Identification of ambisense kolmioviruses

Identification of ambisense kolmioviruses | bioRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (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];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-M677548'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results Identification of ambisense kolmioviruses View ORCID Profile Mai Kishimoto , Sakiho Imai , Manabu Igarashi , View ORCID Profile Masayuki Horie doi: https://doi.org/10.1101/2025.01.08.631871 Mai Kishimoto 1 Laboratory of Veterinary Microbiology, Graduate School of Veterinary Science, Osaka Metropolitan University , Izumisano, Osaka, Japan 2 Osaka International Research Center for Infectious Diseases, Osaka Metropolitan University , Osaka, Japan 3 School of Veterinary Science, College of Life, Environment, and Advanced Science, Osaka Prefecture University , Izumisano, Osaka, Japan Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Mai Kishimoto For correspondence: m.kishimoto{at}omu.ac.jp mhorie{at}omu.ac.jp Sakiho Imai 3 School of Veterinary Science, College of Life, Environment, and Advanced Science, Osaka Prefecture University , Izumisano, Osaka, Japan Find this author on Google Scholar Find this author on PubMed Search for this author on this site Manabu Igarashi 4 Division of Global Epidemiology, International Institute for Zoonosis Control, Hokkaido University , Sapporo, Hokkaido, Japan 5 International Collaboration Unit, International Institute for Zoonosis Control, Hokkaido University , Sapporo, Hokkaido, Japan Find this author on Google Scholar Find this author on PubMed Search for this author on this site Masayuki Horie 1 Laboratory of Veterinary Microbiology, Graduate School of Veterinary Science, Osaka Metropolitan University , Izumisano, Osaka, Japan 2 Osaka International Research Center for Infectious Diseases, Osaka Metropolitan University , Osaka, Japan 3 School of Veterinary Science, College of Life, Environment, and Advanced Science, Osaka Prefecture University , Izumisano, Osaka, Japan Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Masayuki Horie For correspondence: m.kishimoto{at}omu.ac.jp mhorie{at}omu.ac.jp Abstract Full Text Info/History Metrics Supplementary material Preview PDF Abstract Viruses in the family Kolmioviridae (KoVs) are unique among RNA viruses in that they have small, highly self-complementary, circular, negative-sense genomes and are satellite viruses requiring the envelope protein of co-infected helper viruses to form infectious virions. For approximately 40 years, only hepatitis D virus (HDV) had been identified, but recent studies have uncovered novel KoVs in diverse animal species. Serinus canaria-associated deltavirus (scKoV) was recently identified form a single RNA-seq data from canary skin. However, only the partial genome sequence corresponding to the transcript encoding DAg has been identified, leaving questions regarding its full genetic composition and origins. In this study, we examined publicly available RNA-seq data and identified multiple complete genome sequences of scKoV. Our results demonstrated that genetically diverse scKoVs infect multiple bird species with recent inter-order transmission. Additionally, scKoV was detected in various tissues including parenchymal organs, suggesting that scKoV is a genuine avian KoV. Notably, analysis of the genome structure and transcriptional pattern clearly revealed that scKoV transcribes a genomic-sense mRNA encoding a novel gene, in addition to the previously known antigenomic-sense DAg transcript. Furthermore, this newly identified gene appears to express two protein isoforms via alternative splicing. These findings mark the first KoV with an ambisense genome that utilizes alternative splicing, which may represent a strategy to increase gene-coding capacity despite the constraints imposed by its small and self-complementarity genome. Moreover, co-infection with avian bornaviruses was detected in most scKoV-positive RNA-seq datasets, suggesting that avian bornaviruses are candidate helper viruses for scKoV. In conclusion, our study on scKoV provides novel insights into the evolution and diversity of KoVs. 1. Introduction The family Kolmioviridae (KoVs), recently established in the realm Ribozyviria , consists of RNA viruses with negative-stranded circular genomes of approximately 1.5-1.7 kb ( 1 ). A representative KoV is human hepatitis D virus (HDV), which was first reported in 1977 ( 2 ). After the discovery of HDV, no other related viruses were detected for approximately 40 years. However, since 2018, many viruses related to HDV have been discovered in various vertebrates and invertebrates, and currently, KoVs spanning 11 genera, along with additional unassigned viruses, have been identified ( 1 , 3 – 8 ). KoVs share unique features markedly different from other typical RNA viruses (RNA viruses in the kingdom Orthornavirae of the realm Riboviria ) in terms of their genomes, replication, and transmission. The KoV genome is viroid-like, circular, and single-stranded RNA that exhibits high self-complementarity, forming a rod-like structure ( 3 – 9 ). Unlike other RNA viruses, KoVs only encode the delta antigen (DAg), a nucleocapsid-like protein, and lacks RNA-dependent RNA polymerase, a hallmark of RNA viruses. Consequently, KoVs replicate in the cell nucleus depending on the host DNA-dependent RNA polymerase (DdRp). This unique replication occurs though a rolling-circle replication, utilizing the autocatalytic reaction of ribozymes present in the KoV genome and antigenome. ( 10 , 11 ). As KoVs encode only DAg, and lack proteins required for the formation of virus particles, they rely on the envelope proteins of co-infecting “helper” viruses to produce infectious virions. Thus, KoVs are classified as “satellite” viruses ( 5 , 12 , 13 ). KoVs may utilize unique coding strategies to provide proteins