Codon usage bias analysis of the gene encoding NAD+-dependent DNA ligase protein of invertebrate iridescent virus 6

doi:10.21203/rs.3.rs-3138515/v1

Download PDF

Research Article

Codon usage bias analysis of the gene encoding NAD+-dependent DNA ligase protein of invertebrate iridescent virus 6

https://doi.org/10.21203/rs.3.rs-3138515/v1

This work is licensed under a CC BY 4.0 License

Version 1

posted

You are reading this latest preprint version

The genome of Invertebrate iridescent virus 6 (IIV6) contains a sequence that shows similarity to eubacterial NAD+-dependent DNA ligases. The 615-amino acid open reading frame (ORF 205R) consists of several domains, including an N-terminal domain Ia, followed by an adenylation domain, an OB-fold domain, a helix-hairpin-helix (HhH) domain, and a BRCT domain. Notably, the zinc-finger domain, typically present in NAD+-dependent DNA ligases, is absent in ORF 205R. Since the protein encoded by ORF 205R (IIV6 DNA ligase gene) is involved in critical functions such as DNA replication, modification, and repair, it is crucial to comprehend the codon usage associated with this gene. In this paper, the codon usage bias (CUB) in DNA ligase gene of IIV6 and 11 reference iridoviruses was analyzed by comparing the nucleotide contents, relative synonymous codon usage (RSCU), effective number of codons (ENC), codon adaptation index (CAI), relative abundance of dinucleotides and other indices. Both the base content and the RCSU analysis indicated that the A- and T-ending codons were mostly favoured in the DNA ligase gene of IIV6. The ENC value of 35.64 implied a high CUB in the IIV6 DNA ligase gene. The ENC plot, neutrality plot, parity rule 2 plot, correspondence analysis revealed that mutation pressure and natural selection had an impact on the CUB of the IIVs DNA ligase genes. This findings will improve our comprehension of the CUB of IIV6 DNA ligase and reference genes, which may provide the required information for a fundamental evolutionary analysis of these genes.

Invertebrate iridescent virus 6

ORF 205R

DNA ligase

Codon usage bias

Members of the viral family Iridoviridae (identified as iridovirids) are a varied group of large DNA viruses with circularly permutated, terminally redundant, linear double-stranded DNA genomes surrounded by icosahedral capsid [1]. Alphairidovirinae and Betairidovirinae are the two subfamilies that in this family. The former consists of three genera (Ranavirus, Lymphocystivirus and Megalocytivirus), which infect fish, amphibians, reptiles, and bony fish. Iridovirus, Chloriridovirus, Decapodiridovirus, and Daphniairidovirus are the four genera that make up another subfamily that primarily infect invertebrates like crustaceans and insects [2].

Over the last two decades, reports of iridovirid infections has increased remarkably, reflecting the reality of viruses in the Iridoviridae family, were previously thought to be unnoticeable viruses with minimal economic and ecological effect. It is now understood that iridovirids are prevalent in nature and have a substantial impact on contemporary aquaculture and wildlife [3]. Many insects and crustaceans have been reported with invertebrate iridescent virus (IIV) infections. Host species have been reported most frequently from aquatic environments and terrestrial habitats [4–6]. Invertebrate iridoviruses (IIVs) usually cause either patent or covert infection in insects [7, 8]. Some IIVs from fully aquatic invertebrates have also been reported, but their relationships to other IIVs are unknown due to the lack of biological and genetic information [9, 10].

DNA ligases are crucial for the DNA-related processes, including DNA replication, genetic recombination and DNA repair. They are responsible for catalyzing the formation of phosphodiester bonds, specifically at single-strand breaks in double-stranded DNA. This enzymatic activity enables the sealing of these breaks, ensuring the integrity and stability of the DNA molecule [11]. Based on their cofactor requirements, DNA ligases are categorized into two families: NAD+-dependent DNA ligases, which rely on NAD + as a cofactor, and ATP-dependent DNA ligases, which rely on ATP as a cofactor [12]. ATP-dependent DNA ligases have been detected in the genomes of all domains of life [13–18]. In contrast, NAD⁺-dependent ligases are encountered in halophilic archaea, eubacteria, and certain DNA viruses [19–25].

