De Novo assembly and analysis of the transcriptome of the Hyalomma anatolicum genes differentially expressed in normal morphology and disability

Abstract

At present, the research on tick malformations is still in its infancy, mainly focusing on the exploration of the abnormal forms, while the research on its molecular level is relatively scarce. In this study, under identical feeding conditions, three deformed adult ticks that occurred occasionally among 320 laboratory-bred Hyalomma anatolicum were selected as the research subjects, three adult ticks with normal morphology were observed and selected as controls by stereomicroscopy and the differences in gene expression between the two groups were analyzed through transcriptome sequencing technology. The results show that morphological identification and photo analysis reveal that abnormal ticks have deformities in limbs and/or mouthparts. Through differential gene analysis, it was revealed that compared with normal ticks, abnormal ticks showed a downward trend in the expressions of ecdysone-related genes of ecdysone-induced protein, cuticle protein and chitinase, detoxification-related genes of detoxification proteases and cytochrome, immune defense-related genes of antimicrobial peptides and antifreeze protein. However, the gene expressions of heat shock protein, serine protease, serine protease inhibitors, etc. showed an upward trend. This study has for the first time discovered that the transcriptome of adult ticks with morphological abnormalities is significantly different from that of normal individuals, suggesting that the dysregulation of gene expression may be related to morphological abnormalities. An in-depth exploration of the key genes in the growth and development of these ticks is expected to provide potential approaches for the development of new anti-tick strategies. Future studies need to further verify the functions of these differentially expressed genes.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s00436-026-08645-x.

Introduction

Tick deformities usually refer to abnormalities in their morphological structure or physiological function (Luz et al. 2023). These deformities may be caused by multiple factors and have a significant impact on the survival and reproduction of ticks. At the morphological level, local abnormalities are the most common, such as missing foot joints (Molaei and Little 2020) and leg deformations (Liu et al. 2019a; Shuaib et al. 2020). Furthermore, general anomalies also exist, such as hermaphroditism (Chitimia-Dobler and Pfeffer 2017). A long-term study in Brazil has shown that among 15 species of hard ticks collected from different hosts and environments, 31 adult individuals have developmental abnormalities, including both local and overall abnormalities(Luz et al. 2023). In terms of physiological functions, deformities may lead to serious disorders, such as reproductive dysfunction caused by abnormalities in the vaginal opening of female ticks. Such defects not only affect the reproductive ability of individuals but may also indirectly regulate the dynamic balance of the ecosystem by reducing the population renewal rate (Sosnovsky et al. 2020).

Current research has found that the causes of tick deformities can be attributed to three types of factors: environmental, biological and genetic. Among environmental factors, chemical pollution (such as pyrethroid pesticides, heavy metals like cadmium and lead) may cause morphological and physiological abnormalities of ticks (Jyoti et al. 2015; Agwunobi et al. 2020). Extreme climatic conditions (such as high temperatures, droughts or sudden changes in humidity) may affect molting or mating behaviors, indirectly causing physiological dysfunction (Nielebeck et al. 2023; Esteves et al. 2015; Jyoti et al. 2015). Pathogen infection is also a key trigger. Pathogens such as Rickettsia spp. and Babesia spp. can disrupt tissue development by interfering with cell division or gene expression (Owashi et al. 2024; Comeau et al. 2020), while novel RNA viruses and other microorganisms may affect the development of offspring through vertical transmission (Wu et al. 2016). At the genetic level, gene mutations or abnormal epigenetic modifications may lead to dysregulation of the expression of key genes such as shield plate formation and appendage differentiation, thereby causing deformities (Gottlieb and Duron 2021).

At present, the research techniques for tick deformities are mainly focused on morphological analysis. That is, through high-resolution microscopes (such as scanning electron microscopes) and 3D modeling technology, the deformed structures are observed and parameters (such as the area of the mandibular foramen and the length of the foot segments) are quantified to provide an accurate description of the morphological abnormalities (Molaei and Little 2020). Transcriptome analysis has been well-established in tick research (Yu et al. 1971; Ng et al. 2005; Cui et al. 2019), but these studies failed to deeply reveal the molecular mechanisms behind the malformed phenotypes, resulting in still insufficient understanding of abnormal tick development at the genetic level. In this study, transcriptome data from abnormal and normal tick samples were compared to systematically identify differentially expressed genes closely associated with tick physiological dysfunction, including ecdysone-related genes of ecdysone-induced protein, stratum corneum protein and chitinase, detoxification-related genes of detoxification proteases and cytochrome, immune defense-related genes of antimicrobial peptides and antifreeze protein, heat shock protein, serine protease, and serine protease inhibitors. Significant upregulation or downregulation of these genes was directly correlated with tick viability, developmental abnormalities, resistance development, and pathogen transmission efficiency. By elucidating the molecular mechanisms of key functional genes in ticks, this study provides a theoretical foundation and molecular targets for the development of targeted vaccines, precision therapeutics, gene-editing-based control strategies, and environmentally sustainable approaches. Furthermore, it highlights a potential path toward overcoming the limitations of traditional methods, such as resistance development and ecological disruption. Future research should focus on target gene validation, optimization of gene-editing tools, and the integration of eco-friendly technologies to achieve sustainable tick control.

