Skip to main content
Download PDF

Comparative genome-wide identification and characterization of SET domain-containing and JmjC domain-containing proteins in piroplasms

BMC Genomics volume 25, Article number: 804 (2024) Cite this article

A Correction to this article was published on 26 September 2024

This article has been updated

Abstract

Background

SET domain-containing histone lysine methyltransferases (HKMTs) and JmjC domain-containing histone demethylases (JHDMs) are essential for maintaining dynamic changes in histone methylation across parasite development and infection. However, information on the HKMTs and JHDMs in human pathogenic piroplasms, such as Babesia duncani and Babesia microti, and in veterinary important pathogens, including Babesia bigemina, Babesia bovis, Theileria annulata and Theileria parva, is limited.

Results

A total of 38 putative KMTs and eight JHDMs were identified using a comparative genomics approach. Phylogenetic analysis revealed that the putative KMTs can be divided into eight subgroups, while the JHDMs belong to the JARID subfamily, except for BdJmjC1 (BdWA1_000016) and TpJmjC1 (Tp Muguga_02g00471) which cluster with JmjC domain only subfamily members. The motifs of SET and JmjC domains are highly conserved among piroplasm species. Interspecies collinearity analysis provided insight into the evolutionary duplication events of some SET domain and JmjC domain gene families. Moreover, relative gene expression analysis by RT‒qPCR demonstrated that the putative KMT and JHDM gene families were differentially expressed in different intraerythrocytic developmental stages of B. duncani, suggesting their role in Apicomplexa parasite development.

Conclusions

Our study provides a theoretical foundation and guidance for understanding the basic characteristics of several important piroplasm KMT and JHDM families and their biological roles in parasite differentiation.

Peer Review reports

Background

Piroplasmosis is a group of human and veterinary tick-borne diseases caused mainly by parasites belonging to two Apicomplexa genera, Babesia and Theileria [1]. Theileria parasites, which can infect a number of domesticated and wild ruminants around the world, kill millions of cattle each year and cause enormous economic losses to the livestock industry; of these, Theileria annulata and Theileria parva are the most common pathogens, while Babesia can infect a range of warm-blooded vertebrates, including humans and wild and domestic animals [2, 3]. Human babesiosis is a malaria-like disease caused by a wide spectrum of Babesia species, such as Babesia microti [4], Babesia duncani [5], Babesia divergens [6], Babesia motasi, [7] Babesia crassa [8], Babesia bigemina [9], Babesia venatorum [10] and Babesia bovis [11]. Among these species, B. microti is the most common causative agent [12], while B. duncani is a highly virulent zoonotic pathogen that can cause severe to fatal infections in laboratory mice and hamsters. In humans, symptoms of B. duncani infection range from asymptomatic to mild flu-like illness, and even to fatal, particularly in the elderly, post-splenectomy or immunocompromised individuals [13]. B. duncani and B. microti pose health threats to humans, domestic and wild animals [14, 15]. B. duncani has been found in bighorn sheep and mule deer [16]. Also, B. microti has been detected in domestic cats [17] and dogs [18], and small mammals [19, 20] and baboons [21]. Currently, there is a lack of specific drugs or vaccines to treat piroplasm infections, making it urgent to develop effective therapeutic strategies to improve the management of these parasites.

In Apicomplexa parasites, histone lysine methylation levels are associated with parasite virulence [22], motility [23], stage transition [24] and host-parasite interactions [25]. In addition, many key enzymes downstream of histone lysine methylation pathways have been proven to be ideal targets for cancer drug development [26,27,28,29]. Intriguingly, several studies have demonstrated that methyltransferase inhibitors show promise as therapeutic drugs for treating malaria parasites [30, 31], Trypanosoma brucei [32, 33] and Leishmania [34]. Currently, SET (Su(var)3–9, E(z), Trithorax) domain-containing histone lysine methyltransferases (HKMTs) and JmjC (Jumonji C) domain-containing histone demethylases (JHDMs) have been identified and characterized at the genome-wide level in several Apicomplexa parasites, such as Plasmodium falciparum [35], Cryptosporidium parvum [25] and Toxoplasma gondii [36]. The SET domain, a sequence of about 130 amino acid residues first discovered in the Drosophila genome, is the enzymatic activity domain of HKMTs and is highly evolutionarily conserved [37, 38], while, the evolutionarily highly conserved JmjC domain is the functionally active region of the JHDM family [39]. Based on sequence similarity and substrate specificity, SET domain-containing HKMTs can be classified into several subfamilies: SETD1, SETD2, SUV3D9, SMYD, SET7/9 and SETD8 [40], and JHDM can be divided into JHDM1, PHF2/PHF8, JARID, JHDM3/JMJD2, UTX/UTY, JHDM2 and JmjC domain only groups [41]. However, little is known about the classification, structural and physical characteristics, and function of HKMTs and JHDMs in human pathogenic babesia, including B. duncani, B. microti, and in veterinary important pathogens, such as B. bigemina, B. bovis, T. annulata and T. parva.

Here, we conducted systematic and comprehensive research on putative KMT and JHDM genes in several representative piroplasm genomes to disclose the information focusing on their physicochemical properties, chromosome distribution, phylogenetic classification and interspecies collinearity. Furthermore, the expression profiles of the retrieved genes at different developmental stages of B. duncani were determined by real-time quantitative PCR. Our study will provide the scientific community with new viewpoints and clues to better understand HKMTs and JHDMs and pave the way for research on the role of these methylation regulators in the intraerythrocytic development of human pathogenic and veterinary important piroplasm parasites.

Results

Identification and characterization of the putative KMTs and JHDMs in B. duncani, B. bigemina, B. microti, B. bovis, T. annulata and T. parva

By thoroughly searching the B. duncani, B. bigemina, B. microti, B. bovis, T. annulata and T. parva reference genomes with the SET domain sequences of several well-studied HKMTs, 49 putative SET domain-containing candidates were obtained. However, further structure verification analysis with SMART revealed that 11 hits (GenBank ID: KAK2185947, KAK2197250, XP_001610401, BAN65725, XP_001611356, XP_012768058, XP_952658, XP_954450, XP_955402, XP_061162069 and XP_765804) did not possess any SET domain (data not shown). Consequently, 38 putative KMTs were retrieved from the six genomes. The physicochemical properties including the length of the primary sequence, molecular weight, isoelectric point and subcellular localization are listed in Table 1. The molecular weights of the identified putative KMTs varied from 11.03 kDa (BdSET3) to 549.87 kDa (BbSET1); while, the isoelectric points (PIs) of the 38 putative KMTs fluctuated between 4.43 and 9.04. This finding suggested that the KMT family members of these six species are quite different from each other. Moreover, although the subcellular localization of these 38 putative KMTs varied greatly, the same subfamilies had similar subcellular localization, and most of them had nuclear localization (Table 1).