The Iridovirus genus includes Invertebrate iridescent virus 6 (IIV6), which is also called Chilo iridescent virus (CIV). The genome of IIV6 is a linear double-stranded DNA with a total length of 212,482 base pairs [26]. Within this genome, there are 215 regions known as open reading frames (ORFs), that have the potential to encode proteins [27]. One of these ORFs are predicted to be putative DNA ligase (ORF 205R) according to bioinformatics analysis. The amino acid sequence of ORF 205R (IIV6 DNA ligase gene) shows considerable similarity to DNA ligases of other DNA viruses. In addition, ORF 205R shows a high degree of amino acid sequence homology to the DNA ligase of Borrelia burgdorferi (accession: O51502) [26, 28]. Genomic, transcriptomic, and proteomic studies on the molecular biology of IIV6 have elucidated mechanism of replication, classification, and the identities of viral proteins; however, functional genomics studies in IIV6 are limited [29–36].

The standard genetic code is comprised of 64 codons, with three of them functioning as termination codons. Among these 64 codons, 61 codons are responsible for encoding the 20 standard amino acids. Except for methionine and tryptophan, the remaining amino acids are encoded by 2 to 6 codons, which are commonly referred to as synonymous codons [37]. Nevertheless, there is a variation in the utilization of these codons across different organisms, and this phenomenon is termed as codon usage bias (CUB) [38]. CUB is affected by a range of factors, including natural selection, mutation pressure and nucleotide composition [39]. Viruses exhibit diverse patterns of codon usage, and studying codon usage can offer valuable insights into the genetic evolution of viruses and their ability to adapt to specific host organisms [40, 41].

So far, the complete genome sequences of numerous IIVs were ascertained. Research on the CUB of iridoviruses has been limited, with only a small number of virus species being studied. However, a thorough investigation of CUB of IIV6 DNA ligase gene is currently lacking [42–44]. In our laboratory, we successfully cloned the IIV6 DNA ligase gene into the expression plasmid pET15b. However, no biochemical testing has been performed to assess its activity and substrate specificity.

The main objective of this paper was to examine the synonymous codon usage of the IIV6 DNA ligase gene. A comparative analysis was conducted, contrasting its codon usage patterns with those observed in the DNA ligase genes of eleven species of invertebrate iridoviruses. Additionally, the study investigated potential restriction factors that could potentially influence the observed CUB. The codon usage pattern of the IIV6 DNA ligase gene, along with the comparison results, has the potential to uncover important features of the IIV6 genome. Furthermore, this current study has the potential to provide valuable information regarding the expression and potential functions of the IIV6 DNA ligase.

2.1. Bioinformatics analysis

The nucleotide and amino acid sequences of the DNA ligase gene from IIV6 and eleven other iridoviruses were obtained by downloading the data from the NCBI (https://www.ncbi.nlm.nih.gov/genbank/). Comprehensive information regarding the NAD+-dependent DNA ligase genes of the IIVs (Shrimp hemocyte iridescent virus has two DNA ligases), including their accession numbers and host informations, was shown in Table 1. BLAST alignment of DNA ligase amino acid sequences of IIV6, Escherichia coli (accession: CAD6007609.1), Thermus filiformis (accession: AAC68862.1), Acanthamoeba polyphaga mimivirus (accession: YP_003986805.1), Vaccinia virus (accession: YP_233058.1), and Melanoplus sanguinipes entomopoxvirus (accession: AAC97679.1) was performed to detect similarity between sequences.