essential for replication, given the constraints of their small, highly self-complementary genomes. HDV expresses two isoforms of the DAg, known as small and large DAg (S-HDAg and L-HDAg), through A-to-I RNA editing, which is mediated by the host enzyme ADAR1 and modified the stop codon of S-HDAg ORF ( 14 – 17 ). As a result, L-HDAg contains a 19-amino-acid extension at its C-terminus that includes a nuclear export signal ( 18 ) and a farnesylation site which is required to interact with helper virus envelope proteins ( 19 ). HDV utilizes these two isoforms to finely regulate genome replication and virion formation. Although this RNA editing mechanism has only been observed in HDV, other KoVs might employ different strategies to expand their coding capacity. For example, Swiss snake colony virus 1 was reported to express two isoforms of DAg, although the underlaying mechanisms remain unclear ( 20 ). Further, several KoVs, such as DrDV-B, possess additional relatively long ORFs in their genomes ( 5 , 21 ). However, these ORFs have yet to be shown to be expressed as mRNA, and there is no evidence that they are functional viral genes. The Serinus canaria-associated deltavirus (following the establishment of the family Kolmioviridae , we designates it as Serinus canaria-associated kolmiovirus [scKoV]) was recently identified through large-scale analysis of publicly available RNA-seq data, but its characteristics are largely unclear ( 3 ). In the previous study, only partial sequences corresponding to the transcript encoding DAg were identified. However, the rapid increase in publicly available RNA-seq data offers an opportunity to identify the complete viral genome and conduct more detailed analyses ( 22 ). Further, scKoV was suspected to have originated from contaminants in the previous study, as it was only detected in a single RNA-seq dataset from canary skin and is genetically distinct from viruses of the genus Perithurisazvirus , authentic avian KoVs ( 3 ) ( Fig. 1 ). Thus, reanalyzing scKoV with the ever-increasing RNA-seq data may help clarify its origin. Download figure Open in new tab Fig. 1 Phylogenetic relationships of kolmioviruses. The phylogenetic tree was inferred by the Bayesian Markov chain Monte Carlo method based on an amino acid sequence alignment of DAg. Posterior probabilities are shown for all nodes. Figure arts were created with BioRender.com or downloaded from https://www.phylopic.org/ . The scale bar indicates the number of amino acid substitutions per site. In this study, we analyzed public RNA-seq data and identified multiple complete genome sequences of scKoV. We provided strong evidence that scKoV is an authentic avian virus. Further, we showed that scKoV transcribes a genomic-sense mRNA that encodes a novel gene (ORF2) in addition to the well-known antigenomic-sense mRNA encoding DAg. We also revealed that the ORF2 gene appears to express two protein isoforms via alternative splicing. Our findings highlight an adaptive strategy by which KoVs maximize their gene-coding capacity under the constraints of their small and highly self-complementary genomes. 2. Results 2.1. scKoV-derived reads were identified in multiple bird public RNA-seq datasets As described above, the previous study detected scKoV in only one RNA-seq dataset. To further identify scKoV-positive RNA-seq datasets, we mapped 15,452 publicly available bird RNA-seq datasets to the partial sequence of scKoV (BR001664.1). A total of 66 RNA-seq datasets were found to contain scKoV-derived reads, including the dataset in which scKoV was initially identified in the previous study (Tables 1 and S1). The scKoV-reads were found in four bird species: the common canary ( Serinus canaria [Linnaeus, 1758]), European serin ( Serinus serinus [Linnaeus, 1766]), and house finch ( Haemorhous mexicanus [Statius Müller, 1776]) in the order Passeriformes and monk parakeet ( Myiopsitta monachus [Boddaert, 1783]) in the order Psittaciformes . The scKoV-positive RNA-seq datasets were distributed across five BioProjects deposited by four independent research groups (PRJNA300534 and PRJNA591356 were deposited by the same group), suggesting that the scKoV-positive birds originated from diverse sources. The scKoV-positive RNA-seq datasets were derived not only from skin samples but also in various tissues including fat tissue, blood, brain, lung, and ovary. This strongly suggests that scKoV is not a result of body-surface contamination but likely infects birds, potentially causing systemic infection and/or viremia. These findings indicate that scKoV circulates among a broad range of avian hosts, spanning different taxonomic orders. 2.2. The complete genome sequences of scKoV were identified To obtain complete genome sequences of scKoV, each scKoV-positive RNA-seq dataset was assembled. Among the resultant contigs, six contigs were identified as potential complete scKoV genome sequences. Self-dotplot analyses revealed identical sequences at both ends of each contig (Fig. S1), suggesting that they are circular contigs. We mapped the original RNA-seq datasets back to the circularized contigs, confirming that multiple reads spanned the junctions appropriately. These data strongly suggest that the contigs are indeed circular genomes. To obtain additional complete scKoV genomes, we mapped scKoV-positive RNA-seq datasets, from which no complete scKoV genomes had been obtained above, to the circularized complete genomes of scKoV and extracted the consensus sequences. As a result, a total of 16 complete scKoV genomes were reconstructed from the RNA-seq datasets of S. canaria , H. mexicanus , and M. monachus ( Table 1 ). Notably, by this mapping-based method, we succesfully recovered the complete scKoV genome from the RNA-seq datasets where only the partial sequence had been initially reported in the previous study ( 3 ). View this table: View inline View popup Download