Methods

Rabbits and ticks

Four-month-old female New Zealand rabbits (2.5–3.0 kg), purchased from the Experimental Animal Center of Shihezi University, China, were selected for the experiment. The rabbits were fed a commercial diet and housed individually in separate cages at 25 ± 1 °C and 40% relative humidity (RH). Hyalomma anatolicum were placed in cloth bags enclosing the rabbits’ ears to allow blood-feeding. Ticks were checked daily until fully engorged. The replete ticks were then collected and maintained under controlled experimental conditions at 26 ± 1 °C and 75 ± 5% RH (Song et al. 2022). The experiments were conducted in accordance with the guidelines approved by the Animal Protection and Utilization Committee of Shihezi University.

Ticks sample

H. anatolicum were laboratory-reared as previously described (Song et al. 2022). The engorged nymphs molted into adult ticks, and three abnormal ticks out of 320 ticks were observed. To study this phenomenon, we randomly selected three normal ticks and these three abnormal ticks for transcriptome analysis. The selected ticks were washed with phosphate-buffered saline (PH 7.4) at room temperature, placed on sterile gauze to dry, and then transferred into microcentrifuge tubes and immediately frozen in liquid nitrogen.

RNA extraction, library construction, and sequencing

The tick samples were subjected to RNA extraction, purification, and library construction, followed by paired-end sequencing using second-generation sequencing technology on the Illumina platform.

Total RNA was extracted using Trizol reagent (Invitrogen). RNA integrity was assessed using the RNA 6000 Nano assay kit on the Agilent Bioanalyzer 2100 system (Agilent Technologies, CA, USA). The mRNA with polyA structure in total RNA was enriched by Oligo(dT) magnetic beads. The RNA was broken into fragments of about 300 bp in length by ion interruption. cDNA was synthesized using either random hexamer primers or Oligo(dT) primers (PrimeScript™ 1 st stand cDNA Synthesis Kit), followed by Illumina library construction. The average library insert size was approximately 450 bp. Library quality was evaluated using the Agilent 2100 Bioanalyzer.

De Novo assembly, unigene annotation and functional classification

The raw sequencing reads were processed with Cutadapt (v1.16) to remove adapter sequences and low-quality bases. Reads with an average quality score below Q20 were discarded, and those shorter than 50 bp after trimming were removed. The quality of the cleaned data, including Q20, Q30 scores, and GC content, was verified using FastQC (v0.11.8). De novo transcriptome assembly was then performed on the high-quality cleaned reads using Trinity (v2.5.1). Trinity groups transcripts into clusters based on shared sequence content. The longest transcript in the cluster was chosen as the unigene sequence.Functional annotation of unigenes was conducted using the following databases: NR (NCBI non-redundant protein sequences), GO (Gene Ontology), KEGG (Kyoto Encyclopedia of Genes and Genomes), eggNOG (evolutionary genealogy of genes: Non-supervised Orthologous Groups), Swiss-Prot, and Pfam.

Differentially expressed unigene analysis

Differential expression analysis was performed using DESeq2, with thresholds of |log₂Foldchange| > 1 and false discovery rate < 0.05. GO and KEGG enrichment analyses were then conducted on the differentially expressed unigenes using in-house Perl scripts.

Real-time quantitative PCR validation of RNA sequencing (RNA-seq) results

The consistency of gene expression levels was validated by real-time quantitative polymerase chain reaction (RT-qPCR). RT-qPCR was performed using the same transcriptome sequencing samples, and expression levels of six selected genes were assessed: Cystatin-A2 (DN1185), acetylcholinesterase (DN9905), ceramide phosphoethanolamine synthase (DN9153), zinc finger protein 521 (DN114429), adult-specific rigid cuticular protein 15.7 (DN2986), and juvenile hormone acid O-methyltransferase (DN114954). These genes were chosen based on their differential expression between normal ticks (N_tick) and abnormal ticks (Abn_tick). RNA extraction was performed as previously described. First-strand complementary DNA (cDNA) templates were synthesized using the PrimeScript™ 1 st strand cDNA Synthesis Kit (TaKaRa, Japan). Single-stranded cDNA was used as the template for RT-qPCR, which was conducted using the AceQ^® qPCR SYBR^® Green Master Mix (Vazyme, China) on a MA-6000 real-time fluorescence quantitative PCR instrument (MA-6000, Molarray, China). Specific primers for the target genes and the internal control are listed in Table 1. The RT-qPCR procedure consisted of an initial denaturation at 95 °C for 5 min, followed by 40 cycles of denaturation at 95 °C for 15 s and annealing/extension at 60 °C for 30 s. mRNA expression levels from both the transcriptome data and RT-qPCR were normalized to glyceraldehyde-3-phosphate dehydrogenase (GAPDH) (Xu et al. 2019) expression using the comparative cycle threshold method.