Table 1

Details of IIVs DNA ligase genes used for analysis of codon usage
Accession number	Gene	Virus name	Host	Length (bp)
NC_003038.1	205R	Invertebrate iridescent virus 6 (IIV6)	Chilo suppressalis	1848
NC_024451.1	110R	Invertebrate iridescent virus 31 (IIV31)	Armadillidium vulgare	1980
NC_008187.1	MIV052L	Invertebrate iridescent virus 3 (IIV3)	Ochlerotatus taeniorhynchus	2271
NC_023613.1	170R	Invertebrate iridescent virus 25 (IIV25)	Simulium vittatum	1926
NC_021901.1	159R	Invertebrate iridescent virus 22 (IIV22)	Simulium vittatum	1830
NC_015780.1	109R	Invertebrate iridescent virus 9 (IIV9)	Oxycanus dirempta	1890
NC_023615.1	166R	Invertebrate iridescent virus 22A (IIV22A)	Simulium vittatum	1830
NC_023611.1	168R	Invertebrate iridescent virus 30 (IIV30)	Helicoverpa zea	1833
NC_023848.1	AMIV120	Anopheles minimus iridovirus (AMIV)	Anopheles minimus	1914
ON887238.1	185R	Carnivorous sponge associated iridovirus strain MJ4 (CSAIV)	Chondrocladia grandis	1848
NC_055165.1	65R	Shrimp hemocyte iridescent virus (SHIV)	Litopenaeus vannamei	1821
NC_055165.1	55R	Shrimp hemocyte iridescent virus (SHIV)	Litopenaeus vannamei	981
NC_040612.1	87L	Cherax quadricarinatus iridovirus (CQIV)	Cherax quadricarinatus	1821

The domain structure of IIV6 DNA ligase was compared with E.coli LigA. The Conserved Domain Search interface of the NCBI was utilized to identify the distinctive conserved domain structure specific to the DNA ligase superfamily (https://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi). The PROSITE MyDomains image creator tool was used to generate the domain structures (http://www.expasy.org/tools/mydomains/).

2.2. Nucleotide composition analysis

The CAIcal server was utilized to compute the nucleotide content (A%, T%, C%, and G%) as well as the nucleotide contents at the 3rd codon position (A3%, C3%, T3%, and G3%) in the coding sequences of the DNA ligases (http://ppuigbo.me/programs/CAIcal/) [45]. The CodonW program was used to calculate the nucleotide contents (A3s, T3s, G3s, and C3s) at the 3rd position of synonymous codons, as well as the GC contents (GC3s) at the 3rd position synonymous codons. Additionally, the program computed the average values of GC at GC12 positions (http://codonw.sourceforge.net//, written by John Peden).

2.3. Relative synonymous codon usage (RSCU) analysis

To assess the pattern of synonymous codon usage, the RSCU values were calculated for the IIVs DNA ligase genes. This analysis aimed to investigate the features of synonymous codon usage while eliminating the potential effects of amino acid content and coding sequence length across various gene samples. This analysis enables the comparison of codon usage preferences between the virus and its host [41, 46, 47]. The RSCU value was formulated as the ratio between the observed codon usage and its corresponding expected value [47]. A value of 1.0 for the RSCU signifies equal usage frequency among synonymous codons. Values greater than 1.0 or less than 1.0 in the RSCU analysis indicate the abundance or scarcity of specific codons, respectively. Furthermore, in the analysis, codons with RSCU values above 1.6 were classified as overrepresented codons. Conversely, codons with RSCU values below 0.6 were identified as underrepresented codons [48]. In this study, RSCU values of IIVs DNA ligase genes were calculated using CodonW program.

2.4. Effective number of codons (ENC) analysis

The ENC is widely regarded as a highly dependable and robust metric for assessing CUB in genes and genomes and is independent of factors such as the number of amino acid and gene length [49]. The ENC value ranges between 20 and 61. An ENC value of 20 signifies an exceptional bias in codon usage, where only a single codon is selected from each set of synonymous codons. In the absence of bias in codon usage, the ENC value is typically observed to be 61. When ENC is equal to or less than 35, it indicates an extremely strong codon usage bias (Comeron, J. M., Aguadé, 1998; Wright, 1990). The CodonW program was employed to calculate the ENC values.