powerpoint Table 1. Detection of scDeV reads in public RNA-seq data 2.3. Genetically diverse scKoV circulate among multiple bird species To elucidate the evolutionary relationships among scKoVs, we performed a phylogenetic analysis using the complete nucleotide sequences of scKoV genomes. The resulting phylogenetic tree showed three distinct clusters of scKoVs, designated as genotype 1, 2, and 3 ( Fig. 2A ). The genotype 1 included scKoVs identified in all the three bird species ( S. canaria , H. mexicanus , and M. monachus ), while the genotypes 2 and 3 were exclusively found in scKoVs from S. canaria and M. monachus , respectively. Pairwise nucleotide sequence comparisons revealed high nucleotide sequence identities (>95%) within each genotype, whereas inter-genotype nucleotide sequence identities were <84% between genotypes 1 and 2, <83% between genotypes 1 and 3, and <89% between genotypes 2 and 3 ( Fig. 2B ). Download figure Open in new tab Fig. 2 Phylogenetic analysis based on nucleotide sequences of complete scKoV genomes. ( A ) The phylogenetic tree was inferred by the maximum likelihood method using nucleotide sequences of complete scKoV genomes. Bootstrap values are indicated at each branch. The BioProjects of each SRA data that scKoV sequences originated are indicated with dark blue, blue, light blue, and red circles, respectively. The scale bar indicates the number of nucleotide substitutions per site. ( B ) Heat map of pairwise identities of scKoV variants based on nucleotide sequences of complete genomes (lower left) and amino acid sequences of DAg (upper right). ( C ) Detection of mixed infections with scKoV of different genogroups. For BioProject PRJNA679636, their tissue of origin is indicated. We also obtained data indicating that multiple genotypes of scKoV existed within individual hosts. For example, all scKoV-positive RNA-seq datasets from BioProject PRJNA679636 originated from a single individual ( 23 ), and both genotypes 1 and 3 were detected within these datasets ( Table 1 ). We thus investigated whether multiple genotypes of scKoV coexisted within each scKoV-positive sample. The scKoV-positive RNA-seq datasets from BioProjects PRJNA591356, PRJNA939570, and PRJNA679636 were mapped to the genomes of distinct genotypes detected within the same BioProjects in a manner that ensures unique alignment to the best match. The results indicated the coexistence of two genotypes of viruses within individual RNA-seq data in varying ratios, with some data showing nearly a 1:1 ratio of mixed genotypes ( Fig. 2C ). Apparently, these RNA-seq data were not derived from pooled samples of multiple individuals based on the available metadata and literatures. Taken together, these findings suggest that multiple genotypes of scKoV circulate among the birds and may occasionally cause mixed infections. 2.4. scKoV potentially infects to various tissues To understand the tissue tropism of scKoV, we analyzed the number of scKoV-derived reads across the scKoV-positive RNA-seq datasets from BioProject PRJNA679636, which were derived from various tissues of a single individual ( 23 ). The reads per million (RPM) of scKoV was highest in the brain (264.1 RPM in the forebrain and 121.9 RPM in the cerebellum), followed by the lung (164.1 RPM) and ovary (77.3 RPM), while only a small number of scKoV reads were detected in the liver (0.2 RPM) and muscle (5.5 RPM) (Tables 1 and S1 and Fig. 2C ). Moderate amounts of scKoV reads were detected in the kidney (25.2 RPM), heart (22.7 RPM), and spleen (21.8 RPM). These results suggest that scKoV infects a broad range of tissues. 2.5. scKoV exhibits ambisense gene coding and utilizes alternative splicing We next characterized the genome structures of scKoV, revealing that the typical characteristics of KoVs are conserved in scKoVs as follows. The scKoV genomes were approximately 1,670 bp in length, with a GC content of approximately 55%, consistent with other KoV members ( 3 – 8 ). The high self-complementarity of the circular genome, a typical feature of KoVs, was also conserved in scKoV ( Figs. 3A and S2). The relative positions of the DAg-encoding ORF, the downstream poly-A signal, and both the genomic and antigenomic ribozymes were consistent with those of other typical KoVs ( Fig. 3B ). Additionally, the predicted scKoV ribozymes exhibit the conserved HDV ribozyme class, unlike toad and termite KoVs, which retain type III hammerhead ribozymes ( 24 ) ( Figs. 3C and S3). The ribozymes of scKoV contain sequence variations, but these are expected to have minimal effects on their secondary structures (Fig. S3). Download figure Open in new tab Fig. 3 Genome organization and transcriptional pattern of scKoV. ( A ) Self-complementarities of scKoV. The predicted RNA structures were visualized using the Mfold web server ( 56 ). (B) Genome organization of scKoV. Colored arrows indicate annotations (ORFs, ribozymes, and poly-A signals). The numbers indicate nucleotide positions. ( C ) Predicted genomic and antigenomic structures of scKoV. Gray numbers indicate nucleotide positions of each predicted ribozyme. The names of secondary structural elements of ribozymes are indicated in blue. Red triangles indicate catalytic sites. Information of SRR10526804 is indicated as a representative. Information about other variants is provided in Figs. S2, S3, and S4. ( D ) Strand-specific mapping coverage of original short reads of scKoV full-genome sequence. Colored arrows indicate annotations (ORFs, ribozymes, poly-A signals). Light pink box indicates putative intron. Green triangle indicates edge of the rod-like structure of circulated scKoV genome. Information of SRR10526804 is indicated as a representative. Information about other variants is provided in Fig. S5. ( E ) Secondary structures and expanded mapping patterns of the putative promoter regions of scKoV. Conserved domains were annotated as previously