Table 1 Putative SET domain-containing lysine methyltransferases identified in Babesia duncani, Babesia microti, Babesia bigemina, Babesia bovis, Theileria annulata and Theileria parva
Full size table

Additionally, we identified eight putative JHDMs through systematic BLASTp in the six piroplasm genomes with a series of JmjC domain sequences from representative human JHDMs. On the basis of prediction analysis via the ExPASy website, the molecular weights of these JHDMs vary from 33.86 kDa to 84.5 kDa; while, the PIs of these six putative JHDMs are also different from each other (the PI ranges between 5.48 and 8.29). All the putative JHDMs have nuclear localization (Table 2).

Table 2 Putative JmjC domain-containing histone demethylases identified in Babesia duncani, Babesia microti, Babesia bigemina, Babesia bovis, Theileria annulata and Theileria parva
Full size table

Phylogenetic analysis

To analyze the phylogenetic relationships between the putative KMTs of the six species and several well-known HKMTs from Homo sapiens, Drosophila melanogaster and other Apicomplexa species, a phylogenetic tree was constructed from the SET domain amino acid sequences of these proteins by the maximum likelihood ratio method using MEGA 7.0. As shown in Fig. 1A, the 38 putative KMTs were divided into eight KMT subfamilies. However, BmSET6, BdSET6 and BBOVSET6 clustered together to form a new clade distinct from other known HKMTs, suggesting that these three putative KMTs may be parasite-specific enzymes involved in regulating some of the parasite's unique biological processes. Moreover, a phylogenetic cladogram of the JmjC domain proteins was also generated by MEGA 7.0 based on the maximum likelihood ratio algorithm with the JmjC domain protein sequences of the JHDMs of H. sapiens and T. gondii to examine the evolutionary history of these proteins. Of note, the identified JHDMs were divided into two main subfamilies on the basis of their branching features and bootstrap values. As depicted in Fig. 1B, BdJmjC1 and TpJmjC1 were classified into JmjC domain only subgroup, while the remaining JHDMs were assigned to the JARID subfamily.

Fig. 1
figure 1

Phylogenetic trees of the SET domain sequences of the putative KMTs (A) and the JmjC domain sequences of the JHDMs (B). The SET domain sequences of the KMTs and the JmjC domain sequences of the JHDMs were aligned by Clustal W algorithm, and phylogenetic tree files were generated by MEGA 7.0 by the maximum-likelihood method and visualized by R software. The numbers at each branch point on the evolutionary trees represent the bootstrap values. Hs, Homo sapiens; Dm, Drosophila melanogaster; Tg, Toxoplasma gondii; Pf, Plasmodium falciparum; Sc, Saccharomyces cerevisiae; BESB, Besnoitia besnoiti; Bd, Babesia duncani; Bb, Babesia bigemina; BBOV, Babesia bovis; Bm, Babesia microti; Ta, Theileria annulata; Tp, Theileria parva

Full size image

Chromosome distribution and interspecies collinearity analysis of the identified putative KMTs and JHDMs

Chromosome distribution analysis of the screened putative KMTs and JHDMs in the six Piroplasm species based on the GFF genome annotation files revealed that the identified genes were mainly concentrated on three to five chromosomes in each parasite's genome (Fig. 2A-F). The genes identified in B. duncani, B. bovis and T. annulata were mainly distributed on 3 chromosomes, in B. bigemina on 5 chromosomes and in B. microti and T. parva on 4 chromosomes.

Fig. 2
figure 2

Chromosomal distributions (A to F) and interspecies collinearity analysis (G) of putative KMT and JHDM genes. Panels A to F are the chromosomal maps of the putative KMTs and JHDMs in the six piroplasm genomes: Babesia bovis (A), Babesia microti (B), Theileria annulata (C), Babesia bigemina (D), Babesia duncani (E) and Theileria parva (F). The upper part of (G) indicates the interspecies collinearity relationship of putative KMT and JHDM genes between Babesia bigemina, Babesia duncani and Theileria annulata, while the middle part indicates the interspecies relationship of putative KMT and JHDM genes between Babesia bovis, Babesia duncani and Babesia microti; the lower part indicates the interspecies relationship of putative KMT and JHDM genes between Babesia duncani, Theileria parva and Theileria annulata. The yellow lines indicate the collinearity relationship of putative KMT genes between species, and the green lines indicate the collinearity relationship of putative JHDM genes between species

Full size image

To further explore the synteny relationships of the putative KMTs and the JHDMs among B. duncani, B. bigemina, B. bovis, B. microti, T. annulata and T. parva, we conducted an interspecies collinearity analysis. As shown in Fig. 2G, B. duncani and B. bovis share six pairs of collinear putative KMT genes and one pair of collinear JHDM genes; two pairs of collinear putative KMT genes were found between B. duncani and B. microti; seven putative KMT and one JHDM homologous genes were found between B. duncani and B. bigemina, whereas, B. duncani and T. annulata share five putative KMT and one JHDM homologous genes; besides, five putative KMT and two JHDM homologous genes were identified between B. duncani and T. parva and T.parva and T. annulata, respectively.

Conserved motif, gene architecture and domain analysis of the identified putative KMTs and JHDMs

Based on the MEME search, the conserved motifs and the corresponding distributions in the putative KMTs and JHDMs were analyzed. A total of ten conserved motifs were retrieved for the putative KMTs and JHDMs, separately. Notably, the distribution and constitution of the conserved motifs in the putative KMTs vary significantly. Generally, proteins belonging to the same KMT subfamily have similar motif constitutions and distributions. Noteworthily, all of the identified putative KMTs have a motif 1 sequence that contains a core “ELxFDY”, an AdoMet binding and catalytic site (Fig. 3A). Additionally, motif 2, with a “RFINHSCxPN” core, and motif 3, with “GxG” and “YxG” cores, were distributed on most of the identified putative KMTs. “RFINHSCxPN”, “GxG” and “YxG” are also canonical AdoMet catalytic motifs present in the majority of HKMTs from different species [25, 35, 40]. Another thing worth noting is that BdJmjC2, BbJmjC1, BBOVJmjC1, BmJmjC1, TaJmjC2 and TpJmjC2 share a similar composition and distribution of conserved motifs, however, BdJmjC1 has no common motifs (Fig. 3B). What’s more, JHDM motifs 1 and 2, which contain “HxE/ExnH” Fe (II) and “N and K” α-KG binding sites, were highly conserved. The amino acid sequences of the conserved motifs essential for enzyme activity in the identified putative KMTs and JHDMs are shown as sequence logos (Fig. 4).

