d23cf221-39d5-4706-b64f-c30d8f236940","added_by":"auto","created_at":"2025-10-09 13:10:47","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":16478,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDomains identified in \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eIxodes scapularis \u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eDNA methyltransferases and demethylases homologous.\u003c/strong\u003e Conserved domains and binding residues typical in (a) DNMT1, (b) DNMT2, (c) DNMT3, (d) TET3 and (e) TDG were detected in blacklegged tick\u003cem\u003e \u003c/em\u003ehomologs identified by PSI-BLAST. RFD = replication foci domain; CXXC = zinc-finger domain; BAH = bromo adjacent homology domains; HXD = HXD Fe\u003csup\u003e2+\u003c/sup\u003e binding residues; H2OG = H Fe\u003csup\u003e2+ \u003c/sup\u003eand 2-Oxoglutarate binding residues; Tet_JBP = oxygenase domain; d1Isha3 = SCOP d1lsha3 domain; AT = AT hooks; UDG = uracil_DNA glycosylase domain. Numbers represent the protein size in amino acid residues (for TET3, we are displaying the amino acid size for isoform 1.\u003c/p\u003e","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7762123/v1/05e12ea02249f9947371f221.png"},{"id":93143097,"identity":"65b7c75f-e757-4b37-8b43-a02544ceefb7","added_by":"auto","created_at":"2025-10-09 13:18:47","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":22205,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDNMT1 is upregulated in\u003c/strong\u003e\u003cem\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003efemale ticks collected in Texas.\u003c/strong\u003e TX females displayed statistically higher relative expression of DNMT1 compared to males from TX, males from MN, or females from MN. Differences in expression were evaluated using a Two-way ANOVA followed by Tukey’s test for multiple comparisons. Asterisks indicated significant differences between samples. Abbreviations: MN: Minnesota and TX: Texas. Number of ticks compared: MN female=7, MN male=6, TX female=7, and TX male=5. A representative figure from four experiments is shown. The results from all experimental replicates are provided in Supplementary Fig. S3.\u003c/p\u003e","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7762123/v1/a63e0cf897946c4c49a82c7c.png"},{"id":93142080,"identity":"eea3d628-0d8d-4249-b1ad-dcfdc9b2efea","added_by":"auto","created_at":"2025-10-09 13:10:47","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":39316,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMN versus TX ticks present variable methylated level. \u003c/strong\u003eDifferential DNA methylation level in CpG context between ticks from both states, identified by whole bisulfite sequencing (WGBS), were tested using unpaired two-sided t-test (a) and ordinary one-way ANOVA (b), both of which revealed statistically significant differences. Additionally, a comparative analysis was conducted using DNA methylation residues of blacklegged tick populations. Cluster analysis based on correlation distance indicated a distinct separation of the DNA methylation profiles of ticks collected in MN or TX (c). Significant differences were displayed in asterisks. Error bars represent the mean ± SEM of the two variables. The “Y” axis always represents the percentage of DNA 5-Methylcytosine (%5-mC). Abbreviations: MN: Minnesota and TX: Texas.\u003c/p\u003e","description":"","filename":"Onlinefloatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7762123/v1/32843d706b471a153d0004ea.png"},{"id":93140997,"identity":"7bf8e69f-c49c-4ba0-82f8-c4dc0018556e","added_by":"auto","created_at":"2025-10-09 13:02:47","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":34929,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHypomethylated bases are predominantly present within genic regions.\u003c/strong\u003e Hyper- and hypomethylated bases were plotted by genomic features. Salmon bars indicate hyper- DNA methylation in MN ticks relative to TX ticks (levels of methylation in MN/levels of methylation in TX), whereas hypomethylation is represented with dark turquoise bars. The numbers over the bars represent the percentage of differentially methylated bases within each genomic feature. Abbreviation hyper: hypermethylated sites and hypo: hypomethylated sites.\u003c/p\u003e","description":"","filename":"Onlinefloatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7762123/v1/e7a744dfbbe13d543f1d9294.png"},{"id":93141001,"identity":"58847af7-7b4e-4b86-865d-aeb2d8c88a6b","added_by":"auto","created_at":"2025-10-09 13:02:47","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":357440,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDistribution of differentially methylated sites in the blacklegged tick genome\u003c/strong\u003e. The scaffolds with the biggest concentration of differentially methylated bases (DMBs) are highlighted with yellow and their identities are labeled within the map. The salmon dots represent hypermethylated bases, while the turquoise points indicate hypomethylated bases. The abbreviation MN: Minnesota and DMBs: differentially methylated bases.\u003c/p\u003e","description":"","filename":"Onlinefloatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7762123/v1/4768e979ab36b89b19f3bf73.png"},{"id":93144180,"identity":"07ac8286-6132-4b60-a74a-7e443f7991c4","added_by":"auto","created_at":"2025-10-09 13:26:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2282801,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7762123/v1/6af0c9da-8709-4736-8562-cc1c888d0376.pdf"},{"id":93140989,"identity":"8ffa0e1e-d07c-484a-8d3d-69c4a0a2f588","added_by":"auto","created_at":"2025-10-09 13:02:47","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":2320204,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterial1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7762123/v1/86de42ee3e7feef5d1321314.pdf"},{"id":93143098,"identity":"4d373480-cde1-4d4b-ac6e-83da6b476dcf","added_by":"auto","created_at":"2025-10-09 13:18:47","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":296694,"visible":true,"origin":"","legend":"","description":"","filename":"Suplementarymaterial2TableS5S8.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7762123/v1/35377232c3f1b3194574295f.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Contrasting epigenetics of Ixodes scapularis populations","fulltext":[{"header":"Introduction","content":"\u003cp\u003eLyme disease (LD) is the most prevalent vector-borne disease in the United States (US), with 500,000 estimated cases each year [1\u0026ndash;3] and an estimated economic burden of approximately \u003cspan\u003e$\u003c/span\u003e968\u0026nbsp;million annually [4]. In the eastern US, LD is primarily transmitted by the blacklegged tick, \u003cem\u003eIxodes scapularis\u003c/em\u003e Say. This tick is a three-host tick, capable of transmitting and harboring a wide array of pathogenic microorganisms, including \u003cem\u003eBorrelia burgdorferi\u003c/em\u003e (the main causative agent of Lyme disease), \u003cem\u003eAnaplasma phagocytophilum\u003c/em\u003e, and \u003cem\u003eBabesia microti\u003c/em\u003e [5\u0026ndash;7]. Blacklegged ticks can be co-infected with various pathogens simultaneously, which represents a risk for co-infections through the transmission of multiple pathogens in a single bite [8,9]. The lack of efficient tick control methods [3,10], ongoing geographic expansion of tick populations [11\u0026ndash;13], and their ability to carry multiple zoonotic pathogens [5\u0026ndash;7,9,14,15] collectively contribute to the growing health concern posed by this tick species.\u003c/p\u003e\u003cp\u003eBlacklegged ticks have been reported throughout much of the eastern and upper midwestern US [13]. Interestingly, the incidence of pathogens associated with blacklegged ticks shows a disproportionate distribution, with higher transmission rates in northern than in southern states [13,16]. Initially, this variation was attributed to hypothesized differences in vector competence between two presumably different \u003cem\u003eIxodes\u003c/em\u003e species (\u003cem\u003eIxodes dammini\u003c/em\u003e [found in the northern US] and \u003cem\u003eI. scapularis\u003c/em\u003e [found in the southern US]). Nevertheless, mating experiments and phylogenetic analyses determined that these were conspecific populations, resulting in their synonymization to \u003cem\u003eI. scapularis\u003c/em\u003e [17\u0026ndash;19].