Table 1.

Specific primers used in the RT-qPCR validation of RNA-seq results

Primer pair	(5’ to 3’)	Annotation	Unigene
Cys-A2-F	TGTAGCTGACGGGTGTGAAC	cystatin-A2	DN1185
Cys-A2-R	ACCACCGAGAAGACACGATG
Ache-2 F	GTCTGCAAGGGTGTACGTGA	acetylcholinesterase	DN9905
Ache-2R	TGCATCATCCCGGCTTTTCT
CPES-F	CGTGAAGACGACCAGAGTCC	ceramide phosphoethanolamine synthase	DN9153
CPES-R	CAAACAGAGGTGCTGCGTTC
ZNF 521-F	ATGCACTCCAGCGTAGCTTT	Zinc finger protein 521	DN114429
ZNF 521-R	ATAGCAGATACTGGGCACCG
CPR 15. 7-F	AATGACCACGGCCACTACAG	adult-specific rigid cuticular protein 15. 7	DN2986
CPR 15. 7-R	CGTCGATGTCACCCAGGTAG
JHAMT-F	TCAGCCACGAGGAGAAGTTG	juvenile hormone acid O-methyltransferase	DN11495
JHAMT-R	CGGAGACTTACACGCCTTGA
GAPDH-F2	AGAAGGCTCAGCAGCACATT	glyceraldehyde-3-phosphate dehydrogenase	GAPDH
GAPDH-R2	TGTAGGTGGTGTGGTTCACG

Results and discussion

Morphological differences

Under identical feeding conditions (Song et al. 2022), three morphologically abnormal H. anatolicum exhibited morphological deformities following molting from engorged nymphs. Abnormalities were documented using photography. The picture presents dorsal and ventral views of normal ticks and abnormal ticks (Fig. 1). Focus on the normal mouthparts and limb states (n, o, p, q), and use them as the reference benchmark for direct morphological comparison. The deformed parts of abnormal ticks are marked with red arrows, such as abnormal mouthparts structure (e, i, k), limb distortion (b, d, f, h, j, l), and obvious limb absence (m).

Fig. 1.

Comparison of the morphology of normal and abnormal ticks. The illustration contains the dorsal and ventral views of a normal tick (as morphological benchmarks), as well as three rare deformity specimens with missing limbs. The abnormal structure of the capitulum and appendages of the malformed tick has been clearly marked by a red arrow in the figure

Ticks rely on their functional appendages and mouthparts to carry out a series of crucial survival activities (Vancová et al. 2020; Chitimia-Dobler et al. 2023). These activities include precisely locating and attaching to the host by coordinating the movement of appendages, achieving a safe and effective blood-sucking process, and completing mating through precise positioning ability. However, these structural abnormalities, such as limb loss or malformed mouthparts, have severely weakened the ecological adaptability of ticks. Impaired mobility hinders its efficiency in finding a host, increasing the risk of shedding and energy consumption during foraging (Leal et al. 2020). Meanwhile, the defects of the mouthparts disrupt the penetration of the skin, the uptake of blood, and the secretion of anticoagulant compounds, resulting in prolonged eating time and enhanced immune clearance ability of the host (Neelakanta and Sultana 2022). These morphological abnormalities can also interfere with the transmission mechanisms of pathogens such as Borrelia burgdorferi (Lyme disease), thereby reducing the transmission capacity of the vectors (Nuttall 2023). Furthermore, the low mating efficiency caused by motor defects further reduces the reproductive success rate and exacerbates the decline in population size (Chilton et al. 1993). Especially when the malformations result from genetic mutations, it will reduce genetic diversity and adaptability. Studying the causes of these deformities, whether due to environmental stress, pathogenic infections or genetic mutations, not only helps to clarify the developmental biology of ticks, but also provides important information for innovative control strategies, such as targeted induction of debilitating morphological traits to disrupt disease transmission cycles or population sustainability in wild ecosystems.

Sequencing and assembly

Illumina sequencing of six H. anatolicum adult tick samples generated 283,946,816 raw reads (Table 2). After filtering out low-quality reads, 270,588,294 clean reads were retained, accounting for 94.76% of the raw data. De novo transcriptome assembly was performed using Trinity, resulting in a total of 220,262 putative transcripts with an N50 of 2811 bp, which were further clustered into 111,892 unigenes. A summary of the assembly metrics is provided in Table 3. In terms of sequence length, all unigenes were longer than 200 bp, with the longest unigene measuring 28,126 bp (Additional file 1).

Table 2.

