Chromosome-level genome assembly of trypanosomatid parasite Lotmaria passim links chromosome duplication and divergence with infection of honey bees

Chromosome-level genome assembly of trypanosomatid parasite Lotmaria passim links chromosome duplication and divergence with infection of honey bees | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Chromosome-level genome assembly of trypanosomatid parasite Lotmaria passim links chromosome duplication and divergence with infection of honey bees Anthony Nearman, Anzhelika Butenko, Jay D Evans, Evan C Palmer-Young This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5989240/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 01 Dec, 2025 Read the published version in BMC Genomics → Version 1 posted 11 You are reading this latest preprint version Abstract Background. The protist family Trypanosomatidae includes parasites of insects, vertebrates, plants, and even other unicellular eukaryotes. The genomes of these species harbor clues to the evolution of parasitism, adaptation to novel hosts, and infection of mammals. We present an analysis of a chromosome-level genome assembly of Lotmaria passim , the most prevalent known trypanosomatid of honey bees, linking genome sequence and organization to gene expression and infection of bees. Results. The genome showed high synteny with assemblies of other trypanosomatids and especially closely related Leptomonas pyrrhocoris relatives. It included four copies of chromosomes that shared ancestry with the tetrasomic Leishmania Chromosome 31 and are consistently supernumerary throughout Trypanosomatidae. However, these chromosomes showed lower similarity to L. passim relatives than did the genome overall, with sufficient variation across haplotypes to distinguish two separate disomic chromosomes. Transcriptomic analyses showed that these chromosomes are enriched in genes upregulated during bee infection, and each include five paralogs of the GP63 gene implicated in infection of both insects and mammals. Patterns of expression in bees suggested decreased protein synthesis, a shift from carbohydrate- to amino acid-based metabolism, and reduced cell motility in bee guts versus cell culture. In contrast, genes involved in cell adhesion were upregulated, consistent with the importance of attachment to insect tissue in this species and the family overall. Conclusions. Our analysis links differentiation of a conserved supernumerary chromosome with infection of bees, parallel tothis chromosome’s role in Leishmania infection of mammals and linking chromosome-level changes with adaptation to new hosts. aneuploidy trypanosomatid ancestral supernumerary chromosome (TASC) gene duplication phylogenomics polycistronic genome organization post-transcriptional gene regulation differential expression host-parasite interactions Crithidia Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Introduction The trypanosomatids are an intriguing and medically important family of protists that exploit a variety of ecological niches. They include obligate ‘monoxenous’ (single-host) parasites of insects and ‘dixenous’ (two-host) insect-vectored parasites of plants and vertebrates (1–3), namely the Leishmania and Trypanosoma species that cause considerable disability in tropical and subtropical regions (4–6). The factors that enable the radiation of trypanosomatids into novel host environments are therefore of basic and applied interest (2,7). The sequencing of genomes from trypanosomatids across this spectrum of lifestyles has begun to reveal the phylogenetic relationships between species, changes associated with the transition to parasitism, and adaptations to different niches (2,8–10). Several themes have emerged from the species investigated thus far. These include a generally conserved genome structure with high degrees of synteny among distantly related species, the arrangement and transcription of genes in long polycistronic blocks along a given strand of the chromosome, and predominantly post-transcriptional regulation of gene expression (11,12). Expression of cell surface proteins appears to play an important role in interactions with host cells, tissues, and immune systems (12–15). Many species also exhibit duplication of chromosome segments and variation in chromosome copy number, or aneusomy (9,16,17). This can aid in regulation of gene dosage in the absence of fine-scale transcriptional control while conserving polycistronic arrays. It can also facilitate adaptation to ecological and evolutionary pressures, such as exposure to toxins and novel host environments (17–20). One remarkable example is the Leishmania Chromosome 31, which is consistently tetrasomic (i.e., present as four copies) (20) . It is also enriched in genes that are upregulated during infection of vertebrates, suggesting that this duplication aided the ability to colonize these new hosts (19). A recent investigation of over 800 trypanosomatid genome assemblies revealed that scaffolds and chromosomes syntenic with Chromosome 31 are in fact tetrasomic across a wide range of mono- and dixenous species, suggesting that this aneusomy is ancestral in the trypanosomatid family rather than a specific adaptation of Leishmania (17). However, its importance for the infection of other hosts and insect vectors remains unclear. Among the monoxenous trypanosomatids, several species are associated with bees. Crithidia bombi and C. expoeki , the main species identified in bumble bees, have emerged as models of host-parasite ecology and evolution and revealed the context- and life stage-dependent effects of trypanosomatid infection on insects (21–23). Lotmaria passim , on the other hand, is the most prevalent trypanosomatid species known in honey bees (24). It exhibits a global distribution, high prevalence, negative effects on bee survival, and an association with collapsing colonies (25–34), suggesting its importance as a threat to bee health. In addition, L. passim ’s bee gut niche offers several parallels with the intracellular niche of Leishmania in vertebrates (2,35). These include exposure to elevated temperatures similar to those of the mammalian bloodstream in honey bee colonies (36,37); and establishment in the acidic environment of the bee hindgut (38), where pH resembles that in the acidic phagolysosome colonized by Leishmania amastigotes (39,40). Hence, its adaptations to this niche could provide insights into trypanosomatids’ infection of mammals. A recently published high-quality, chromosome-level assembly of the BRL type strain of L. passim (41) represents a dramatic improvement over the draft genome published ten years prior, before the differentiation of L. passim from its relative C. mellificae (42). To our knowledge, it represents the first chromosome-level assembly for a species in the Crithidiatae clade comprised of Lotmaria, Leptomonas, and Crithidia (8); the first for a monoxenous species in the Leishmaniianae subfamily that includes the Leishmania ; and the second for a monoxenous trypanosomatid (after Angomonas deanei (43)). This yielded a more complete understanding of the genome’s structure, while providing a framework to investigate the relationship between gene arrangement, expression, and function. One of the striking elements of the assembly was the presence of a paralogous chromosome pair represented by Chromosomes 5 and 6, the origins and significance of which remained unclear (41) . To discover the distinguishing features of the L. passim genome– including its paralogous chromosome pair– and their relevance to infection of honey bees, we compared the structure of the genome with that of related trypanosomatids, quantified spatial patterns of gene expression within and across chromosomes, and analyzed functional changes in gene expression of parasites in bee guts relative to cell cultures. Based on the structure of assemblies from other trypanosomatids, we expected that the genome would be characterized by long polycistronic gene blocks syntenic with those of relatives and linked to gene expression. As gene dosage is considered a means of adaptation to new environments, we predicted that the previously duplicated (now paralogous) chromosomes would be enriched in genes upregulated during bee infection. Given that this species attaches to the bee gut wall, we expected an upregulation of genes involved in adhesion during establishment in bees. Further, conditions in the bee gut mirror those encountered by Leishmania in blood cells, we also predicted transcriptional similarities between cells in the bee gut and Leishmania amastigotes (the mammal-associated life stage). Our results highlight the evolution of L. passim 's two paralogous chromosomes and their orthology with Leishmania spp. supernumerary Chromosome 31. We also link genes on these chromosomes with infection of bees and point to the importance of attachment to host tissue in the parasite's life cycle. Methods Synteny analysis The genome of the L. passim BRL type strain (maintained in the American Type Culture Collection as isolate "PRA-422", GenBank assembly GCA_037349495.1) was previously sequenced using a combination of Pac-Bio HiFi and Illumina Hi-C technologies, assembled to 31 nuclear chromosomes, and annotated with 10,288 genes (41). Conservation of gene order (synteny) between L. passim and other Leishmaniianae species with high-quality assemblies ( Leptomonas seymouri ; Crithidia bombi , C. expoeki, and C. fasciculata ; Leishmania major and L. braziliensis (Supplementary Table S1)) was quantified using SyMAP v5.9.9 (44). This analysis identifies synteny blocks with at least seven matched sequences of approximately collinear genes (allowing for inverted regions and some intervening non-aligned genes) as well as strictly collinear gene sets that contain neither gaps nor inversions. SyMAP raw data was exported and visualized using the R package circlize (45). Phylogenetic reconstruction To define the phylogenetic relationships between L. passim and other trypanosomatids, we constructed a tree based on predicted proteins from 14 Lotmaria, Leptomonas, Crithidia, and Leishmania species in the Leishmaniianae subfamily (Supplementary Table S2). For species without publicly available annotations, we used those made in a previous phylogenomic analysis (8). Proteins were aligned using MAFFT through Orthofinder, resulting in 2663 shared single-copy orthologs from which a phylogenetic tree was inferred using the STAG method (46). Tree visualization was performed using R packages ape and ggtree (47,48). Spatial analysis of genes and gene expression To quantify the spatial clustering of genes by strand within each chromosome, we created a matrix for all gene pairs and their distances apart along the chromosome. We used this to model the correlation between log 10 (pairwise distance) (included as both a linear and quadratic term) and the probability of genes being on the same strand using a binomial model with chromosome as a random effect. This and subsequent models were implemented in R version 4.4 using package glmmTMB to construct models, car to evaluate significance of predictor terms, emmeans to compute marginal means for different values of predictor variables, and ggplot2 to visualize results (49–52). We also used a binomial model to compare the proportion of features annotated as pseudogenes on the paralogous Chromosomes 5 and 6 vs the rest of the genome. We then combined our new genome annotation with publicly available transcriptomic data to examine chromosome-scale patterns of gene expression and up- and downregulation in honey bee hindguts relative to parasite cell cultures. The transcriptomic data (originally described in (33)) consisted of 30 samples from the type strain ‘SF’ (ATCC isolate ‘PRA-403’ (42)) grown in antibiotic-supplemented ‘FPFB’ medium (53) and gut samples of parasite-inoculated honey bees ( Apis mellifera ) at 7, 12, 20, and 27 d post-inoculation (n = 6 replicate libraries per group). Reads from the associated SRA files were mapped to the genome using the short reat alignment software STAR (54) and summarized by gene using featureCounts (55). Reads that mapped to multiple genes were fractionally distributed among each potential gene from which they could have originated. One of the replicates for the 7 d time point was excluded due to low read counts. Differential expression was analyzed using DESeq2 (56). Only genes covered by at least ten reads in at least five transcriptome libraries from each group were retained for further analysis, leaving 10100 genes of the original 10288 coding loci. Fractional counts were rounded to the nearest integer and normalized by library size (i.e., the total number of parasite-mapped counts). Differential expression in the bee gut relative to cell culture at each time point post-inoculation was assessed using negative binomial models with Benjamin-Hochberg correction for multiple testing within each time point. Variance-stabilized read counts, which approximate normalized read counts on the log 2 scale and