Fig. 3
figure 3

Conserved motif (left), domain (middle) and gene structure (right) analysis of putative KMTs (A) and JHDMs (B) in Babesia duncani, Babesia bigemina, Babesia bovis, Babesia microti, Theileria annulata and Theileria parva

Full size image
Fig. 4
figure 4

The sequence logo of the conserved motifs found in the putative KMTs (A) and JHDMs (B) in Babesia duncani, Babesia bigemina, Babesia bovis, Babesia microti, Theileria annulata and Theileria parva

Full size image

Gene structure exploration of the CDS, UTR and intron in the SET domain and JmjC domain gene families was carried out based on the genome annotation file (GFF). According to the gene structure analysis results, the number of exons in the SET gene family members fluctuated considerably (Fig. 3A). For example, BBOVSET7 has 15 exons, while nine of the putative KMTs have only one exon. Interestingly, UTRs were found in the six putative KMT genes of B. bovis. For the JmjC gene family, the exon number of each member also varied drastically, ranging between 4 (BdJmjC1) and 12 (TaJmjC2 and TpJmjC2) (Fig. 3B).

The functional conserved domains of the identified putative KMTs and JHDMs were obtained by a conserved domain search in the NCBI-CDD database. As shown in Fig. 3A, the domain constitutions in the same subfamily are obviously conserved. Among these 38 putative KMTs, with the exception of TaSETup3, additional conserved domains were found only in SETD1 family members, and all other subfamily members contained only one conserved SET domain. On the other hand, except for BdJmjC1 and TpJmjC1, all the identified JHDMs also contain a JmjN domain in addition to a JmjC domain. Moreover, a zf-C5HC2 domain was found to exist in BmJmjC1 and TaJmjC2 (Fig. 3B).

Gene expression profile of the putative KMTs and JHDMs in B. duncani

To figure out the gene expression patterns of the putative KMTs and JHDMs in B. duncani, we conducted real-time qPCR to determine the relative expression levels of these genes at different developmental stages. All the amplification reactions were performed in parallel in three duplicates. The primers, reaction systems and amplification conditions for RT‒qPCR used in our study are listed in Tables S3 and S4, respectively. Meanwhile, the detailed information on the S1/S2/S3 stage samples and the results of relative expression levels as well as the statistical estimates are shown separately in supplementary Table S5 and S6. According to the heatmap of the relative gene expression levels (Fig. 5A), the expression patterns of the putative KMTs and the JHDMs varied significantly at different developmental stages. The majority of the putative KMT and JHDM genes exhibited increased expression with parasite development, with the exception of BdSET1, whose expression decreased as B. duncani parasites developed from S1 to S2 and increased from S2 to S3. These results imply that the identified putative KMT and JHDM genes may be involved in the intraerythrocytic development of B. duncani, especially BdSET1 which may be a crucial regulator of stage transition.

Fig. 5
figure 5

Expression profiles of the putative KMT and JHDM genes at different developmental stages in Babesia duncani. A Heatmap of the relative expression levels of the putative KMT and JHDM genes in S1-, S2- and S3-stage Babesia duncani. B Images of S1, S2 and S3 intraerythrocytic stages of Babesia duncani from Giemsa-stained thin blood smears

Full size image

Discussion

Histone methylation plays an essential role in various biological processes in Apicomplexa parasites, including transcriptional regulation, chromatin remodeling, parasite-host interactions, parasite differentiation and pathogenicity [22, 25, 42, 43]. HKMTs and JHDMs are the “writers” and “erasers” of histone methylation, respectively, and are critical for maintaining dynamic changes in histone methylation levels. The widely studied functions and evolutionary history of the members of the HKMT and JHDM families in several Apicomplexa parasites, including P. falciparum [22, 35, 44, 45], T. gondii [36] and C. parvum [25], have stimulated our interest in the identification and characterization of the SET domain-containing or JmjC domain-containing gene families in the human pathogenic genus Babesia, such as B. microti and B. duncani, and in piroplasms of veterinary importance such as B. bovis, B. bigemina, T. annulata and T. parva.

In the current study, we conducted genome-wide identification and characterization of SET domain-containing KMTs and JHDMs in B. duncani, B. bovis, B. bigemina, B. microti, T. annulata and T. parva. A total of 38 putative KMT and eight JHDM genes were obtained, and SMART confirmed the presence of the SET domain and JmjC domain in each putative KMT and JHDM, respectively. However, the number of putative KMTs and JHDMs in the B. microti, B. duncani, B. bovis and B. bigemina genomes is close to that in the P. falciparum [35] and C. parvum [25] genomes, much less than that in H. sapiens (HKMTs > 50 and HKDMs > 30) [46], which may be due to the relatively compact size of the genome of Apicomplexa parasites (genome size of B. duncani 10.4 Mb, B. bigemina 13.8 Mb, B. bovis 8.2 Mb, B. microti 6.4 Mb, T. annulata 8.4 Mb, T. parva 8.3 Mb, P. falciparum 23.3 Mb and C. parvum 9.1 Mb, whereas H. sapiens 3.1 Gb) and demonstrates the importance of the HKMT and JHDM gene families in Apicomplexa parasite evolution. The phylogenetic tree revealed that the 38 putative KMTs can be grouped into eight distinct subfamilies: SETD1, SETD2, SETD8, SVU39, SET7/9, SMYD, LSMT and others (a clade distinct from other known HKMT subfamilies). In T. gondii, TgAKMT can affect parasite motility, invasion and parasite egress by methylating non-histone proteins, and when TgAKMT is knocked out, parasite motility is inhibited and invasion and parasite egress are reduced [23, 36, 47]. Putative KMTs (BdSET5, BBOVSET5, BbSET5, BmSET5, TaSETup1 and TpSET5) that cluster with TgAKMT have been identified in each of these six Apicomplexan piroplasm genomes, and these genes are likely involved biological processes similar to those of TgAKMT. Interestingly, in the study by Cheeseman et al., TaSETup1 showed the ability to methylate H3K18 and may be involved in the regulation of stage differentiation in T. annulata [42]. These findings indicate that putative KMTs clustering with TgAKMT may be able to catalyze both non-histone and histone substrates to exert effects on parasite behavior. Since AKMT (Apicomplexa lysine methyltransferase) is a methyltransferase that does not exist in mammals but only in Apicomplexa parasites, investigating its mechanism in parasite development and pathogenesis could help develop new therapeutic strategies to control parasites. In addition, in P. falciparum, PfSET2 regulates var gene expression by modulating H3K36me3 levels on var genes, and in the absence of PfSET2, all var genes are expressed [22, 48, 49]. In this study, a SETD2 HKMT homologue was found in the genomes of each of the six piroplasm species. Future research to confirm whether these genes are involved in modulating the expression of var antigens in these six piroplasm strains, as they are in P. falciparum, will provide some theoretical support for the development of vaccines against these parasites. Moreover, we did not observe any intraspecies collinearity between these screened genes (data not shown), indicating that no duplicate events of these methylation-related genes occurred during evolution. Importantly, interspecies collinearity analysis of piroplasm species also unraveled the significance of the HKMT and JHDM genes in species evolution.