Sequencing data statistics

Sample	Raw_Reads	Raw_Bases	Valid_Reads	Valid_Bases	Valid%	Q20%	Q30%
Abn_tick1	51,980,070	7,797,010,500	49,583,942	7,437,591,300	95. 39%	98. 24	94. 87
Abn_tick2	50,107,902	7,516,185,300	47,699,646	7,154,946,900	95. 19%	98. 24	94. 9
Abn_tick3	46,679,824	7,001,973,600	44,523,174	6,678,476,100	95. 37%	98. 34	95. 14
N_tick1	43,471,968	6,520,795,200	41,436,784	6,215,517,600	95. 31%	98. 06	94. 46
N_tick2	45,841,872	6,876,280,800	43,555,210	6,533,281,500	95. 01%	98. 05	94. 46
N_tick3	45,865,180	6,879,777,000	43,789,538	6,568,430,700	95. 47%	98. 17	94. 74

Table 3.

Summary of the H. anatolicum transcriptome assembly

Type	Total Length (bp)	Sequence Number	Max. Length (bp)	Mean Length (bp)	N50 (bp)	N50 Sequence No.	N90 (bp)	N90 Sequence No.	GC%
Transcript	317,108,033	220,262	28,126	1440	2811	31,569	509	138,314	48
Unigene	115,187,431	111,892	28,126	1029	1740	15,307	397	78,459	47

Species distribution and correlation analysis

Functional annotation of the assembled unigenes was performed by analyzing the 111,892 unigene sequences against six reference databases. The National Center for Biotechnology Information non-redundant protein database showed the highest identification rate at 27.13%, whereas the KEGG database had the lowest at 8.50% (Table 4). Among the annotated unigenes, 87.72% shared homology with tick species sequences, and nearly half were most similar to Rhipicephalus sanguineus (Fig. 2). The heatmap tree (Additional file 2) illustrates correlations between the sample groups. Samples within the N_tick group exhibited a high degree of correlation (r ≈ 0.96), indicating strong intra-group similarity. Although the Abn_tick group showed a moderate degree of internal correlation, its values showed significant dispersion (r = 0.88 ~ 0.94), which may be due to the transcription profile of Abn_tick3. In contrast, Abn_tick1 and Abn_tick2 not only were highly correlated with each other (r ≈ 0.94) but also showed strong correlations with the normal group (r = 0.91 ~ 0.92), possibly indicating a conserved global transcriptional structure between these specific abnormal samples and the normal phenotype.

Table 4.

Summary of annotation results

Database	Number	Percentage
NR	30,352	27.13
GO	12,419	11.10
KEGG	9514	8.50
Pfam	12,643	11.30
eggNOG	20,923	18.70
Swissprot	14,304	12.78
In all database	6308	5.64

Fig. 2.

Species distribution on NR annotation. The pie chart of taxonomic assignment of unigenes. The percentage of unigenes assigned to each taxonomic group is shown on the right. Best hits to “Others” include arthropods other than tick species

Analysis of differences in gene expression between groups

To clarify the molecular regulatory mechanism of abnormal conditions on ticks, this study conducted a transcriptome comparative analysis of abnormal ticks (Abn_tick) and normal ticks (N_tick). Based on 109,322 detected genes, a total of 88,389 common genes that were stably expressed in both groups were obtained (Fig. 3A). By setting a difference threshold (log₂FoldChange > 1, p-value < 0.05), a total of 2,422 Differentially Expressed Genes (DEGs) were identified, among which 1,386 genes were upregulated and 1,036 genes were down-regulated (Fig. 3B). This result initially indicates that abnormal factors have induced extensive transcriptome changes, and the response of upregulated gene expression is more active. Further, hierarchical clustering analysis was conducted based on the expression levels of all DEGs. The heat map showed that abnormal samples and normal samples formed two independent clustering branches respectively, visually confirming the systematic differences in transcriptional patterns between groups (Fig. 3C). Trend clustering analysis further identified multiple gene clusters with obvious expression dynamics (Fig. 3D). These co-expression modules suggest that there may be biological pathways or functional units subject to co-regulation, providing clues for subsequent mechanism analysis.

Fig. 3.

Results of Transcriptome Differential Expression analysis. A Venn diagrams of shared and uniquely differentially expressed genes in the comparison between the two groups (Abn_tick vs N_tick). The overlapping area indicates the number of shared genes. B The histogram shows the number of up-regulated and down-regulated differentially expressed gene in both compared group. C Hierarchical clustering heat maps of differentially expressed genes in all samples. The colored bars indicate the changes in gene expression levels after standardization; Similar colors indicate high correlation. Green indicates low expression and red indicates high expression. D Trend clustering analysis of differentially expressed genes between normal and abnormal samples

GO classification

The annotated sequences were functionally categorized using GO classification across three main categories: molecular function, cellular component, and biological process. GO terms were retrieved from the GO database and used to assign functional roles to the genes (Fig. 4).

Fig. 4.

Gene Ontology classifcation of H. anatolicum transcriptome data. Bars and numbers represent number of genes in each protein class. Red bars refer to biological process, green bars refer to cellular component and blue bars refer to molecular function. The X axis shows the number of unigenes in each category

The most abundantly annotated GO terms were cellular anatomical entity and cellular process, followed by binding activity and metabolic process. Additional GO annotations included response to stimulus, protein-containing complex, transporter activity, and cellular component organization or biogenesis.