have similar variance throughout the range of counts, were computed based on dispersion parameter estimates for negative binomial distributed data and were used as the response variable for analysis of spatial clustering in expression (56). Differences in proportions of differentially expressed genes between the paralogous chromosomes and the rest of the nuclear genome were evaluated using binomial models for five different differential expression categories: Significant (adjusted p-value < 0.05) upregulation, downregulation, or differential expression in either direction with respect to cultured cells; and strong (adjusted p-value 2-fold change) up- and downregulation. Because the gene expression patterns within each chromosome were generally consistent across the four time points, we fit a single model for each expression category with chromosome type (Chromosomes 5 and 6 vs rest of genome) as a fixed predictor and time point as a random effect. We also compared the absolute expression level (measured as log 2 (transcripts per million (TPM), pooled across all libraries)) between genes on Chromosomes 5 and 6 vs. other chromosomes. The amount of variance in expression explained by same-stranded gene clusters of more than 10 consecutive genes was tested using linear mixed models. The response variable was the log 2 scale variance stabilized read count, corrected for gene length by dividing each count by the length of the corresponding gene and multiplying by the median gene length for the whole data set. We ran separate models with and without the genes with low read counts that were excluded from differential expression analyses, and a third model with log 2 (transcripts per million (TPM)) as the response variable. In each case, chromosomes and gene clusters were used as random effects, and a separate model was fit for each of the 5 treatment groups. The proportion of total variance in read counts explained by the random effects was extracted using the ‘extract_variance_components’ function from R package mixedup (57). Correlations in absolute and differential expression between adjacent genes was modeled with expression of each focal gene as the response variable; expression of the preceding gene, whether or not the two genes were on the same strand of the chromosome, and their interaction as predictor variables; and chromosome as a random effect. Separate models were fitted using variance-stabilized read counts– with and without low-count genes– and TPM as response variables for absolute expression (as for strand-wise gene clusters above) and log 2 -fold change vs cultured cells for differential expression. A separate model was fit for each treatment group (for absolute expression) or time point (for differential expression). Functional gene annotation and patterns of expression We conducted functional analyses of changes in gene expression using Gene Set Enrichment Analysis (GSEA) of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) terms. Genes were assigned tentative GO terms by submitting the annotated protein sequences to the PANNZER2 server (58). Terms were filtered to retain only predictions with a positive prediction value of >0.5, resulting in annotations for 2,457 of the original 10,288 submitted sequences. Parent terms in the GO hierarchy implied by each prediction were added using the buildGOmap function of R package ClusterProfiler (59). The resulting set of terms was then filtered using FunTaxIS-lite to remove terms unlikely to occur in trypanosomatids (60). Annotated genes were similarly assigned KEGG functions based on protein sequences and annotated to associated pathways using BlastKOALA (61), which inferred KEGG terms for 2,693 of the submitted protein sequences. The resulting list of terms was filtered to retain only pathways annotated in reference kinetoplastid genomes present in the KEGG database. Gene set enrichment analysis was implemented in ClusterProfiler on all terms associated with at least 15 genes (62). Genes were ranked within each time point using the test statistic from the differential expression estimate for bee gut-derived relative to cultured cells (i.e., the ratio of the estimated log2-fold change to the standard error of the estimate) as the signal-to-noise ratio. These ranks were used to calculate an enrichment score and associated p-value for the gene set associated with each GO term or KEGG pathway, along with identification of the ‘leading edge’ genes that contributed most strongly to each gene set’s pattern of differential expression (62). Finally, for the GO analysis, closely related terms with semantic similarity of 0.5 or higher were simplified to use only the term with the lowest p-value in each cluster of related terms (63). We discuss only gene sets with adjusted p-values <0.01. Results and Discussion Synteny with divergence of the ancestrally tetrasomic chromosome The L. passim nuclear genome was assembled to 31 chromosome-level scaffolds with telomeric repeats at their termini, along with the mitochondrial (kinetoplast) maxi- and minicircles typical of trypanosomatids. The genome assembly displayed a high degree of synteny with related species in the Leishmaniinae subfamily, supporting the phylogenetic placement of L. passim within the Crithidia/Leptomonas/Lotmaria clade (Figure 1, Figure 2). Synteny was highest with the close relative Leptomonas pyrrhocoris , for which the L. passim genome was 97% covered by 49 synteny blocks, including 62 sets of at least 20 collinear genes. However, synteny was also strong with Crithidia bombi (87% across 71 blocks) and C. fasciculata (92% across 57 blocks), and slightly lower but with fewer blocks for the chromosome-level assemblies of Leishmania major (86%, 41 blocks) and L. braziliensis (86%, 48 blocks) (Figure 2). In four cases (Chromosomes 1, 2, 4, and 13), L. passim chromosomes displayed synteny to multiple full chromosomes of L. major (Figure 1) . For example, L. passim Chromosome 1 incorporated synteny blocks spanning L. major Chromosomes 36 and 3, parallel to the fusion of L. major Chromosomes 36 and 20 in L. mexicana (19). The paralogous L. passim Chromosomes 5 and 6 showed substantially lower levels of synteny with homologous chromosomes in other species (Figure 2). Only around half the combined length of these chromosomes showed synteny with C. bombi and C. fasciculata and no synteny was detected with C. expoeki or either species of Leishmania , contrasting with the >80% synteny of the genome overall (of which Chromosomes 5 and 6 constitute ~12%) for each of these comparator species (Figure 2). However, each of Chromosomes 5 and 6 was syntenic with the tetrasomic scaffolds 12, 29, and 32 of the L. pyrrhocoris assembly (Figure 3) (9,17), suggesting that these three scaffolds (ordered 32, 12, 29) comprise a single L. pyrrhocoris chromosome. These L. pyrrhocoris scaffolds were in turn syntenic with the ancestrally tetrasomic Chromosome 31 of L. major , strongly suggesting that these L. passim chromosomes share ancestry with the Leishmania Chromosome 31. This synteny, however, was not inferred when comparing L. passim with L. major directly (Figure 1) . These findings suggest that Chromosomes 5 and 6 have substantially diverged from their ancestral state in L. passim and compared to the equivalent genomic regions of other monoxenous species. The combination of a high quality assembly and high nucleotide divergence between the two haplotype pairs (88.8% sequence identity) allowed us to distinguish two separate disomic chromosomes in L. passim (Figure 1), which contrasts with the tetrasomy concluded for the other species (17,19). Nevertheless, divergence of these chromosomes is consistent with the high nucleotide diversity of the tetrasomic genome scaffolds within populations of Crithidia, Leptomonas, and Leishmania relatives (17). Additional haplotype-level sequences of this tetrasomic region in other trypanosomatids are needed to determine whether its assortment into two chromosome pairs is unique to L. passim . However, analysis of the L. major Friedlin genome found evidence for only 239 polymorphic sites on Chromosome 31 (64), suggesting >99.98% identity across haplotypes over this ~1.5 Mb region. Structural patterns of gene arrangement and transcription Our annotation of genes indicated the presence of long clusters of genes on the same strand that in some cases spanned entire chromosomes, consistent with the previously described organization of trypanosomatid genes in long polycistronic units (11). Adjacent gene pairs had a 97% chance of being located on the same strand; genes within 1 Kb of one another had a >90% chance of sharing a strand, and those within 10Kb a >80% chance (Supplementary Figure 1). The strand-wise arrangement of genes was conspicuously strong on the paralogous Chromosomes 5 and 6 (Figure 4), where essentially all (96%) of the annotated regions (including intact protein-coding genes as well as non-coding RNAs and predicted pseudogenes) were on the negative strand, consistent with annotations of the tetrasomic chromosomes with shared ancestry in other trypanosomatids (17,19). We used publicly available L. passim transcriptomic data (33) in combination with our new chromosome-level genome assembly and its annotation to re-examine structural and functional patterns of gene expression during infection of honey bees. Roughly two-thirds of annotated genes were differentially expressed in bees vs. log-phase cell cultures at each of the four time points post-inoculation (Figure 5). The duplicated Chromosomes 5 and 6 were conspicuously enriched in genes upregulated in the bee gut environment, with higher probabilities of genes being upregulated and lower probabilities of genes being downregulated. Across all time points, genes on these two chromosomes were more than twice as likely to be upregulated by greater than two-fold relative to genes on other chromosomes (Figure 5). However, genes on the duplicated chromosomes were expressed at more than two-fold lower levels (i.e., fewer read counts) than those on other chromosomes (Supplementary Figure 2; Supplementary Figure 3), thereby compensating for the doubling of copy numbers resulting from chromosome duplication. A similar pattern, in which genes on the ancestrally tetrasomic chromosome are collectively expressed at similar levels to those on disomic chromosomes despite having twice as many copies, was likewise reported for the Leishmania Chromosome 31 (17). The paralogous chromosomes were also enriched in predicted pseudogenes, with a >50% increase in proportions of this feature type relative to the rest of the genome (Supplementary Figure 4). We also assessed spatial patterns of gene expression within chromosomes and their relationship to strand-wise gene arrays, which are canonically transcribed as a single polycistronic unit (11). We found weak but highly significant positive correlations between expression levels of adjacent genes in each sample group (e.g., ꭕ 2 1 = 671, P < 0.001 for cell cultures with low-count genes excluded). However, the correlation between neighbors was stronger for neighboring genes on the same versus opposite strands of the chromosome, as evidenced by the significance of the neighbor expression x shared strand interaction term (e.g., ꭕ 2 1 = 23.6, P < 0.001 for cell cultures, Figure 6). The fixed-effects model explained 5-10% of the variance in each sample group, suggesting a detectable signal of polycistronic transcription despite considerable post-transcriptional regulation of mRNA levels; this observation might be at least partly attributed to the origin of a portion of sequencing reads from precursor mRNAs. Same-stranded arrays of >10 consecutive genes explained 8-16% of variation in expression levels when modeled as a random effect, depending on whether genes with low read counts were excluded (Supplementary Figure 5). We also found positive correlations between differential expression of neighboring genes in bee guts vs. cell culture, although these were less pronounced than for absolute expression, and no significant difference was evident between gene pairs on the same vs. opposing strands (i.e., P > 0.05 for neighbor log 2 -fold change by shared strand interaction term, Supplementary Figure 6). The proportion of variance explained by the fixed effects model (comprising log 2 -fold change of the neighboring gene, whether neighbors were on the same strand, and their interaction) was <1% for every time point, indicating that differential expression of neighboring genes is only weakly interdependent. Functional analysis of transcription We used our annotation to analyze functional patterns of differential gene expression in the gut vs. cell culture environment using Gene Set Enrichment Analyses, which characterize the rank-based distribution of changes in expression level (relative to cultured cells) for the set of genes associated with each function-related term (62). Gene ontology (GO) term enrichment analyses were generally consistent across different time points post-inoculation, with many of the same terms occurring repeatedly among the most highly enriched gene sets (Figure 7). Most of the strong enrichment scores were associated with down-regulated gene sets. There was a general decrease in expression of gene sets encoding proteins of carbohydrate metabolism and ribosomal protein synthesis, consistent with adaptations to a low-nutrient environment in the bee hindgut. There was also a decrease in expression of gene sets involved in responses to oxidative stress and detoxification, possibly reflecting the relatively low oxygen levels in the gut or, alternatively, the fact that cultures were grown in antibiotic-enriched media. Upregulated gene sets annotated for metallopeptidase activity, exopeptidase activity, and amino acid metabolism were suggestive of a shift from carbohydrate- to amino acid-based metabolism, similar to changes reported in other trypanosomatids in the insect gut vs. rich culture media (65) and conclusions from the initial publication describing this dataset (33). At 7 d post-inoculation, we found downregulation of gene sets encoding proteins associated with the GO term ‘microtubule-based process’, with several flagellar proteins among the genes contributing to the downregulation. This pattern was consistent with observations of reduced flagella in attached haptomonad morphotypes carpeting the bee gut epithelium, as opposed to the freely swimming promastigotes found in log-phase cultures (66,67). This was followed by upregulation of the endomembrane system-associated gene set, suggesting reorganization of cellular structure and intracellular machinery as cells proliferated along the gut wall (Figure 7). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was concordant with the GO analysis, indicating downregulation of gene sets related to protein synthesis, energy metabolism and glutathione-based antioxidant metabolism, and flagellar and motor proteins. This was countered by upregulation of gene sets related to amino acid metabolism (arginine biosynthesis; 2-oxocarboxylic acid metabolism; and alanine, aspartate, and glutamate metabolism; Figure 8). Upregulation of the autophagy-associated gene set at the first time point (7 d post-inoculation) was further suggestive of a nutrient-limited environment in the bee gut; this term was not highlighted by the original study’s GO term analysis (33). We also found upregulation of the gene set encoding proteins for variants of GP63/leishmanolysin–a glycoprotein and peptidase involved in cell adhesion and cleavage of host effector proteins. The N-glycan biosynthesis-related gene set was likewise upregulated, which was not reported previously (33). Upregulated genes in this set included several glycosyltransferases, which catalyze the attachment and removal of sugar and acetylglucosamine groups from proteins (Supplementary Figure 7). Both GP63 and N-glycan biosynthesis gene sets are likely important for adherence to and interaction with host tissues or gut biofilms (13,14). Attachment to the insect gut epithelium is a process common to most of the trypanosomatids, with cell surface proteins playing a key role in the process (13). In C. fasciculata, which like L. passim attaches to the hindgut wall and assumes a truncate morphology with a reduced flagellum, similar upregulation of GP63 proteins and genes involved in cell adhesion was observed during infection of mosquitoes as well as in adherent cultured cells (14). Given that the attachment process generally occurs on the time scale of hours rather than days (13), closer attention in the period immediately post-inoculation could provide greater insight into how L. passim gene expression changes during initiation of infection. Overall, the functional patterns of differential expression bear strong similarity to those reported in other trypanosomatids during both insect and mammal infection. Transcriptomes of Herpetomonas muscarum in Drosophila relative to cell cultures likewise indicated a pattern of increased amino acid utilization and autophagy (68). Like the changes in C. fasciculata (14), they also showed reduced expression of flagellum-related genes and increased expression of multiple GP63 peptidases as well as other proteins associated with the cell surface (68). In addition, post-inoculation upregulation of genes involved in DNA replication and repair in H. muscarum (68) was concordant with the upregulation of gene sets annotated for nucleic acid catalytic and helicase activities in our GO term enrichment analysis. Beyond the insect gut, several aspects of L. passim gene expression in bees resembled those found in Leishmania species in the transition from the insect-associated promastigote form (in cell culture) to the amastigote form associated with vertebrate blood cells. These include down-regulation of gene sets associated with growth, carbon metabolism and flagellar motility; and upregulation of gene sets encoding peptidases and cell surface proteins (19,69). In light of these similarities, it is understandable how the same genes and related regions of the genome, such as the glycoprotein anchor and other surface protein-associated genes that are enriched on the ancestrally tetrasomic chromosome (17), could be important for both insect and vertebrate infection, and why this supernumerary region of the genome was enriched in genes upregulated during both Leishmania infection of blood cells (19) and L. passim infection of the bee gut described here. Maintaining and diversifying additional copies of such niche-specific, surface protein-encoding genes could enable parasites to continually evade recognition and subvert attack by current and novel hosts across evolutionary time. The most apparent fluctuations in differential expression across time points was found for gene sets annotated as components of the leishmaniasis and trypanosomiasis pathways, each of which appeared among the top up- or downregulated sets at different time points (Figure 8). Both terms describe genes involved in trypanosomatid infection of mammals, consisting mostly of host immune pathways along with a few parasite-derived virulence factors and immunomodulators. The leishmaniasis pathway gene set was down-regulated at 7 d, upregulated at 12 d, then downregulated again at 20 d post-inoculation. This reflected strong downregulation of cysteine peptidase B (CPB) at 7 d and 20d and downregulation of elongation factor 1-alpha (EEF1a) at 20 d, which was countered by strong upregulation GP63-family genes from 12 d onwards (Figure 9). The trypanosomiasis pathway gene set was downregulated at 7 d– again reflecting downregulation of cysteine peptidase B (CPB)– but upregulated at 12 and 20 d, reflecting increased expression of multiple paralogs of GP63 and thimet oligopeptidase (THOP1/tropolysin) (Figure 9). GP63 is noted for providing resistance to complement-mediated lysis in the bloodstream as well as to hydrolytic enzymes in the sand fly gut (15), whereas cysteine peptidase inhibits inflammatory signaling pathways (70)– including the JAK-STAT pathway important for clearing infection with the trypanosomatid H. muscarum in Drosophila (71). Although both represent large protein families, this suggests that these genes could likewise protect parasites from host (bee) defenses or suppress their expression in response to infection. Indeed, very few changes in host gene expression occurred in L. passim- inoculated honey bees (33); only modest and transient upregulation of immune genes occurred in honey bees inoculated with C. mellificae (72); and most bumble bee immune genes showed little induction following in inoculation with C. bombi (73), with the most infectious stains eliciting the weakest expression of antimicrobial peptides (74). Scrutiny of genes involved in these pathways reflected both the structure of the genome and the limitations of the RNAseq analysis. Strings of paralogs generally appeared as tandemly arrayed genes along the chromosome, including 2 sets of 5 paralogs of GP63 on the Chromosomes 5 and 6 and over 30 consecutive paralogs of EEF1A on Chromosome 18 (Figure 9). Due to the sequence similarity among paralogs, sequencing reads could not be unambiguously assigned. These reads were distributed fractionally across each gene to which they aligned, resulting in read counts that were identical (or nearly so) among many spatially clustered paralogs, and non-independence of differential expression estimates for each one. This limitation in precision of mapping also likely inflated our estimates of correlations between transcript levels of neighboring genes (Figure 6). Another limitation of the functional analysis was the absence of annotations for a significant portion of the genes– around three-fourths using our present method– leaving changes that involve these loci uncharacterized. For example, we were able to identify only a few differentially expressed gene sets with >10% of the strongly contributing ‘leading edge’ genes located on the paralogous chromosomes. All but one set (GO term ‘kinase activity’) was upregulated. Most were related to amino acid metabolism and peptidase activity, including ‘L-amino acid biosynthetic process’, ‘proteinogenic amino acid biosynthetic process’, ‘L-amino acid metabolic process’, ‘metallopeptidase activity’, and ‘exopeptidase activity’ in the GO analysis; and ‘2-oxocarboxylic acid metabolism’ and ‘arginine biosynthesis’ in the KEGG analysis. The remaining upregulated sets were for the KEGG terms ‘RNA polymerase’, ‘trypanosomiasis’, and ‘leishmaniasis’; however, each of these included only two leading edge genes on the paralogous chromosomes. Conclusions Our analysis leverages one of the first chromosome-level assemblies of an insect-specific trypanosomatid parasite of bees to illuminate the structural singularities of the genome and how they relate to gene expression, host infection, and parasite evolution. By linking the differentiation of an ancestrally tetrasomic region into two distinct, disomic chromosomes with the presence of genes upregulated in the honey bee host, our findings provide a fitness-related explanation for this salient genomic feature. Our transcriptomic analysis highlights shared patterns of gene expression across diverse trypanosomatids during host infection, as well as similarities between the functional changes that occur during infection of insects and vertebrates. The paralogous chromosomes, including genes for surface proteins that directly interface with hosts, appear to have disproportionate importance for establishment in both types of host. Hence, both elevated copy number and divergence of these chromosomes and their genes was likely advantageous in colonizing the diverse ecological niches occupied by trypanosomatids, including the hindgut of honey bees. Declarations Acknowledgments The authors thank Amanda Albanaz for proteome annotations of Crithidia mellificae , Crithidia bombi , and Crithidia expoeki . Funding This project was supported by U.S. Department of Agriculture National Institute of Food and Agriculture Grant 2020-67013-31861 to JDE and ECPY, U.S. Department of Agriculture National Institute of Food and Agriculture Postdoctoral Fellowship 2022-67012-37482 to ECPY, an Eva Crane Trust Grant to JDE and ECPY, and the U.S. Department of Agriculture Agricultural Research Service Beltsville Bee Research Laboratory in-house funds. Data availability The L. passim BRL (2024) Hi-C and HiFi raw reads are available on NCBI GenBank (accession ID: SRX22798691 and SRX22798690); the assembled chromosomes (accession ID: GCA_037349495.1), maxicircle, and minicircles and annotation are listed under BioProject PRJNA1049372. The annotated genome is available on FigShare as a supplement to our previous article documenting the assembly (41) at https://doi.org/10.25387/g3.27121227 and will be added to the above BioProject pending acceptance by NCBI. RNA sequence data were used from NCBI BioProject PRJNA587465. The gene counts, GO terms assigned by Pannzer2, and KEGG terms assigned by BlastKOALA are provided as supplementary materials. Ethics approval and consent to participate: N/A Consent for publication: All authors agreed to submission of the manuscript Competing interests: The authors declare that they have no competing interests. Authors’ contributions: AN, JDE, and ECPY conceived the study. AN and ECPY analyzed the data with guidance from AB. ECPY wrote the first draft of the manuscript. All authors revised the manuscript. References Maslov DA, Votýpka J, Yurchenko V, Lukeš J. Diversity and phylogeny of insect trypanosomatids: all that is hidden shall be revealed. 