reported ( 25 ). ( F ) Nucleotide alignment of predicted intron region using representative variants of scKoV in each genotype. Dots indicate common bases in the alignment. Gray and blue box indicate conserved GU-AG boundary and polypyrimidine tract, respectively. Gray numbers indicate nucleotide position in alignment of full-genome sequences. Notably, two additional ORFs (tentatively named ORF2 and ORF3) were identified on both the genomic- and antigenomic-senses, respectively, which were located in the self-complementary region of the DAg ORF ( Figs. 3A and 3B ). ORF2 is conserved in all scKoVs, whereas ORF3 is absent in one virus (BR002468.1, assembled from SRR13480248) (Fig. S4). Moreover, an additional poly-A signal was located immediately downstream of ORF2 ( Fig. 3B ). To elucidate the transcriptional patterns of scKoVs, we mapped scKoV-positive RNA-seq datasets to the corresponding viral genomes. The results exhibited a bimodal mapping pattern (Fig. S5), suggesting the presence of a novel transcript in addition to the one encoding DAg. To further characterize the putative novel transcript, we mapped strand-specific RNA-seq datasets (BioProjects PRJNA591356 and PRJNA939570) to the corresponding viral genomes. The mapping patterns clearly indicated the presence of a genomic-sense transcript encoding ORF2, as well as the typical antigenomic-sense transcript encoding DAg ( Figs. 3D and S5). The boundary between the genomic and antigenomic transcripts was estimated to be located at the edge of the rod-like structure of the scKoV genome, which is thought to function as a transcriptional promoter ( 25 ). The edge of the rod in scKoV largely retained the conserved domains previously reported in HDVs (Fig. S6) ( 25 ). Furthermore, based on the mapping patterns of the RNA-seq data in BioProject PRJNA591356, the transcription start sites of the genomic- and antigenomic-sense transcripts were predicted to be located between the internal and external bulges of the rod edge ( Fig. 3E ). These data strongly suggest that scKoV expresses a genomic-sense transcript encoding ORF2. The mapping results also showed several putative splicing junctions. Among them, the one located in the genomic-sense ORF2 transcript is prominent and reliable, as a large number of reads consistently spanned the junction across all the RNA-seq data ( Figs. 3D and S5). The putative intron retains the typical features of major eukaryotic introns, including the GU-AG motifs of donor/acceptor sites and a polypyrimidine tract present upstream of the AG motif at the end of the intron ( Fig. 3F ) ( 26 ). Notably, the spliced ORF2 transcript encodes a protein that differs from the unspliced ORF2 transcript in its C-terminal region ( Fig. 3D and Table S2). To investigate the function of the putative proteins translated from unspliced and spliced ORF2 transcripts (designated ORF2a and ORF2b, respectively), we first performed sequence similarity searches. However, neither protein showed sequence similarity to any known protein. Additionally, no significant biases in hydrophobicity or polarity were observed (Figs. S7A and S7B). We also carried out a series of in silico analyses, including functional domain searches, predictions of topological structures, nuclear localization signals, and transmembrane domains (Fig. S7C), but could not find any functional domains. An intrinsically disordered region was identified exclusively in the C-terminal third of the ORF2b (Fig. S7D). Additionally, structural predictions indicated that the N-terminus of the ORF2 protein forms a well-defined helical structure, whereas the C-terminus of the ORF2 lacks a defined structure (Fig. S7E). These findings suggest that scKoV expresses genomic-sense transcripts encoding proteins of unknown function. 2.6. No evidence for RNA-editing was found on the stop codon of DAg HDV utilizes the host A-to-I RNA editing machinery at the stop codon of DAg to express the larger isoform of DAg protein. To investigate whether scKoV also employs A-to-I RNA editing, we analyzed nucleotide variations at the stop codons of each ORF using the mapping data. Base variations (A-to-G or T-to-C), potentially resulting from A-to-I editing of the genome or antigenome, were observed in 11 out of the 16 mapping datasets (Table S3). However, except for SRR23747114, the stop codons of the extended DAg ORFs, generated by the cancellation of the original stop codon through A-to-I RNA editing, were located downstream of the poly-A signal (Fig. S8). These results suggest that scKoV is unlikely to utilize host A-to-I RNA editing to produce DAg proteins of different lengths. 2.7. Avian bornaviruses are the candidate helper virus for scKoV To gain insights into potential helper viruses for scKoV, we searched for co-existing viruses in the scKoV-positive RNA-seq datasets. BLAST searches using the assembled contigs revealed that contigs derived from avian bornaviruses (ABVs), canary bornavirus 1 and 3 (CnBV-1 and -3) and parrot bornavirus 2 (PaBV-2) (the genus Orthobornavirus of the family Bornaviridae ) were detected in 64 out of 66 scKoV-positive datasets ( Figs. 4A and S9). CnBV-1 and 3 were detected in the RNA-seq datasets from S. canaria , S. serinus , and H. mexicanus (the order Passeriformes ), while PaBV-2 was detected in the data from M. monachus (the order Psittaciformes ). No other enveloped viruses were identified. We also analyzed the correlation between their read counts. As a result, the RPMs of scKoV and ABVs showed a weak positive correlation ( Fig. 4B ). These results suggest that scKoV may utilize co-infecting ABVs as helper viruses. Download figure Open in new tab Fig. 4 Co-existing viruses in scKoV-positive RNA-seq data. ( A ) Co-existing avian bornaviruses (ABVs) (left panel) and scKoV-derived read number (right panel) detected from each RNA-seq dataset are shown. Black indicates the presence of a viral contig, while white indicates its absence. Read per million (RPM) of scKoV is shown as a heatmap. Results from RNA-seq data with scKoV RPM ≥ 5 are shown. Full information is available in Fig. S8. ( B ) Scatter plot showing RPM of scKoV and ABVs of each RNA-seq data. The linear prediction is shown as a dotted line. The correlation coefficient (R 2 ) of the linear prediction is shown on the graph. 