2.5. ENC-GC3s plot analysis

The ENC plot is extensively utilized to explore the impact of GC3s content on CUB [49], which helps in exploring whether mutation pressure or natural selection is influencing the genes. The following formula was utilized to calculate the expected ENC values [51]:

$${ENC}_{exp}=2+s+\frac{29}{{s}^{2}+(1-{s}^{2})}$$

“s” stands for the given GC3s% value. If the points locate above or near the expected curve (standard curve), it indicates the codon usage is solely constrained by the mutation pressure and the observed ENC values surpass the expected ENC values. Else, if point falls below and deviates from the expected curve, with the observed value being lower than the expected value, it suggests the potential contribution of natural selection in influencing the patterns of codon usage [52].

2.6. Neutrality plot analysis

To assess the impact of mutation pressure and natural selection on the patterns of codon usage of IIVs DNA ligase genes, the analysis of neutrality plot was conducted. In the neutrality plot, the GC12s values are represented on the y-axis (ordinate), while the GC3s values are depicted on the x-axis (abscissa). Each point on the plot represents an individual gene. The GC3s and GC12s values of IIVs DNA ligase genes were calculated by CodonW program and then linear regression analysis were performed. The presence of a significant correlation with the regression line slope suggests the influence of mutational forces on the patterns of codon usage. A significant correlation is observed between the GC12s and GC3s values when the regression slope is approximately 1, it suggests a stronger impact of mutation pressure on the genes. Conversely, when the regression slope is 0, it reveals a considerable impact of natural selection on the patterns of codon usage. [53, 54].

2.7. Parity rule 2 (PR2) plot analysis

The analysis of PR2 plot was utilized to examine the impact of mutation pressure and natural selection on the CUB in DNA ligase genes. The PR2 plot was constructed using the AT bias [A3/(A3 + T3)] as the y-axis and the GC bias [G3/(G3 + C3)] as the x-axis for the third codon position (A3s, T3s, G3s, and C3s) [55]. In the PR2 plot, the midpoint of the plot is situated at 0.5, shows that A and T as well as G and C are equally represented. This symmetry suggests the absence of bias in both mutation pressure and natural selection between the DNA strands. When the bias value is greater than 0.5 in the PR2 plot, it signifies a preference for purine nucleotides (A or G) over pyrimidine nucleotides (T or C). Conversely, it means that pyrimidine nucleotides are preferred over purine nucleotides, indicating that both factors affect the observed CUB in the genes [56].

2.8. Codon adaptation index (CAI) analysis

CAI is a valuable metric that is used to assess and quantify the bias in synonymous codon usage. It provides insights into gene expression levels and can be used to evaluate how well viral genes have adapted to their host organisms. The CAI is between 0 and 1, where higher CAI values indicate a greater degree of adaptability of a sequence to its host [47]. The CAI values were determined by utilizing the CAIcal server, which takes into account the synonymous codon usage pattern of the host organisms as a references. The reference synonymous codon usage values were obtained from HIVE-CUTs databases (https://hive.biochemistry.gwu.edu/review/codon2), in which the host species were Chilo suppresalis, Armadillidium vulgare, Ochlerotatus taeniorhynchus, Simulium vittatum, Oxycanus dirempta, Helicoverpa zea, Anopheles minimus, Chondrocladia grandis, Litopenaeus vannamei and Cherax quadricarinatus, as the existing hosts of IIVs (Table 1). The expected CAI values (E-CAI) for the coding sequences of DNA ligases were determined using the eCAIcal server [45, 47].