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Supplementary Files Gene.counts.long.csv annotationpannzer2web20240823.txt blastkoalauserkodefinition.txt GSEA.GOsimp.merged.csv GSEA.keggleish.merged.csv SupplementaryInformation.docx Cite Share Download PDF Status: Published Journal Publication published 01 Dec, 2025 Read the published version in BMC Genomics → Version 1 posted Editorial decision: Revision requested 20 Mar, 2025 Reviews received at journal 14 Mar, 2025 Reviews received at journal 09 Mar, 2025 Reviewers agreed at journal 24 Feb, 2025 Reviewers agreed at journal 24 Feb, 2025 Reviewers agreed at journal 24 Feb, 2025 Reviewers invited by journal 24 Feb, 2025 Editor invited by journal 24 Feb, 2025 Editor assigned by journal 13 Feb, 2025 Submission checks completed at journal 11 Feb, 2025 First submitted to journal 08 Feb, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5989240","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":413997735,"identity":"8b52f89d-ae51-475a-9c2c-a8dfc8d6d810","order_by":0,"name":"Anthony Nearman","email":"","orcid":"","institution":"USDA-ARS Bee Research Laboratory","correspondingAuthor":false,"prefix":"","firstName":"Anthony","middleName":"","lastName":"Nearman","suffix":""},{"id":413997736,"identity":"ae24197a-b83d-41d6-8986-2279e40faf2a","order_by":1,"name":"Anzhelika Butenko","email":"","orcid":"","institution":"Czech Academy of Sciences","correspondingAuthor":false,"prefix":"","firstName":"Anzhelika","middleName":"","lastName":"Butenko","suffix":""},{"id":413997737,"identity":"fa7ff889-dded-41e5-a6da-b45fd6898021","order_by":2,"name":"Jay D Evans","email":"","orcid":"","institution":"USDA-ARS Bee Research Laboratory","correspondingAuthor":false,"prefix":"","firstName":"Jay","middleName":"D","lastName":"Evans","suffix":""},{"id":413997738,"identity":"3672e069-bc9a-4823-8de6-2301343bfa00","order_by":3,"name":"Evan C Palmer-Young","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABFklEQVRIiWNgGAWjYBADGTiLH0QkFBDWwgNnSTaAtBiQosXgAJjErZRfIvnZA8Yddjy67b3PJD623bHbfH514ocHBgzy/GIHsGqRnJFmbsB4JpnH7MxxM8mZbc+St914u1kC6DDDmbMTsGoxOHPATIKxjZnH7EYamzRv2+FksxtnN4C0JBjcxq7F/szxb0At9Txm959BtBjPOLv5Bz4tBuw9IFsOA21hA2uxM+Dv3YbXFonjPWUSiWeOA/2Sxmw549zhBIkbvNssEgwkcPqFv5l9m8THHdVyZsePMd74UHbYnr//7OabPyps5PmlsWsBg8QGMMUiAWZLgFVK4FYOAowQLcwfQOHBwH8Av+pRMApGwSgYcQAAWbxexChJfcEAAAAASUVORK5CYII=","orcid":"","institution":"USDA-ARS Bee Research Laboratory","correspondingAuthor":true,"prefix":"","firstName":"Evan","middleName":"C","lastName":"Palmer-Young","suffix":""}],"badges":[],"createdAt":"2025-02-08 17:53:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5989240/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5989240/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12864-025-12082-y","type":"published","date":"2025-12-01T15:57:50+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":76085576,"identity":"ed180e41-64f7-4456-8673-e4b0230aec18","added_by":"auto","created_at":"2025-02-12 07:26:03","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":757893,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSynteny of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eL. passim \u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003echromosomes with\u003c/strong\u003e\u003cem\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003etrypanosomatid relatives \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eLeishmania major\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e and \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eLeptomonas pyrrhocoris\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e.\u003c/strong\u003e\u003cem\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/em\u003eLabeled bands depict scaffolds of \u003cem\u003eL. passim\u003c/em\u003e and (A) \u003cem\u003eL. major\u003c/em\u003eor (B) \u003cem\u003eL. pyrrhocoris\u003c/em\u003e. Arcs connect syntenic regions. (A) The\u003cem\u003e \u003c/em\u003eparalogous \u003cem\u003eL. passim\u003c/em\u003e Chromosomes 5 and 6 and the tetrasomic \u003cem\u003eL. major\u003c/em\u003e Chromosome 31 constitute the only chromosome-scale synteny gaps. (B) All major genomic regions are shared between \u003cem\u003eL. passim \u003c/em\u003eand \u003cem\u003eL. pyrrhocoris, \u003c/em\u003ewith the region syntenic with paralogous Chromosomes 5 and 6 split across 3 \u003cem\u003eL. pyrrhocoris \u003c/em\u003escaffolds.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-5989240/v1/286b3804ec747f3c303999fc.png"},{"id":76084679,"identity":"df988653-00c1-4c4a-9531-313f392db6b1","added_by":"auto","created_at":"2025-02-12 07:18:03","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":380576,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePhylogenetic placement and proportions of the \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eL. passim \u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003egenome and paralogous Chromosomes 5 and 6 syntenic with genomes of selected relatives. \u003c/strong\u003e(A) Whole-genome phylogeny depicting relationships between \u003cem\u003eL. passim, L. pyrrhocoris, \u003c/em\u003eand other trypanosomatids in the Leishmaniianae subfamily. The tree was inferred from protein sequences of 2663 single-copy orthologs. Our assembly is labeled ‘BRL (2024)’. The position of the ‘SF’ strain used for the first draft genome assembly is also shown \u003ca href=\"https://www.zotero.org/google-docs/?krTEU4\"\u003e(42)\u003c/a\u003e. For \u003cem\u003eC. bombi \u003c/em\u003eand \u003cem\u003eC. expoeki, \u003c/em\u003enodes are shown for both the original published annotations by Schmid-Hempel and colleagues (‘SH’ \u003ca href=\"https://www.zotero.org/google-docs/?43koBA\"\u003e(75)\u003c/a\u003e) and independent annotations of the same assemblies created in a review of trypanosomatid phylogenomics by Kostygov and colleagues (‘Kos’ \u003ca href=\"https://www.zotero.org/google-docs/?eWzYFb\"\u003e(8)\u003c/a\u003e). All nodes had support values of 1 based on 1,000 resamples. (B) Synteny of paralogous chromosomes and genome overall. Y-axis shows species analyzed; x-axis represents proportion of the \u003cem\u003eL. passim \u003c/em\u003egenomic of chromosome region covered by synteny blocks. Shading of bars corresponds to the region quantified. “Total” indicates the entire nuclear genome.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-5989240/v1/5736bde00a62c8bad56bc899.png"},{"id":76084249,"identity":"8ca1f99f-a5d9-4c8e-b0e9-65acd5ceee8f","added_by":"auto","created_at":"2025-02-12 07:10:03","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":191635,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThree-way synteny between \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eL. passim \u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eChromosomes 5 and 6; \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eL. pyrrhocoris \u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003etetrasomic scaffolds 12, 29, and 32; and \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eL. major \u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003etetrasomic Chromosome 31. \u003c/strong\u003eThe \u003cem\u003eL. passim \u003c/em\u003eChromosomes 5 and 6 are syntenic with the same \u003cem\u003eL. pyrrhocoris \u003c/em\u003escaffolds that showed synteny with \u003cem\u003eL. major \u003c/em\u003eChromosome 31. This strongly suggests shared ancestry between the corresponding chromosomes of \u003cem\u003eL. passim \u003c/em\u003eand \u003cem\u003eL. major\u003c/em\u003e).\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-5989240/v1/603875fc968f8b4919915956.png"},{"id":76084252,"identity":"cff14ddd-2ba5-4bbd-8a0b-c37317207aa6","added_by":"auto","created_at":"2025-02-12 07:10:03","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":301398,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCircular representation of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eLotmaria passim\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e BRL (2024) genome assembly. \u003c/strong\u003eRadial segments correspond to the 31 nuclear chromosomes, numbered by size from largest to smallest. Outer ring: sequencing depth. Gray points show base-level read depth, subsampled at 100 bp intervals. Blue line trace represents 1 Kb moving average. Large red circle represents the chromosome-level median. Faint scatter of gray points with roughly half the read depth of the chromosome overall suggests heterozygous sites. Concentric yellow, orange, and red lines represent 50%, 100%, and 150% of the median chromosome-level depth; this corresponds to expected depths for monosomic, disomic, and trisomic chromosomes, respectively. The paralogous Chromosomes 5 and 6 appear as disomic chromosomes with distinct coverage traces. Inner ring: relative density of coding regions (percent of each 10 Kb interval covered by predicted exons), colored by strand (blue: positive, orange: negative), suggesting long stretches of polycistronic genes on the same strand and strand-biased gene arrangement on Chromosomes 5 and 6. Opaque red link between Chromosomes 5 and 6 indicates the similarity between these two regions.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-5989240/v1/01886aa3540cc7c7a4472b1c.png"},{"id":76084251,"identity":"8f99e2fa-a36f-4173-98f4-428673884ea2","added_by":"auto","created_at":"2025-02-12 07:10:03","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":90996,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eParalogous Chromosomes 5 and 6 are enriched in genes upregulated during infection of honey bees\u003c/strong\u003e. (A) Model coefficients for proportions of genes significantly (P \u0026lt; 0.05) and strongly (\u0026gt;2-fold change subset) up- and down-regulated in bee gut vs. culture environments. X-axis shows model coefficients and 95% confidence intervals for genes on Chromosomes 5 and 6 versus the rest of the genome. (B) Proportions of genes significantly up- and down-regulated on each chromosome and time point post-inoculation. Horizontal lines indicate median proportions. Shapes represent the four times of sampling, in days post-inoculation.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-5989240/v1/25e7bcacd2b4582bdf0806f1.png"},{"id":76084260,"identity":"f69cd073-4256-4539-82ea-53c6634c14b9","added_by":"auto","created_at":"2025-02-12 07:10:03","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":805323,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eExpression levels of adjacent genes are correlated, with stronger correlations between neighboring genes located on the same strand \u003c/strong\u003eof the chromosome\u003cstrong\u003e. \u003c/strong\u003eY- and X-axes show log-transformed expression levels (transcripts per million) of each pair of neighboring genes. Trendlines show correlations with 95% CI shaded bands, in red for neighbors on opposite strands and blue for neighbors on the same strand. Panels in rows indicate sample groups (cultured cells and cells from bee guts at different time points post-inoculation). Panels in columns show data with and without low-count (i.e., low expression level) genes excluded.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-5989240/v1/08769677e58ba4f01387cf34.png"},{"id":76084688,"identity":"b826260e-0c85-43e6-b4ed-3022dff6d570","added_by":"auto","created_at":"2025-02-12 07:18:03","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":85665,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGene ontology gene set enrichment for \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eL. passim\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eexpression levels\u003c/strong\u003e in honey bee gut samples at 4 time points post-inoculation relative to cultured cells. Y-axis shows the term description. Panels show gene sets up- and down-regulated. Shading is proportional to the p-value for the test and size to the proportion of annotated genes that contribute to the up- or down-regulation (i.e., ‘leading edge’ genes).\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-5989240/v1/1407c90380ffc67e636be427.png"},{"id":76085579,"identity":"58c76fff-faf9-47d6-9168-165efdfd3934","added_by":"auto","created_at":"2025-02-12 07:26:03","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":89056,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eKEGG pathway gene set enrichment \u003c/strong\u003efor L. passim expression levels in honey bee gut samples at 4 time points post-inoculation relative to cultured cells. Y-axis shows the term description. Panels show gene sets up- and down-regulated. Shading is proportional to the p-value for the test and size to the proportion of annotated genes that contribute to the up- or down-regulation (i.e., ‘leading edge’ genes).