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. Author manuscript; available in PMC: 2023 Jun 1.
Published in final edited form as: Infect Genet Evol. 2023 Mar 5;110:105421. doi: 10.1016/j.meegid.2023.105421

Mammalian orthoreoviruses exhibit rare genotype variability in genome constellations

Julia R Diller a, Timothy W Thoner Jr b, Kristen M Ogden a,b,*
PMCID: PMC10112866  NIHMSID: NIHMS1888078  PMID: 36871695

Abstract

Mammalian orthoreoviruses (reoviruses) are currently classified based on properties of the attachment protein, σ1. Four reovirus serotypes have been identified, three of which are represented by well-studied prototype human reovirus strains. Reoviruses contain ten segments of double-stranded RNA that encode 12 proteins and can reassort during coinfection. To understand the breadth of reovirus genetic diversity and its potential influence on reassortment, the sequence of the entire genome should be considered. While much is known about the prototype strains, a thorough analysis of all ten reovirus genome segment sequences has not previously been conducted. We analyzed phylogenetic relationships and nucleotide sequence conservation for each of the ten segments of more than 60 complete or nearly complete reovirus genome sequences, including those of the prototype strains. Using these relationships, we defined genotypes for each segment, with minimum nucleotide identities of 77–88% for most genotypes that contain several representative sequences. We applied segment genotypes to determine reovirus genome constellations, and we propose implementation of an updated reovirus genome classification system that incorporates genotype information for each segment. For most sequenced reoviruses, segments other than S1, which encodes σ1, cluster into a small number of genotypes and a limited array of genome constellations that do not differ greatly over time or based on animal host. However, a small number of reoviruses, including prototype strain Jones, have constellations in which segment genotypes differ from those of most other sequenced reoviruses. For these reoviruses, there is little evidence of reassortment with the major genotype. Future basic research studies that focus on the most genetically divergent reoviruses may provide new insights into reovirus biology. Analysis of available partial sequences and additional complete reovirus genome sequencing may also reveal reassortment biases, host preferences, or infection outcomes that are based on reovirus genotype.

Keywords: Reovirales, Reovirus, Reassortment, Segmented, dsRNA, Genotype

1. Introduction

Many properties, including host range, cell and tissue tropism, pathogenicity, vector specificity, antigenicity, and the relatedness of viral genomes or genes, can be used to classify viruses (species parameters from the International Committee on Taxonomy of Viruses (ICTV): https://ictv.global/taxonomy/). Historically, human viruses often have been classified based on serological properties. However, the availability of growing numbers of viral genome sequences has permitted more complete nucleic acid characterization, prediction of encoded proteins, and new opportunities to understand the makeup of viral genomes and to classify viruses based on genetic relatedness. For segmented viruses, sequencing and segment classification have revealed the constellations, or specific assortments, of segments that comprise viral genomes and permitted detection of reassortants, viruses that contain mixtures of segments derived from multiple parent viruses (Anbalagan et al., 2014a; De Grazia et al., 2016; Hoxie and Dennehy, 2021; Matthijnssens et al., 2008a; Steel and Lowen, 2014; Stott et al., 1987; Trifkovic et al., 2021). Reassortment is a key driver of segmented virus evolution but appears to be limited in natural settings and is constrained by viral RNA and protein incompatibilities (Klempa, 2018; Lowen, 2017; McDonald et al., 2016; Varsani et al., 2018; Wille and Holmes, 2020). Lack of complete genome sequence information and a system by which to group or classify the segments can limit our understanding of diversity and evolution for segmented viruses.

Mammalian orthoreoviruses (reoviruses) are segmented double-stranded RNA viruses in the order Reovirales (Matthijnssens et al., 2022a). While reoviruses infect humans, they have rarely been associated with acute disease (Dermody et al., 2013; Eledge et al., 2019; Hermann et al., 2004; Steyer et al., 2013; Tyler et al., 2004). Reoviruses can infect a broad range of other mammalian hosts and in some cases have been associated with respiratory and diarrheal disease (Fukutomi et al., 1996; Thimmasandra Narayanappa et al., 2015; Zhang et al., 2011). The reovirus genome contains ten dsRNA segments, three large (L1–L3), three medium (M1-M3), and four small (S1-S4) (Dermody et al., 2013; Lemay, 2018). Most segments encode a single ORF, but S1 and M3 each encode two ORFs. In total, reovirus encodes eight structural and four non-structural proteins.