2.9. Correspondence analysis (COA)

COA is a valuable multidimensional statistical technique utilized to obtain a deeper understanding of patterns of codon usage [57]. To investigate the predominant factors of codon usage pattern in DNA ligase genes, COA was performed in this study. The CodonW program was employed to calculate the RSCU values for 59 codons, except for the start codon (ATG) for Methionine, the Trp codon (TGG), and three stop codons.

2.10. Relative dinucleotide abundance analysis

The codon usage in viruses is influenced by their characteristic frequency of 16 dinucleotides [58]. The method proposed by Kariin and Burge was employed to evaluate the relative dinucleotide abundance in the DNA ligase genes [59].

The EMBOSS COMPSEQ program (https://www.bioinformatics.nl/cgi-bin/emboss/compseq) was employed to determine the relative dinucleotide abundance in DNA ligase genes, utilizing the equation below:

$$\text{ρxy=}\frac{\text{ ƒxy}}{\text{ƒyƒx}}$$

In this equation, ƒx represents the frequency of base X, ƒy stands for the frequency of base Y, ƒyƒx means the expected frequency of the dinucleotide XY, and ƒxy stands for the actual frequency of the dinucleotide XY. If ρxy is more than 1.23, it suggests that the XY dinucleotide is overrepresented compared to random mononucleotides. Conversely, if ρxy is less than 0.78, it suggests that the XY dinucleotide is underrepresented in comparison to random mononucleotides [60].

2.11. General average hydropathicity (Gravy) and aromaticity (Aroma) analysis

The aromaticity and hydropathicity of a gene product are essential factors that provide valuable insights into the impact of natural selection. The Aroma value represents aromaticity, while the Gravy value represents hydropathicity [61]. The Gravy value ranges between − 2 and 2, with a positive value indicating a hydrophobic protein and a negative value indicating a hydrophilic protein. Aromaticity refers to the presence of aromatic amino acids within the translated gene product. The Gravy and Aroma indices were computed using the CodonW program.

2.12. Statistical analysis

The statistical analysis in this study was conducted using the OriginPro 9.0 software. To perform correlation analysis, Spearman's rank correlation test was employed. P-values below 0.05 were deemed significant to determine the presence of a statistically significant correlation.

3.1. Conserved domain structure analysis of IIV6 DNA ligase

The IIV6 genome contains a coding sequence that produces a 615-amino acid protein, which has been identified as an NAD+-dependent DNA ligase. BLAST homology searches revealed that the DNA ligase protein in the IIV6 genome exhibits low identity with DNA ligases from previously characterized organisms, including Escherichia coli (24%), Thermus filiformis (22%), Acanthamoeba polyphaga mimivirus (31%), Vaccinia virus (22%), and Melanoplus sanguinipes entomopoxvirus (30%) [11, 22, 25, 62, 63]. Despite the relatively low sequence similarity, IIV6 DNA ligase protein displays several conserved residues that play a role in DNA ligase activity in related proteins. One of these residues is lysine 101, which is located within the conserved motif I KxDG and serves as the site for AMP binding. IIV6 DNA ligase has the catalytic core composed of an adenylation domain (amino acid 57–285) and OB-fold domain (amino acid 293–362). The IIV6 DNA ligase core is preceded by an N-terminal Ia domain (amino acid 1–56), which contains the nicotinamide mononucleotide binding site that is present in all NAD+-dependent DNA ligases [64] and by two C-terminal domains: a helix-hairpin-helix (HhH) domain (amino acid 471–520) and a BRCT domain (amino acid 549–612) and the zinc finger domain is absent in IIV6 DNA ligase (Fig. 1).