\u003c/p\u003e","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-5989240/v1/feed10d324f2d12f78934f16.png"},{"id":76084698,"identity":"8af21ecb-c59c-4da8-afac-4128fdc41be9","added_by":"auto","created_at":"2025-02-12 07:18:04","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":267639,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDifferential expression of genes annotated as constituents of the ‘African trypanosomiasis’ (‘Tryp’) and ‘Leishmaniasis’ KEGG pathways. \u003c/strong\u003eShading corresponds to T-statistic for differential expression for bee gut vs. cultured cells at each time point post-inoculation. Open circles are sized in proportion to the log\u003csub\u003e2\u003c/sub\u003e-fold change. Y-axis numbers correspond to paralogs within each gene type, numbered consecutively according to their position in the genome. Panels labeled ‘both’ correspond to genes included in both the trypanosomiasis and leishmaniasis pathways. Letters and signs within the plot indicate genes most strongly contributing to up- (“+”) or downregulation (“-”) of the leishmaniasis (“L”) and trypanosomiasis (“T”) pathways at each time point. Abbreviations: ICP: inhibitor of cysteine peptidase; ptrB: protease (Oligopeptidase) B; THOP: thimet oligopeptidase (“Tropolysin”); TLTF: T lymphocyte-triggering factor; CPB: cysteine peptidase B; GP63: major surface glycoprotein 63 (“Leishmanolysin”); EEF1A: elongation factor 1-alpha; ERK: extracellular signal-regulated kinase, MAPK: mitogen-activated protein kinase.\u003c/p\u003e","description":"","filename":"floatimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-5989240/v1/dc563b7e2231b570a79ef406.png"},{"id":97724046,"identity":"f0495f30-456d-47e9-8187-f4e978d4fb2f","added_by":"auto","created_at":"2025-12-08 16:11:20","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3632071,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5989240/v1/6aa90afb-d23a-4973-9d67-df7cf4e1d909.pdf"},{"id":76084298,"identity":"f8d72268-aef1-4303-a975-2f5f0c048086","added_by":"auto","created_at":"2025-02-12 07:10:04","extension":"csv","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":22897263,"visible":true,"origin":"","legend":"","description":"","filename":"Gene.counts.long.csv","url":"https://assets-eu.researchsquare.com/files/rs-5989240/v1/03ec28a73592556a631b9db9.csv"},{"id":76084274,"identity":"fe687eb2-644f-4862-bfb3-b175c6789723","added_by":"auto","created_at":"2025-02-12 07:10:04","extension":"txt","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":11052616,"visible":true,"origin":"","legend":"","description":"","filename":"annotationpannzer2web20240823.txt","url":"https://assets-eu.researchsquare.com/files/rs-5989240/v1/f2974a1b23776d31e80d2745.txt"},{"id":76084254,"identity":"48085b9f-ba4e-48b1-8d98-6881a0d9af9e","added_by":"auto","created_at":"2025-02-12 07:10:03","extension":"txt","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":396864,"visible":true,"origin":"","legend":"","description":"","filename":"blastkoalauserkodefinition.txt","url":"https://assets-eu.researchsquare.com/files/rs-5989240/v1/102e82d2232f34208de33723.txt"},{"id":76084266,"identity":"2b701ace-4746-4f84-ae6f-571bc50370b0","added_by":"auto","created_at":"2025-02-12 07:10:03","extension":"csv","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":180735,"visible":true,"origin":"","legend":"","description":"","filename":"GSEA.GOsimp.merged.csv","url":"https://assets-eu.researchsquare.com/files/rs-5989240/v1/5d6f71d07c36ecc3e947b647.csv"},{"id":76084686,"identity":"effbdc3c-6a0f-49bb-9ce3-47d1280d94ef","added_by":"auto","created_at":"2025-02-12 07:18:03","extension":"csv","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":73805,"visible":true,"origin":"","legend":"","description":"","filename":"GSEA.keggleish.merged.csv","url":"https://assets-eu.researchsquare.com/files/rs-5989240/v1/a867e2d4767056180953bb57.csv"},{"id":76084684,"identity":"b3255dfb-feaf-47cd-8be6-9630ae71add6","added_by":"auto","created_at":"2025-02-12 07:18:03","extension":"docx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":499001,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryInformation.docx","url":"https://assets-eu.researchsquare.com/files/rs-5989240/v1/2ad83068291d0fe048c87397.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Chromosome-level genome assembly of trypanosomatid parasite Lotmaria passim links chromosome duplication and divergence with infection of honey bees","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe trypanosomatids are an intriguing and medically important family of protists that exploit a variety of ecological niches. They include obligate \u0026lsquo;monoxenous\u0026rsquo; (single-host) parasites of insects and \u0026lsquo;dixenous\u0026rsquo; (two-host) insect-vectored parasites of plants and vertebrates (1\u0026ndash;3), namely the \u003cem\u003eLeishmania \u003c/em\u003eand \u003cem\u003eTrypanosoma \u003c/em\u003especies that cause considerable disability in tropical and subtropical regions (4\u0026ndash;6). The factors that enable the radiation of trypanosomatids into novel host environments are therefore of basic and applied interest (2,7).\u003c/p\u003e\n\u003cp\u003eThe sequencing of genomes from trypanosomatids across this spectrum of lifestyles has begun to reveal the phylogenetic relationships between species, changes associated with the transition to parasitism, and adaptations to different niches (2,8\u0026ndash;10). Several themes have emerged from the species investigated thus far. These include a generally conserved genome structure with high degrees of synteny among distantly related species, the arrangement and transcription of genes in long polycistronic blocks along a given strand of the chromosome, and predominantly post-transcriptional regulation of gene expression (11,12). Expression of cell surface proteins appears to play an important role in interactions with host cells, tissues, and immune systems (12\u0026ndash;15).\u003c/p\u003e\n\u003cp\u003eMany species also exhibit duplication of chromosome segments and variation in chromosome copy number, or aneusomy (9,16,17). This can aid in regulation of gene dosage in the absence of fine-scale transcriptional control while conserving polycistronic arrays. It can also facilitate adaptation to ecological and evolutionary pressures, such as exposure to toxins and novel host environments (17\u0026ndash;20). One remarkable example is the \u003cem\u003eLeishmania \u003c/em\u003eChromosome 31, which is consistently tetrasomic (i.e., present as four copies)\u003cem\u003e \u003c/em\u003e(20)\u003cem\u003e.\u003c/em\u003e It is also enriched in genes that are upregulated during infection of vertebrates, suggesting that this duplication aided the ability to colonize these new hosts (19). A recent investigation of over 800 trypanosomatid genome assemblies revealed that scaffolds and chromosomes syntenic with Chromosome 31 are in fact tetrasomic across a wide range of mono- and dixenous species, suggesting that this aneusomy is ancestral in the trypanosomatid family rather than a specific adaptation of \u003cem\u003eLeishmania \u003c/em\u003e(17). However, its importance for the infection of other hosts and insect vectors remains unclear.\u003c/p\u003e\n\u003cp\u003eAmong the monoxenous trypanosomatids, several species are associated with bees. \u003cem\u003eCrithidia bombi\u003c/em\u003e and \u003cem\u003eC. expoeki\u003c/em\u003e, the main species identified in bumble bees, have emerged as models of host-parasite ecology and evolution and revealed the context- and life stage-dependent effects of trypanosomatid infection on insects (21\u0026ndash;23). \u003cem\u003eLotmaria passim\u003c/em\u003e, on the other hand, is the most prevalent trypanosomatid species known in honey bees (24). It exhibits a global distribution, high prevalence, negative effects on bee survival, and an association with collapsing colonies (25\u0026ndash;34), suggesting its importance as a threat to bee health. In addition, \u003cem\u003eL. passim\u003c/em\u003e\u0026rsquo;s bee gut niche offers several parallels with the intracellular niche of \u003cem\u003eLeishmania \u003c/em\u003ein vertebrates (2,35). These include exposure to elevated temperatures similar to those of the mammalian bloodstream in honey bee colonies (36,37); and establishment in the acidic environment of the bee hindgut (38), where pH resembles that in the acidic phagolysosome colonized by \u003cem\u003eLeishmania \u003c/em\u003eamastigotes (39,40). Hence, its adaptations to this niche could provide insights into trypanosomatids\u0026rsquo; infection of mammals.\u003c/p\u003e\n\u003cp\u003eA recently published high-quality, chromosome-level assembly of the BRL type strain of \u003cem\u003eL. passim \u003c/em\u003e(41) represents a dramatic improvement over the draft genome published ten years prior, before the differentiation of \u003cem\u003eL. passim \u003c/em\u003efrom its relative \u003cem\u003eC. mellificae\u003c/em\u003e (42). To our knowledge, it represents the first chromosome-level assembly for a species in the Crithidiatae clade comprised of \u003cem\u003eLotmaria, Leptomonas, \u003c/em\u003eand \u003cem\u003eCrithidia \u003c/em\u003e(8); the first for a monoxenous species in the Leishmaniianae subfamily that includes the \u003cem\u003eLeishmania\u003c/em\u003e; and the second for a monoxenous trypanosomatid (after \u003cem\u003eAngomonas deanei \u003c/em\u003e(43)). This yielded a more complete understanding of the genome\u0026rsquo;s structure, while providing a framework to investigate the relationship between gene arrangement, expression, and function. One of the striking elements of the assembly was the presence of a paralogous chromosome pair represented by Chromosomes 5 and 6, the origins and significance of which remained unclear (41)\u003cem\u003e.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTo discover the distinguishing features of the \u003cem\u003eL. passim\u003c/em\u003e genome\u0026ndash; including its paralogous chromosome pair\u0026ndash; and their relevance to infection of honey bees, we compared the structure of the genome with that of related trypanosomatids, quantified spatial patterns of gene expression within and across chromosomes, and analyzed functional changes in gene expression of parasites in bee guts relative to cell cultures. Based on the structure of assemblies from other trypanosomatids, we expected that the genome would be characterized by long polycistronic gene blocks syntenic with those of relatives and linked to gene expression. As gene dosage is considered a means of adaptation to new environments, we predicted that the previously duplicated (now paralogous) chromosomes would be enriched in genes upregulated during bee infection. Given that this species attaches to the bee gut wall, we expected an upregulation of genes involved in adhesion during establishment in bees. Further, conditions in the bee gut mirror those encountered by \u003cem\u003eLeishmania \u003c/em\u003ein blood cells, we also predicted transcriptional similarities between cells in the bee gut and \u003cem\u003eLeishmania \u003c/em\u003eamastigotes (the mammal-associated life stage). Our results highlight the evolution of \u003cem\u003eL. passim\u003c/em\u003e\u0026apos;s two paralogous chromosomes and their orthology with \u003cem\u003eLeishmania \u003c/em\u003espp. supernumerary Chromosome 31. We also link genes on these chromosomes with infection of bees and point to the importance of attachment to host tissue in the parasite\u0026apos;s life cycle.\u003c/p\u003e"},{"header":"Methods","content":"\u003ch2\u003eSynteny analysis\u003c/h2\u003e\n\u003cp\u003eThe genome of the \u003cem\u003eL. passim\u003c/em\u003e BRL type strain (maintained in the American Type Culture Collection as isolate \u0026quot;PRA-422\u0026quot;, GenBank assembly GCA_037349495.1) was previously sequenced using a combination of Pac-Bio HiFi and Illumina Hi-C technologies, assembled to 31 nuclear chromosomes, and annotated with 10,288 genes (41).\u003c/p\u003e\n\u003cp\u003eConservation of gene order (synteny) between \u003cem\u003eL. passim \u003c/em\u003eand other Leishmaniianae species with high-quality assemblies (\u003cem\u003eLeptomonas seymouri\u003c/em\u003e; \u003cem\u003eCrithidia bombi\u003c/em\u003e,\u003cem\u003e C. expoeki,\u003c/em\u003e and \u003cem\u003eC. fasciculata\u003c/em\u003e; \u003cem\u003eLeishmania major\u003c/em\u003e and \u003cem\u003eL. braziliensis \u003c/em\u003e(Supplementary Table S1)) was quantified using SyMAP v5.9.9 (44). This analysis identifies synteny blocks with at least seven matched sequences of approximately collinear genes (allowing for inverted regions and some intervening non-aligned genes) as well as strictly collinear gene sets that contain neither gaps nor inversions. SyMAP raw data was exported and visualized using the R package \u003cem\u003ecirclize \u003c/em\u003e(45).\u003c/p\u003e\n\u003ch2\u003ePhylogenetic reconstruction\u003c/h2\u003e\n\u003cp\u003eTo define the phylogenetic relationships between \u003cem\u003eL. passim \u003c/em\u003eand other trypanosomatids, we constructed a tree based on predicted proteins from 14 \u003cem\u003eLotmaria, Leptomonas, Crithidia, \u003c/em\u003eand \u003cem\u003eLeishmania \u003c/em\u003especies in the Leishmaniianae subfamily (Supplementary Table S2). For species without publicly available annotations, we used those made in a previous phylogenomic analysis (8). Proteins were aligned using MAFFT through Orthofinder, resulting in 2663 shared single-copy orthologs from which a phylogenetic tree was inferred using the STAG method (46). Tree visualization was performed using R packages \u003cem\u003eape\u003c/em\u003e and \u003cem\u003eggtree \u003c/em\u003e(47,48).