\u003c/p\u003e\u003cp\u003eTicks from southern and northern regions exhibit differences in seasonal activity [20], infection rate [21], host association [22], and host-seeking behavior [23,24]. Specifically, in the southern regions, immature blacklegged ticks display a preference for feeding on \u003cem\u003eB. burgdorferi\u003c/em\u003e incompetent reptiles, whereas northern ticks predominantly favor \u003cem\u003eB. burgdorferi\u003c/em\u003e competent mammalian hosts, such as the white-footed mouse (\u003cem\u003ePeromyscus leucopus\u003c/em\u003e) [22]. The divergence in host association may also drive differences in questing behavior, with southern immature life stages maintaining a lower questing height, often remaining beneath the leaf litter. In contrast, northern immatures are more commonly found above the leaf litter, actively searching for hosts [23,25]. These variations in host-seeking behavior and host preference may partially explain the differences in nymphal infection prevalence and tick-borne pathogen transmission between the southeastern and northern US regions [22\u0026ndash;24].\u003c/p\u003e\u003cp\u003eHowever, the genetic and molecular mechanisms that contribute to the observed phenotypic differences among blacklegged ticks from these two different geographic locations remain to be determined. DNA methylation has been documented in the genome of blacklegged tick cell lines (IDE2, IDE8, and ISE18) [26] and is suspected to drive phenotypic plasticity in arthropods [27]. Further, recent assembly and annotation of the \u003cem\u003eI. scapularis\u003c/em\u003e genome revealed the presence of epigenetic clusters (polycomb and trithorax group proteins) known to regulate transcription [28]. Whether DNA methylation plays a role in blacklegged tick adaptation to environmental conditions, e.g., temperature, remains unknown [29\u0026ndash;31]. Given the potential link between DNA methylation and tick phenotypic plasticity, we investigated i) global DNA methylation levels, ii) differentially methylated regions (DMRs), and iii) the relative expression of DNA methylating and demethylating enzymes in two blacklegged tick populations, one representing northern [Minnesota] and one southern [Texas] US. Given that these populations experience different ecological conditions, we hypothesized that blacklegged ticks from the north and south differ in the level of 5-methylcytosine (5-mC) methylation within their genomes, and that these differences are concentrated at specific loci. The aim of this study was to determine whether differences in DNA methylation correspond to geographic origin, specifically testing southern and northern blacklegged tick populations. Our results confirmed that ticks collected from Minnesota (MN) and Texas (TX) present distinct 5-mC profiles. By creating a methylation gradient among tick populations, we combined this information with genetic markers to predict the vectorial potential of blacklegged tick populations.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cb\u003eThe percentage of 5-methylcytosine (%5-mC) varies among\u003c/b\u003e \u003cb\u003eIxodes scapularis\u003c/b\u003e \u003cb\u003epopulations across different years and geographical regions\u003c/b\u003e\u003c/p\u003e\u003cp\u003ePrevious studies have identified distinct genetic differences between northern and southern blacklegged ticks [32,33]. To assess whether variation between these populations also includes disparities in the level of DNA methylation, we quantified the level of 5-mC in MN and TX blacklegged tick populations using ELISA assays. Our preliminary results showed significant variation in methylation levels between ticks from MN and TX, with MN ticks displaying higher methylation levels than TX ticks (p\u0026thinsp;=\u0026thinsp;0.0015). Nevertheless, due to the few ticks tested, these experiments were repeated to confirm the results.\u003c/p\u003e\u003cp\u003eWe performed further testing using ticks collected in 2021 and 2022 to determine whether these variations were replicable. We observed high variability in %5-mC between groups during two distinct years (Supplementary Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Notably, no significant differences were found between MN and TX ticks collected in Spring 2021 (p\u0026thinsp;=\u0026thinsp;0.8490) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea, Supplementary Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). However, significant variation in the %5-mC was observed between MN and TX ticks collected in Spring 2022, using unpaired two-sided t-test (2022; t (30)\u0026thinsp;=\u0026thinsp;4.568, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). Moreover, within each location, alterations in methylation levels were observed between tick sexes (Supplementary Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Yet, males from MN displayed higher %5-mC in their genome, regardless of season or collection year (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec, Supplementary Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003ee, f).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eIdentification of genes encoding the enzymes putatively associated with DNA methylation homeostasis in blacklegged tick\u003c/h2\u003e\u003cp\u003eCurrently, the genes encoding DNA methyltransferases (DNMTs) and thymine DNA glycosylase (TDG) within the genome of the blacklegged tick have been annotated using gene prediction [34]. To confirm the identity of DNMTs and demethylases of this species, we conducted a homology search using PSI-BLAST with human and mouse homologs. These species were chosen as they possess a complete set of DNMTs, unlike other arthropods, such as \u003cem\u003eDrosophila\u003c/em\u003e, which possess only one DNA methylation enzyme (homolog of DNMT2) [26]. We identified a complete set of homologs for three DNMTs, along with the ten-eleven translocation (TET) 3 and TDG enzymes, known to modulate demethylation. The top homologous proteins found in the \u003cem\u003eI. scapularis\u003c/em\u003e genome exhibited identity percentages ranging from 57.5 to 42.0%, when compared to the human homologs, and query coverage between 99\u0026thinsp;\u0026minus;\u0026thinsp;32% (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eBlacklegged tick DNA methyltransferases and demethylases identified by PSI-BLAST.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProtein\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOrganism\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBest Hit\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eI. scapularis\u003c/em\u003e accession number\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eQuery cover (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eE-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003ePercentage of Identity (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eSize protein (aa)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDNMT1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eHomo sapiens\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDNA (cytosine-5)-methyltransferase PliMCI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eXP_029831274\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e57.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1,363\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDNMT2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eHomo sapiens\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003etRNA (cytosine(38)-C(5))-methyltransferase [\u003cem\u003eI. scapularis\u003c/em\u003e]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eXP_029848442\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6e-91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e42.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e361\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDNMT3A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eHomo sapiens\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDNA (cytosine-5)-methyltransferase 3A isoform X1 [\u003cem\u003eI. scapularis\u003c/em\u003e]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eXP_040064066\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7e-96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e48.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e363\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTDG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eMus musculus\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eG/T mismatch-specific thymine DNA glycosylase [\u003cem\u003eI. scapularis\u003c/em\u003e]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eXP_029824608\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1e-78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e55.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e705\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003eTET3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e\u003cem\u003eHomo sapiens\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003euncharacterized protein LOC8042599 isoform X1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eXP_029838410\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1e-118\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e48.