3.2. Compositional analysis in IIVs DNA ligase gene

To emphasize the possible impact of nucleotide contents on codon usage, we initially analyzed the nucleotide contents of the DNA ligase genes (Table 2). Analysis of base composition of IIVs DNA ligase genes demonstrated that the mean values of A%, G%, C% and T% were 36.69, 19.90, 15.11, and 28.30, respectively (Fig. 2A). It was found that the A/T nucleotide frequencies in IIVs DNA ligase genes were significantly higher compared to the G/C nucleotide frequencies. Likewise, the nucleotides A/T were most abundant in the IIV6 DNA ligase gene, with compositions of 42.37% and 31.60%, respectively, followed by G (14.23%) and C (11.80%). To obtain a more comprehensive understanding of how nucleotide content influences the pattern of codon usage in the DNA ligase genes of IIVs, we calculated the nucleotide content specifically at the 3rd position of synonymous codons (A3, T3, C3, G3) (Table 2). The nucleotide content at the 3rd position of synonymous codons was found to be as follows: A3 (46.34%), T3 (45.63%), C3 (18.87%), and G3 (19.34%) (Fig. 2B).These findings suggest that A/T-ending codons may be more prevalent than G/C-ending codons, and this pattern was consistently observed in the IIV6 DNA ligase gene. These results suggest that in IIVs DNA ligase genes, compositional factors play a crucial role in determining the total nucleotide content and the nucleotide content at the 3rd position.

Table 2

Nucleotide composition analysis of IIVs DNA ligase genes
IIVs DNA ligase genes	A%	C%	T%	G%	A3s%	C3s%	T3s%	G3s%	AT%	GC%	GC1%	GC2%	AT3%	GC3s%	GC12%	ENC	CAI	E-CAI
IIV6 205R	42.37	11.80	31.60	14.23	63.32	10.26	51.71	6.89	73.97	26.03	37.66	26.95	86.53	12.35	32.35	35.64	0.84	0.86
IIV31 110R	35.96	16.82	29.14	18.08	45.82	18.49	46.72	18.75	65.10	34.90	41.36	33.94	70.61	27.57	37.70	48.84	0.71	0.73
IIV3 MIV052L	29.19	23.38	22.63	24.79	28.03	39.18	26.13	31.84	51.83	48.17	63.80	38.71	43.20	54.72	43.90	55.27	0.49	0.48
IIV25 170R	39.20	12.36	31.67	16.77	52.65	11.00	54.58	12.06	70.87	29.13	39.88	29.60	82.09	16.77	34.80	40.70	0.48	0.56
IIV22 159R	40.16	11.42	31.75	16.67	54.84	9.68	57.42	7.65	71.91	28.09	40.16	29.84	85.74	12.70	35.05	39.40	0.48	0.57
IIV9 109R	38.89	12.65	31.90	16.56	52.39	11.75	55.05	10.30	70.79	29.21	40.63	29.52	82.54	16.29	35.30	39.91	0.75	0.85
IIV22A 166R	39.95	11.26	31.91	16.89	54.74	9.01	58.15	7.39	71.86	28.14	40.49	30.16	86.23	12.06	35.35	37.26	0.49	0.56
IIV30 168R	39.83	11.51	31.81	16.86	53.66	10.06	57.39	8.62	71.63	28.37	39.77	30.11	84.78	13.68	35.00	38.77	0.75	0.79
AMIV 120	30.88	19.59	24.92	24.61	31.17	28.08	34.34	35.18	55.80	44.20	47.49	36.05	50.94	47.90	41.85	55.82	0.50	0.54
CSAIV 185R	29.38	22.29	21.43	26.89	27.53	38.64	24.42	37.91	50.81	49.19	49.19	37.82	39.45	58.67	43.45	57.50	0.51	0.61
SHIV 65R	39.32	12.90	28.61	19.17	50.78	18.14	43.54	22.82	67.93	32.07	37.40	28.17	69.36	28.69	32.70	46.32	0.54	0.59
SHIV 55R	32.52	17.53	21.92	28.03	36.72	22.89	40.16	29.18	54.43	45.57	61.47	34.86	59.63	39.18	48.10	55.70	0.66	0.63
CQIV 087L	39.32	12.96	28.56	19.17	50.78	18.14	43.54	22.82	67.87	32.13	37.40	28.34	69.36	28.69	32.80	46.25	0.83	0.83
Mean	36.69	15.11	28.30	19.90	46.34	18.87	45.63	19.34	64.99	35.01	44.36	31.85	70.03	28.41	37.57	45.95	0.62	0.68
SD	0.045	0.043	0.041	0.045	0.115	0.106	0.116	0.113	0.085	0.085	0.088	0.039	0.169	0.167	0.050	0.079	0.14	0.13
A3, T3, C3, and G3 represent the frequency of the nucleotide A, T, C, and G at the third positions of codons; GC12 represents the G + C content at the first and second positions of codons; GC3s represents the frequency of the nucleotide G + C at the third positions of synonymous codons; ENC represents the effective number of codons; CAI represents codon adaptation index