KEGG pathway enrichment analysis

To further interpret systemic functions, the H. anatolicum dataset was mapped to KEGG pathways. The 20 most significantly enriched pathways are shown in Fig. 5. These pathways included those related to protein processing, glycan biosynthesis, lipid metabolism, detoxification, and defense responses.

Fig. 5.

Signifcantly enriched KEGG pathways associated with normal tick and abnormal tick. The X axis shows the rich factor that is the ratio of diferentially expressed unigenes in a pathway term to all gene numbers annotated in the same pathway term. The bubbles represent the number of unigenes and the gradient coloration indicates the corrected P-value by the FDR method. Only pathways with P < 0. 05 were shown

Among abnormal ticks, multiple signaling pathways related to metabolic processes (such as steroid hormone biosynthesis), DNA damage repair (such as chemical carcinogenesis), immune regulation (such as antigen presentation), and longevity (such as the nematode longevity pathway) show significant enrichment phenomena. The abnormalities of these pathways may be associated with the physiological state changes of ticks (such as pathological responses, environmental adaptability or host immune escape), providing a clear direction for subsequent research.

Differential gene analysis between abnormal and normal ticks

The structural integrity of limbs and mouthparts is essential for the growth, development, and reproduction of ticks. Differential gene analysis revealed that compared with normal ticks, abnormal ticks had downregulated genes related to ecdysone-related genes of ecdysone-induced protein, cuticle protein and chitinase, detoxification-related genes of detoxification proteases and cytochrome, immune defense-related genes of antimicrobial peptides and antifreeze protein (Table 5). Investigating candidate genes involved in tick deformities at the genetic level may offer a novel approach for anti-tick strategies.

Table 5.

Selected differentially expressed unigenes (down and up) putatively between normal ticks and abnormal ticks

Predictive Function	NR Annotation	Regulation	N_tick	Abn_tick	Log2 Fold change (Abn_tick/N_tick)	P-value	Gene ID
Reproduction/development	TPA: ecdysone-induced protein 63 F 1	down	11. 99	0. 89	−3.76	0. 015	DN43239
	juvenile hormone acid O-methyltransferase	down	29. 78	5. 00	−2.57	0. 004	DN114954
	craniofacial development protein 2	down	5. 47	0	-Inf	0. 046	DN23834
	arylsulfatase B	down	5. 80	0	-Inf	0. 038	DN61560
	double-strand-break repair protein	down	8460. 95	664. 47	−3.67	0. 011	DN3576
Hydrolyzation	chitotriosidase-1	down	166. 52	37. 22	−2.16	0. 009	DN62451
Exoskeleton formation/ development	adult-specific rigid cuticular protein 15. 7	down	598. 11	62. 14	−3.27	0. 006	DN2986
	cuticle protein 16. 8	down	78. 40	8. 27	−3.25	0. 035	DN140519
	cuticle protein 10. 9	down	16. 76	3. 00	−2.48	0. 031	DN128394
	glycine-rich cell wall structural protein 1. 0	down	166. 19	14. 85	−3.48	< 0. 001	DN9891
	collagen alpha-1 (I) chain	down	833. 90	115. 86	−2.85	< 0. 001	DN167182
Drug resistance	cytochrome P450 2A12	down	32. 71	2. 78	−3.55	0. 030	DN28459
	cytochrome P450 3A4	down	220. 09	52. 62	−2.06	0. 012	DN134629
Oxidant metabolism /detoxification	glutathione S-transferase Mu 2	down	412. 91	3. 43	−6.91	0. 008	DN7352
	Epsilon class glutathione S-transferase protein 1	down	24. 76	6. 12	−2.02	0. 027	DN3406
Defence	zonadhesin	down	7. 23	0	-Inf	0. 017	DN167776
	ice-structuring glycoprotein	down	1149. 76	35. 84	−5.00	0. 020	DN4689
Immunity /antimicrobial	ctenidin-1	down	25. 52	0	-Inf	< 0. 001	DN5799
	lachesin	down	288. 71	59. 42	−2.28	< 0. 001	DN19269
	A disintegrin and metalloproteinase with thrombospondin motifs 12	down	114. 24	10. 68	−3.42	0. 032	DN2750
	hemocytin	down	9333. 85	3495. 35	−1.42	0. 004	DN566
	complement factor B	down	17. 24	0. 57	−4.91	< 0. 001	DN41024
	N-acetylmuramoyl-L-alanine amidase	down	12. 27	0. 94	−3.70	0. 013	DN8014
Blood feeding	venom serine carboxypeptidase	down	365. 28	0	-Inf	0. 034	DN1392
	chymotrypsin-like protease CTRL-1	down	2357. 82	991. 78	−1.25	0. 004	DN3077
	thromboxane-A synthase	down	411. 53	15. 64	−4.72	0. 002	DN6323
Metabolism/ detoxification	sulfotransferase family cytosolic 1B member 1	down	564. 85	129. 67	−2.12	< 0. 001	DN826
	sulfotransferase 1E1	down	72. 07	9. 91	−2.86	< 0. 001	DN30772
	vitamin D 25-hydroxylase	down	11. 23	0. 29	−5.29	0. 017	DN53846
	alpha-tocopherol transfer protein	down	304. 37	79. 28	−1.94	0. 001	DN686
Response to Stress Conditions	heat shock protein 90 − 2	up	0	11. 99	Inf	0. 001	DN60626
Blood feeding	kunitz-type serine protease inhibitor 6	up	2. 038	110. 32	5.76	< 0. 001	DN1721
	serine protease inhibitor swm-1	up	0. 34	8. 30	4.61	0. 026	DN42504
	venom peptide MmKTx	up	2. 71	47. 54	4.13	< 0. 001	DN8449
	chymotrypsin inhibitor	up	8. 55	118. 47	3.79	0. 033	DN160582
	cystatin-A2	up	338. 10	2699. 58	3.00	0. 023	DN1185
	BPTI/Kunitz domain-containing protein	up	4. 10	24. 58	2.58	0. 021	DN12498
	boophilin-H2	up	370. 08	1478. 30	2.00	< 0. 001	DN8393
Antimicrobial	antimicrobial peptide microplusin	up	746. 75	28,927. 73	5.28	0. 003	DN42436
	defensin	up	0. 66	22. 09	5.05	0. 020	DN146342
	lysozyme c-1	up	107. 52	2121. 36	4.30	0. 021	DN1310
	TPA: lysozyme f2	up	18. 25	82. 91	2.18	0. 012	DN138005
Protein Degradation	transmembrane protease serine 9	up	146. 26	1838. 24	3.65	< 0. 001	DN6118
	serine proteinase stubble	up	1. 02	9. 68,307	3.24	0. 046	DN11708
	procathepsin L	up	8. 19	55. 41	2.76	0. 030	DN20844
	cathepsin D	up	63. 60	248. 41	1.97	< 0. 001	DN120291