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e2,116\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003euncharacterized protein LOC8042599 isoform X2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eXP_040075936\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e9ee-119\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e48.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e2,090\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003euncharacterized protein LOC8042599 isoform X3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eXP_040075937\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1e-118\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e48.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e2,062\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003euncharacterized protein LOC8042599 isoform X4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eXP_040075938\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e8e-119\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e48.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e2,036\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003euncharacterized protein LOC8042599 isoform X5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eXP_029838415\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2e-119\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e48.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1,767\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003euncharacterized protein LOC8042599 isoform X6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eXP_040360312\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2-e-119\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e48.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1,713\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTo validate that the identified genes encode homologs to these enzymes, the presence of conserved domains within each putative blacklegged tick homolog was confirmed using the normal mode in SMART [35]. A potential homologous DNMT1 from the blacklegged tick, abbreviated as IscDNMT1, encoded a full-length protein of 1,363 amino acids, displaying four distinct domains: (1) the replication foci domain (DNMT1-RFD) facilitating methylation at the correct residue (positions 160\u0026ndash;293); (2) a zinc-finger domain (zf-CXXC) that binds to an unmethylated CpG site (positions 396\u0026ndash;442); (3) two consecutive bromo adjacent homology domains (BAH) typical of DNMT1 (positions 513\u0026ndash;642 and 694\u0026ndash;863) associated with DNA (cytosine-5) methyltransferases; and (4) the DNA methylase domain (c-5 cytosine-specific DNA methylase) responsible for methylating the fifth carbon of cytosine in DNA and producing the modification C5-methylcytosine (positions 902-1,355; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). On the other hand, IscDNMT2 encoded a 361 amino acid polypeptide, and IscDNMT3 exhibited a full-length chain of 363 amino acids, both displaying a unique DNA methylase domain in their polypeptide sequences at positions 19\u0026ndash;357 and 58\u0026ndash;235, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb, c).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eIn the case of IscTET3, this demethylase consisted of six isoforms ranging in length from 1,713 to 2,116 amino acids (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Each isoform features an oxygenase domain (Tet_JBP) responsible for catalyzing the conversion of 5-mC into 5-hydroxymethylcytosine (5hmC), followed by subsequent 5-formylcytosine (5fC) and 5-carboxylcytosine (5caC). The Tet_JBP domain is consistently positioned at the end of the sequences alongside a DNA binding domain (PBD/zf-CXXC), which is absent in isoforms X5 and X6 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed, Supplementary Fig \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e). IscTDG encoded a protein of 705 amino acids with three primary domains: (1) SCOP d1lsha3 domain, serving an unknown function, located at position 71\u0026ndash;111, (2) three DNA binding domains (AT hooks) positioned at 158\u0026ndash;170, 188\u0026ndash;200, and 509\u0026ndash;521, and (3) an Uracil-DNA glycosylase domain (UDG), a member of DNA repair enzymes responsible for actively removing products generated by TET at position 247\u0026ndash;440 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee).\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eDNMT1 was differentially expressed among blacklegged tick adults collected in Texas and Minnesota\u003c/h3\u003e\n\u003cp\u003eTo investigate whether the differences in methylation levels correlate with variations in methylase and de-methylase expression, we used qRT-PCR to study the relative expression of blacklegged tick DNA methyltransferases and demethylases that differ between populations in MN and TX. Three experimental replicate qRT-PCRs were conducted for each enzyme. The relative expression of all enzymes was normalized to \u003cem\u003eactin\u003c/em\u003e as a reference gene. Comparisons were made between locations and sexes. The relative expression of the other DNMT2, DNMT3, and the two demethylases varied greatly between experiments (Supplementary Fig. S3), showing no discernible pattern. On the other hand, females from TX showed a significantly increased expression of DNMT1 when compared to females from MN (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e; p\u0026thinsp;=\u0026thinsp;0.0008). These females also presented notably higher levels of DNMT1 expression when compared to males from both regions (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e; TX p\u0026thinsp;=\u0026thinsp;0.0184, and MN p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). In contrast, no significant changes in expression were found between males from MN and TX (p\u0026thinsp;=\u0026thinsp;0.2359).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\n\u003ch3\u003eHyper- and hypomethylated genes potentially associated with regional adaptation in Minnesota ticks\u003c/h3\u003e\n\u003cp\u003eWe utilized whole genome bisulfite sequencing (WGBS) and nanopore sequencing to analyze 5-mC, primarily in the CpG context, the most prevalent form of DNA methylation in arthropods [36\u0026ndash;38]. DMRs were identified in genes and putative promoter regions. Five to six samples per location were subjected to bisulfite sequencing (three replicates for each sex except for males from MN that only had two replicates). Each sample contained five to six ticks categorized by sex. The average bisulfite conversion rate was 99.69%. The mean number of raw sequences obtained from pooled females and males was 220,369,976 for MN and 332,314,072 for TX.\u003c/p\u003e\u003cp\u003eAfter quality control, the mean number of sequences was 218,315,030 (30.85 GB) for MN and 329,009,097 (46.475 GB) for TX (Supplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). These reads were then mapped to the reference genome (NCBI, ASM1692078v2). There was an average mapping efficiency of 13.2% for MN and 16.6% for TX, with an CpG coverage around 24.6X and 21.3X for MN and TX, respectively, ensuring reliable alignments (Supplementary Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e, S3). For nanopore sequencing, the mean number of raw sequences obtained was 17,259,423 (29.58 GB) and 9,431,732 (25.88 GB) for individual adult females from MN and TX. Mapped sequences achieved efficiencies of 97.93% and 98.20% with CpG coverage of 11.53X and 10.83X for MN and TX, respectively (Supplementary Table S4).\u003c/p\u003e\u003cp\u003eTo characterize the DNA methylation in the MN and TX populations, we examined DNA methylation levels in distinct contexts using WGBS, a method that has previously been used in ticks [36]. Genome-wide bisulfite sequencing revealed that the 5-mC in the CpG context was the most abundant, with an average of 11.12% for MN ticks and 14.01% for TX ticks (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea). Additionally, TX females exhibited statistically higher levels of 5-mC in the CpG context compared to TX males, MN females, and MN males; while TX males had higher CpG 5-mC compared to MN males and females (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0051). Notably, TX ticks exhibited increased levels of 5-mC compared to MN ticks (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea; t (9)\u0026thinsp;=\u0026thinsp;4.682, p\u0026thinsp;=\u0026thinsp;0.0011). The next most common context was CHH, showing 4.42% and 4.31%. This was followed by CHG with 3.48% and 3.51% in MN and TX. However, no meaningful variation in DNA methylation was observed among populations in any of these contexts (Supplementary Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e, Supplementary Fig. S4a, b; CHH p\u0026thinsp;=\u0026thinsp;0.4460 and CHG p\u0026thinsp;=\u0026thinsp;0.5760).