Historically, reoviruses have been classified based on serotype, which is determined by the S1-encoded viral attachment protein, σ1, but reoviruses exhibit diversity among multiple genome segments. Based on neutralization and hemagglutinin inhibition properties of σ1, four reovirus serotypes (T1-T4) have been assigned to date (Attoui et al., 2001; El Mekki et al., 1981; Sabin, 1959). Lang (T1), Jones (T2), and Dearing (T3) serve as prototype strains and represent the three major reovirus serotypes, and Ndelle is currently the only T4 reovirus that has been identified. Reovirus serotype assignments have been supported as distinct reovirus S1 groupings based on numerous phylogenetic analyses. S1 is the most genetically divergent of the ten reovirus genome segments (Dermody et al., 1990; Feng et al., 2022; Jiang et al., 2006; Song et al., 2008; Yan et al., 2022). Lang and Dearing L3, M3, M2, S3, and S4 segments are more closely related to one another than to the corresponding Jones segments (Harrison et al., 1999; Kedl et al., 1995; McCutcheon et al., 1999; Wiener and Joklik, 1988), whereas L2 and S1 are more equivalently divergent among the three prototype strains (Breun et al., 2001; Wiener and Joklik, 1988). However, phylogenetic evidence suggests that L1, L2, S2, S3, and S4 have diverged in a serotype-independent manner (Breun et al., 2001; Chapell et al., 1994; Goral et al., 1996; Kedl et al., 1995; Leary et al., 2002).

A thorough analysis of all ten reovirus genome segment sequences has not been previously conducted. The primary aim of the current study is to understand phylogenetic relationships among the ten viral genome segments and across the complete viral genome for reoviruses collected from different animal hosts in different geographic locations at different times over the past 70 years. Such an analysis might reveal the presence of preferred assortments of reovirus genome constellations and the extent of natural reassortment among more genetically divergent genome segments. In this study, we analyze phylogenetic relationships and nucleotide sequence conservation for each of the ten genome segments of the prototype reoviruses and all other reoviruses for which complete or nearly complete genome sequences have been reported. We use these relationships to genotype the reovirus segments based on phylogeny and nucleotide identity, gain insight into the variety of detected reovirus genome constellations, and propose an updated nomenclature system for reoviruses that provides information about the identity of each segment.

2. Materials and methods

2.1. Study overview

To gain insight into evolutionary divergence among reoviruses, we aligned the nucleotide and deduced amino acid sequences and computed pairwise distances for 66 reoviruses of human, chamois, cow, bat, deer, lion, mink, mouse, palm civet, pig, shrew, vole, wild boar, or wastewater origin (Table S1). We constructed ML trees using the nucleotide alignments. In some cases, we also constructed ML trees based on deduced amino acid sequences. However, we favored nucleotide-based analysis because these sequences incorporate untranslated regions at 5′ and 3′ segment termini, and they are less conserved than the deduced amino acid sequences, which often exhibit limited diversity (Table 1). We used the ML trees and pairwise distances as a basis for assigning genotypes and clades for each of the ten reovirus segments.

Table 1.

Nucleotide and amino acid identities of select reoviruses in comparison to prototype Lang and Dearing strains.

MRV00304/2014 SI-MRV03 19-LN21 Jones SI-MRV08
Lang Dearing Lang Dearing Lang Dearing Lang Dearing Lang Dearing
L1 (λ3) 86(96)a 86(97) 81(97) 82(97) 75(92) 76(92) 75(92) 76(92) 75(92) 76(92)
L2 (λ2) 89(96) b 76((91) 75(91) 78(94) 73(87) 73(88) 72(87) 74(87) 73(87) 74(86)
L3 (λ1) 83(98) 83(98) 80(97) 80(97) 77(96) 77(96) 77(96) 76(96) 76(95) 76(95)
Ml (μ2) 72(80) 72(79) 80(93) 80(93) 71(83) 71(82) 71(81) 71(80) 70(82) 70(81)
M2 (μ1) 77(92) 77(91) 82(97) 81(96) 78(95) 77(95) 77(97) 77(97) 78(97) 77(97)
M3 (μNS) 86(94) 91(95) 78(91) 78(90) 73(85) 73(84) 71(82) 71(83) 72(83) 72(83)
S1 (σl) 73(78) 43(24) 77(82) 43(26) 57(53) 44(28) 57(50) 46(28) 57(50) 43(27)
S1 (σls) 73(72) 43(21) 77(68) 43(27) 57(42) 44(29) 57(39) 46(28) 57(40) 43(30)
S2 (σ2) 85(98) 92(99) 80(96) 79(96) 79(95) 77(95) 77(94) 78(94) 78(95) 77(95)
S3 (σNS) 86(96) 94(99) 83(96) 82(96) 76(89) 76(89) 73(86) 74(86) 73(86) 74(86)
S4 (σ3) 92(95) 93(95) 82(92) 83(93) 76(89) 76(88) 78(90) 77(90) 78(90) 77(89)
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a

Nucleotide and (amino acid) identities compared with serotype representative strains Lang and Dearing are indicated as percentages.

b

Bold, italicized text indicates a shared genotype.

2.2. Virus sequences

Accession numbers for reovirus genome segment sequences used in the current analyses are shown in Table S1. Sequences represent all complete or nearly complete reovirus genomes deposited in GenBank (https://www.ncbi.nlm.nih.gov/genbank/) as of November 2, 2021. Although only five of ten segments were sequenced for Ndelle, this virus was included because it is the only known representative of reovirus serotype 4.