The ecdysone-induced calcium-binding protein TPA (E63-1) was initially discovered in the early pupation region of Drosophila melanogaster 63 F, where it is significantly expressed in response to ecdysone pulses. This protein plays a key role in the reprogramming of gene expression at the end of larval development, marking the initiation of the metamorphosis process. At the 63 F locus, there are two ecdysone-inducing genes: E63-1 and E63-2. Among them, the E63-1 gene is specifically expressed in the salivary glands in the later stage of the third larva (Andres and Thummel 1995; Vaskova et al. 2000). In the abnormal tick group, transcripts annotated as TPA (ecdysone-induced protein 63 F-1, DN43239, TPM: 156.54) were significantly down regulated compared to the normal tick group (TPM: 36.89). This observation indicates that there may be potential abnormalities in the metamorphosis and development of ticks, particularly affecting the salivary glands. Therefore, in the context of vaccine development, targeting the salivary glands may represent a more direct strategy potentially impairing molting and subsequent developmental processes.

In arthropods such as ticks, molting is a complex process involving the degradation of old exoskeletons and the formation of new ones, in which chitinase and cuticle proteins play essential roles in this process. Chitinase promotes the decomposition of old exoskeletons and the formation of new exoskeletons by degrading chitin (Liu et al. 2019b), which is particularly crucial during developmental stages such as from nymph to adult (Zhang et al. 2024). Cuticle proteins, as structural components of the exoskeleton, maintain morphological integrity, protect internal tissues, and participate in physiological processes such as molting (Muthukrishnan et al. 2020). RNA-seq analysis revealed that expression levels of chitinase (chitotriosidase-1, DN62451, TPM: 359.33) and cuticular proteins adult-specific rigid cuticular protein 15.7 (DN2986, TPM: 4707.06), cuticle protein 16.8 (DN140519, TPM: 235.39), and cuticle protein 10.9 (DN128394, TPM: 129.59) were significantly lower in abnormal ticks than in normal ticks (TPM: 255.51, TPM: 1555.71, 78.98, TPM: 73.75). This aberrant expression may disrupt the degradation and reconstruction of the exoskeleton, potentially contributing to tick malformations.

Several proteins involved in detoxification are present in ticks, including cytochrome P450 enzymes and glutathione S-transferases (GSTs). Cytochrome P450 is the main detoxification enzyme system of ticks, participating in compound metabolism and closely related to the development of drug resistance in ticks (Vontas et al. 2020; Nauen et al. 2022). GSTs is a multifunctional enzyme that can reduce the toxicity of exogenous toxins and promote their excretion, while participating in the metabolism of endogenous compounds and maintaining cellular homeostasis (Enayati et al. 2005; Masoud et al. 2023). GSTs play a key role in the resistance of insects and ticks to insecticides by enhancing metabolic detoxification and reducing the active concentration of compounds (Tao et al. 2022; Sun et al. 2024). In this study, the downregulation of detoxification-related proteins cytochrome P450 2A12 (DN28459, TPM: 115.50), cytochrome P450 3A4 (DN134629, TPM: 566.26), glutathione S-transferase Mu 2 (DN7352, TPM: 3177.67), and Epsilon-class glutathione S-transferase 1 (DN3406) may impair the detoxification capacity of abnormal ticks (TPM: 31.28, TPM: 430.67, TPM: 83.98).