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAdditionally, pooled females and males from WGBS were used for comparative analysis to identify differentially methylated genes in CpG sites among both blacklegged tick populations. Two distinct clusters were identified according to correlation distance method that coincides with principal component analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec, Supplementary Fig. S4c), indicating methylation profile variations between MN and TX blacklegged tick populations. Noteworthy, in this later analysis, the CpG methylation profiles from TX ticks were more distinct from each other, especially TX2 and TX3, which correspond to females from the same geographic location in Texas (Supplementary Fig. S4c).\u003c/p\u003e\u003cp\u003eFurthermore, differentially methylated CpG sites were identified in MN and TX populations, with the most abundant genes being hypomethylated bases (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e), i.e., blacklegged ticks from TX showed greater methylation differences in genic regions compared to MN ticks. A total of 431 and 3565 hyper- and hypomethylated sites (associated with 11 and 163 genes), respectively, were identified in the analysis comparing MN to TX ticks (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, Table S5, S6). Many of these sites are distributed across the largest scaffolds, such as NW_024609883.1 and NW_024609839.1.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eNanopore sequencing revealed an opposite trend, where female ticks from MN showed greater methylation in genic regions than female ticks from TX. Ultimately, nanopore sequencing validated the site-specific DMRs in genes identified by WGBS, notably three genes (XM_029973219.3, XM_029971324.3, XM_040219496.1) with hypermethylation signatures in TX organisms (Supplementary Table S6, S7). In total, nanopore sequencing identified 114 genic DMRs between these two populations of blacklegged ticks, with 63 of these DMRs corresponding to unique protein-coding genes (Supplementary Table S7, S8, Supplementary Fig. S5).\u003c/p\u003e\u003cp\u003eVariation between blacklegged tick in the north and south may result from epigenetic and genetic differentiation [39,40]. This latter mechanism can be tracked by examining single nucleotide variation [39]; therefore, we explored variable sites in males and females from both locations using WGS. Females and males from both locations were assigned to one population for this analysis. The mean of raw sequences was 333,465,834 bases (33.47 GB) and decreased to 333,465,831 (32.52 GB) after quality control. Filtered sequences were then mapped to the reference genome (NCBI, ASM1692078v2) with a mean percentage of mapped reads of 97.51% (Supplementary Table S9). In total, 143,654,820 variable sites were detected from WGS from MN and TX ticks together, and after being filtered out, the total SNPs were 19,799,421 (Supplementary Table S10). The SNPs were checked against the cytosines identified as differentially methylated to correct for genetic changes that may have been previously identified as differentially methylated bases (DMBs). This led to the elimination of six DMBs as they were SNPs modifications and of LOC8034183 from the final hypomethylated list. No DMBs were removed from the hypermethylated list because no overlaps with SNPs were found.\u003c/p\u003e\u003cp\u003ePromoter methylation in this tick species was analyzed from the differentially methylated sites. A total of 9 hypermethylated and 5 hypomethylated candidate promoter regions were found in MN compared to TX ticks. These hypermethylated sites were found in the promoter areas of genes encoding a histone H3, small subunit, and 5.8S ribosomal RNA. On the contrary, hypomethylated residues within promoters were found in genes encoding transmembrane protein 50A and protein-cysteine N-palmitoyltransferase Rasp (Supplementary Table S11).\u003c/p\u003e\n\u003ch3\u003eOverrepresented Gene Ontology (GO) terms in hypomethylated genes\u003c/h3\u003e\n\u003cp\u003eTo infer the potential impact of the variability in methylation on the biology and vector competency of this tick species, we performed enrichment analysis based on GO, protein and molecular function, and pathways. Hypomethylated genes were overrepresented in 68 GO terms associated with purine nucleotide catabolic process (GO:0006195), rho protein signal transduction (GO:0007266), homophilic cell adhesion via plasma membrane adhesion molecules (GO:0007156), axon guidance (GO:0007411), import into cell (GO:0098657), synaptic vesicle (GO:0008021), axon (GO:0030424), intracellular non-membrane-bounded organelle (GO:0043232), cell periphery (GO:0071944), and kinase activity (GO:0016301) (Supplementary Table S12-S14,Supplementary Fig. S6). Three types of proteins were overrepresented in those genes, including non-receptor serine/threonine protein kinase (PC00167) and RNA metabolism protein (PC00031) (Supplementary Table S15, Supplementary Fig. S7). No enrichment of hypomethylated genes was identified in pathways. Similarly, a lack of significant enrichment was associated with hypermethylated genes.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eExamining the genetic composition of blacklegged ticks across their geographical range in the US provides critical insight into the genetic basis that may underline distinctive biological characteristics and behaviors. This may potentially affect pathogen transmission and the prevalence of disease transmission in these regions. Previous studies have leveraged population genetic analyses to describe the contributions of evolutionary forces in shaping genetic heterogeneity [39,41]. Yet, whether epigenetic divergence occurs within tick populations is unknown. In ticks, DNA methylation may represent an alternative fine scale modulatory response to fluctuating environmental conditions, such as rapid thermal acclimatization and/or adaptation to local ecological niches [36,42]. Our study characterized differences in DNA methylation between two blacklegged tick populations in the US (MN and TX), uncovering global methylation signatures, differentially methylated genic regions, and expression variation of genes encoding enzymes involved in the homeostasis of DNA methylation.\u003c/p\u003e\u003cp\u003eEpigenetic mechanisms, particularly DNA methylation catalyzed by DNMTs, have been associated with arthropod phenotypic plasticity in response to environmental cues. Environmental stressors, such as extreme temperatures, can cause fluctuations in the expression levels of DNMTs [30,31]. Blacklegged tick populations are exposed to considerable variation in environmental conditions that may impose disparate constraints on fundamental biological processes and require unique molecular responses. In other hard tick species, transient exposure to cold increased the expression of DNA methyltransferases [42], suggesting that these enzymes contribute to winter survival in ticks. Although the enzymes involved in DNA methylation establishment (DNMT3) and maintenance (DNMT1) have been reported in hard tick species, including the blacklegged tick [26,36,42\u0026ndash;44] these studies did not identify other enzymes required for DNA methylation homeostasis, such as demethylases. Our result showed that the blacklegged tick genome possesses a complete set of DNA methylation machinery, including demethylases, TET, and TDG, indicating that methylation is a coordinated and dynamic process in blacklegged ticks.\u003c/p\u003e\u003cp\u003eIn addition to identifying the components of the methylation machinery, we found significant differences in the expression level of DNMT1 (Supplementary Fig. S3). This indicates that blacklegged tick populations may diverge in their ability to maintain DNA methylation profiles. Notably, TX females exhibited higher relative expression of DNMT1 than males of the same location (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Intersex disparities in DNMT1 expression levels have been recorded in another arthropod, the mealybug (Hemiptera: Pseudococcidae). In this case, mealybug females showed higher DNMT1 expression levels than males, suggesting that DNA methylation maintenance enzymes may contribute to sex-specific methylation patterns and sexual differentiation [45]. Sexual dimorphism is morphologically apparent in blacklegged ticks, where females are generally larger and possess a smaller scutum than males [11]. However, since the current blacklegged tick genome is from a single female, we could not determine whether variations in methylation patterns exist among females and males. Thus, further research is required to assess the role of IscDNMT1 and DNA methylation in blacklegged tick sexual differentiation.