2.3. Maximum likelihood analyses

For nucleotide analyses, nucleotide sequences extending beyond the 5′ and 3′ termini were trimmed in the original fasta files. Trimmed sequences were aligned using MAFFT 7.4 with the E-INS-I strategy (Katoh and Standley, 2013). Maximum likelihood (ML) trees were constructed using the General Time Reversible model (Nei and Kumar, 2000) in MEGA X (Kumar et al., 2018) with 1000 bootstrap replications. For σ1s amino acid analyses, when not reported in GenBank, σ1s sequences were determined using the translate tool in Expasy from the Swiss Institute of Bioinformatics (https://web.expasy.org/translate/). An open reading frame within ~75 nt of the σ1 ATG that encoded at least 70 amino acids was included in the alignment. Amino acid sequences were aligned using MAFFT 7.4 with the E-INS-I strategy. ML trees were constructed using the Jones-Taylor-Thornton matrix-based model in MEGA X (Jones et al., 1992; Kumar et al., 2018) with 1000 bootstrap replications.

2.4. Construction of pairwise identity frequency matrices and graphs

Estimates of evolutionary divergence between aligned sequences were made using the Compute Pairwise Distances function in MEGA X (Kumar et al., 2018). All ambiguous positions were removed for each sequence pair. The percent nucleotide identities were calculated from number of base differences per site from between sequences. Pairwise identity frequency graphs were constructed by plotting calculated pairwise identities in a graph with the percentage identity plotted on the x axis and the frequency of detection of pairwise identity plotted on the y axis. Identity frequencies were plotted using a 1% or 2% binning interval.

2.5. Genotype assignments

For each ML tree, we considered several possible alternatives for assigning specific clusters as genotypes or clades. Initial definitions of relationships among segments as interserotype, intraserotype, intergenotype, intragenotype, or intraclade were made based on branching patterns in ML trees and clustering of pairwise identity frequency. The final genotype assignments were made based on the following criteria: (i) bootstrap values at nodes defining genotypes had values equal to or greater than 85%, and (ii) we observed minimal overlap in intergenotype and intragenotype identity. Similar strategies have been used to define genotype cutoffs for classification of rotavirus and avian reovirus (Jeong et al., 2015; Marthaler et al., 2013; Marthaler et al., 2014; Matthijnssens et al., 2008a; Mor et al., 2015; Mor et al., 2014; Shepherd et al., 2018). In some cases, these strict definitions were insufficient to distinguish reovirus serotypes, genotypes, and clades. For example, for the S1 segment, some serotype 3 nodes branching prior to those defining genotypes had relatively low bootstrap support, but the genetic distances and ratios of intergenotype to intragenotype identity supported the genotype definitions. To gain deeper insight into relationships among segments, we divided the average percent identity for the defined “inter” group by the average percent identity for the defined “intra” group. In every case, the ratio of the intergenotype identity and intragenotype identity (intergenotype identity/intragenotype identity) was less than 0.9, and the ratio of intragenotype and interclade identity (intragenotype/interclade) was less than 1. Although cutoff percentages defining genotypes and clades were anticipated to fall at the percentages that separate the intergenotype and intragenotype identities for graphed data, this was not always the case for clusters containing few representatives.

3. Results and discussion

3.1. Reovirus serotype relationships

S1 is the most genetically divergent reovirus segment (Dermody et al., 1990; Feng et al., 2022; Jiang et al., 2006; Song et al., 2008) and historically has been used to classify reoviruses. In nucleotide-based ML trees, the 61 S1 sequences included in the analysis clustered into branches by serotype that are supported by strong bootstrap values of 96–100%, with Ndelle clustering with the T3 S1 segments. Sequences are depicted in Fig. 1A as red (T1), green (T2), blue (T3), and purple (T4). In general, the percent nucleotide identity for S1 is above 58% within a serotype and below 60% between serotypes, with many sequences of different serotypes sharing less than 45% S1 nucleotide identity (Fig. 1B and Table S8). An exception is T4 strain Ndelle, which shares 70–71% S1 nucleotide identity with several T3 reoviruses. Thus, despite serological differences, Ndelle is genotypically more similar to T3 reoviruses than to T1 or T2 reoviruses. Within each serotype, many S1 sequences clustered on branches that are supported by strong bootstrap values (Fig. 1A). We used a combination of bootstrap support, percent nucleotide identity, and the ratio of intragenotype to intraserotype identity to determine which of these branches define genotypes. We defined three T1, seven T2, and two T3 S1 genotypes, whose member sequences are colored in different shades of the corresponding serotype color in Fig. 1A. Genotype percent nucleotide identities were equal to or higher than 78% (Fig. 1B and Table S8). Serotype and genotype groupings are generally well supported by clustering of amino acid sequences in ML trees for the S1-encoded σ1s and σ1 proteins (Fig. 1C and data not shown).

Fig. 1.

Fig. 1.