Due to the limited number of transcription factors in Apicomplexa protozoan genomes, other epigenetic regulatory mechanisms, such as histone lysine/arginine methylation or acetylation may also contribute greatly to protozoan development [43, 50, 51]. Previous studies have demonstrated that histone methylation levels are involved in orchestrating the cell differentiation of Apicomplexa parasites and their complex life cycle [25, 42, 52]. Accordingly, dynamic changes in histone lysine methylation levels usually occur together with alterations in gene expression throughout the parasite development stages [44, 53,54,55]. Therefore, we analyzed the expression patterns of the putative KMTs and JHDMs in different developmental stages of B. duncani. According to the relative expression levels of the genes identified by RT‒qPCR (Fig. 5), the putative KMT and JHDM genes exhibit distinct expression profiles in different intraerythrocytic developmental stages. The expression level of BdSET1 gradually decreased with parasite development from S1 to S2, and increased as B. duncani parasites developed from S2 to S3. BdSET1 is a SETD1 superfamily member supported by a high bootstrap value according to the phylogenetic tree constructed from well-studied HKMTs (Fig. 1A). Furthermore, BdSET1 possesses four additional PHDs and one bromodomain, similar in domain number and constitution to other SETD1 family members, such as BmSET1, BbSET1 TaSETup5 and TpSET1 (Fig. 3A). The PHD and bromodomain can bind to the H3K4 site and are essential for the HKMT activity of SETD1 family members [56,57,58]. Therefore, we speculate that BdSET1 may be able to catalyze H3K4 to form mono-, di- or trimethylated H3K4. Besides, H3K4 methylation is an active marker of transcription and several studies have demonstrated that the methylation level of H3K4 is associated with parasite life cycle progression [58]. These findings raise the possibility that BdSET1 might be a critical regulator of B. duncani parasite development. However, more well-designed studies should be performed to support this speculation.

Conclusions

In general, this study could help the scientific community acquire more basic information on the HKMTs and JHDMs of human pathogenic and veterinary important Piroplasm parasites and lay a theoretical foundation for future works on the mechanisms of histone lysine methylation regulation in Apicomplexa babesia parasite differentiation.

Materials and methods

Identification of putative KMTs and JHDMs

The SET motifs of several well-studied histone lysine methyltransferases (shown in supplementary Table S1) from different species, including human, Drosophila, and Apicomplexa protozoans like Toxoplasma gondii and Plasmodium falciparum [25], were used as queries with BLASTp algorithm (https://blast.ncbi.nlm.nih.gov/) to search for potential SET domain-containing KMTs in B. duncani (accession number: GCA_028658345.1), B. microti (GCF_000691945.2), B. bigemina (GCF_000981445.1), B. bovis (GCF_000165395.2), T. annulata (GCF_000003225.4) and T. parva (GCF_000165365.1) genomes. Parallelly, the amino acid sequences of the JumonjiC (JmjC) domain of representative human histone lysine demethylases [41] (Table S2) were also subjected to a search for putative JHDMs in the same genome sets. Moreover, the presence of SET domain in putative KMTs and the presence of JmjC domain in putative JHDMs of these six species were confirmed using the Simple Modular Architecture Research Tool (SMART, http://smart.embl.de/). The basic characteristics of the identified proteins, including molecular weight (kDa) and isoelectric point (PI), were obtained by the ExPASy website tool (https://prosite.expasy.org/). Besides, Euk-mPLoc 2.0 online software [59] (http://www.csbio.sjtu.edu.cn/bioinf/euk-multi-2/) was used to predict the subcellular localization of the putative KMTs and JHDMs.

Phylogenetic analysis

Multiple sequence alignment was performed using the Megalign tool by the Clustal W algorithm imbedded in MEGA 7 software (Molecular Evolutionary Genetics Analysis Version 7.0) to compare the conserved SET domain or JmjC domain sequences of the identified proteins with the representative HKMTs or JHDMs listed in Tables S1 and S2, respectively. Subsequently, phylogenetic tree files for the SET domain or the JmjC domain sequences of these proteins were generated using MEGA 7 with the maximum likelihood (ML) algorithm due to its relatively higher accuracy and faster computing speed. The reliability was evaluated by 1000 bootstrap replications. Thereafter, visualization and beautification of the tree files were performed on the R-project platform using the “ggplot2”, “treeio” and “ggtree” packages [60, 61].

Chromosomal distribution and interspecies collinearity analysis

The genome sequence (FASTA) and annotation (GFF) files of the six piroplasm strains were downloaded from GenBank. The chromosome length and gene distribution information obtained from the genome annotation file (GFF) and the gene IDs of the identified putative KMTs and JHDMs were visualized with the “Gene Location Visualize from GTF/GFF” program imbedded in TBtools software. The interspecies collinearity relationships of the putative KMT and JHDM genes among B. duncani, B. bovis, B. microti, B. bigemina, T. annulata and T. parva were evaluated via the Multiple Collinearity Scan toolkit (MCScanX) (e-value threshold = 1e-10) and visualized via the Multiple Synteny Plot program in TBtools [62].

Conserved motif, architecture and gene structure analysis

The conserved motifs of putative KMTs or JHDMs of the six species were searched using the Multiple Em for Motif Elicitation (MEME) online website tool (https://meme-suite.org/meme/tools/meme) [63] with the parameters set to a maximum number of motifs of 10 and an optimal motif width of 6—50. The gene structure of putative KMTs and JHDMs, including CDSs, introns and UTRs, were predicted and visualized by TBtools using the corresponding genome annotation files of these species. The conserved domains of all the identified proteins were analyzed and searched with the NCBI Batch CD-search Tool (https://www.ncbi.nlm.nih.gov/Structure/bwrpsb/bwrpsb.cgi). Moreover, sequence logos for the conserved motif of the identified proteins were generated through a MEME search and visualized on the R-project platform using the “ggplot2” and “ggseqlogo” packages [64].