\u003c/p\u003e\u003cp\u003eThe remaining enzymes showed considerable variation in relative expression levels without any consistent trend, which might reflect the wide range of global 5-mC levels uncovered in blacklegged tick genomes. Nevertheless, global 5-mC methylation in blacklegged tick genomes was consistent with levels reported in other chelicerate species, including ticks [26,36]. Nwanade et al. [36] reported approximately 3% 5-mC levels in CpG contexts of lab breeding \u003cem\u003eH. longicornis\u003c/em\u003e females; however, laboratory reared ticks raised under controlled settings might not accurately reflect the suite of abiotic and biotic stressors shaping DNA methylation in natural tick populations. Using multiple molecular approaches, we discovered consistent differences in DNA methylation levels between MN and TX ticks, suggesting either (1) a northern population with higher levels of DNA methylation supported by ELISA and nanopore sequencing, or (2) lower levels of methylation in MN compared to TX ticks supported by WGBS. Bisulfite sequencing identified 5-mC based on conversion of non-methylated cytosine to uracil by sodium bisulfite treatment followed by PCR amplification, and ultimately, the change of modified cytosine to thymine. Subsequently, converted DNA sequencing is carried out using next-generation sequencing for short reads [46].\u003c/p\u003e\u003cp\u003eAlthough both technologies offer high efficiency (\u0026gt;\u0026thinsp;90%) and accuracy in base calling (Q20), bisulfite sequencing has limitations. For instance, it cannot differentiate between early demethylation products such as 5-hydroxymethylcytosine (5-hmC) and 5mC, leading to an overestimation of methylated cytosine levels [46,47]. This limitation may contribute to our varying results. However, it is important to emphasize that the heterogeneity in sample size and years of sample collection could also significantly influence the results. For example, WGBS sequencing was performed on pools of males or females, while nanopore sequencing used a single female. As such, our WGBS data presents consensus methylated regions between the sexes and multiple individual ticks, which might eliminate regions present in nanopore sequencing. These DMRs detected by nanopore sequencing may be individual specific and thus not detected in other ticks.\u003c/p\u003e\u003cp\u003eDespite this, three differentially methylated genes, basic proline-rich, sortilin-related receptor, and peptidase M20 domain-containing protein 2-like, were shared across these two sequencing methods, which were hypermethylated in TX ticks. These genes may be associated with local adaptation to specific ecological conditions that require their hypermethylation in Texas. For instances, basic proline-rich gene (XM_029973219.3), which, among other functions, facilitates digestion as a component of mammalian saliva [48,49]. Interestingly, this protein presents homology with a zinc finger protein in humans, ZNF608 (NP_001372550.1), which is also present in insects. Curiously, this transcriptional regulator is involved in sexual dimorphism in the broad-horned flour beetle (\u003cem\u003eGnatocerus cornutus\u003c/em\u003e) [50]. A second gene encodes a sortilin-related receptor (SORL1) (XM_029971324.3). In honeybees (\u003cem\u003eApis mellifera)\u003c/em\u003e, SORL1 is expressed in the brains of worker bees in response to ecdysone-regulated foraging behavior [51]. A third gene, peptidase M20 domain-containing protein 2-like (XM_040219496.1), it is also known as Xaa-Arg dipeptidase in humans, and has been identified in hard ticks [52]. However, the specific function of these genes in tick biology has not been defined.\u003c/p\u003e\u003cp\u003eOther hypomethylated genes likely associated with regional adaptation were identified within the WGBS dataset. These genes included those encoding a serine/threonine-protein kinase pim-1-like (XM_040208937.1), two metalloproteases, one cubilin-like (XM_042292858.1), a venom metalloproteinase antarease-like TtrivMP_A (XM_040212634.1) and proline-rich protein (XM_040216711.3), which may serves as a cryoprotectant in insects [53] and plants [54], and a mitogen-activated kinase (XM_029987871.4). However, the function of these proteins in response to abiotic factors has not been experimentally tested.\u003c/p\u003e\u003cp\u003eMoreover, cis-regulatory elements, such as promoters, and epigenetic modifications coordinate to regulate the spatiotemporal expression of transcriptional programs in arthropods [55], yet their contribution to modulating gene expression in blacklegged ticks remains unknown. We identified hyper- and hypomethylated CpG sites in MN ticks compared to TX ticks, falling within 14 putative promoter regions of the tick genome. For instance, possible promoter regions of histone genes were found to be highly methylated in MN relative to TX. A second mechanism by which DNA methylation may affect gene regulation is through CpG islands and island shores, which are stretches of DNA with high densities of CpG bases. These islands can be methylated, leading to gene silencing, especially during imprinting [56]. Nevertheless, whether methylation of promoter regions or CpG islands in ticks results in inhibition or induction of gene expression remains to be determined.\u003c/p\u003e\u003cp\u003eNotably, variations in DNA methylation, either depletion or addition, have been recorded as a response to distinct climatic conditions experienced in unique geographical locations by disparate populations of the same species [40,57]. Our study provides the first report, to our knowledge, of the expression levels of enzymes involved in DNA methylation homeostasis, global DNA methylation level differences, and differentially methylated genomic regions among blacklegged tick populations from contrasting geographic regions in the US. Beside the genetic mechanism such as pleiotropy and epistasis, epigenetic mechanisms provide an individual with the ability to modify its morphology, physiology, and behavior in response to environmental stimuli, known as phenotypic flexibility [58\u0026ndash;62]. Given that ticks have a complex life cycle with prolonged off-host periods that expose them to experience several environmental stressors, ticks are under variable selective pressures to respond to external fluctuating stimuli. As such, it is highly plausible that epigenetic factors influence tick activity, biology, and potentially vectorial capacity. Although not all stimuli have an effect in the epigenetic landscape of organisms [60], contrasting hot weather [30,63], host preference [64,65], photoperiod [38] and winter temperatures [36,40] may lead to the non-uniformity in methylation patterns found between MN and TX ticks. Our study has several limitations, including differences in ages between ticks, variance in collection years, and the limited number of tick samples used for nanopore sequencing. Yet, our study serves as an initial resource for future research to build upon by experimentally evaluating the role of epigenetic modifications in tick biology.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec8\"\u003e\n \u003cdiv id=\"Sec9\"\u003e\n \u003ch2\u003e2.1 Tick collections\u003c/h2\u003e\n \u003cp\u003eQuesting adult blacklegged tick were collected from distinct locations in MN and TX (Supplementary Table S16) between 2016\u0026ndash;2023, except for 2018 and 2020 when collection was not performed. Females and males were collected from the vegetation along trails with tick drags (BioQuip, Rancho Dominguez, CA, US) and placed in 100% ethanol or RNAlater (Invitrogen, Waltham, MA, US). Collected ticks were immediately stored at -80\u0026deg;C until DNA and RNA isolation was carried out. Only unfed adults were used for these experiments. Immature \u003cem\u003eI. scapularis\u003c/em\u003e stages are rarely collected from the vegetation in the south [66,67] and, we did not collect any during our study period. Further, methylation from the bloodmeal within engorged ticks may affect our results and maintaining ticks at laboratory conditions until molting may also affect their methylation patterns; therefore, we decided to perform these analyses on unfed adult ticks collected from the field only. While we recognized that pathogens might exert epigenetic control [68\u0026ndash;70], the influence of pathogen infections on DNA methylation remains unclear and warrants further investigation in future studies.