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(A) Maximum likelihood tree assembled from S1 nucleotide sequences. Horizontal branch lengths are drawn to scale, representing substitutions per nucleotide. Bootstrap values (1000 replicates) are shown as percentages. The dashed line indicates the current division into genotypes. Virus names are colored based on σ1 serotype and genotype in shades of red (T1), green (T2), blue (T3), and purple (T4). Currently assigned genotypes are indicated to the right of the tree. (B) Nucleotide identity frequencies for analyzed S1 sequences. (C) Maximum likelihood tree assembled from amino acid sequences of S1-encoded σ1s proteins, colored based on genotype assignments in panel A. Horizontal branch lengths are drawn to scale, representing substitutions per amino acid. Bootstrap values (1000 replicates) are shown as percentages.

3.2. Evolutionary relationships among other reovirus segments

Relationships among reovirus segments other than S1 are generally less well studied. We identified three general scenarios describing relationships among most sequences analyzed for segments other than S1: (i) we defined more than a single genotype, (ii) we defined a single genotype containing multiple sub-genotype clades, or (iii) we defined a single more homogeneous genotype that lacked distinct sub-genotype clades. These three scenarios described the majority of analyzed sequences, but for each segment we also identified a small subset of outliers, which we defined as distinct genotypes.

For reovirus segments L2 and S4, most sequences clustered in one of two major genotypes. In nucleotide-based ML trees, 59 of the 65 L2 sequences included in the analysis clustered into one of two branches that are supported by bootstrap values of 100%, which we defined as distinct genotypes (Fig. 2A). We identified four additional genotypes based on bootstrap support, pairwise percent nucleotide identity, and the ratio of intragenotype to intergenotype identity (Fig. 2A,C and Table S3). L2 sequences shared less than 82% intergenotype nucleotide identity and greater than 84% intragenotype nucleotide identity. For the S4 segment, 62 of the 65 sequences included in the analysis clustered into one of two branches that are supported by bootstrap values of 98% and 100%, which we defined as distinct genotypes (Fig. 2B). We identified two additional genotypes based on bootstrap support, pairwise percent nucleotide identity, and the ratio of intragenotype to intergenotype identity (Fig. 2B,D and Table S11). S4 sequences typically shared 80% or less intergenotype nucleotide identity and 82% or greater intragenotype nucleotide identity (Fig. 2D). However, while Jones and SI-MRV08 reovirus S4 sequences cluster distinctly with high confidence in ML trees, they share slightly higher nucleotide identities, up to 84%, with some S4 genotype 4 sequences (Fig. 2B and Table S11).

Fig. 2.

Fig. 2.

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(A-B) Maximum likelihood trees assembled from nucleotide sequences of the L2 (A) and S4 (B) segments. Horizontal branch lengths are drawn to scale, representing substitutions per nucleotide. Bootstrap values (1000 replicates) are shown as percentages. The dashed line indicates the current division into genotypes, which are shown to the right of the tree as different colors and labeled. (C–D) Nucleotide identity frequencies for analyzed L2 (C) and S4 (D) sequences.

For reovirus segments L3 and M2, most sequences clustered in a single genotype that we further subdivided into sub-genotype clades. In nucleotide-based ML trees, 59 of the 63 L3 sequences included in the analysis clustered into a single branch with 100% bootstrap support, which we defined as a single genotype (Fig. 3A). Within this branch, we identified three sub-genotype clades based on bootstrap support, pairwise percent nucleotide identity, and the ratio of intraclade to intragenotype identity (Fig. 3A,C and Table S4). We identified four L3 sequences, SI-MRV03, 19-LN21, Jones, and SI-MRV08, as belonging to three additional genotypes, based on bootstrap support, pairwise percent nucleotide identity, and the ratio of intragenotype to intergenotype identity. L3 sequences shared less than 82% intergenotype nucleotide identity, 82–88% intragenotype nucleotide identity, and greater than 86% intraclade identity (Fig. 3C). Although nucleotide identity cutoffs between genotype and clade are not entirely clean, bootstrap support for clades is strong, and intraclade to intragenotype ratios support these divisions (Fig. 3A,C and not shown) In nucleotide-based ML trees, 53 of the 63 M2 sequences included in the analysis clustered into a single branch with 99% bootstrap support, which we defined as a single genotype (Fig. 3B). Within this branch, we identified four sub-genotype clades based on bootstrap support, pairwise percent nucleotide identity, and the ratio of intraclade to intragenotype identity (Fig. 3B,D and Table S6). We identified ten M2 sequences as belonging to three additional genotypes, based on bootstrap support, pairwise percent nucleotide identity, and the ratio of intragenotype to intergenotype identity. M2 sequences generally shared less than 80% intergenotype nucleotide identity, 80–88% intragenotype nucleotide identity, with a very small number of sequences exceeding this percent identity, and 87% or greater intraclade identity (Fig. 3D).

Fig. 3.

Fig. 3.

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(A-B) Maximum likelihood trees assembled from nucleotide sequences of the L3 (A) and M2 (B) segments. Horizontal branch lengths are drawn to scale, representing substitutions per nucleotide. Bootstrap values (1000 replicates) are shown as percentages. The dashed line indicates the current division into genotypes and clades, which are shown to the right of the tree as different colors and shades of color, respectively, and labeled. (C–D) Nucleotide identity frequencies for analyzed L3 (C) and M2 (D) sequences.