Antifreeze proteins (AFPs) are widely present in insects, fish, plants, and other organisms, where they inhibit ice crystal growth or lower the freezing point to prevent cellular damage (Duman and Newton 2020; Baskaran et al. 2021). As ectothermic animals, ticks rely on environmental adaptability for survival. Expression levels of antifreeze proteins zonadhesin (DN167776, TPM: 63.83) and ice-structuring glycoprotein (DN4689, TPM: 2885.59) were significantly lower in abnormal ticks than in normal ticks (TPM: 0, TPM: 286.12), suggesting that its low-temperature resistance may be reduce.

Antimicrobial peptides (AMPs) are a class of small-molecule peptides with broad-spectrum antimicrobial activity, widely present in animals, plants, and microorganisms (Valdez-Miramontes et al. 2021). As obligate blood-feeding arthropods, ticks are exposed to various pathogens throughout their life cycle, among which antimicrobial peptides play a key role. These peptides protect the tick by directly killing or inhibiting the growth of microorganisms such as bacteria, fungi, and parasites (Fogaça et al. 2021). Ctenidins (e.g., ctenidin-1, DN5799) are glycine-rich antimicrobial peptides originally identified in the hemocytes of the spider Cupiennius salei (Baumann et al. 2010). Based on RNA-seq analysis, the expression level of ctenidin-1 was significantly lower in abnormal ticks (TPM: 0) than in normal ticks (TPM: 373.78). This suggests that malformed ticks may be more susceptible to pathogen invasion during critical stages of growth and development, potentially impairing their overall viability.

Simultaneously, ticks appear to activate intrinsic protective mechanisms by initiating stress responses in reaction to potential environmental stressors, as indicated by the upregulation of genes such as heat shock proteins, serine proteases, and serine protease inhibitors (Table 5).

Heat shock protein 90 (Hsp90) is a highly conserved molecular chaperone that participates in the folding, stabilization and functional regulation of proteins and plays a key role in responding to environmental stress (Quel et al. 2020). Ticks often face temperature fluctuations due to the complexity of their habitats and life cycles. Hsp90 helps them adapt to extreme temperatures. Hard ticks, which are widely distributed, exhibit differential expression of Hsp90 under various thermal conditions, underscoring its role in temperature adaptation (Stevenson et al. 2022; Li et al. 2023). B. burgdorferi relies on ticks as vectors, and Hsp90 may play a regulatory role in the interaction between ticks and pathogens (Taraveau et al. 2023). Additionally, research indicates that Hsp90 is essential for egg hatching and larval development in Ornithodoros moubata, likely due to its chaperone-mediated involvement in developmental processes (Taraveau et al. 2023). The upregulation of heat shock proteins pecifically heat shock protein 90 − 2 (DN60626, N_tick TPM: 0, Abn_tick TPM: 32.57) in abnormal ticks suggests that these individuals may be undergoing physiological or environmental stress. In response, tick cells may enhance protein homeostasis by increasing the expression of heat shock proteins to mitigate potential cellular damage or dysfunction. This upregulation may represent a self-protective mechanism under abnormal conditions, aiming to preserve essential physiological functions and improve survival.

Serine proteases and serine protease inhibitors (Serpins) form a dynamic regulatory system in ticks, playing essential roles in maintaining physiological homeostasis and adaptive functions. Serine proteases participate in multiple processes during blood-feeding, including blood digestion, anticoagulation, and immune modulation (Reyes et al. 2020). In contrast, Serpins regulate enzymatic balance by inhibiting excessive serine protease activity, thereby preventing uncontrolled proteolysis (Verissimo et al. 2020). The tick innate immune system relies on serine protease cascades for example, those involved in coagulation and antimicrobial peptide release to combat pathogen invasion. Serpins modulate this system by preventing overactivation of immune responses that could result in self-damage. Disruption of this protease–inhibitor equilibrium may lead to abnormal reproduction, immune dysregulation, or altered pathogen transmission capacity. In the ovaries of Rhipicephalus haemaphysaloides, Serpin molecules have been shown to play important roles in reproduction. Their high expression may regulate proteolytic activity involved in vitellogenin processing or signaling pathways critical to embryonic development, thereby promoting oviposition and enhancing larval survival (Hao et al. 2017). Imbalanced expression of serine proteases transmembrane protease serine 9 (DN6118; N_tick TPM: 1347.86, Abn_tick TPM: 3527.73) and serine proteinase stubble (DN11708, N_tick TPM: 21.78, Abn_tick TPM: 42.86) and Serpins kunitz-type serine protease inhibitor 6 (DN1721, N_tick TPM: 47.21, Abn_tick TPM: 532.25) and serine protease inhibitor swm-1 (DN42504, N_tick TPM: 7.21, Abn_tick TPM: 36.57) may contribute to reproductive abnormalities in ticks, such as reduced egg hatching rates or developmental defects in larvae.