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e2.2 Quantification of 5-Methylcystosine (5-mC) levels in blacklegged tick\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eTicks were removed from the storage solution and washed three times with 1 ml 1x Phosphate Buffered Saline (PBS). They were then separated by sex into different groups, depending on the downstream procedure as described below. Preliminary measurements of 5-mC levels were performed using DNA from ticks collected in Chippewa National Forest, Camp Ripley and Saint Croix State Park, MN and Harris County, TX in 2017 (Supplementary Table S16). Methylation levels were measured with MethylFlash Global DNA Methylation (5-mC) ELISA Easy Kit [Colorimetric] (Epigentek, Farmingdale, NY, US).\u003c/p\u003e\n \u003cp\u003eAll following assays were performed using adult ticks collected from 2021\u0026ndash;2022 from MN and TX (Supplementary Table S16). DNA was isolated using the Quick-DNA/RNA Microprep Plus kit (Zymo Research Corporation). DNA isolation was performed according to the manufacturer indications with the following modifications: 200 \u0026micro;L of the lysis buffer was used to homogenize the ticks using a Fisherbrand RNase-free disposable pestle (Fisher Scientific, Waltham, MA, US) and 30 \u0026micro;L of DNA/RNase free water for the final elution of DNA. DNA concentration and integrity were assessed with a NanoQuant Infinite M200PRO (Tecan Group Ltd., Mannedorf, Switzerland) with the i-control 1.12 software and stored at -80\u0026deg;C until use. The DNA cytosine methylation in the blacklegged tick was measured using the 5-mC ELISA kit (Zymo Research Corporation), according to the manufacturer\u0026rsquo;s instructions. In brief, 100 ng of DNA were denatured at 98\u0026deg;C for 5 minutes and applied to each well. 5-mC was detected using a mouse anti-5-methylcytosine monoclonal antibody (clone 7D21; Zymo Research Corporation) and an HRP-labeled secondary antibody. Samples were assessed in duplicates. Each assay included a standard curve with known 5-mC percentages to determine the methylation levels in the samples. Change in color, which reflects the presence of 5-mC, was quantified using a NanoQuant Infinite M200PRO (Tecan Group Ltd.) with Magellan 7.1 with an absorbance of 450 nm. The %5-mC was calculated using a standard curve. Statistical differences in the 5-mC level were determined using an unpaired two-tailed t-test in GraphPad Prism 9.2.0 (GraphPad Software, San Diego, CA, US). Differences in 5-mC levels were compared using geographic location and sex as variables.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e2.3 Characterization of 5-mC patterns in Texas and Minnesota blacklegged tick populations using WGBS\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eDNA was isolated from three groups of pooled ticks (five to six ticks), separated by sex and location, using the Quick-DNA/RNA Microprep Plus kit (Zymo Research) following the manufacturer directions with a few modifications. Briefly, ticks were crushed in 400 \u0026micro;L of lysis buffer using Fisherbrand RNase-free disposable pestles (Fisher Scientific) and eluted with a final volume of 50 \u0026micro;L of DNA/RNase free water per sample. DNA from three groups of female and male ticks were submitted to GENEWIZ (South Plainfield, NJ, US) on dry ice for WGBS. DNA quality was assessed in a Qubit 2.0 Fluorometer (Life Technologies, Carlsbad, CA, US) to detect DNA concentration and possible RNA contamination. Samples with RNA contamination were RNAse treated before building libraries.\u003c/p\u003e\n \u003cp\u003eBisulfite conversion, library preparation and sequencing were also conducted by the company mentioned above. In brief, Bisulfite treatment was performed with the EZ DNA Methylation Gold Kit (Zymo Research). DNA was fragmented with Covaris (PerKinElmer Covaris, Woburn, MA, US) and library preparation was performed using the Accel-NGS Methyl-Seq kit (Swift Biosciences, Ann Arbor, MI, US). A\u0026thinsp;~\u0026thinsp;0.5% unmethylated lambda DNA spike-in was used as a bisulfite conversion rate control and for downstream bioinformatics. Sequencing libraries were validated using the Agilent Tapestation 4200 (Agilent Technologies, Palo Alto, CA, US) and quantified by Qubit 2.0 fluorometer as well as by quantitative real-time PCR (Applied Biosystem, Carlsbad, CA, US). Finally, sequencing libraries were multiplexed and sequenced on the Illumina HiSeq instrument (4000 or equivalent) according to manufacturer\u0026rsquo;s instructions. The samples were sequenced using a 2x150 Paired End (PE) configuration. The information and accession number for each sequence is provided in Supplementary Table S17.\u003c/p\u003e\n \u003cp\u003eTo identify changes in DNA methylation sites between populations, WGBS data were quality filtered and trimmed using Trim Galore v0.6.10 using the default setting [71]. Filtered bisulfite reads were mapped to the reference genome (NCBI, ASM1692078v2; [28]) using bowtie2 v2.5.3, followed by deduplication and methylated cytosine calling implemented in Bismark v0.24.2 [72]. Hyper/hypomethylated sites were processed by Methylkit package v1.28.0 implemented in R v4.3.3 [73] with a q-value cutoff at 0.01 and the minimum difference in the methylation levels was set to 25 percentage value. DMBs were compared with gene annotation (NCBI, ASM1692078v2). Genes with at least one hypo or hypermethylated site were considered as a hyper- or hypomethylated gene. Methylkit and circlize v0.4.16 packages [74] were used to visualize and map chromosome-wide differentially methylated region distribution and associated with feature annotations in the WGBS datasets.\u003c/p\u003e\n \u003cp\u003eTo ensure that observed disparities in methylation between the MN and TX blacklegged tick populations were due to epigenetic rather than genetic variation, WGS sequences (Supplementary Table S17) from males and females of this tick collected in 2021 from Lake Elmo Park Reserve, Minnesota and Big Thicket State Park, Texas were used to filter out variable sites that overlap methylated cytosine in CpG context following the Rahman and Lozier approach [40].\u003c/p\u003e\n \u003cp\u003eDNA was extracted from single ticks and prepared for Illumina sequencing. Individuals were homogenized in 1.5 mL tubes in liquid nitrogen baths with liquid nitrogen-cooled pestles. DNA was isolated using the E.Z.N.A. Insect DNA Kit (Omega Bio-tek, Inc., Norcross, GA, US). Following isolation, genomic DNA was evaluated using a NanoDrop 2000 Spectrophotometer (Thermo Fisher Scientific, Waltham, MA, US). Illumina libraries were prepared using the FS DNA Library Prep Kit and NEBNext Multiplex Oligos for Illumina (New England Biolabs, Ipswich, MA, US). Size selection and cleanup were performed with SPRIselect beads (Beckman Coulter, Inc., Brea, CA, US). The prepared libraries were sequenced at the USDA-ARS Veterinary Pest Genetics Research Unit in Kerrville, Texas, on a NextSeq 2000 system with a P3 flow cell and a 200-cycle reagent cartridge (Illumina, Inc., San Diego, CA, US).\u003c/p\u003e\n \u003cp\u003eTo identify variable sites such as single nucleotide polymorphisms (SNPs), raw sequences were trimmed and filtered out using bbduk v39.11 [75]. Trimmed reads were subsequently mapped to the \u003cem\u003eI. scapularis\u003c/em\u003e reference genome (NCBI, ASM1692078v2) using the BWA-MEM algorithm from BWA v07.17 [76]. The sequence alignment map (SAM) files were then converted to binary format and sorted by coordinates using SAMtools v1.19.2 [77]. Mark duplication and the index of binary alignment map (BAM) files were conducted with Picard v3.2.0 [78]. The output files were used for SNP identification with FreeBayes v1.3.8 [79]. To simplify data interpretation and mitigate potential sequencing artifacts that could introduce errors downstream [80,81], the initial variable site set was further refined using VCFtools v0.1.16 [82]. This process involved removing indels, non-biallelic SNPs, sites with low read depth, quality score Q\u0026thinsp;\u0026ge;\u0026thinsp;20, and minor allele counts\u0026thinsp;\u0026ge;\u0026thinsp;2. Additionally, SNPs with excessive coverage were excluded from the final VCF file, utilizing VCFtools along with AWK v5.1.0 (https://www.gnu.org/software/gawk/manual/gawk.html#Manual-History), as outlined by Rahman and Lozier[40] [https://github.com/steph166/contrastingEpigenetics-].\u003c/p\u003e\n \u003cp\u003eSNPs were compared to hyper- and hypomethylated genes using the GenomicRanges package [83] in R v4.3.3. Any differentially methylated genes overlapping with the SNP site were excluded from the final list.