For reovirus segments L1, M1, M3, S2, and S3, most sequences clustered in a single genotype that we did not further divide into subclades. For reovirus segments M3 and S2, in nucleotide-based ML trees, all but four of the sequences included in the analysis clustered into a single branch with very strong (99–100%) bootstrap support, which we defined as a single genotype (Fig. 4A–B). Within the major branch, an additional subdivision could not be made with very high confidence. For both M3 and S2, we identified four sequences, SI-MRV03, 19-LN21, Jones, and SI-MRV08, as belonging to three additional genotypes. We detected clear intragenotype and intergenotype boundaries based on pairwise nucleotide identities, with M3 and S2 sequences both generally sharing 80% or less intergenotype nucleotide identity 82% or greater intragenotype nucleotide identity (Fig. 4C–D). For reovirus segments L1 and M1, in nucleotide-based ML trees, all but five of the sequences included in the analysis clustered into a single branch with very strong (99–100%) bootstrap support, which we defined as a single genotype (Fig. S1A-B). Within this branch, an additional subdivision could not be made with very high confidence. We identified L1 and M1 sequences for SI-MRV03, 19-LN21, Jones, SI-MRV08, and MRV00304/2014 as belonging to four additional genotypes. Although there might be strong bootstrap support for some additional subdivisions, L1 and M1 sequences within the major genotype exhibited limited genetic variability (Fig. S1A-B). Furthermore, we detected clear intragenotype and intergenotype boundaries based on pairwise nucleotide identities, with L1 sequences generally sharing 86% or less intergenotype nucleotide identity 87% or greater intragenotype nucleotide identity and M1 sequences generally sharing 77% or less intergenotype nucleotide identity 84% or greater intragenotype nucleotide identity (Fig. S1C-D). The high level of L1 nucleotide identity is not surprising, as this segment encodes the viral RNA-dependent RNA polymerase (Starnes and Joklik, 1993; Tao et al., 2002). The structural organization of the RNA-dependent RNA polymerase enzymatic domains is highly conserved, even among divergent viruses, and the function of this enzyme is critical for viral replication (Ferrero et al., 2018; McDonald et al., 2009b). For S3, most sequences clustered into two branches that were supported by strong bootstrap values (Fig. S2A). However, since the ratio of intraclade identity to intragenotype identity was greater than 1, and there was not a distinct pairwise identity boundary, we did not identify these branches as sub-genotype clades (Fig. S2B and not shown). Instead, we identified the major branch from which these two branches split, which also had strong bootstrap support, as a distinct S3 genotype (Fig. S2A). We identified four sequences, SI-MRV03, 19-LN21, Jones, and SI-MRV08, as belonging to three additional S3 genotypes (Fig. S2A-B). S3 sequences generally share 81% or less intergenotype nucleotide identity 85% or greater intragenotype nucleotide identity. Inclusion of greater numbers of reovirus segment sequences in ML trees could potentially clarify boundaries and alter genotype or sub-genotype clade classification for some reovirus segments, including S3. However, our observations suggest that many segments other than S1 exhibit relatively limited overall genetic diversity for many sequenced reoviruses.

Fig. 4.

Fig. 4.

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(A-B) Maximum likelihood trees assembled from nucleotide sequences of the M3 (A) and S2 (B) segments. Horizontal branch lengths are drawn to scale, representing substitutions per nucleotide. Bootstrap values (1000 replicates) are shown as percentages. The dashed line indicates the current division into genotypes, which are shown to the right of the tree as different colors and labeled. (C–D) Nucleotide identity frequencies for analyzed M3 (C) and S2 (D) sequences.

3.3. Reovirus genome constellations

A summary of defined genotypes and clades, along with the minimum nucleotide identity for each classification, is shown in Fig. 5. For S1, we identified 13 genotypes. For each reovirus segment other than S1, we identified six or fewer genotypes, with only four genotypes identified for six of the ten reovirus segments. For most reovirus segments, genotypes that contain more than a few sequences have minimum nucleotide identity values of 78–88%. These include S1 genotypes T1–1, T2–1, T2–3, T3–1, and T3–2; L1, L3, M1, M2, M3, S2, and S4 genotype 1; and L2 and S4 genotypes 1 and 4. While we have not yet sequenced enough reovirus genomes or analyzed enough sequences to feel confident in proposing strict nucleotide identity cutoffs for genotype classification for each segment, we propose that the percentage identity for such cutoffs likely should be in the high seventies to mid-eighties for most reovirus segments and genotypes. Consistent with our findings, nucleotide identity cutoffs for species A and C rotaviruses, which were defined using similar methodologies and are in the same viral order as reoviruses, are in the range of 79–91% and 79–86%, respectively (Matthijnssens et al., 2008a; Wang et al., 2021). For species B rotavirus VP7, NSP2, and NSP5 segments, genotype percent nucleotide identity cutoffs of 80%, 75%, and 78%, respectively, have been proposed (Marthaler et al., 2012; Suzuki et al., 2012a; Suzuki et al., 2012b). Likewise, genotype cutoffs of 83–90% have been proposed for M- and L-class segments of turkey arthritis reoviruses (Mor et al., 2015; Mor et al., 2014).