\u003c/p\u003e\n\u003ch2\u003eSpatial analysis of genes and gene expression\u003c/h2\u003e\n\u003cp\u003eTo quantify the spatial clustering of genes by strand within each chromosome, we created a matrix for all gene pairs and their distances apart along the chromosome. We used this to model the correlation between log\u003csub\u003e10\u003c/sub\u003e(pairwise distance) (included as both a linear and quadratic term) and the probability of genes being on the same strand using a binomial model with chromosome as a random effect. This and subsequent models were implemented in R version 4.4 using package \u003cem\u003eglmmTMB\u003c/em\u003e to construct models, \u003cem\u003ecar\u003c/em\u003e to evaluate significance of predictor terms, \u003cem\u003eemmeans\u003c/em\u003e to compute marginal means for different values of predictor variables, and \u003cem\u003eggplot2\u003c/em\u003e to visualize results (49\u0026ndash;52). We also used a binomial model to compare the proportion of features annotated as pseudogenes on the paralogous Chromosomes 5 and 6 vs the rest of the genome.\u003c/p\u003e\n\u003cp\u003eWe then combined our new genome annotation with publicly available transcriptomic data to examine chromosome-scale patterns of gene expression and up- and downregulation in honey bee hindguts relative to parasite cell cultures. The transcriptomic data (originally described in (33)) consisted of 30 samples from the type strain \u0026lsquo;SF\u0026rsquo; (ATCC isolate \u0026lsquo;PRA-403\u0026rsquo; (42)) grown in antibiotic-supplemented \u0026lsquo;FPFB\u0026rsquo; medium (53) and gut samples of parasite-inoculated honey bees (\u003cem\u003eApis mellifera\u003c/em\u003e) at 7, 12, 20, and 27 d post-inoculation \u003cem\u003e \u003c/em\u003e(n = 6 replicate libraries per group). Reads from the associated SRA files were mapped to the genome using the short reat alignment software \u003cem\u003eSTAR\u003c/em\u003e (54) and summarized by gene using \u003cem\u003efeatureCounts\u003c/em\u003e (55). Reads that mapped to multiple genes were fractionally distributed among each potential gene from which they could have originated. One of the replicates for the 7 d time point was excluded due to low read counts.\u003c/p\u003e\n\u003cp\u003eDifferential expression was analyzed using \u003cem\u003eDESeq2\u003c/em\u003e (56). Only genes covered by at least ten reads in at least five transcriptome libraries from each group were retained for further analysis, leaving 10100 genes of the original 10288 coding loci. Fractional counts were rounded to the nearest integer and normalized by library size (i.e., the total number of parasite-mapped counts). Differential expression in the bee gut relative to cell culture at each time point post-inoculation was assessed using negative binomial models with Benjamin-Hochberg correction for multiple testing within each time point. Variance-stabilized read counts, which approximate normalized read counts on the log\u003csub\u003e2 \u003c/sub\u003escale and have similar variance throughout the range of counts, were computed based on dispersion parameter estimates for negative binomial distributed data and were used as the response variable for analysis of spatial clustering in expression (56).\u003c/p\u003e\n\u003cp\u003eDifferences in proportions of differentially expressed genes between the paralogous chromosomes and the rest of the nuclear genome were evaluated using binomial models for five different differential expression categories: Significant (adjusted p-value \u0026lt; 0.05) upregulation, downregulation, or differential expression in either direction with respect to cultured cells; and strong (adjusted p-value \u0026lt; 0.05 and \u0026gt;2-fold change) up- and downregulation. Because the gene expression patterns within each chromosome were generally consistent across the four time points, we fit a single model for each expression category with chromosome type (Chromosomes 5 and 6 vs rest of genome) as a fixed predictor and time point as a random effect. We also compared the absolute expression level (measured as log\u003csub\u003e2\u003c/sub\u003e(transcripts per million (TPM), pooled across all libraries)) between genes on Chromosomes 5 and 6 vs. other chromosomes.\u003c/p\u003e\n\u003cp\u003eThe amount of variance in expression explained by same-stranded gene clusters of more than 10 consecutive genes was tested using linear mixed models. The response variable was the log\u003csub\u003e2\u003c/sub\u003e scale variance stabilized read count, corrected for gene length by dividing each count by the length of the corresponding gene and multiplying by the median gene length for the whole data set. We ran separate models with and without the genes with low read counts that were excluded from differential expression analyses, and a third model with log\u003csub\u003e2\u003c/sub\u003e(transcripts per million (TPM)) as the response variable. In each case, chromosomes and gene clusters were used as random effects, and a separate model was fit for each of the 5 treatment groups. The proportion of total variance in read counts explained by the random effects was extracted using the \u0026lsquo;extract_variance_components\u0026rsquo; function from R package \u003cem\u003emixedup\u003c/em\u003e (57).\u003c/p\u003e\n\u003cp\u003eCorrelations in absolute and differential expression between adjacent genes was modeled with expression of each focal gene as the response variable; expression of the preceding gene, whether or not the two genes were on the same strand of the chromosome, and their interaction as predictor variables; and chromosome as a random effect. Separate models were fitted using variance-stabilized read counts\u0026ndash; with and without low-count genes\u0026ndash; and TPM as response variables for absolute expression (as for strand-wise gene clusters above) and log\u003csub\u003e2\u003c/sub\u003e-fold change vs cultured cells for differential expression. A separate model was fit for each treatment group (for absolute expression) or time point (for differential expression). \u003c/p\u003e\n\u003ch2\u003eFunctional gene annotation and patterns of expression\u003c/h2\u003e\n\u003cp\u003eWe conducted functional analyses of changes in gene expression using Gene Set Enrichment Analysis (GSEA) of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) terms. Genes were assigned tentative GO terms by submitting the annotated protein sequences to the \u003cem\u003ePANNZER2\u003c/em\u003e server (58). Terms were filtered to retain only predictions with a positive prediction value of \u0026gt;0.5, resulting in annotations for 2,457 of the original 10,288 submitted sequences. Parent terms in the GO hierarchy implied by each prediction were added using the \u003cem\u003ebuildGOmap\u003c/em\u003e function of R package \u003cem\u003eClusterProfiler\u003c/em\u003e (59). The resulting set of terms was then filtered using \u003cem\u003eFunTaxIS-lite\u003c/em\u003e to remove terms unlikely to occur in trypanosomatids (60). Annotated genes were similarly assigned KEGG functions based on protein sequences and annotated to associated pathways using \u003cem\u003eBlastKOALA\u003c/em\u003e (61), which inferred KEGG terms for 2,693 of the submitted protein sequences. The resulting list of terms was filtered to retain only pathways annotated in reference kinetoplastid genomes present in the KEGG database.\u003c/p\u003e\n\u003cp\u003eGene set enrichment analysis was implemented in \u003cem\u003eClusterProfiler\u003c/em\u003e on all terms associated with at least 15 genes (62). Genes were ranked within each time point using the test statistic from the differential expression estimate for bee gut-derived relative to cultured cells (i.e., the ratio of the estimated log2-fold change to the standard error of the estimate) as the signal-to-noise ratio. These ranks were used to calculate an enrichment score and associated p-value for the gene set associated with each GO term or KEGG pathway, along with identification of the \u0026lsquo;leading edge\u0026rsquo; genes that contributed most strongly to each gene set\u0026rsquo;s pattern of differential expression (62). Finally, for the GO analysis, closely related terms with semantic similarity of 0.5 or higher were simplified to use only the term with the lowest p-value in each cluster of related terms (63). We discuss only gene sets with adjusted p-values \u0026lt;0.01.\u003c/p\u003e"},{"header":"Results and Discussion","content":"\u003ch2\u003eSynteny with divergence of the ancestrally tetrasomic chromosome\u003c/h2\u003e\n\u003cp\u003eThe \u003cem\u003eL. passim \u003c/em\u003enuclear genome was assembled to 31 chromosome-level scaffolds with telomeric repeats at their termini, along with the mitochondrial (kinetoplast) maxi- and minicircles typical of trypanosomatids. The genome assembly displayed a high degree of synteny with related species in the Leishmaniinae subfamily, supporting the phylogenetic placement of \u003cem\u003eL. passim \u003c/em\u003ewithin the \u003cem\u003eCrithidia/Leptomonas/Lotmaria \u003c/em\u003eclade (Figure 1, Figure 2). Synteny was highest with the close relative \u003cem\u003eLeptomonas pyrrhocoris\u003c/em\u003e, for which the \u003cem\u003eL. passim \u003c/em\u003egenome was 97% covered by 49 synteny blocks, including 62 sets of at least 20 collinear genes. However, synteny was also strong with \u003cem\u003eCrithidia bombi \u003c/em\u003e(87% across 71 blocks) and \u003cem\u003eC. fasciculata \u003c/em\u003e(92% across 57 blocks), and slightly lower but with fewer blocks for the chromosome-level assemblies of \u003cem\u003eLeishmania major \u003c/em\u003e(86%, 41 blocks) and \u003cem\u003eL. braziliensis \u003c/em\u003e(86%, 48 blocks) (Figure 2). In four cases (Chromosomes 1, 2, 4, and 13), \u003cem\u003eL. passim \u003c/em\u003echromosomes displayed synteny to multiple full chromosomes of \u003cem\u003eL. major \u003c/em\u003e(Figure 1)\u003cem\u003e. \u003c/em\u003eFor example, \u003cem\u003eL. passim \u003c/em\u003eChromosome 1 incorporated synteny blocks spanning \u003cem\u003eL. major\u003c/em\u003e Chromosomes 36 and 3,\u003cem\u003e \u003c/em\u003eparallel to the fusion of \u003cem\u003eL. major \u003c/em\u003eChromosomes 36 and 20 in \u003cem\u003eL. mexicana \u003c/em\u003e(19).\u003c/p\u003e\n\u003cp\u003eThe paralogous \u003cem\u003eL. passim \u003c/em\u003eChromosomes 5 and 6 showed substantially lower levels of synteny with homologous chromosomes in other species (Figure 2). Only around half the combined length of these chromosomes showed synteny with \u003cem\u003eC. bombi \u003c/em\u003eand \u003cem\u003eC. fasciculata \u003c/em\u003eand no synteny was detected with \u003cem\u003eC. expoeki \u003c/em\u003eor either species of \u003cem\u003eLeishmania\u003c/em\u003e, contrasting with the \u0026gt;80% synteny of the genome overall (of which Chromosomes 5 and 6 constitute ~12%) for each of these comparator species (Figure 2). However, each of Chromosomes 5 and 6 was syntenic with the tetrasomic scaffolds 12, 29, and 32 of the \u003cem\u003eL. pyrrhocoris \u003c/em\u003eassembly (Figure 3) (9,17), suggesting that these three scaffolds (ordered 32, 12, 29) comprise a single \u003cem\u003eL. pyrrhocoris \u003c/em\u003echromosome. These \u003cem\u003eL. pyrrhocoris \u003c/em\u003escaffolds were in turn syntenic with the ancestrally tetrasomic Chromosome 31 of \u003cem\u003eL. major\u003c/em\u003e, strongly suggesting that these \u003cem\u003eL. passim \u003c/em\u003echromosomes share ancestry with the \u003cem\u003eLeishmania \u003c/em\u003eChromosome 31. This synteny, however, was not inferred when comparing \u003cem\u003eL. passim \u003c/em\u003ewith \u003cem\u003eL. major \u003c/em\u003edirectly\u003cem\u003e \u003c/em\u003e(Figure 1)\u003cem\u003e. \u003c/em\u003eThese findings suggest that Chromosomes 5 and 6 have substantially diverged from their ancestral state in \u003cem\u003eL. passim \u003c/em\u003eand compared to the equivalent genomic regions of other monoxenous species.\u003c/p\u003e\n\u003cp\u003eThe combination of a high quality assembly and high nucleotide divergence between the two haplotype pairs (88.8% sequence identity) allowed us to distinguish two separate disomic chromosomes in \u003cem\u003eL. passim \u003c/em\u003e(Figure 1), which contrasts with the tetrasomy concluded for the other species (17,19). Nevertheless, divergence of these chromosomes is consistent with the high nucleotide diversity of the tetrasomic genome scaffolds within populations of \u003cem\u003eCrithidia, Leptomonas, \u003c/em\u003eand \u003cem\u003eLeishmania \u003c/em\u003erelatives (17). Additional haplotype-level sequences of this tetrasomic region in other trypanosomatids are needed to determine whether its assortment into two chromosome pairs is unique to \u003cem\u003eL. passim\u003c/em\u003e. However, analysis of the \u003cem\u003eL. major \u003c/em\u003eFriedlin genome found evidence for only 239 polymorphic sites on Chromosome 31 (64), suggesting \u0026gt;99.98% identity across haplotypes over this ~1.5 Mb\u003cem\u003e \u003c/em\u003eregion.