In vivo parasite culture and collection of merozoites at different developmental stages

A vial of B. duncani WA1 purchased from ATCC and cryopreserved in liquid nitrogen at Vector and Vector-Borne Diseases (VVBD) Laboratory, Lanzhou Veterinary Research Institute (LVRI) (CAAS Lanzhou, China) was thawed quickly in a water bath at 37℃. Immediately, a 10-week-old female Golden Syrian hamster (Chales River Laboratories, Beijing, China) was inoculated with the whole vial of parasite via intraperitoneal injection. Parasitemia was monitored daily from day 5 post infection (p.i.) by thin blood smears stained with Giemsa prepared via lateral saphenous venipuncture through microscopic examination with a × 1000 oil-immersion lens. When the parasitemia increased to approximately 10%, the hamster was anesthetized with isoflurane (Orbiepharm, Qingdao, China) in an ABS Rodent Gas Anesthesia System (Yuyan Instruments Corporation, Shanghai) with consumption of isoflurane set at 5 ml/hour. The hamsters were then euthanized by collecting blood via cardiac puncture. Fresh infected blood was diluted in RPMI-1640 medium. Immediately following dilution, six 10-week-old female Golden Syrian hamsters (Chales River Laboratories, Beijing, China) were inoculated with diluted blood (2500 infected erythrocytes/500 μL/hamster). Thin blood smears were prepared and stained with Giemsa to monitor the parasite morphology daily after 5 dpi. Based on the parasite morphology within erythrocytes under microscopy and the intraerythrocytic cell division cycle of Babesia spp. proposed by Rezvani, et al. [65], the developmental stages of B. duncani could be artificially divided into several phases. Distinct morphologies (e.g. single-ring, double-ring and tetradic forms) could represent different developmental stages (named as S1/S2/S3 stages, respectively). In the early stages of infection, single-ring forms predominate (> 90%), and as the infection progresses, double-ring and tetradic forms progressively increase, and when double-ring forms predominate over tetradic forms, the developmental stage is assumed to be S2, whereas when tetradic forms predominate over single-ring forms, it can be considered to be S3. Hamsters were anesthetized and euthanized as aforementioned, and blood samples were collected in EDTA-K2 anticoagulant vacuum tubes. Immediately thereafter, B. duncani merozoites were extracted from infected erythrocytes and purified as previously described [66].

Total RNA extraction, cDNA library establishment and real-time quantitative PCR (RT‒qPCR)

For all merozoites at different developmental stages, 100 μl of purified merozoites was used to extract total RNA using TRIzol Reagent (Life Technologies) according to the manufacturer’s instructions. After removing the potentially contaminating genomic DNA by a gDNA eraser kit (Takara), 1 μg of total RNA was reverse transcribed to establish a cDNA library using PrimScript™ RT reagent kit (Takara) in a 20 μl reaction. RT‒qPCR was carried out on an Agilent Mx3005P instrument (Agilent Technologies) to determine the relative gene expression levels using a TB Green® Kit (Takara Bio USA, Inc.) in accordance with the manufacturer’s instructions. A housekeeping gene of B. duncani HSP70 (BdWA1_003044) was used as the internal reference gene [42] and the relative expression levels of the identified putative KMTs and JHDMs were calculated using the 2−∆ΔCt method [67]. The average relative expression of the putative KMT and JHDM genes at different developmental stages was visualized using the Heatmap Illustrator program embedded in TBtools software.

Availability of data and materials

All data generated or analysed during this study are included in this article and its supplementary information files. The genomic data used in this study are available in the NCBI database (https://www.ncbi.nlm.nih.gov/datasets/genome/; accession numbers: GCA_028658345.1 for B. duncani; GCF_000691945.2 for B. microti; GCF_000981445.1 for B. bigemina; GCF_000165395.2 for B. bovis; GCF_000003225.4 for T. annulata and GCF_000165365.1 for T. parva).

Change history

Abbreviations

SET:

Su(var.)3–9 (Suppressor of variegation 3–9), E(Z) (Enhancer of zeste) and Trx(Trithorax)

JmjC:

Jumonji C

HKMT:

Histone lysine methyltransferase

JHDM:

JmjC domain histone demethylases

me1:

Monomethylated

me2:

Dimethylated

me3:

Trimethylated

SUV39:

Suppressor of variegation 3–9

EZ:

Enhancer of zeste

LSMT:

Large subunit methyltransferase

SMYD:

Su(Var)3–9, Enhancer-of-zeste and Trithorax (SET) and Myeloid, Nervy, and DEAF-1 (MYND)

LSD:

Lysine specific demethylase

FAD:

Flavin adenine dinucleotide

PHD:

Plant homeodomain

PHF2/PHF8:

PHD finger lysine-specific demethylase 2/8

JARID:

Jumonji/ARID domain-containing protein

UTX/UTY:

Ubiquitously transcribed TPR gene on X/Y chromosome

MEME:

Multiple Em for Motif Elicitation

UTR:

Untranslated region

SMART:

Simple Modular Architecture Research Tool

PCR:

Polymerase chain reaction

References

  1. Zanet S, Trisciuoglio A, Bottero E, de Mera IG, Gortazar C, Carpignano MG, Ferroglio E. Piroplasmosis in wildlife: Babesia and Theileria affecting free-ranging ungulates and carnivores in the Italian Alps. Parasit Vectors. 2014;7:70.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Tait A, Hall FR. Theileria annulata: control measures, diagnosis and the potential use of subunit vaccines. Rev Sci Tech (International Office of Epizootics). 1990;9(2):387–403.

    Article  CAS  Google Scholar 

  3. Malgwi SA, Ogunsakin RE, Oladepo AD, Adeleke MA, Okpeku M. A forty-year analysis of the literature on Babesia Infection (1982–2022): a systematic bibliometric approach. Int J Environ Res Public Health. 2023;20(12):6156.

  4. Lim PL, Chavatte JM, Vasoo S, Yang J. Imported human babesiosis, Singapore, 2018. Emerg Infect Dis. 2020;26(4):826–8.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Scott JD. First record of locally acquired human babesiosis in Canada caused by Babesia duncani: a case report. SAGE Open Med Case Rep. 2017;5:2050313X17725645.

    PubMed  PubMed Central  Google Scholar 

  6. Montero E, Folgueras M, Rodriguez-Pérez M, Pérez-Ls L, Díaz-Arias J, Meana M, Revuelta B, Haapasalo K, Collazos J, Asensi V, et al. Retrospective study of the epidemiological risk and serological diagnosis of human babesiosis in Asturias, Northwestern Spain. Parasit Vectors. 2023;16(1):195.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Hong SH, Kim SY, Song BG, Rho JR, Cho CR, Kim CN, Um TH, Kwak YG, Cho SH, Lee SE. Detection and characterization of an emerging type of Babesia sp. similar to Babesia motasi for the first case of human babesiosis and ticks in Korea. Emerg Microbes Infect. 2019;8(1):869–78.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Jia N, Zheng YC, Jiang JF, Jiang RR, Jiang BG, Wei R, Liu HB, Huo QB, Sun Y, Chu YL, et al. Human babesiosis caused by a Babesia crassa-like pathogen: a case series. Clin Infect Dis : an official publication of the Infectious Diseases Society of America. 2018;67(7):1110–9.