Fig. 5.

Fig. 5.

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Minimum nucleotide percentage identity values defining genotypes for the ten reovirus genome segments. Assigned genotype and sub-genotype clade numbers and colors match those in Figs. 1–4 and S1-S2. For genotypes and clades that contain more than one reovirus, the minimum percent nucleotide identity is indicated on the right.

To better understand relationships among segments, we applied our genotype and clade assignments to the complete genomes of all reoviruses in the analysis. The results, which are shown in Fig. 6, reveal the genome constellations for many reoviruses. In general, S1 genotypes assort independently from the remaining segments in the reovirus genome and do not appear to correlate strongly with host species or collection year. It is interesting that S1, which encodes viral attachment protein σ1, assorts independently from the remaining genome segments. This is not the case for all dsRNA viruses. For example, for human rotaviruses, which are also members of the order Reovirales, in many cases the genotypes of segments encoding the viral attachment protein and outer capsid protein can be strong predictors of the genotype of the remining genome segments (Matthijnssens et al., 2022b; Matthijnssens et al., 2008a; Matthijnssens et al., 2008b; McDonald et al., 2009a). However, the lack of correlation between S1 genotype and host species is consistent with previous observations made for T3 reovirus S1 sequences (Dermody et al., 1990).

Fig. 6.

Fig. 6.

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Allele-based genome constellations for reoviruses included in the current analysis based on newly assigned genotypes and clades. Bars representing genome segments are colored and labeled based on genotype and clade assignments, as shown in Figs. 1–5 and described in the text. Viruses are ordered based on similarity of genome constellation, excluding the S1 genotype, and then by collection year.

Excepting the S1 segment, most reoviruses have entirely or almost entirely genotype 1 constellations, with some genomes containing a single genotype 4 L2 or S4 segment. Prototype human reovirus strains Lang and Dearing both have primarily genotype 1 constellations but differ in S1 and L2 genotype and in M2 sub-genotype clade. In general, there do not appear to be strong associations between constellation and animal species or sample collection year for reoviruses containing primarily genotype 1 constellations. Most reoviruses containing a genotype 4 S4 segment are of porcine origin, and a subset of these viruses also contain a genotype 2 M2 segment. It is possible that amino acid differences in the encoded σ3 or μ1 viral capsid proteins confer a replication advantage in specific animal hosts. About half of the reoviruses containing a genotype 4 L2 segment were derived from bats, although this L2 genotype was first detected in humans in the 1950’s. The two reoviruses containing a genotype 6 L2 segment were isolated in China in 2003 and 2004, but from different animal species (Duan et al., 2003; Li et al., 2015; Song et al., 2008). Both of these reoviruses were associated with respiratory illness in the hosts from which they were isolated and caused alveolar damage and other symptoms in mouse and/or macaque models of infection (Duan et al., 2003; He et al., 2005; Li et al., 2015; Song et al., 2014). These effects have not been linked to the L2 segment. Given the limited number of sequences in the analysis, we are hesitant to make inferences about which viruses or segment genotypes preceded others evolutionarily. However, some segments within the predominantly genotype 1 constellations likely were shared via reassortment, and host species does not appear to have posed a substantial barrier to segment transfer in most cases. Limited genetic diversity among primarily genotype 1 reoviruses may facilitate genetic complementation and reassortment during coinfection.

For five of the analyzed reoviruses, several or all genome segments have genotypes that differ from those of the majority of analyzed reovirus sequences. Two reoviruses, SI-MRV08 and prototype T2 strain Jones (Breun et al., 2001; Dermody et al., 1991; Harrison et al., 1999; McCutcheon et al., 1999; Nibert et al., 1990; Seliger et al., 1992; Wiener and Joklik, 1987, 1988, 1989), have entirely genotype 2 constellations. 19-LN21, has an entirely genotype 3 constellation, excluding the S1 segment (Feng et al., 2022). SI-MRV03 (Naglič et al., 2018) has eight genotype 4 segments. Finally, MRV00304/2014 (Anbalagan et al., 2014b) has three genotype 5 segments. Thus, although a predominantly genotype 1 constellation appears to be predominant, reoviruses with genotype 2 or 3 constellations or a mixed-genotype constellation exist in nature.

