198
Views
0
CrossRef citations to date
0
Altmetric
RESEARCH ARTICLE

Genomic analysis of canine pneumoviruses and canine respiratory coronavirus from New Zealand

ORCID Icon, ORCID Icon, ORCID Icon & ORCID Icon
Pages 191-200 | Received 08 Nov 2023, Accepted 18 Mar 2024, Published online: 22 Apr 2024

Figures & data

Figure 1. Schematic representation of the organisation of the genome of canine respiratory coronavirus (CRCoV; based on isolate BJ232; GenBank accession KX432213). The open reading frames (ORF) are numbered within or above the rectangles, and the protein products of the structural and accessory genes are specified below. The positive-sense, single-stranded, 30.8 kb RNA genome is capped at the 5’ end and expressed through a process of discontinuous transcription. A common leader sequence (L) encoded at the 5′ of the genome is present at the 5’ end of each mRNA. The region sequenced in the current study is shown below the genome, with a thin line indicating the missing sequence.

Figure 1. Schematic representation of the organisation of the genome of canine respiratory coronavirus (CRCoV; based on isolate BJ232; GenBank accession KX432213). The open reading frames (ORF) are numbered within or above the rectangles, and the protein products of the structural and accessory genes are specified below. The positive-sense, single-stranded, 30.8 kb RNA genome is capped at the 5’ end and expressed through a process of discontinuous transcription. A common leader sequence (L) encoded at the 5′ of the genome is present at the 5’ end of each mRNA. The region sequenced in the current study is shown below the genome, with a thin line indicating the missing sequence.

Table 1. Signalment of dogs that were the source of samples used for canine pneumovirus glycoprotein G sequencing.

Figure 2. Evolutionary relationships of canine pneumoviruses based on the analysis of glycoprotein G amino acid sequences (n = 24). The evolutionary history was inferred by using the maximum likelihood method and the JTT matrix-based model (Jones et al. Citation1992). The tree with the highest log likelihood ( –2,648.85) is shown. The percentage of trees in which the associated taxa clustered together in a bootstrap test (100 replicates) is shown below the branches (only values ≥ 50% are shown). Initial tree(s) for the heuristic search were obtained automatically by applying Neighbor-Join and BioNJ algorithms to a matrix of pairwise distances estimated using the JTT model, and then selecting the topology with superior log likelihood value. A discrete Gamma distribution was used to model evolutionary rate differences among sites (five categories (+G, parameter = 0.6156)). The tree is drawn to scale, with branch lengths measured in the number of substitutions per site. All positions with 90% site coverage were eliminated (i.e. <10% alignment gaps, missing data, and ambiguous bases were allowed at any position (partial deletion option)). There were a total of 414 positions in the final dataset. Evolutionary analyses were conducted in MEGA11 (Tamura et al. Citation2021). Tree was visualised using the Interactive Tree of Life online tool (Letunic and Bork Citation2021).

Figure 2. Evolutionary relationships of canine pneumoviruses based on the analysis of glycoprotein G amino acid sequences (n = 24). The evolutionary history was inferred by using the maximum likelihood method and the JTT matrix-based model (Jones et al. Citation1992). The tree with the highest log likelihood ( –2,648.85) is shown. The percentage of trees in which the associated taxa clustered together in a bootstrap test (100 replicates) is shown below the branches (only values ≥ 50% are shown). Initial tree(s) for the heuristic search were obtained automatically by applying Neighbor-Join and BioNJ algorithms to a matrix of pairwise distances estimated using the JTT model, and then selecting the topology with superior log likelihood value. A discrete Gamma distribution was used to model evolutionary rate differences among sites (five categories (+G, parameter = 0.6156)). The tree is drawn to scale, with branch lengths measured in the number of substitutions per site. All positions with 90% site coverage were eliminated (i.e. <10% alignment gaps, missing data, and ambiguous bases were allowed at any position (partial deletion option)). There were a total of 414 positions in the final dataset. Evolutionary analyses were conducted in MEGA11 (Tamura et al. Citation2021). Tree was visualised using the Interactive Tree of Life online tool (Letunic and Bork Citation2021).