\u003c/p\u003e\n\u003ch2\u003eStructural patterns of gene arrangement and transcription\u003c/h2\u003e\n\u003cp\u003eOur annotation of genes indicated the presence of long clusters of genes on the same strand that in some cases spanned entire chromosomes, consistent with the previously described organization of trypanosomatid genes in long polycistronic units (11). Adjacent gene pairs had a 97% chance of being located on the same strand; genes within 1 Kb of one another had a \u0026gt;90% chance of sharing a strand, and those within 10Kb a \u0026gt;80% chance (Supplementary Figure 1). The strand-wise arrangement of genes was conspicuously strong on the paralogous Chromosomes 5 and 6 (Figure 4), where essentially all (96%) of the annotated regions (including intact protein-coding genes as well as non-coding RNAs and predicted pseudogenes) were on the negative strand, consistent with annotations of the tetrasomic chromosomes with shared ancestry in other trypanosomatids (17,19).\u003c/p\u003e\n\u003cp\u003eWe used publicly available \u003cem\u003eL. passim \u003c/em\u003etranscriptomic data (33) in combination with our new chromosome-level genome assembly and its annotation to re-examine structural and functional patterns of gene expression during infection of honey bees. Roughly two-thirds of annotated genes were differentially expressed in bees vs. log-phase cell cultures at each of the four time points post-inoculation (Figure 5). The duplicated Chromosomes 5 and 6 were conspicuously enriched in genes upregulated in the bee gut environment, with higher probabilities of genes being upregulated and lower probabilities of genes being downregulated. Across all time points, genes on these two chromosomes were more than twice as likely to be upregulated by greater than two-fold relative to genes on other chromosomes (Figure 5). However, genes on the duplicated chromosomes were expressed at more than two-fold lower levels (i.e., fewer read counts) than those on other chromosomes (Supplementary Figure 2; Supplementary Figure 3), thereby compensating for the doubling of copy numbers resulting from chromosome duplication. A similar pattern, in which genes on the ancestrally tetrasomic chromosome are collectively expressed at similar levels to those on disomic chromosomes despite having twice as many copies, was likewise reported for the \u003cem\u003eLeishmania \u003c/em\u003eChromosome 31 (17). The paralogous chromosomes were also enriched in predicted pseudogenes, with a \u0026gt;50% increase in proportions of this feature type relative to the rest of the genome (Supplementary Figure 4).\u003c/p\u003e\n\u003cp\u003eWe also assessed spatial patterns of gene expression within chromosomes and their relationship to strand-wise gene arrays, which are canonically transcribed as a single polycistronic unit (11). We found weak but highly significant positive correlations between expression levels of adjacent genes in each sample group (e.g., ꭕ\u003csup\u003e2\u003c/sup\u003e\u003csub\u003e1\u003c/sub\u003e= 671, P \u0026lt; 0.001 for cell cultures with low-count genes excluded). However, the correlation between neighbors was stronger for neighboring genes on the same versus opposite strands of the chromosome, as evidenced by the significance of the neighbor expression x shared strand interaction term (e.g., ꭕ\u003csup\u003e2\u003c/sup\u003e\u003csub\u003e1\u003c/sub\u003e= 23.6, P \u0026lt; 0.001 for cell cultures, Figure 6). The fixed-effects model explained 5-10% of the variance in each sample group, suggesting a detectable signal of polycistronic transcription despite considerable post-transcriptional regulation of mRNA levels; this observation might be at least partly attributed to the origin of a portion of sequencing reads from precursor mRNAs. Same-stranded arrays of \u0026gt;10 consecutive genes explained 8-16% of variation in expression levels when modeled as a random effect, depending on whether genes with low read counts were excluded (Supplementary Figure 5). We also found positive correlations between differential expression of neighboring genes in bee guts vs. cell culture, although these were less pronounced than for absolute expression, and no significant difference was evident between gene pairs on the same vs. opposing strands (i.e., P \u0026gt; 0.05 for neighbor log\u003csub\u003e2\u003c/sub\u003e-fold change by shared strand interaction term, Supplementary Figure 6). The proportion of variance explained by the fixed effects model (comprising log\u003csub\u003e2\u003c/sub\u003e-fold change of the neighboring gene, whether neighbors were on the same strand, and their interaction) was \u0026lt;1% for every time point, indicating that differential expression of neighboring genes is only weakly interdependent.\u003c/p\u003e\n\u003ch2\u003eFunctional analysis of transcription\u003c/h2\u003e\n\u003cp\u003eWe used our annotation to analyze functional patterns of differential gene expression in the gut vs. cell culture environment using Gene Set Enrichment Analyses, which characterize the rank-based distribution of changes in expression level (relative to cultured cells) for the set of genes associated with each function-related term (62). Gene ontology (GO) term enrichment analyses were generally consistent across different time points post-inoculation, with many of the same terms occurring repeatedly among the most highly enriched gene sets (Figure 7). Most of the strong enrichment scores were associated with down-regulated gene sets. There was a general decrease in expression of gene sets encoding proteins of carbohydrate metabolism and ribosomal protein synthesis, consistent with adaptations to a low-nutrient environment in the bee hindgut. There was also a decrease in expression of gene sets involved in responses to oxidative stress and detoxification, possibly reflecting the relatively low oxygen levels in the gut or, alternatively, the fact that cultures were grown in antibiotic-enriched media. Upregulated gene sets annotated for metallopeptidase activity, exopeptidase activity, and amino acid metabolism were suggestive of a shift from carbohydrate- to amino acid-based metabolism, similar to changes reported in other trypanosomatids in the insect gut vs. rich culture media (65) and conclusions from the initial publication describing this dataset (33).\u003c/p\u003e\n\u003cp\u003eAt 7 d post-inoculation, we found downregulation of gene sets encoding proteins associated with the GO term \u0026lsquo;microtubule-based process\u0026rsquo;, with several flagellar proteins among the genes contributing to the downregulation. This pattern was consistent with observations of reduced flagella in attached haptomonad morphotypes carpeting the bee gut epithelium, as opposed to the freely swimming promastigotes found in log-phase cultures (66,67). This was followed by upregulation of the endomembrane system-associated gene set, suggesting reorganization of cellular structure and intracellular machinery as cells proliferated along the gut wall (Figure 7).\u003c/p\u003e\n\u003cp\u003eKyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was concordant with the GO analysis, indicating downregulation of gene sets related to protein synthesis, energy metabolism and glutathione-based antioxidant metabolism, and flagellar and motor proteins. This was countered by upregulation of gene sets related to amino acid metabolism (arginine biosynthesis; 2-oxocarboxylic acid metabolism; and alanine, aspartate, and glutamate metabolism; Figure 8). Upregulation of the autophagy-associated gene set at the first time point (7 d post-inoculation) was further suggestive of a nutrient-limited environment in the bee gut; this term was not highlighted by the original study\u0026rsquo;s GO term analysis (33). We also found upregulation of the gene set encoding proteins for variants of GP63/leishmanolysin\u0026ndash;a glycoprotein and peptidase involved in cell adhesion and cleavage of host effector proteins. The N-glycan biosynthesis-related gene set was likewise upregulated, which was not reported previously (33). Upregulated genes in this set included several glycosyltransferases, which catalyze the attachment and removal of sugar and acetylglucosamine groups from proteins (Supplementary Figure 7). Both GP63 and N-glycan biosynthesis gene sets are likely important for adherence to and interaction with host tissues or gut biofilms (13,14).\u003c/p\u003e\n\u003cp\u003eAttachment to the insect gut epithelium is a process common to most of the trypanosomatids, with cell surface proteins playing a key role in the process (13). In \u003cem\u003eC. fasciculata, \u003c/em\u003ewhich like \u003cem\u003eL. passim \u003c/em\u003eattaches to the hindgut wall and assumes a truncate morphology with a reduced flagellum, similar upregulation of GP63 proteins and genes involved in cell adhesion was observed during infection of mosquitoes as well as in adherent cultured cells (14). Given that the attachment process generally occurs on the time scale of hours rather than days (13), closer attention in the period immediately post-inoculation could provide greater insight into how \u003cem\u003eL. passim \u003c/em\u003egene expression changes during initiation of infection.\u003c/p\u003e\n\u003cp\u003eOverall, the functional patterns of differential expression bear strong similarity to those reported in other trypanosomatids during both insect and mammal infection. Transcriptomes of \u003cem\u003eHerpetomonas muscarum\u003c/em\u003e in \u003cem\u003eDrosophila \u003c/em\u003erelative to cell cultures likewise indicated a pattern of increased amino acid utilization and autophagy (68). Like the changes in \u003cem\u003eC. fasciculata \u003c/em\u003e(14), they also showed reduced expression of flagellum-related genes and increased expression of multiple GP63 peptidases as well as other proteins associated with the cell surface (68). In addition, post-inoculation upregulation of genes involved in DNA replication and repair in \u003cem\u003eH. muscarum \u003c/em\u003e(68) was concordant with the upregulation of gene sets annotated for nucleic acid catalytic and helicase activities in our GO term enrichment analysis. Beyond the insect gut, several aspects of \u003cem\u003eL. passim \u003c/em\u003egene expression in bees resembled those found in \u003cem\u003eLeishmania \u003c/em\u003especies\u003cem\u003e \u003c/em\u003ein the transition from the insect-associated promastigote form (in cell culture) to the amastigote form associated with vertebrate blood cells. These include down-regulation of gene sets associated with growth, carbon metabolism and flagellar motility; and upregulation of gene sets encoding peptidases and cell surface proteins (19,69). In light of these similarities, it is understandable how the same genes and related regions of the genome, such as the glycoprotein anchor and other surface protein-associated genes that are enriched on the ancestrally tetrasomic chromosome (17), could be important for both insect and vertebrate infection, and why this supernumerary region of the genome was enriched in genes upregulated during both \u003cem\u003eLeishmania \u003c/em\u003einfection of blood cells (19) and \u003cem\u003eL. passim \u003c/em\u003einfection of the bee gut described here. Maintaining and diversifying additional copies of such niche-specific, surface protein-encoding genes could enable parasites to continually evade recognition and subvert attack by current and novel hosts across evolutionary time.\u003c/p\u003e\n\u003cp\u003eThe most apparent fluctuations in differential expression across time points was found for gene sets annotated as components of the leishmaniasis and trypanosomiasis pathways, each of which appeared among the top up- or downregulated sets at different time points (Figure 8). Both terms describe genes involved in trypanosomatid infection of mammals, consisting mostly of host immune pathways along with a few parasite-derived virulence factors and immunomodulators. The leishmaniasis pathway gene set was down-regulated at 7 d, upregulated at 12 d, then downregulated again at 20 d post-inoculation. This reflected strong downregulation of cysteine peptidase B (CPB) at 7 d and 20d and downregulation of elongation factor 1-alpha (EEF1a) at 20 d, which was countered by strong upregulation GP63-family genes from 12 d onwards (Figure 9). The trypanosomiasis pathway gene set was downregulated at 7 d\u0026ndash; again reflecting downregulation of cysteine peptidase B (CPB)\u0026ndash; but upregulated at 12 and 20 d, reflecting increased expression of multiple paralogs of GP63 and thimet oligopeptidase (THOP1/tropolysin) (Figure 9). GP63 is noted for providing resistance to complement-mediated lysis in the bloodstream as well as to hydrolytic enzymes in the sand fly gut (15), whereas cysteine peptidase inhibits inflammatory signaling pathways (70)\u0026ndash; including the JAK-STAT pathway important for clearing infection with the trypanosomatid \u003cem\u003eH. muscarum\u003c/em\u003e in \u003cem\u003eDrosophila \u003c/em\u003e(71). Although both represent large protein families, this suggests that these genes could likewise protect parasites from host (bee) defenses or suppress their expression in response to infection. Indeed, very few changes in host gene expression occurred in \u003cem\u003eL. passim-\u003c/em\u003einoculated honey bees (33); only modest and transient upregulation of immune genes occurred in honey bees inoculated with \u003cem\u003eC. mellificae \u003c/em\u003e(72); and most bumble bee immune genes showed little induction following in inoculation with \u003cem\u003eC. bombi \u003c/em\u003e(73), with the most infectious stains eliciting the weakest expression of antimicrobial peptides (74).