2.8. Other possible ambisense kolmioviruses We investigated whether any known KoVs exhibit ambisense gene expression. Among the KoVs with genome sequences deposited in GenBank or reported by the Serratus project ( 27 ), six additional KoVs possessed genomic-sense ORFs upstream of poly-A signals ( Figs 5A , 5B , and S10). Of these, Amboli leaping frog ( Indirana chiravasi ) kolmiovirus (icKoV) and Babylonia areolata KoV (baKoV) displayed clear bimodal transcription patterns ( Figs.5C and S10). Furthermore, for icKoV, the closest relative of scKoV, mapping of the strand-specific RNA-seq dataset (SRR8954567) revealed transcripts derived from both the genome and antigenome strands, like the pattern observed in scKoV ( Fig. 5C ). However, unlike scKoV, icKoV lacks clear alternative splicing site. The icKoV ORF2 showed 36.6% amino acid sequence identity with scKoV ORF2a, and sequence alignment revealed the N-terminal 80 residues are relatively well conserved ( Fig. 5D ). Download figure Open in new tab Fig. 5 identification of other potential ambisense KoV. (A) Phylogenetic tree of all known KoVs. The tree was inferred by the Bayesian Markov chain Monte Carlo method based on an amino acid sequence alignment of DAg. Posterior probabilities are shown for all nodes. The scale bar indicates the number of amino acid substitutions per site. KoVs with potential ambisense genome structures are shown in blue, and those with confirmed ambisense transcription patterns are shown in red. ( B ) Genome organization of Amboli leaping frog KoV (icKoV). Colored arrows indicate annotations (ORFs, ribozymes, and poly-A signals). The numbers indicate nucleotide positions. ( C ) Strand-specific mapping coverage of original short reads of icKoV. Colored arrows indicate annotations (ORFs, ribozymes, poly-A signals). Green triangle indicates edge of the rod-like structure of circulated scKoV genome. ( D ) Amino acid alignment of scKoV ORF2a and icKoV ORF2. Identical amino acid residues are highlighted in black, similar substitutions in grey, and gaps are shown as dashes. For other potential ambisense KoVs, mapping patterns did not exhibit a clear bimodal distribution (Fig. S10), suggesting that these ORFs may not be transcribed. As those RNA-seq libraries were prepared via rRNA depletion rather than poly-A enrichment, we cannot exclude the possibility that the data do not accurately reflect transcription. In addition, in DrDV-B, the ORF2 start codon is not conserved across all viral strains (Fig. S11A). These genomic-sense ORFs also lack similarity in both secondary and 3D structure to scKoV ORF2 (Figs. S11B and S11C), implying that they may not encode conserved genes. These results suggest that the ambisense genome structure may be conserved among closely related species of scKoV. 3. Discussion Although many novel KoVs have been identified recently, the diversity of KoVs remains unclear since some KoVs have not yet been characterized well. We previously identified scKoV from a single canary RNA-seq datasets, which is distantly related to the other avian KoVs, but only a partial sequence corresponding to the DAg mRNA had been identified. In this study, we identified the complete genome sequences of scKoV and revealed its unique genetic features among KoVs. Notably, we showed a series of evidence strongly suggesting that scKoV expresses genomic-sense transcripts encoding proteins of unknown function, designated ORF2, besides the antigenomic-sense transcript encoding DAg ( Figs. 3B and 3D ). Although KoVs are currently classified as negative-strand RNA viruses, our findings strongly suggest that scKoV is an ambisense virus. Furthermore, our data indicate that the genomic-sense transcript undergoes alternative splicing, potentially encoding two ORF2 protein isoforms. Therefore, scKoV employs a unique strategy to maximize its coding capacity under the constraints of its small and self-complementary circular genome. Our results strongly suggest that the promoter of scKoV could initiate bidirectional transcription. HDV transcribes mRNA using the host DdRp, with the rod-like edge of its circular RNA genome functioning as a transcriptional promoter, and the promoter on the genomic-strand initiate the transcription of antigenomic-strand mRNA ( 25 ). In scKoV, the mapping pattern clearly revealed that the transcripts were expressed in both the genomic- and antigenomic-senses, with the edge of the rod-like structure serving as the boundary ( Figs. 3D and 3E ). Some RNA-seq datasets showed that the approximate initiation sites of both the genomic- and antigenomic-sense transcripts are located between the internal and external bulges at edge of the rod-like structure, which is close to the location previously identified in HDV ( 25 ). Although further experiments are necessary, these observations suggest that both the genomic and antigenomic rod edges of scKoV possess distinct promoter activity. The presence of KoVs with bidirectional and monodirectional promoters provides valuable insights into their evolutionary processes and difference in replication strategies. Our mapping analyses revealed potential splicing events in the genomic transcripts of scKoV. While the majority of RNA viruses replicate in the host cytoplasm, a few lineages, such as KoVs, bornaviruses, orthomyxoviruses, and some rhabdoviruses, transcribe in the host cell nucleus and employ the host splicing machinery, which occurs inside of the nucleus, to express multiple proteins from the same genomic regions ( 28 – 31 ). However, evidence for alternative splicing in KoVs has been lacking thus far. Here, we identified a putative splicing site in the scKoV ORF2 gene ( Figs. 3D and 3F ), which may lead to the expression of two isoforms of ORF2 proteins ( Fig. 3D ). Thus, this study provides the first evidence that KoV utilizes alternative splicing and emphasizes the need for future characterization of other KoV strains, considering the potential use of alternative splicing mechanisms. The ambisense coding strategy of scKoV is analogous to that of other circular RNA viruses. KoVs share the genome structure and the replication mechanism with circular RNA replicons, including viroids, virusoids, and other unclassified mobile genetic elements ( 32 , 33 ). Recent studies have revealed an unprecedented diversity of circular RNA replicons ( 27 , 34 , 35 ). Among the newly identified circular RNA viruses, fungal viruses in the phylum Ambiviricota (the kingdom Orthornavirae of the realm Riboviria ) possess at least two non-overlapping ambisense ORFs, one of which encodes a distinct viral RdRp, suggesting their role as evolutionary intermediates ( 34 , 36 ). The genome of scKoV exhibits a similar organization to that of ambiviruses, with the two ORFs (DAg and ORF2) arranged in an ambisense orientation within a self-complementary region ( Fig. 3 ). This suggests that ambisense coding strategies may be common among certain circular RNA viruses. Our findings strongly suggest that birds are the authentic host of scKoV. The previous study proposed the possibility that scKoV does not infect canaries but rather originates from contaminants, based on the following two points: (i) scKoV is distantly related to tgDeV, which is an authentic avian virus found in a wide range of passerine birds; (ii) scKoV was detected only in a single RNA-seq dataset obtained from canary skin ( 3 ). However, our study identified scKoV in several passerine birds, including canaries, as well as in a parrot (Tables 1 and S1). Additionally, scKoV was detected not only in the skin but also in multiple parenchymal organs, fat tissue, and blood (Tables 1 and S1). Furthermore, the bimodal transcription patterns observed for scKoV suggest active transcription of viral mRNA in those tissues ( Fig. 3D ). These findings strongly suggest that scKoV is an authentic avian virus rather than a contaminant. The existence of avian kolmioviruses that are phylogenetically distinct from the lineages of known reptilian, avian, and mammalian KoVs ( Fig. 1 ), suggests that KoVs infecting the above-mentioned animals are far more genetically diverse than previously thought. Further studies on KoVs are required to understand their host range and genetic diversity. The identification of the complete scKoV genome will contribute to updating the taxonomy of KoVs. The current genus demarcation criterion established by the International Committee on Taxonomy of Viruses (ICTV) is DAg with ≤60% amino acid sequence identity ( 1 ). Thus, scKoV is classified as a new genus because its DAg sequence identity to other KoVs is below 40% ( 3 ). We further demonstrated the presence of genetic diversity within scKoVs. The ICTV species demarcation criteria require ≤80% nucleotide genome identity and ≤70% S-DAg amino acid identity ( 1 ). Based on these criteria, the three groups of scKoV are classified as different genotypes of the same species ( Fig. 2B ). Given the limited information on viral genome sequences for classifying KoVs into distinct species within the same genus, our findings on scKoV sequence diversity may help refine future classification criteria for KoVs. Our study revealed that scKoV has a broad host range and the potential for interspecies transmission. Our findings suggest that scKoV, particularly genotype 1, is capable of interspecies transmission between birds of different orders ( Fig. 2A ). It has been suggested that KoVs have evolved through the multiple interspecies transmission ( 3 , 8 ). Thus, evidence of relatively recent inter-order transmission of scKoV may provide insights into the evolutionary history of KoVs. Further detailed analyses of the host specificity of scKoV are necessary. We also reveal the mixed infections of different genotypes of scKoV in some individuals. scKoVs of different genotypes were detected mixed within RNA-seq data from the same individual ( Fig. 2C ). These mixed infections, observed across multiple BioProjects and in some cases with nearly equal ratios and certain read numbers of different genotypes, suggest that they are unlikely to be due to contamination and/or index hopping during sampling, library preparation, and sequencing processes. HDV has been reported to undergo recombination between different genotypes during coinfection ( 37 ). Our findings of mixed infection with scKoVs belonging to different genotypes provide important insights into the epidemiology and evolution of KoVs. Our study identified ABVs as candidate helper viruses for scKoV. The helper viruses for non-HDV KoVs remain largely unknown except for snake deltavirus that utilizes the envelope proteins of co-infected reptarenavirus or hartmanivirus in the family Arenaviridae ( 5 , 13 ). Our previous study indicated co-existence of scKoV with CnBV in a single RNA-seq dataset (SRR2915371); however, this RNA-seq dataset was derived from a pooled sample from multiple individuals, and no definitive evidence of co-infection between scKoV and CnBV was obtained ( 3 ). In this study, we identified CnBV-1, CnBV-3 and PaBV-2, which encode envelope glycoproteins, in 64 out of 66 scKoV-positive RNA-seq datasets ( Figs. 4A and S8). Notably, except for the RNA-seq dataset in which scKoV was previously identified ( 3 ), none of these were clearly from pooled samples. Although further experimental validation is needed, these results suggest that ABVs are helper viruses for scKoV. Further, our