    Article  CAS  Google Scholar 

  9. Calvopiña M, Montesdeoca-Andrade M, Bastidas-Caldes C, Enriquez S, Rodríguez-Hidalgo R, Aguilar-Rodríguez D, Cooper P. Case report: first report on human infection by tick-borne Babesia bigemina in the Amazon region of Ecuador. Front Public Health. 2023;11:1079042.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Huang L, Sun Y, Huo DD, Xu M, Xia LY, Yang N, Hong W, Nie WM, Liao RH, Zhang MZ, et al. Successful treatment with doxycycline monotherapy for human infection with Babesia venatorum (Babesiidae, Sporozoa) in China: a case report and proposal for a clinical regimen. Infect Dis Poverty. 2023;12(1):67.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Gaffar FR, Franssen FF, de Vries E. Babesia bovis merozoites invade human, ovine, equine, porcine and caprine erythrocytes by a sialic acid-dependent mechanism followed by developmental arrest after a single round of cell fission. Int J Parasitol. 2003;33(14):1595–603.

    Article  CAS  PubMed  Google Scholar 

  12. Foster E, Maes SA, Holcomb KM, Eisen RJ. Prevalence of five human pathogens in host-seeking Ixodes scapularis and Ixodes pacificus by region, state, and county in the contiguous United States generated through national tick surveillance. Ticks Tick Borne Dis. 2023;14(6):102250.

    Article  PubMed  Google Scholar 

  13. Pal AC, Renard I, Singh P, Vydyam P, Chiu JE, Pou S, Winter RW, Dodean R, Frueh L, Nilsen AC, et al. Babesia duncani as a model organism to study the development, virulence, and drug susceptibility of intraerythrocytic parasites in vitro and in vivo. J Infect Dis. 2022;226(7):1267–75.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Mamoun CB, Allred DR. Babesiosis. eLS. 2018:1–8.

  15. Zhou X, Xia S, Huang JL, Tambo E, Zhuge HX, Zhou XN. Human babesiosis, an emerging tick-borne disease in the People’s Republic of China. Parasit Vectors. 2014;7:509.

    PubMed  PubMed Central  Google Scholar 

  16. Thomford JW, Conrad PA, Boyce WM, Holman PJ, Jessup DA. Isolation and in vitro cultivation of Babesia parasites from free-ranging desert bighorn sheep (Ovis canadensis nelsoni) and mule deer (Odocoileus hemionus) in California. J Parasitol. 1993;79(1):77–84.

    Article  CAS  PubMed  Google Scholar 

  17. Bosman A-M, Penzhorn BL, Brayton KA, Schoeman T, Oosthuizen MC. A novel Babesia sp. associated with clinical signs of babesiosis in domestic cats in South Africa. Parasit Vectors. 2019;12(1):138.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Gabrielli S, Otašević S, Ignjatović A, Savić S, Fraulo M, Arsić-Arsenijević V, Momčilović S, Cancrini G. Canine Babesioses in Noninvestigated Areas of Serbia. Vector Borne Zoonotic Dis (Larchmont, NY). 2015;15(9):535–8.

    Article  Google Scholar 

  19. Chen X-R, Ye LI, Fan J-W, Li C, Tang F, Liu WEI, Ren L-Z, Bai J-Y. Detection of Kobe-type and Otsu-type Babesia microti in wild rodents in China’s Yunnan province. Epidemiol Infect. 2017;145(13):2704–10.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Gao ZH, Huang TH, Jiang BG, Jia N, Liu ZX, Shao ZT, Jiang RR, Liu HB, Wei R, Li YQ, et al. Wide distribution and genetic diversity of Babesia microti in small mammals from Yunnan Province, Southwestern China. PLoS Negl Trop Dis. 2017;11(10):e0005898.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Akinyi MY, Tung J, Jeneby M, Patel NB, Altmann J, Alberts SC. Role of grooming in reducing tick load in wild baboons (Papio cynocephalus). Anim Behav. 2013;85(3):559–68.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Jiang L, Mu J, Zhang Q, Ni T, Srinivasan P, Rayavara K, Yang W, Turner L, Lavstsen T, Theander TG, et al. PfSETvs methylation of histone H3K36 represses virulence genes in Plasmodium falciparum. Nature. 2013;499(7457):223–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Heaslip AT, Nishi M, Stein B, Hu K. The motility of a human parasite, Toxoplasma gondii, is regulated by a novel lysine methyltransferase. PLoS Pathog. 2011;7(9):e1002201.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Bohaliga GAR, Johnson WC, Taus NS, Hussein HE, Bastos RG, Suarez CE, O’Connor R, Ueti MW. Identification of a putative methyltransferase gene of Babesia bigemina as a novel molecular biomarker uniquely expressed in parasite tick stages. Parasit Vectors. 2018;11(1):480.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Sawant M, Benamrouz-Vanneste S, Meloni D, Gantois N, Even G, Guyot K, Creusy C, Duval E, Wintjens R, Weitzman JB, et al. Putative SET-domain methyltransferases in Cryptosporidium parvum and histone methylation during infection. Virulence. 2022;13(1):1632–50.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Kaur P, Shankar E, Gupta S. EZH2-mediated development of therapeutic resistance in cancer. Cancer Lett. 2024;586:216706.

    Article  CAS  PubMed  Google Scholar 

  27. de Oliveira Filho RS, de Oliveira DA, Nisimoto MM, Marti LC. A review of advanced cutaneous melanoma therapies and their mechanisms, from immunotherapies to lysine histone methyl transferase inhibitors. Cancers. 2023;15(24):5751.

  28. Rao H, Liu C, Wang A, Ma C, Xu Y, Ye T, Su W, Zhou P, Gao WQ, Li L, et al. SETD2 deficiency accelerates sphingomyelin accumulation and promotes the development of renal cancer. Nat Commun. 2023;14(1):7572.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Zheng X, Luo Y, Xiong Y, Liu X, Zeng C, Lu X, Wang X, Cheng Y, Wang S, Lan H, et al. Tumor cell-intrinsic SETD2 inactivation sensitizes cancer cells to immune checkpoint blockade through the NR2F1-STAT1 pathway. J Immunother Cancer. 2023;11(12):e007678.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Ngwa CJ, Kiesow MJ, Orchard LM, Farrukh A, Llinás M, Pradel G. The G9a histone methyltransferase inhibitor BIX-01294 modulates gene expression during Plasmodium falciparum gametocyte development and transmission. Int J Mol Sci. 2019;20(20):5087.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Chan A, Dziedziech A, Kirkman LA, Deitsch KW, Ankarklev J. A histone methyltransferase inhibitor can reverse epigenetically acquired drug resistance in the malaria parasite Plasmodium falciparum. Antimicrob Agents Chemother. 2020;64(6):e02021.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Steketee PC, Vincent IM, Achcar F, Giordani F, Kim DH, Creek DJ, Freund Y, Jacobs R, Rattigan K, Horn D, et al. Benzoxaborole treatment perturbs S-adenosyl-L-methionine metabolism in Trypanosoma brucei. PLoS Negl Trop Dis. 2018;12(5):e0006450.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Zuma AA, Santos JO, Mendes I, de Souza W, Machado CR, Motta MCM. Chaetocin-A histone methyltransferase inhibitor-Impairs proliferation, arrests cell cycle and induces nucleolar disassembly in Trypanosoma cruzi. Acta Trop. 2017;170:149–60.