Figure 3. Schematic representation of the genomic organisation of the region between the spike (S) protein gene and the envelope (E) protein gene of canine respiratory coronaviruses (CRCoV) and bovine coronavirus (BCoV). Representative viruses are listed on the right. The GenBank accession numbers for these viruses are: 240/05 (EU999954), K9 (GQ918141), K37 (JX860640), K39 (GQ918143), BJ232 (KX432213), 4182 (DQ682406), D187NS_THA2022 (OQ621724), D206NS_THA2022 (OQ621723), PP014_THA2013 (OQ621712), PP146_THA2015 (OQ621713), BCoV Mebus (BCU00735). Isolates T0715, T1030 and T1207 are included based on description in Erles et al. (Citation2007). Dark shading indicates non-expressed regions of the genome.

Figure 3. Schematic representation of the genomic organisation of the region between the spike (S) protein gene and the envelope (E) protein gene of canine respiratory coronaviruses (CRCoV) and bovine coronavirus (BCoV). Representative viruses are listed on the right. The GenBank accession numbers for these viruses are: 240/05 (EU999954), K9 (GQ918141), K37 (JX860640), K39 (GQ918143), BJ232 (KX432213), 4182 (DQ682406), D187NS_THA2022 (OQ621724), D206NS_THA2022 (OQ621723), PP014_THA2013 (OQ621712), PP146_THA2015 (OQ621713), BCoV Mebus (BCU00735). Isolates T0715, T1030 and T1207 are included based on description in Erles et al. (Citation2007). Dark shading indicates non-expressed regions of the genome.

Table 2. Coding capacity and putative protein products expressed from the 3’ end of CRCoV 046/16.

Figure 4. Evolutionary relationships of canine respiratory coronaviruses from various countries based on partial nucleotide sequences of the spike gene (n = 37). The New Zealand sequence is in bold. The evolutionary history was inferred by using the maximum likelihood method and Tamura-Nei model (Tamura and Nei Citation1993). The tree with the highest log likelihood (–5,109.77) is shown. The percentage of trees in which the associated taxa clustered together in the bootstrap test (100 replicates) is shown below the branches for values ≥ 50%. Initial tree(s) for the heuristic search were obtained automatically by applying Neighbor-Join and BioNJ algorithms to a matrix of pairwise distances estimated using the Tamura-Nei model, and then selecting the topology with superior log likelihood value. A discrete Gamma distribution was used to model evolutionary rate differences among sites (five categories (+G, parameter = 0.1139)). The tree is drawn to scale, with branch lengths measured in the number of substitutions per site. All positions with <90% site coverage were eliminated (i.e. <10% alignment gaps, missing data, and ambiguous bases were allowed at any position (partial deletion option)). There were a total of 2,457 positions in the final dataset. Evolutionary analyses were conducted in MEGA11 (Tamura et al. Citation2021). Tree was visualised using Interactive Tree of Life online tool (Letunic and Bork Citation2021).

Figure 4. Evolutionary relationships of canine respiratory coronaviruses from various countries based on partial nucleotide sequences of the spike gene (n = 37). The New Zealand sequence is in bold. The evolutionary history was inferred by using the maximum likelihood method and Tamura-Nei model (Tamura and Nei Citation1993). The tree with the highest log likelihood (–5,109.77) is shown. The percentage of trees in which the associated taxa clustered together in the bootstrap test (100 replicates) is shown below the branches for values ≥ 50%. Initial tree(s) for the heuristic search were obtained automatically by applying Neighbor-Join and BioNJ algorithms to a matrix of pairwise distances estimated using the Tamura-Nei model, and then selecting the topology with superior log likelihood value. A discrete Gamma distribution was used to model evolutionary rate differences among sites (five categories (+G, parameter = 0.1139)). The tree is drawn to scale, with branch lengths measured in the number of substitutions per site. All positions with <90% site coverage were eliminated (i.e. <10% alignment gaps, missing data, and ambiguous bases were allowed at any position (partial deletion option)). There were a total of 2,457 positions in the final dataset. Evolutionary analyses were conducted in MEGA11 (Tamura et al. Citation2021). Tree was visualised using Interactive Tree of Life online tool (Letunic and Bork Citation2021).
Supplemental material

Supplemental Material

Download PDF (93.1 KB)