data provide insights into the hypothesis that KoVs have evolved with diverse satellite-helper relationships. Co-infection with scKoV and ABV suggests that the pathogenicity of scKoV in infected birds needs to be considered. Co-infection of HDV and HBV accelerates the pathogenic effects of HBV, leading to severe or fulminant hepatitis and progression to hepatocellular carcinoma ( 38 ). The pathogenicity of scKoV remains unknown due to the lack of metadata clarifying whether scKoV-positive RNA-seq data were obtained from healthy birds. In contrast, the co-infecting PaBV is a causative agent of proventricular dilatation disease (PDD), an immune-mediated inflammatory disease ( 39 , 40 ). Similarly, CnBV was also reported to be associated with PDD in canaries, but experimental infections using a CnBV isolate have not successfully reproduced the pathology, suggesting that other factors may be involved in the onset of the disease ( 41 ). Analogous to co-infection of HDV and HBV, scKoV may also contribute to or exacerbate PDD through co-infection with CnBV. Further epidemiological studies of scKoV and CnBV is required to clarify the etiology of PDD. Our analysis suggests that scKoV may have the potential to infect various tissues. While HDV is known for its high tropism for the liver ( 12 ), non-HDV KoVs have been detected in multiple organs ( 3 , 7 , 8 , 13 ). Like other non-HDV KoVs, scKoV was found to predominantly target the skin, fat tissue, blood, and some parenchymal organs, rather than the liver ( Table 1 and Fig. 2C ). ABVs, candidate helper viruses for scKoV, can also infect various organs ( 41 , 42 ). Our results support the hypothesis that while the tissue tropism of scKoV and other KoVs is broad, it is likely dependent on the tissue infectivity of the helper virus ( 3 , 7 , 13 ). Taken together, we provide novel insights into the genomic features, replication strategies, epidemiology, and satellite-helper relationships of KoVs through the comprehensive and detailed analyses of the complete scKoV genomes. Further analyses are needed to explore the broader diversity of KoVs. 4. Materials and Methods 4.1. Detection of scKoV-derived reads from public RNA-seq data RNA-seq data from birds (in the class Aves without Gallus gallus [Linnaeus, 1758]) were downloaded from the NCBI Sequence Read Archive ( 43 ) (accessed on Jan 20, 2024) and mapped to the partial scKoV genome (BR001664.1) using Magic-BLAST v1.7.1 ( 44 ) with the options “-splice T -word_size 16 -lcase_masking”. The mapped read numbers were counted using SAMtools v1.19 ( 45 ). The mapping results were manually verified, and reads that were locally aligned to sequences of less than 25 bases in the reference were excluded as non-specific mapping. 4.2. Identification of complete scKoV genomes The scKoV-positive RNA-seq data were downloaded and dumped using SRA Toolkit ( https://github.com/ncbi/sra-tools ), which were preprocessed using fastp v0.23.4 ( 46 ) with the options “-l 35 -x -y”. The preprocessed reads were mapped to the host genome sequences using HISAT2 v2.2.1 ( 47 ) with the default settings. The unmapped reads were extracted with SAMtools v1.19 and subjected to de novo assembly using Trinity v2.15.1 ( 48 ) with the default settings. The scKoV contigs were identified through a two-step sequence similarity search: BLASTn against the partial scKoV genome and BLASTx against the clustered nr database ( 43 ), using BLAST+ v2.15.0 ( 49 ). Self-dotplot analysis of the linear scKoV contigs was performed using the YASS program with the default settings ( 50 ). Contigs with identical ends were manually circularized using Geneious Prime v2024.0.5 ( https://www.geneious.com ). The circularities of scKoV contigs were further verified by mapping short reads to the circularized scKoV contigs using Geneious and manually checking the mapped reads across the circularized boundaries. For RNA-seq data where circularized scKoV contigs could not be obtained by de novo assembly, the scKoV-positive RNA-seq data were mapped to the circular scKoV contigs using Geneious and extracted the circular consensus sequences. For all the contigs, all positions were confirmed to be covered with at least three reads. 4.3. Phylogenetic analysis Phylogenetic relationship among all known KoVs were inferred as follows. The amino acid sequences of KoV DAg were aligned by MAFFT v7.490 with the E-INS-I algorithm ( 51 ). The phylogenetic tree was constructed using the Bayesian Markov chain Monte Carlo (MCMC) method in MrBayes version 3.2.7a ( 52 ) with two independent runs, four chains per run, and the JTT model of substitution. The analysis was run for 5 million iterations, with samples taken every 5,000 steps. The average standard deviation of split frequencies was 0.010. For the nucleotide sequences of the full-length scKoV genomes, multiple sequence alignment was performed using MAFFT v7.490 with the E-INS-I algorithm ( 51 ). Pairwise sequence identities were calculated based on the alignment using Geneious. A maximum-likelihood tree was constructed using the TVM+I+G4 model, selected as the best-fit model based on the minimum AIC in RAxML v1.1.0 ( 53 ). The reliability of the tree was assessed by 1,000 bootstrap resampling with the transfer bootstrap expectation method ( 54 ). Both trees were visualized and annotated in the Interactive Tree Of Life (iTOL) v6.9.1 ( 55 ). 4.4. Sequence Characterization The self-complementarities of scKoV genomes were analyzed using the Mfold web server ( 56 ) with the default settings. Genomic and antigenomic ribozyme structures were initially inferred using the IPknot web server ( 57 ), with the visualized output from IPknot serving as a guide for manual ribozyme structure drawing. Poly-A signals (AAUAAA) were manually identified in both strands of KoV genomes. ORFs were detected using the ‘Find ORF’ function in Geneious, with a minimal threshold of 300 nucleotides. ORFs that overlap with the terminal rod-like structure of the viral genome, where the putative transcriptional promoter is located, poly(A) signal, or the predicted ribozyme regions were excluded. 