\u003c/p\u003e\n \u003cp\u003eAdditionally, putative promoter regions in blacklegged tick were analyzed for variation in 5-mC levels, which might influence gene expression [84,85]. Thus, DMBs were examined in search of hyper- and hypomethylated promoter regions. Putative promoter regions in this tick species were defined as those located within 2000 bp upstream of the transcription starting site (TSS) [86\u0026ndash;88]. A new column titled \u0026ldquo;promoter\u0026rdquo; was incorporated into the gene information set, containing the beginning of each potential promoter region and the start location gene at the end of the potential region. Subsequently, differentially methylated genes previously identified were merged with gene information (GenesLocations), using \u0026ldquo;scaffold name\u0026rdquo; as a common column between the two datasets. Candidate differentially methylated promoter regions were identified based on where methylated site \u0026ge; promoter start and \u0026lt;\u0026thinsp;promoter end using the IF function in Excel.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e2.4 Gene ontology associated with hyper- and hypomethylated genes in blacklegged tick populations\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eGene ontology and pathway analyses were conducted for hyper- and hypomethylated genes identified in MN ticks in comparison to TX ticks, using the Panther Classification System v19.0 [89,90]. The statistical overrepresentation test was selected for the analysis, with Fisher\u0026rsquo;s test employed as the default statistical method.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e2.5 DNA isolation and nanopore sequencing\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eBlacklegged ticks collected from Carlos Avery Wildlife Management Area, MN and Beech woods trail, Big Thicket State Park, TX in 2023 [41] were morphologically identified using keys from Kierans and Clifford [91] and Cooley and Kohls [92]. Ticks were rinsed with molecular grade water and transferred to DNA/RNA shield until DNA extraction. DNA was extracted using a Qiagen MagAttract kit (Qiagen, Germantown, MD, US) according to the manufacturer\u0026rsquo;s instructions, with a final elution step extended to 1 hour at 37\u0026deg;C. DNA was sheared by 20 passes through a standard 30-gauge insulin syringe. Library prep was performed with an SQK-LSK-114 native ligation sequencing kit (ONT, Oxford, United Kingdom). Sequencing was performed on a P2 Solo instrument and base called using Nvidia 4090 GPUs. Sequencing was performed over three days with nuclease flush and library reload every 24 hours. Individual adult females were used for sequencing of blacklegged ticks from MN and TX.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e2.6 Characterization of 5-mC patterns in Texas and Minnesota\u003c/strong\u003e \u003cstrong\u003eI. scapularis\u003c/strong\u003e \u003cstrong\u003epopulations using Oxford Nanopore Technologies\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eNanopore sequencing is a single-molecule sequencing platform that leverages electrical currents across nanopores embedded in a flow cell to detect individual nucleotides of a DNA fragment as they pass through the nanopores. The change in electrical current is determined by the molecular weight of the passing nucleotide, which is deciphered through a bioinformatic process called base calling. Methylated bases possess unique molecular weights and can be detected natively. We implemented nanopore sequencing as an alternative method to validate the global 5-mC methylation levels and DMRs observed with WGBS. Raw data from all runs were base called together using Dorado v0.8.1 with the \u0026ldquo;super accuracy\u0026rdquo; model dna_r10.4.1_e8.2_400bps_supv4.2.0. Base modifications were called simultaneously using the Dorado flag \u0026mdash;modified-bases 5mC_5hmC. Read quality was assessed using Nanoq v0.10.0 [93]. Global DNA methylation and hydroxymethylation (5-mC and 5hmC) at cytosine-guanine dinucleotides (CpGs) were identified using modified base information stored in the initial base calling output files for two female individual blacklegged ticks (MN and TX, respectively) [94]. The two blacklegged tick individual output files were concatenated and aligned to the PalLabHiFi assembly using Minimap2 v2.28 [95]. The resulting mapped BAM files containing modified base information were converted to bedMethyl format using Modkit v0.4.1 [96], and global 5-mC and 5hmC percentages were calculated using AWK v5.3.\u003c/p\u003e\n \u003cp\u003eDifferential methylation analyses were performed according to Flack et al. [94]. Count filtering, tiling into 100 bp windows, and differential methylation analysis were performed with MethylKit v1.30.0 [73]. Windows were considered DMRs if they had at least 10 CpGs, a mean absolute difference in methylation\u0026thinsp;\u0026ge;\u0026thinsp;50%⁠, and a Benjamini\u0026ndash;Hochberg-adjusted P-value of ⁠0.05 [97]. CpG sites are locations on a DNA strand where a cytosine is directly followed by a guanine nucleotide, connected by a phosphate bond. The cytosine within the CpG dinucleotide context can be methylated. DMRs were annotated by identifying the nearest gene with BedTools [98]. DMRs identified between individuals were visualized with karyotypeR v1.30.0 [99].\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e2.7 Identification of demethylation and methylation enzymes homologous in blacklegged tick populations.\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eDNA methylation is carried out by a group of enzymes that add a methyl group onto the 5th carbon in cytosine, DNMTs, which are traditionally named DNMT1, DNMT2, and DNMT3 [56,100]. Demethylation in the genome is regulated by TET dioxygenases and TDG [85]. To establish whether these enzymes are present in the genome of the blacklegged tick, we used the protein sequences of \u003cem\u003eHomo sapiens\u003c/em\u003e DNMT1 (AAI26228.1), DNMT2 (CAG29312.1), DNMT3a (AAH23612.1), and TET3 (NP_001274420.1) to identify homologs. Additionally, \u003cem\u003eMus musculus\u003c/em\u003e TDG (NP_766140.2) was used. Homologs were determined by Position-Specific Iterative (PSI)-BLAST search (NCBI, NIH, Bethesda, MD, US). The identity of the homologs was corroborated by confirming the presence of conserved domains within the proteins, using SMART v9 [35].\u003c/p\u003e\n \u003cp\u003eThe Expasy Translate Tool (Swiss Institute of Bioinformatics, Lausanne, Switzerland; [101]) was used to discard any non-protein coding sequence and identify the mRNA coding sequence for each enzyme, except TET3, for which several isoforms were identified. Trimmed sequences were used to design oligos using the Geneious Prime v2021.2 (Biomatters Inc, Auckland, New Zealand) and OligoAnalyzer Tool in IDT (Integrated DNA Technology Inc, Coralville, IA, US; [102]). In the case of DNMT3 and TDG, probes were designed using the PrimerQuest Tool. In the case of TET3, all isoform sequences were aligned in Geneious Prime v.2021.2 to locate a conserved region among all isoforms and primers were designed using this region (see Supplementary Fig. S8).\u003c/p\u003e\n \u003cp\u003eTo ascertain the expression of these enzymes in both populations of blacklegged ticks, RNA from individual ticks was purified from the lysate flow-through of the purified DNA from the ticks used in our 5-mC quantification experiments described above. RNA was isolated using the Quick-DNA/RNA Microprep Plus kit (Zymo Research), according to the manufacturer\u0026rsquo;s indications. RNA was eluted with 30 \u0026micro;l of DNA/RNase free water. cDNA was synthesized from the mRNA isolated from ticks collected from either MN or TX, using the Verso cDNA Synthesis Kit (Thermo Scientific), following the manufacturer\u0026rsquo;s protocols. Amplicons were amplified using GoTaq Flexi DNA Polymerase (Promega Corporation, Madison, WI) with the following thermal cycling conditions: one cycle of 95\u0026deg;C for 3 minutes, followed by 95\u0026deg;C for 60 s, 52\u0026ndash;55\u0026deg;C for 60 s, and 72\u0026deg;C for 30 s per 34 cycles, and a final extension at 72\u0026deg;C for 5 minutes. To verify the identity of the amplicons, PCR products were purified using QIAquick PCR purification kit (Qiagen), according to the manufacturer\u0026rsquo;s instructions. Purified PCR products were submitted to EtonBio (Eton Bioscience, Inc., San Diego, CA, US) for Sanger sequencing. The sequence identity was confirmed by BLAST and deposited in NCBI (Supplementary Table S18).\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e2.8 Measurement of DNA methylation and demethylation enzymes relative expression\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eIn other arthropod species, such as bees and ants, stimuli and memory formation can lead to the differential expression of DNMTs and TET [103,104]. Likewise, in ticks, cold temperatures can affect the expression of DNMTs [42]. To assess whether methylating and demethylating enzymes were differentially expressed in blacklegged tick populations, the primers listed in Supplementary Table S19 were used to assess the relative expression of DNMTs, TET, and TDG enzymes. The mRNA was normalized to 100 ng and used for cDNA synthesis as described above.