3.4. Reoviruses with divergent genome constellations

MRV00304/2014, SI-MRV03, 19-LN21, Jones, and SI-MRV08 are the rare few reoviruses among those analyzed that exhibit substantial genotype variability in their genome constellations. So, what is special about these reoviruses? MRV00304/2014 was isolated from a calf with diarrhea in the United States in 2014 (Anbalagan et al., 2014b). The MRV00304/2014 L1, M1, and M2 segments have a unique genotype. The M1-encoded μ2 protein is 75–80% identical, and the M2-encoded μ1 protein is ~90–92% identical to that of other reoviruses in the current analysis. These are the lowest amino acid identities detected for these proteins in our analysis (data not shown). At 96–97% identical, the L1-encoded λ3 protein of MRV00304/2014 is more similar to other analyzed λ3 proteins. Differences in L1, M1, and M2 for MRV00304/2014 compared with other reoviruses are reflected in the branch lengths in ML trees based on nucleotide sequences (Figs. 3 and S1). Since MRV00304/2014 is the only bovine reovirus in the analyzed collection, comparison with other bovine reovirus sequences may reveal whether there is any species specificity for these L1, M1, and M2 genotypes. SIMRV03 (Naglič et al., 2018) was isolated from a bat in Slovenia in 2012. Although all segments except M2 and S4 are assigned a unique genotype in the current analysis, the nucleotide and amino acid identities of most segments are higher for this virus than for 19-LN21, Jones, and SI-MRV08, suggesting a closer evolutionary relationship (Figs. 2–4, S1–S2, and Table 1). For nearly all segments, 19-LN21, Jones, and SIMRV08 cluster separately from other reovirus sequences, with Jones and SI-MRV08 clustering together (Figs. 2–4 and S1–S2). These viruses also have some of the lowest amino acid identities of the collection, including for the L1-encoded λ3, L2-encoded λ2, L3-encoded λ1, M3-encoded μNS, S2-encoded σ2, S3-encoded σNS, and S4-encoded σ3 proteins (Table 1 and not shown). 19-LN21 was isolated from a bat in the United States in 2019 (Feng et al., 2022). It has been shown to have a close evolutionary relationship with strain T2W, which was one of multiple pathogens detected in a fatal case from an immunocompromised infant in Canada in 1997 (Hermann et al., 2004; Jiang et al., 2006). Despite having been isolated more than 50 years apart and on different continents, human reoviruses Jones and SI-MRV08 share a genome constellation that distinguishes them from other reoviruses in the analysis.

3.5. Reassortment

The extent to which reoviruses with divergent genome constellations reassort with other reoviruses is currently unclear. MRV00304/2014 and SI-MRV03 each contain at least a few genome segments with the same genotypes as other more frequently detected reoviruses (Fig. 6). For 19-LN21, Jones, and SI-MRV08, no reassortment with other genotypes was detected in our analysis other than for the M2 genotype of Jones and SI-MRV08, which was detected in a small number of porcine reovirus genomes (Fig. 6). It is unclear whether the lack of detection of reassortants is due to incompatibility of segments or to low prevalence or inadequate sampling of reoviruses containing the genotypes of interest. The collection of reoviruses analyzed in the current study is relatively small, limited in host diversity, and includes few viruses from Africa, Central or South America, or Australia. In tissue culture, Jones genome segments can be individually introduced into a Dearing reovirus genetic background (Moody and Joklik, 1989). Reassortment under artificial conditions, however, does not necessarily indicate that intergenotype reassortment would be favorable in a natural setting. It is possible that we would detect additional evidence of reassortment between genotypes if we included partial reovirus genome sequences in the current analysis (Feng et al., 2022). For human species A rotaviruses, strains with one of two discrete genotype constellations, which may include specific combinations of segments encoding outer-capsid proteins, appear to have been most successful at sustaining human infections and causing disease (Matthijnssens and Van Ranst, 2012). Thus, there may be pressure for segmented viruses to maintain specific gene sets. More exhaustive studies and the addition of greater numbers of complete reovirus genome sequences collected from more geographic sites to the database likely will reveal reovirus reassortment allowances and biases in the future. Although increased levels of genetic diversity among reoviruses, which is underscored by rare genotypes, may decrease reassortment potential, they also may increase the overall adaptability and host range of these viruses.

Reassortment may occur among reoviruses containing primarily genotype 1 segments, and our analysis may underestimate the incidence of such reassortment by detecting only intergenotype reassortants. For example, Harima et al. reported that the sequences of many genome segments of three porcine reoviruses circulating in Zambia in 2018, Strain 85, Strain 96, and Strain 117, shared high nucleotide identity (Harima et al., 2020). However, the S3 segment of Strain 96 was more closely related to sequences from mink, human, and a bat reovirus, whereas the other two strains clustered on a distinct branch of a phylogenetic tree along with bovine and human reoviruses. They hypothesize that reassortment led to this difference as well as differences in the L1 and M3 segments of Strain 117. In our analysis, the three porcine reoviruses have identical genotypes for each segment and identical genome constellations (Fig. 6). Thus, we detect no evidence of reassortment. Two porcine reoviruses collected from a single farm in Italy in 2016 and 2018, MRV3/Swine/Italy/52154–4/2016 and MRV2/Swine/Italy/90178–3/2018, were reported to differ in S1 and M2 sequence and to have genome constellations that arose through multiple reassortment events. In our analysis, the two reoviruses differed in S1 serotype and genotype and in M2 clade. Thus, our constellation analysis conducted primarily at the genotype level can detect reassortment among viruses with substantial genetic diversity, but a different analysis may be required to detect reassortment among more genetically similar reoviruses. Notably, phylogenetic and constellation analyses have been applied towards distinguishing and determining the stability of viral genomic sub-constellations (De Grazia et al., 2016).