    Article  CAS  PubMed  Google Scholar 

  34. Rodrigues JC, Attias M, Rodriguez C, Urbina JA, Souza W. Ultrastructural and biochemical alterations induced by 22,26-azasterol, a delta(24(25))-sterol methyltransferase inhibitor, on promastigote and amastigote forms of Leishmania amazonensis. Antimicrob Agents Chemother. 2002;46(2):487–99.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Cui L, Fan Q, Miao J. Histone lysine methyltransferases and demethylases in Plasmodium falciparum. Int J Parasitol. 2008;38(10):1083–97.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Pivovarova Y, Liu J, Lesigang J, Koldyka O, Rauschmeier R, Hu K, Dong G. Structure of a novel dimeric SET domain methyltransferase that regulates cell motility. J Mol Biol. 2018;430(21):4209–29.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Del Rizzo PA, Trievel RC. Substrate and product specificities of SET domain methyltransferases. Epigenetics. 2011;6(9):1059–67.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Qian C, Zhou MM. SET domain protein lysine methyltransferases: structure, specificity and catalysis. Cell Mol Life Sci CMLS. 2006;63(23):2755–63.

    Article  CAS  PubMed  Google Scholar 

  39. Tsukada Y, Fang J, Erdjument-Bromage H, Warren ME, Borchers CH, Tempst P, Zhang Y. Histone demethylation by a family of JmjC domain-containing proteins. Nature. 2006;439(7078):811–6.

    Article  CAS  PubMed  Google Scholar 

  40. Husmann D, Gozani O. Histone lysine methyltransferases in biology and disease. Nat Struct Mol Biol. 2019;26(10):880–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Klose RJ, Kallin EM, Zhang Y. JmjC-domain-containing proteins and histone demethylation. Nat Rev Genet. 2006;7(9):715–27.

    Article  CAS  PubMed  Google Scholar 

  42. Cheeseman K, Jannot G, Lourenço N, Villares M, Berthelet J, Calegari-Silva T, Hamroune J, Letourneur F, Rodrigues-Lima F, Weitzman JB. Dynamic methylation of histone H3K18 in differentiating Theileria parasites. Nat Commun. 2021;12(1):3221.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Pain A, Renauld H, Berriman M, Murphy L, Yeats CA, Weir W, Kerhornou A, Aslett M, Bishop R, Bouchier C, et al. Genome of the host-cell transforming parasite Theileria annulata compared with T. parva. Science. 2005;309(5731):131–3.

    Article  CAS  PubMed  Google Scholar 

  44. Chen PB, Ding S, Zanghì G, Soulard V, DiMaggio PA, Fuchter MJ, Mecheri S, Mazier D, Scherf A, Malmquist NA. Plasmodium falciparum PfSET7: enzymatic characterization and cellular localization of a novel protein methyltransferase in sporozoite, liver and erythrocytic stage parasites. Sci Rep. 2016;6:21802.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Kishore SP, Stiller JW, Deitsch KW. Horizontal gene transfer of epigenetic machinery and evolution of parasitism in the malaria parasite Plasmodium falciparum and other apicomplexans. BMC Evol Biol. 2013;13:37.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Cole CG, McCann OT, Collins JE, Oliver K, Willey D, Gribble SM, Yang F, McLaren K, Rogers J, Ning Z, et al. Finishing the finished human chromosome 22 sequence. Genome Biol. 2008;9(5):R78.

    Article  PubMed  PubMed Central  Google Scholar 

  47. Sivagurunathan S, Heaslip A, Liu J, Hu K. Identification of functional modules of AKMT, a novel lysine methyltransferase regulating the motility of Toxoplasma gondii. Mol Biochem Parasitol. 2013;189(1–2):43–53.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Sethumadhavan DV, Govindaraju G, Jabeena CA, Rajavelu A. Plasmodium falciparum SET2 domain is allosterically regulated by its PHD-like domain to methylate at H3K36. Biochim Biophys Acta. 2021;1864(10):194744.

    Article  CAS  Google Scholar 

  49. Ukaegbu UE, Kishore SP, Kwiatkowski DL, Pandarinath C, Dahan-Pasternak N, Dzikowski R, Deitsch KW. Recruitment of PfSET2 by RNA polymerase II to variant antigen encoding loci contributes to antigenic variation in P. falciparum. PLoS Pathog. 2014;10(1):e1003854.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Han Z, Zheng Y, Shi Y, Chen F, Wu C, Wang L, Lu S, Li D, Guan X, He L, et al. Transcriptional variation in Babesia gibsoni (Wuhan isolate) between in vivo and in vitro cultures in blood stage. Parasit Vectors. 2023;16(1):268.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Wang J, Chen K, Yang J, Zhang S, Li Y, Liu G, Luo J, Yin H, Wang G, Guan G. Comparative genomic analysis of Babesia duncani responsible for human babesiosis. BMC Biol. 2022;20(1):153.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Harris CT, Tong X, Campelo R, Marreiros IM, Vanheer LN, Nahiyaan N, Zuzarte-Luís VA, Deitsch KW, Mota MM, Rhee KY, et al. Sexual differentiation in human malaria parasites is regulated by competition between phospholipid metabolism and histone methylation. Nat Microbiol. 2023;8(7):1280–92.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Coleman BI, Skillman KM, Jiang RHY, Childs LM, Altenhofen LM, Ganter M, Leung Y, Goldowitz I, Kafsack BFC, Marti M, et al. A Plasmodium falciparum histone deacetylase regulates antigenic variation and gametocyte conversion. Cell Host Microbe. 2014;16(2):177–86.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Li Y, Liew YJ, Cui G, Cziesielski MJ, Zahran N, Michell CT, Voolstra CR, Aranda M. DNA methylation regulates transcriptional homeostasis of algal endosymbiosis in the coral model aiptasia. Sci Adv. 2018;4(8):eaat2142.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Bougdour A, Braun L, Cannella D, Hakimi MA. Chromatin modifications: implications in the regulation of gene expression in Toxoplasma gondii. Cell Microbiol. 2010;12(4):413–23.