\u003c/p\u003e\n\u003cp\u003eScrutiny of genes involved in these pathways reflected both the structure of the genome and the limitations of the RNAseq analysis. Strings of paralogs generally appeared as tandemly arrayed genes along the chromosome, including 2 sets of 5 paralogs of GP63 on the Chromosomes 5 and 6 and over 30 consecutive paralogs of EEF1A on Chromosome 18 (Figure 9). Due to the sequence similarity among paralogs, sequencing reads could not be unambiguously assigned. These reads were distributed fractionally across each gene to which they aligned, resulting in read counts that were identical (or nearly so) among many spatially clustered paralogs, and non-independence of differential expression estimates for each one. This limitation in precision of mapping also likely inflated our estimates of correlations between transcript levels of neighboring genes (Figure 6).\u003c/p\u003e\n\u003cp\u003eAnother limitation of the functional analysis was the absence of annotations for a significant portion of the genes\u0026ndash; around three-fourths using our present method\u0026ndash; leaving changes that involve these loci uncharacterized. For example, we were able to identify only a few differentially expressed gene sets with \u0026gt;10% of the strongly contributing \u0026lsquo;leading edge\u0026rsquo; genes located on the paralogous chromosomes. All but one set (GO term \u0026lsquo;kinase activity\u0026rsquo;) was upregulated. Most were related to amino acid metabolism and peptidase activity, including \u0026lsquo;L-amino acid biosynthetic process\u0026rsquo;, \u0026lsquo;proteinogenic amino acid biosynthetic process\u0026rsquo;, \u0026lsquo;L-amino acid metabolic process\u0026rsquo;, \u0026lsquo;metallopeptidase activity\u0026rsquo;, and \u0026lsquo;exopeptidase activity\u0026rsquo; in the GO analysis; and \u0026lsquo;2-oxocarboxylic acid metabolism\u0026rsquo; and \u0026lsquo;arginine biosynthesis\u0026rsquo; in the KEGG analysis. The remaining upregulated sets were for the KEGG terms \u0026lsquo;RNA polymerase\u0026rsquo;, \u0026lsquo;trypanosomiasis\u0026rsquo;, and \u0026lsquo;leishmaniasis\u0026rsquo;; however, each of these included only two leading edge genes on the paralogous chromosomes.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eOur analysis leverages one of the first chromosome-level assemblies of an insect-specific trypanosomatid parasite of bees to illuminate the structural singularities of the genome and how they relate to gene expression, host infection, and parasite evolution. By linking the differentiation of an ancestrally tetrasomic region into two distinct, disomic chromosomes with the presence of genes upregulated in the honey bee host, our findings provide a fitness-related explanation for this salient genomic feature. Our transcriptomic analysis highlights shared patterns of gene expression across diverse trypanosomatids during host infection, as well as similarities between the functional changes that occur during infection of insects and vertebrates. The paralogous chromosomes, including genes for surface proteins that directly interface with hosts, appear to have disproportionate importance for establishment in both types of host. Hence, both elevated copy number and divergence of these chromosomes and their genes was likely advantageous in colonizing the diverse ecological niches occupied by trypanosomatids, including the hindgut of honey bees.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAcknowledgments\u003c/h2\u003e\n\u003cp\u003eThe authors thank Amanda Albanaz for proteome annotations of \u003cem\u003eCrithidia mellificae\u003c/em\u003e, \u003cem\u003eCrithidia bombi\u003c/em\u003e, and \u003cem\u003eCrithidia expoeki\u003c/em\u003e.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThis project was supported by U.S. Department of Agriculture National Institute of Food and Agriculture Grant 2020-67013-31861 to JDE and ECPY, U.S. Department of Agriculture National Institute of Food and Agriculture Postdoctoral Fellowship 2022-67012-37482 to ECPY, an Eva Crane Trust Grant to JDE and ECPY, and the U.S. Department of Agriculture Agricultural Research Service Beltsville Bee Research Laboratory in-house funds.\u003c/p\u003e\n\u003ch2\u003eData availability\u003c/h2\u003e\n\u003cp\u003eThe \u003cem\u003eL. passim\u003c/em\u003e BRL (2024) Hi-C and HiFi raw reads are available on NCBI GenBank (accession ID: SRX22798691 and SRX22798690); the assembled chromosomes (accession ID: GCA_037349495.1), maxicircle, and minicircles and annotation are listed under BioProject PRJNA1049372. The annotated genome is available on FigShare as a supplement to our previous article documenting the assembly (41) at https://doi.org/10.25387/g3.27121227 and will be added to the above BioProject pending acceptance by NCBI. RNA sequence data were used from NCBI BioProject PRJNA587465. The gene counts, GO terms assigned by Pannzer2, and KEGG terms assigned by BlastKOALA are provided as supplementary materials. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u003c/strong\u003e N/A\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication: \u003c/strong\u003eAll authors agreed to submission of the manuscript\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests: \u003c/strong\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions: \u003c/strong\u003eAN, JDE, and ECPY conceived the study. AN and ECPY analyzed the data with guidance from AB. ECPY wrote the first draft of the manuscript. All authors revised the manuscript. \u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMaslov DA, Vot\u0026yacute;pka J, Yurchenko V, Luke\u0026scaron; J. Diversity and phylogeny of insect trypanosomatids: all that is hidden shall be revealed. Trends Parasitol. 2013 Jan;29(1):43\u0026ndash;52.\u003c/li\u003e\n\u003cli\u003eLuke\u0026scaron; J, Skalick\u0026yacute; T, T\u0026yacute;č J, Vot\u0026yacute;pka J, Yurchenko V. Evolution of parasitism in kinetoplastid flagellates. Mol Biochem Parasitol. 2014 Jul 1;195(2):115\u0026ndash;22.\u003c/li\u003e\n\u003cli\u003eLuke\u0026scaron; J, Butenko A, Hashimi H, Maslov DA, Vot\u0026yacute;pka J, Yurchenko V. Trypanosomatids Are Much More than Just Trypanosomes: Clues from the Expanded Family Tree. Trends Parasitol. 2018 Jun 1;34(6):466\u0026ndash;80.\u003c/li\u003e\n\u003cli\u003eMcGwire BS, Satoskar AR. 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Immune gene expression in \u003cem\u003eBombus terrestris\u003c/em\u003e : signatures of infection despite strong variation among populations, colonies, and sister workers. PLOS ONE. 2013 Jul 15;8(7):e68181.\u003c/li\u003e\n\u003cli\u003eBarribeau SM, Sadd BM, du Plessis L, Schmid-Hempel P. Gene expression differences underlying genotype-by-genotype specificity in a host\u0026ndash;parasite system. Proc Natl Acad Sci. 2014 Mar;111(9):3496\u0026ndash;501.\u003c/li\u003e\n\u003cli\u003eSchmid-Hempel P, Aebi M, Barribeau S, Kitajima T, Plessis L du, Schmid-Hempel R, et al. The genomes of Crithidia bombi and C. expoeki, common parasites of bumblebees. PLOS ONE. 2018 Jan 5;13(1):e0189738.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-genomics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"gics","sideBox":"Learn more about [BMC Genomics](http://bmcgenomics.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/gics","title":"BMC Genomics","twitterHandle":"#BMCGenomics","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"aneuploidy, trypanosomatid ancestral supernumerary chromosome (TASC), gene duplication, phylogenomics, polycistronic genome organization, post-transcriptional gene regulation, differential expression, host-parasite interactions, Crithidia","lastPublishedDoi":"10.21203/rs.3.rs-5989240/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5989240/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground. \u003c/strong\u003eThe protist family Trypanosomatidae includes parasites of insects, vertebrates, plants, and even other unicellular eukaryotes. The genomes of these species harbor clues to the evolution of parasitism, adaptation to novel hosts, and infection of mammals. We present an analysis of a chromosome-level genome assembly of\u003cem\u003e Lotmaria passim\u003c/em\u003e, the most prevalent known trypanosomatid of honey bees, linking genome sequence and organization to gene expression and infection of bees.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults. \u003c/strong\u003eThe genome showed high synteny with assemblies of other trypanosomatids and especially closely related \u003cem\u003eLeptomonas pyrrhocoris\u003c/em\u003e relatives. It included four copies of chromosomes that shared ancestry with the tetrasomic \u003cem\u003eLeishmania \u003c/em\u003eChromosome 31 and are consistently supernumerary throughout Trypanosomatidae. However, these chromosomes showed lower similarity to \u003cem\u003eL. passim \u003c/em\u003erelatives than did the genome overall, with sufficient variation across haplotypes to distinguish two separate disomic chromosomes. Transcriptomic analyses showed that these chromosomes are enriched in genes upregulated during bee infection, and each include five paralogs of the GP63 gene implicated in infection of both insects and mammals. Patterns of expression in bees suggested decreased protein synthesis, a shift from carbohydrate- to amino acid-based metabolism, and reduced cell motility in bee guts versus cell culture. In contrast, genes involved in cell adhesion were upregulated, consistent with the importance of attachment to insect tissue in this species and the family overall.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions. \u003c/strong\u003eOur analysis links differentiation of a conserved supernumerary chromosome with infection of bees, parallel tothis chromosome’s role in \u003cem\u003eLeishmania \u003c/em\u003einfection of mammals and linking chromosome-level changes with adaptation to new hosts.\u003c/p\u003e","manuscriptTitle":"Chromosome-level genome assembly of trypanosomatid parasite Lotmaria passim links chromosome duplication and divergence with infection of honey bees","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-02-12 07:09:58","doi":"10.21203/rs.3.rs-5989240/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-03-20T16:19:10+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-03-14T22:45:24+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-03-09T17:56:36+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"58001753687557924649054936573212808429","date":"2025-02-24T18:33:54+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"244688559785249616775453338438456860701","date":"2025-02-24T17:59:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"339814700760957636900020502732988799509","date":"2025-02-24T15:07:43+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-02-24T14:56:02+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-02-24T12:18:24+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-02-13T05:36:10+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-02-11T05:20:28+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Genomics","date":"2025-02-08T17:51:24+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-genomics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"gics","sideBox":"Learn more about [BMC Genomics](http://bmcgenomics.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/gics","title":"BMC Genomics","twitterHandle":"#BMCGenomics","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1c44fd18-bc90-48bf-886f-bc7b4f4633df","owner":[],"postedDate":"February 12th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-08T16:06:02+00:00","versionOfRecord":{"articleIdentity":"rs-5989240","link":"https://doi.org/10.1186/s12864-025-12082-y","journal":{"identity":"bmc-genomics","isVorOnly":false,"title":"BMC Genomics"},"publishedOn":"2025-12-01 15:57:50","publishedOnDateReadable":"December 1st, 2025"},"versionCreatedAt":"2025-02-12 07:09:58","video":"","vorDoi":"10.1186/s12864-025-12082-y","vorDoiUrl":"https://doi.org/10.1186/s12864-025-12082-y","workflowStages":[]},"version":"v1","identity":"rs-5989240","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5989240","identity":"rs-5989240","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}