\u003c/p\u003e\n \u003cp\u003eThe relative expression of DNMT1, DNMT2, and TET was evaluated using SyBR Green (Thermo Fisher Scientific, Carlsbad, CA, US), according to the manufacturer\u0026rsquo;s directions. However, DNMT3 and TDG were measured using TaqMan Fast Advanced Master Mix (Thermo Fisher Scientific), due to the presence of primer dimer and secondary products that could not be eliminated. All primers and probes are listed in Supplementary Table S19. All denaturing steps were performed at 95\u0026deg;C for 60 s and annealing temperature between 52\u0026ndash;55\u0026deg;C for 60 s over 39 cycles (see Supplementary Table S19, S20 for details about reaction conditions). Fluorescence was recorded during the annealing step to evaluate amplification. The specificity of the primers was verified by adding a melting curve step in the SyBR Green assays. Three biological replicates were performed to evaluate the relative expression of each gene. For the DNMT1 gene, four replicates were performed to achieve a consensus. All reactions were performed in a CXF Opus 96 (Bio-Rad Laboratories Inc, Hercules, CA, US).\u003c/p\u003e\n \u003cp\u003eThe relative expression of methylation and demethylation enzymes was calculated using 2\u003csup\u003e\u0026minus;\u0026Delta;CT\u003c/sup\u003e method [105], using actin as a normalizing gene [106]. Significant differences in gene expression were evaluated using a Two-way ANOVA in GraphPad Prism 9.4.1 (GraphPad Software, San Diego, CA, US).\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003ch3\u003eData availability\u003c/h3\u003e\n\u003cp\u003eRaw data from WGBS and WGS associated with this manuscript has been deposited in the National Center for Biotechnology Information (NCBI) under Bioproject number PRJNA1081399, and the nanopore raw reads can be found at https://datadryad.org/dataset/doi:10.5061/dryad.sbcc2frh8#citations. All code used for the analysis of the data, along with the raw output, is available in the public repository: https://github.com/steph166/contrastingEpigenetics-.\u003c/p\u003e\n\u003cp\u003eAccession numbers, PCR and qPCR amplification conditions, WGBS, WGB, and nanopore statistics and results, as well as a full list of differentially methylated sites and enrichment analyses in putative promoters and genes, are available in the supplementary material associated with this manuscript.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eThis research was funded by the USDA National Institute of Food and Agriculture Hatch MultistateProject #TEX0-1-7714, Texas A\u0026amp;M University the T3: Triads for Transformation to AOC, USDA award 58-8042-7-070 and Texas A\u0026amp;M University insect vector to RFM, and by a grant provide by the Midwest Center for Occupational Health and Safety Pilot Projects Research Training Program to JC. AL and SO were supported by EFAS-REEU (grant no. 2016-67032- 25013). The funders did not play any role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConceptualization: AOC and JDO; Methodology: AOC, JDO, PS, MCG, and CF; Investigation: SGV, JC, PS, AL, EL, CH, BLG, CC, CW, SO, MT, TJ, NAM, and AOC; Formal analysis: SGV, JC, PS, CF, and AOC; Validation: SGV and JC; Resources: PS, TJ, RFM, DMT, JDO, and AOC; Visualization: SGV and JC; Writing \u0026ndash; original draft preparation: SGV and JC; Writing \u0026ndash; review and editing: PS, JC, BLG, MT, TJ, MCG, RFM, DMT, CF, JDO and AOC; Supervision: JDO, CF, and AOC; Project administration: JDO and AOC; Funding acquisition: JDO and AOC.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe thank Dr. Donald H. Bouyer at UTMB who kindly provided DNA for TX ticks to assess the preliminary measurement of 5-mC level. This article reports the results of research only. Mention of a proprietary product does not constitute an endorsement or a recommendation by the USDA for its use. The USDA is an equal opportunity provider and employer.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eCenters for Disease Control and Prevention (CDC). Tickborne disease surveillance data summary; 2024. Database: CDC Ticks https://www.cdc.gov/ticks/data-research/facts-stats/tickborne-disease-surveillance-data-summary.html (2024).\u003c/li\u003e\n\u003cli\u003eKugeler, K. J., Schwartz, A. M., Delorey, M. J., Mead, P. S. \u0026amp; Hinckley, A. F. Estimating the frequency of Lyme disease diagnoses, United States, 2010–2018. \u003cem\u003eEmerg. Infect. 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Commun.\u003c/em\u003e \u003cb\u003e12\u003c/b\u003e, 3696; https://doi.org/10.1038/s41467-021-23900-8 (2021).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":true,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"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":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"DNA methylation, epigenetics, ticks, DNA methyltransferases","lastPublishedDoi":"10.21203/rs.3.rs-7762123/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7762123/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eHard ticks are a source of public health concern, in part due to their ability to inhabit different environmental regions, which increases human encounters. In the United States (US), blacklegged ticks (\u003cem\u003eIxodes scapularis\u003c/em\u003e Say), the primary vector of Lyme disease, exhibit various phenotypes depending on their geographic origin (i.e. northern and southern US ticks). Although genetics may partially explain how blacklegged tick populations acclimate to different environmental conditions across the US, epigenetics may also contribute to their success. Epigenetic mechanisms, such as DNA methylation, might modulate gene expression allowing for rapid adaptation. To gain insight into the potential contribution of DNA methylation, an Enzyme-Linked Immunosorbent Assay (ELISA) was utilized to evaluate differences in DNA methylation levels between blacklegged ticks collected from Minnesota (northern region) and Texas (southern region). DNA methylation profiles from both populations were characterized using bisulfite and nanopore sequencing. Our results revealed significant variability in methylation levels between the southern and northern tick populations and a highly variable relative expression of DNA methyltransferases and demethylases. Overall, northern blacklegged ticks exhibited a reduction in DNA methylation compared to southern ticks. Basic proline-rich protein, sortilin-related receptor, and peptidase M20 domain-containing protein 2-like are among the genes that exhibit a depletion in DNA methylation. Our findings revealed that blacklegged tick populations possess distinctive DNA methylation profiles, which may contribute to their phenotypic plasticity across the US. This study aims to pave the way for future research into the potential molecular mechanisms that allow ticks to successfully acclimatize to their present habitat.\u003c/p\u003e","manuscriptTitle":"Contrasting epigenetics of Ixodes scapularis populations","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-09 13:02:43","doi":"10.21203/rs.3.rs-7762123/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-11-14T11:16:57+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-13T05:08:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"89413170462118829734409657072928152175","date":"2025-11-11T07:00:16+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-01T02:03:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"243992934305584967243812238002527584205","date":"2025-10-23T17:04:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"125468931525299520071414295252684271081","date":"2025-10-13T18:27:10+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-07T13:44:12+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-10-07T10:26:38+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-06T11:09:08+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-04T07:47:43+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-10-01T19:30:14+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"81d58b65-178f-47c6-8876-215698dd246a","owner":[],"postedDate":"October 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":55975483,"name":"Biological sciences/Ecology"},{"id":55975484,"name":"Earth and environmental sciences/Ecology"},{"id":55975485,"name":"Biological sciences/Genetics"},{"id":55975486,"name":"Biological sciences/Molecular biology"},{"id":55975487,"name":"Biological sciences/Zoology"}],"tags":[],"updatedAt":"2026-04-29T08:54:49+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-09 13:02:43","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7762123","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7762123","identity":"rs-7762123","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}