Examining the GC content at each codon position provides a useful tool for assessing base composition bias and understanding its potential implications in molecular evolution and genetic processes. The mean GC nucleotide contents were 44.36% at the first codon position (GC1); 31.85% at the second codon position (GC2); 37.57% at the first and second codon position (GC12). Based on the analysis, the mean AT content was determined to be 64.99%, while the mean GC content was calculated to be 35.01% (Fig. 2C). Additionally, the mean AT3 content was found to be 70.03%, and the mean GC3 content was 28.41% (Fig. 2D). Similar results were found in IIV6 DNA ligase coding sequence. These findings show that the IIVs DNA ligase coding sequences are AT-rich and there is a preference for A/T nucleotides at the third codon position.

3.3. RSCU analysis

To examine the patterns of synonymous codon usage and assess the potential bias towards A/T-terminated codons, we calculated the RSCU for codons in the IIV6 DNA ligase and compared with that of its host (Table 3). Among the 18 most prevalent codons, the majority of them were A/T-terminated codons. Specifically, there were eleven T-ending codons, including TGT (C), GAT (D), TTT (F), CAT (H), AAT (N), CCT (P), TAT (Y), GCT (A), ATT (I), GTT (V), and TCT (S). Additionally, there were seven A-ending codons, namely TTA (L), CAA (Q), AAA (K), GAA (E), AGA (R), TCA (S), and GGA (G). Remarkably, the results revealed a notable trend where a majority of the over-represented codons (RSCU > 1.6) in the IIV6 DNA ligase gene was were found to have A-ended nucleotides. Conversely, the most under-represented codons (RSCU < 0.6) had C-ended, as illustrated in Table 3. These findings strongly indicate that mutation pressure played a substantial role in influencing the codon usage patterns observed in the IIV6 DNA ligase gene.