RT-qPCR validation of RNA-seq data

To validate the RNA-seq results, the expression levels of six selected genes, three upregulated and three downregulated, were assessed using RT-qPCR, with GAPDH as the internal reference gene. The selected genes encode the following proteins: Cystatin-A2 (DN1185), acetylcholinesterase (DN9905), ceramide phosphoethanolamine synthase (DN9153), zinc finger protein 521 (DN114429), adult-specific rigid cuticular protein 15.7 (DN2986), and juvenile hormone acid O-methyltransferase (DN114954) (Fig. 6). Comparison of RT-qPCR and RNA-seq results confirmed that all six genes exhibited consistent transcriptional expression trends. The normalized fold-change values, calculated using GAPDH as a reference, are presented in Table 1. Transcripts encoding Cystatin-A2, acetylcholinesterase, CPES, ZNF521, CPR15.7, and JHAMT showed similar expression patterns in RT-qPCR analysis (Fig. 6).

Fig. 6.

RT-qPCR validation of selected 6 differentially expressed genes in the RNA-seq. RT-qPCR was performed using cDNA templates derived from adult H. anatolicum. The expression profiles of the 6 genes in 2 kinds of the tick are indicated above. Red bar represents normal ticks (N_ tick) and beige bar represents abnormal ticks (Abn_tick)

Conclusions

This study shows for the first time that the transcriptome of adult ticks with abnormal morphology is significantly different from that of normal individuals, providing the first indirect evidence that “dysregulated gene expression may be associated with abnormal morphology”. Using RNA-seq analysis, we systematically annotated gene functions at the whole transcriptome level and speculated that the differential expression of ecdysin-related genes, such as ecdysin-induced proteins, cuticle proteins, and chitinases, was closely related to developmental malformations in ticks. At the same time, the abnormal expression of detoxification related genes such as detoxification protease and cytochrome P450, and immune defense related genes such as antimicrobial peptides and antifreeze proteins may affect the metabolism, stress resistance and interaction ability of ticks with pathogens, thereby reducing their physiological function, survival adaptability and disease transmission potential.

Based on these molecular-level insights, we propose a novel eco-friendly control strategy centered on targeted population suppression. The core approach involves utilizing these key adaptive genes as intervention targets. On one hand, their encoded proteins can serve as potential new targets for anti-tick vaccines. By vaccinating hosts, an immune response can be triggered during tick feeding to neutralize these critical proteins, thereby directly reducing their adaptive capacity in the wild. Additionally, gene-targeting technologies (e.g., RNAi, CRISPR/Cas9) can be employed for functional validation and knockout, enabling the design of engineered ticks carrying heritable traits that reduce adaptability (e.g., conditional cold sensitivity or immune deficiency). When coupled with gene drive systems, such traits can spread within wild populations, subsequently subjecting them to strong selective pressure under environmental stressors (e.g., low temperatures), potentially leading to population decline. This strategy transcends simple competitive replacement by actively propagating genetic burdens.

We acknowledge that limitations in laboratory rearing of abnormal ticks constrained our sample size and experimental design. The hypothesized role of molting-related gene expression from larva to adult requires further validation. Nevertheless, this study delineates a novel molecular research direction and offers a preliminary scientific foundation for both understanding tick developmental anomalies and innovating genetic-based population control strategies.

Supplementary Information

Below is the link to the electronic supplementary material.

Abbreviations

H. anatolicum

Hyalomma anatolicum

B. burgdorferi

Borrelia burgdorferi

CRISPR/Cas9

CRISPR-associated protein 9

GSTs

glutathione S-transferases

AMPs

Antimicrobial peptides

AFPs

Antifreeze proteins

Hsp90

Heat shock protein 90

Serpins

serine protease inhibitors

Author contributions

RS and JZ conceived and designed the study, and wrote the manuscript. JZ, RS and TG performed the experiments and analyzed the data. JZ, RS, RX, NL MZ, and YW contributed to study design and edited the manuscript. SW provided critical guidance during the manuscript revision. All authors read and approved the final manuscript.

Funding

This work was supported by “Tianshan Talent” Youth Support Talent Project (2024TSYCQNTJ0056), Science and Technology Program of XPCC (2025ZD002), the Natural Science Foundation of China (32202833), The Youth Innovative and Outstanding Talent Program (CXBJ202311).

Data availability

The sequences obtained and analyzed during the present study are deposited in the GenBank database under the accession numbers (SRR33822874, SRR33822875, SRR33822876, SRR33822877, SRR33822878, SRR33822879).

Declarations

Ethical approval and consent to participate

This study was reviewed and approved by the ethics committee of School of Medicine, Shihezi University in accordance with the medical regulations of China (A2022-053-01).

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.