3.6. Reovirus genome-based classification

A useful classification system for sequenced reoviruses, like that currently used for rotaviruses (Matthijnssens et al., 2008a), should include information regarding genotype for each of the ten segments. We propose an ordered listing, in which S1 serotype and genotype are listed first, followed by genotypes of the remaining segments in order from largest to smallest, as shown in Fig. 6. In this case, the genome constellation for Lang would be T1(1)1–1-1a-1-1c-1-1-1-1 (or simply T1 (1)-1–1–1-1-1-1-1-1-1) and would represent the genotypes for segments S1-L1-L2-L3-M1-M2-M3-S2-S3-S4. The genome constellation for Jones would be T2(6)-2–2–2-2-2-2-2-2-2, and that for Dearing would be T3(1)-1–4-1a-1-1a-1-1-1-1 (or simply T3(1)-1–4–1-1-1-1-1-1-1). Such a classification system would reveal genetic information about the complete reovirus genome and simplify the search for evidence of genetic linkage or reassortment between more distantly related reoviruses.

4. Conclusions

For many decades, researchers have focused on a small number of prototype strains when studying reovirus biology. Lang, Jones, and Dearing, which are considered prototype reoviruses, have long been known to differ in the sequence of the S1 gene and properties of the σ1 attachment protein it encodes. To more thoroughly represent the breadth of reovirus diversity, the complete genome sequence should be considered. We propose a genotyping scheme for each reovirus genome segment, with minimum nucleotide identities of 77–88% for most genotypes that contain many representative sequences. In the current analysis, we have found that for most sequenced reoviruses, segments other than S1 cluster into a small number of genotypes and a limited array of genome constellations that do not differ greatly over time or based on animal host. While the two best studied reoviruses, Lang and Dearing, differ in the properties of the attachment protein, most of their other segments share the same genotype. We find that in addition to S1, Lang and Dearing differ considerably only in L2 sequence. In contrast, SI-MRV03, 19-LN21, Jones, and SI-MRV08 have genome constellations in which genotypes of most segments differ from those of most other sequenced reoviruses. The genotypes of all segments of prototype strain Jones differ from those of both Lang and Dearing. While much research to date has focused on the Lang and Dearing reovirus strains, comparative studies of nucleic acid sequence and secondary structure elements as well as encoded protein functions among the most genetically divergent reoviruses may provide new insights into reovirus biology. By studying reoviruses with segments that differ in genotype across the entire genome, researchers may gain a clearer picture of the breadth of biological properties of reovirus RNAs and their encoded proteins. Thus, we recommend that future research be focused on more genetically divergent reoviruses. In the current analysis, we also found limited evidence for intergenotype reassortment between reoviruses with highly divergent genome constellations. It remains to be determined whether animal host, geographic location, or RNA or protein incompatibilities play a role in intergenotype reassortment restriction, or whether our findings result from sampling limitations. Analysis of available partial sequences and additional complete reovirus genome sequencing may reveal reassortment biases, host preferences, or infection outcomes that are based on reovirus genotype. In the future, we hope to see an expansion of available complete reovirus genome sequences from different hosts and locations, which will permit even more robust genotypic analyses and perhaps validate a new nomenclature system for reoviruses that includes genotypic information for each segment.

Supplementary Material

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Acknowledgements

We thank Dr. Terence Dermody for critical review of the manuscript and helpful discussions. This work was supported by the National Institutes of Health (1R01AI155646). The contents of this publication are solely the responsibility of the authors and do not necessarily represent the views of the National Institutes of Health.

Declaration of Competing Interest

Kristen Ogden reports financial support was provided by National Institutes of Health.

Footnotes

Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.meegid.2023.105421.

Data availability

GenBank accession numbers for all viral genome segment sequences used in the current study are provided in Table S1.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

1
NIHMS1888078-supplement-1.xlsx (18.7KB, xlsx)
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NIHMS1888078-supplement-2.xls (75.5KB, xls)
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NIHMS1888078-supplement-3.xls (71KB, xls)
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NIHMS1888078-supplement-4.docx (1MB, docx)
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NIHMS1888078-supplement-5.xls (67.5KB, xls)
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NIHMS1888078-supplement-6.xls (75KB, xls)
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NIHMS1888078-supplement-7.xls (70KB, xls)
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NIHMS1888078-supplement-8.xls (72KB, xls)
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NIHMS1888078-supplement-9.xls (70KB, xls)
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NIHMS1888078-supplement-10.xls (76KB, xls)
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NIHMS1888078-supplement-11.xls (68KB, xls)
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NIHMS1888078-supplement-12.xls (73.5KB, xls)

Data Availability Statement

GenBank accession numbers for all viral genome segment sequences used in the current study are provided in Table S1.

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