4.5. Short read mapping to analyze mixed infection with scKoV of different genogroups The short reads from scKoV-positive RNA-seq data belonging to BioProjects PRJNA591356, PRJNA939570, and PRJNA679636 were mapped to scKoV sequences of different genogroups detected from the same BioProject (scKoV from SRR10526804 and SRR10526851 for PRJNA591356, scKoV from SRR23747122 and SRR23747110 for PRJNA939570, scKoV from SRR13480248 and SRR13480240 for PRJNA679636). Mapping was performed using of HISAT ver 2.2.1. with the ‘-k 1’ option. The mapped read numbers were counted using SAMtools v1.19 ( 45 ). The data with RPM>10 were visualized. 4.6. Short read mapping to analyze transcriptional patterns The short reads from scKoV-positive RNA-seq data were preprocessed as described above (see the section 4.2 ) and mapped to the corresponding scKoV genomes using HISAT2 v2.2.1 ( 47 ) with the options “-k 2 --max-intronlen 1000 --rna-strandness RF”. To accurately evaluate reads spanning the circularized genome boundaries, 2x tandemly repeated genomes were used as the references. The “-k 2” option in HISAT2 was selected to ensure precise mapping to the 2x genomes. For strand-specific RNA-seq data, the “--rna-strandness RF” option was also used to retain strand information. The mapped reads were counted using SAMtools v1.19 ( 45 ). 4.7. Characterization of ORF2 proteins The amino acid sequences of both ORF2a and ORF2b were analyzed using BLASTp, employing the PSI-BLAST and the DELTA-BLAST algorithms with an e-value threshold of < 0.05. Theoretical molecular weight and isoelectric point was calculated using ProtParam web server ( https://web.expasy.org/protparam/ ). Amino acid sequence alignments, colored according to hydrophobicity and polarity, were generated using Geneious. Membrane topology of ORF2 proteins was inferred using DeepTMHMM ver. 1.0 ( 58 ). Nuclear localization signal was inferred using the cNLS mapper web server with a cut-off value of 3.0 ( 59 ). Intrinsically disordered region were predicted using AIUPred web server ( 60 ). Secondary structures of ORF2 proteins were predicted using JPred v4 ( 61 ).Protein structure predictions were performed by AlphaFold3 web server ( 62 ). 4.8. Detection of RNA-editing on the stop codon of DAg Sequence variations at the DAg stop codon were identified in the mapping data of section 4.5 using ‘Find SNP/Variants’ in Geneious. 4.9. Detection of co-existing viruses To identify co-existing viruses in scKoV-positive RNA-seq data, the assembled contigs (see the section 4.2 ) were clustered using CD-HIT v 4.8.1 ( 63 ) with the 95 % threshold. The clustered contigs of 500 nucleotides or longer were extracted using SeqKit v2.4.0 ( 64 ), which were subjected to a two-step sequence similarity search. The first search was conducted by MMseqs2 (version c48da9d781b81804727b5cccfed7f97cfcc20c9d) ( 65 ) with the default settings against a custom database consisting of viral protein sequences with a threshold E-value of 0.001. The custom database was created as follows. Viral protein sequences were downloaded from the NCBI nr database on June 22, 2023, which was clustered by using CD-HIT v4.8.1 ( 63 ) with a threshold of 0.9. Contigs alignable to viral sequences other than retroviruses and environmental viruses were extracted. The second BLASTx search was then performed using the extracted contigs as queries against the NCBI clustered nr database ( 43 ) with the options “-e-value < 1e-4 -word_size 2 -max_target_seqs 10” on Aug 26, 2024. The contigs with the best hit to viruses were extracted and manually analyzed. Contigs with the best hit to bornaviruses (the family Bornaviridae ) were further subjected to a BLASTn search against a database of CnBVs and PaBVs to accurately identify the species/genotypes. To quantify ABVs-derived reads in scKoV-positive RNA-seq data, preprocessed reads were mapped using HISAT2 ( 47 ) with the option “-k 1” against CnBV-1 (NC_030690.1), CnBV-3 (NC_024296.1), and newly obtained PaBV contig assembled from SRR13480248 (Supplementary Materials) because the genome sequence of co-existed PaBV is slightly different from the ones deposited in INSDC. Acknowledgements The super-computing resources were provided by Human Genome Center, the Institute of Medical Science, the University of Tokyo. This study was supported by KAKENHI grant numbers 21H01199 (MH), 22K19234 (MI and MH), 23K20902 (MH), 24K21922 (MH), and 24K18455 (MK) and the 2024 Osaka Metropolitan University (OMU) Strategic Research Promotion Project (Young Researcher) (MK). 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Share Identification of ambisense kolmioviruses Mai Kishimoto , Sakiho Imai , Manabu Igarashi , Masayuki Horie bioRxiv 2025.01.08.631871; doi: https://doi.org/10.1101/2025.01.08.631871 Share This Article: Copy Citation Tools Identification of ambisense kolmioviruses Mai Kishimoto , Sakiho Imai , Manabu Igarashi , Masayuki Horie bioRxiv 2025.01.08.631871; doi: https://doi.org/10.1101/2025.01.08.631871 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Microbiology Subject Areas All Articles Animal Behavior and Cognition (7622) Biochemistry (17648) Bioengineering (13870) Bioinformatics (41880) Biophysics (21423) Cancer Biology (18553) Cell Biology (25458) Clinical Trials (138) Developmental Biology (13364) Ecology (19866) Epidemiology (2067) Evolutionary Biology (24290) Genetics (15589) Genomics (22475) Immunology (17711) Microbiology (40327) Molecular Biology (17145) Neuroscience (88472) Paleontology (666) Pathology (2826) Pharmacology and Toxicology (4815) Physiology (7635) Plant Biology (15114) Scientific Communication and Education (2044) Synthetic Biology (4286) Systems Biology (9815) Zoology (2268)