    Article  CAS  PubMed  Google Scholar 

  56. Ortiz G, Kutateladze TG, Fujimori DG. Chemical tools targeting readers of lysine methylation. Curr Opin Chem Biol. 2023;74:102286.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Wysocka J, Swigut T, Xiao H, Milne TA, Kwon SY, Landry J, Kauer M, Tackett AJ, Chait BT, Badenhorst P, et al. A PHD finger of NURF couples histone H3 lysine 4 trimethylation with chromatin remodelling. Nature. 2006;442(7098):86–90.

    Article  CAS  PubMed  Google Scholar 

  58. Salusso A, Zlocowski N, Mayol GF, Zamponi N, Rópolo AS. Histone methyltransferase 1 regulates the encystation process in the parasite Giardia lamblia. FEBS J. 2017;284(15):2396–409.

    Article  CAS  PubMed  Google Scholar 

  59. Chou KC, Shen HB. A new method for predicting the subcellular localization of eukaryotic proteins with both single and multiple sites: Euk-mPLoc 2.0. PloS One. 2010;5(4):e9931.

    Article  PubMed  PubMed Central  Google Scholar 

  60. Wang LG, Lam TT, Xu S, Dai Z, Zhou L, Feng T, Guo P, Dunn CW, Jones BR, Bradley T, et al. Treeio: an R package for phylogenetic tree input and output with richly annotated and associated data. Mol Biol Evol. 2020;37(2):599–603.

    Article  CAS  PubMed  Google Scholar 

  61. Yu G, Lam TT, Zhu H, Guan Y. Two methods for mapping and visualizing associated data on phylogeny using Ggtree. Mol Biol Evol. 2018;35(12):3041–3.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Chen C, Wu Y, Li J, Wang X, Zeng Z, Xu J, Liu Y, Feng J, Chen H, He Y, et al. TBtools-II: A “one for all, all for one” bioinformatics platform for biological big-data mining. Mol Plant. 2023;16(11):1733–42.

    Article  CAS  PubMed  Google Scholar 

  63. Bailey TL, Elkan C. Fitting a mixture model by expectation maximization to discover motifs in biopolymers. Proc Int Conf Intell Syst Mol Biol. 1994;2:28–36.

    CAS  PubMed  Google Scholar 

  64. Wagih O. ggseqlogo: a versatile R package for drawing sequence logos. Bioinformatics (Oxford, England). 2017;33(22):3645–7.

    CAS  PubMed  Google Scholar 

  65. Rezvani Y, Keroack CD, Elsworth B, Arriojas A, Gubbels MJ, Duraisingh MT, Zarringhalam K. Comparative single-cell transcriptional atlases of Babesia species reveal conserved and species-specific expression profiles. PLoS Biol. 2022;20(9):e3001816.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Guan G, Moreau E, Liu J, Ma M, Rogniaux H, Liu A, Niu Q, Li Y, Ren Q, Luo J, et al. BQP35 is a novel member of the intrinsically unstructured protein (IUP) family which is a potential antigen for the sero-diagnosis of Babesia sp. BQ1 (Lintan) infection. Vet Parasitol. 2012;187(3–4):421–30.

    Article  CAS  PubMed  Google Scholar 

  67. Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) method. Methods (San Diego, Calif). 2001;25(4):402–8.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

We would like to thank all the members of Vector and Vector-Borne Diseases (VVBD) Laboratory who helped with this study but are not listed in this paper.

Funding

This work was financially supported by grants from the National Key Research and Development Program of China (2022YFD1800200), the National Nature Science Foundation of China (NO. 31972701), the Science Fund for Creative Research Groups of Gansu Province, China (22JR5RA024), Natural Science Foundation of Gansu, China (22JR5RA031), the Agricultural Science and Technology Innovation Program, China (ASTIP) (CAAS-ASTIP-2016-LVRI), NBCIS (CARS-37), National Parasitic Resources Center, China (NPRC-2019–194-30), the Leading Fund of Lanzhou Veterinary Research Institute, China (LVRI-SZJJ-202105), and the hatching program of the State Key Laboratory for Animal Disease Control and Prevention, China (SKLVEB2021CGQD02 and SKLADCP2023HP04).

Author information

Author notes

  1. Qindong Liang and Shangdi Zhang contributed equally to this work.

  2. Hong Yin, Guiguan Guan and Chongge You contributed equally to this work and share last authorship.

Authors and Affiliations

  1. Laboratory Medicine Center, The Second Hospital & Clinical Medical School, Lanzhou University, Lanzhou, Gansu, 730030, P. R. China

    Qindong Liang, Shangdi Zhang & Chongge You

  2. State Key Laboratory of Veterinary Etiological Biology, Key Laboratory of Veterinary Parasitology of Gansu Province, Lanzhou Veterinary Research Institute, Chinese Academy of Agricultural Science, Lanzhou, Gansu, 730046, P. R. China

    Qindong Liang, Zeen Liu, Jinming Wang, Hong Yin & Guiquan Guan

  3. State Key Laboratory for Animal Disease Control and Prevention, College of Veterinary Medicine, Lanzhou University, Lanzhou Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Lanzhou, Gansu, 730000, P. R. China

    Jinming Wang & Guiquan Guan

  4. Jiangsu Co-Innovation Center for the Prevention and Control of Important Animal Infectious Disease and Zoonose, Yangzhou University, Yangzhou, 225009, P. R. China

    Hong Yin

Authors
  1. Qindong Liang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Shangdi Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Zeen Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jinming Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Hong Yin
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Guiquan Guan
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Chongge You
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

CGY, GQG, HY and QDL designed and planned this study. QDL, SDZ, JMW and ZEL conducted the experiments and performed the data analysis. QDL and SDZ drafted the manuscript. CGY, GQG, JMW and HY critically revised the paper. All the authors have read the paper and agree to its publication.

Corresponding authors

Correspondence to Hong Yin, Guiquan Guan or Chongge You.

Ethics declarations

Ethics approval and consent to participate

All of the animal experimental protocols were approved by the Animal Ethics Committee of Lanzhou Veterinary Research Institute, Chinese Academy of Agricultural Sciences (Approval No. LVRIAEC-2023–03). All of the experiments were carried out under the Ethical Procedures and Guidelines of People’s Republic of China.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

The original online version of this article was revised: the authorship panel was modified to designate Hong Yin, Guiguan Guan and Chongge You as equal contributors and shared last authors.

Supplementary Information

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Liang, Q., Zhang, S., Liu, Z. et al. Comparative genome-wide identification and characterization of SET domain-containing and JmjC domain-containing proteins in piroplasms. BMC Genomics 25, 804 (2024). https://doi.org/10.1186/s12864-024-10731-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12864-024-10731-2

Keywords

BMC Genomics

ISSN: 1471-2164

Contact us