Table 3

The relative synonymous codon usage frequency of IIV6 DNA ligase gene (IIV6 205R) and natural host of IIV6
		RSCU				RSCU
AA	Codon	IIV6 205R	C. Suppressalis	AA	Codon	IIV6 205R	C. suppressalis
Phe (F)	TTT	1.71	1.71	Ala (A)	GCT	2.18	2.07
	TTC	0.29	0.29		GCC	0.00	0.40
Leu (L)	TTA	3.43	3.54		GCA	1.82	1.49
	TTG	0.76	0.49		GCG	0.00	0.04
	CTT	1.05	0.85	Tyr (Y)	TAT	1.33	1.75
	CTC	0.10	0.23		TAC	0.67	0.25
	CTA	0.38	0.77	His (H)	CAT	1.75	1.55
	CTG	0.29	0.11		CAC	0.25	0.45
Ile (I)	ATT	1.50	1.70	Gln (Q)	CAA	1.83	1.66
	ATC	0.32	0.30		CAG	0.17	0.34
	ATA	1.18	1.80	Asn (N)	AAT	1.68	1.68
Val (V)	GTT	1.89	1.52		AAC	0.32	0.32
	GTC	0.42	0.24	Lys (K)	AAA	1.92	1.85
	GTA	1.47	2.00		AAG	0.08	0.15
	GTG	0.21	0.24	Asp (D)	GAT	1.54	1.63
Ser (S)	TCT	2.63	2.13		GAC	0.46	0.37
	TCC	0.00	0.75	Glu (E)	GAA	1.73	1.71
	TCA	1.69	1.83		GAG	0.27	0.29
	TCG	0.00	0.19	Cys (C)	TGT	1.60	1.38
	AGT	1.31	0.62		TGC	0.40	0.63
	AGC	0.38	0.58	Arg (R)	CGT	0.00	0.42
Pro (P)	CCT	1.88	1.38		CGC	0.55	0.53
	CCC	0.24	1.22		CGA	0.55	2.84
	CCA	1.88	1.38		CGG	0.00	0.21
	CCG	0.00	0.03		AGA	4.36	1.41
					AGG	0.55	0.49
Thr (T)	ACT	1.16	1.48	Gly (G)	GGT	1.00	1.12
	ACC	0.21	0.98		GGC	0.13	0.12
	ACA	2.63	1.39		GGA	2.63	2.44
	ACG	0.00	0.14		GGG	0.25	0.32
AA, amino acid; RSCU, relative synonymous codon usage value. Green colors denote codons favored by IIV6 DNA ligase gene and host (RSCU > 1). Overrepresented (RSCU ≥ 1.6) and underrepresented (RSCU < 0.6) codons are marked as bold with red and blue colors, respectively. The optimal codons for IIV6 DNA ligase gene are underlined

Similar patterns of codon usage were observed in the DNA ligase genes of other IIVs. These genes showed a preference for specific codons such as ATT (I), TCT (S), TTA (L), and AGA (R), which were consistently favored across the codons (Fig. 3). These results provide further evidence that A/T-terminated codons are favored in the IIVs DNA ligase genes.

To identify the potential impact of the host organism on the CUB of the IIV6 DNA ligase gene, the codon usage patterns of the DNA ligase gene and those of its host (Chilo suppressalis) were compared. The analysis revealed that out of the fifty nine synonymous codons in the IIV6 DNA ligase gene, 44 codons showed similarity to those found in Chilo suppressalis, the host organism (Table 3). In particular, codons such as TTT (F), TTA (L), ATT (I), TCT (S), CCT (P), ACT (T), GCT (A), TAT (Y), CAT (H), AAT (N), AAA (K), GAA (E), and GGA (G) showed a close similarity between the IIV6 DNA ligase gene and its host organism. However, codons like AGT (S), CCC (P), ACA (T), CGA (R), and AGA (R) exhibited a significant discrepancy between the IIV6 DNA ligase gene and its host. The consistency observed in the patterns of codon usage between the IIV6 DNA ligase gene and its natural host may contribute to enhanced translational efficiency of viral genes.

3.4. Analysis of the effective number of codons (ENC) and ENC plot

The ENC is a vital parameter for assessing codon usage patterns, providing valuable information about codon usage bias and the factors affecting it. The research conducted in this study examined different ENC values (ranging from 35.64 to 57.50) for the DNA ligase genes of IIVs. The average ENC value of 45.95 indicated a low level of bias in codon usage within these genes (Table 2). The ENC values of IIVs DNA ligase genes exhibited significant differences, particularly the ENC value (35.64) of IIV6 DNA ligase gene was notably lower compared to the other IIVs DNA ligase genes. This indicates that the IIV6 DNA ligase gene exhibits a slightly elevated level of codon usage bias when compared to the other genes.

In order to conduct a more in-depth analysis of the CUB within the genes, an ENC-GC3s plot was created (Fig. 4). The results suggest that both mutational pressure and natural selection make a contribution the codon usage patterns observed in the DNA ligase genes of IIVs. This is supported by most of the data points lying below the expected curve, demonstrating the influence of selective forces, while a smaller number of points are positioned above the curve, suggesting the impact of mutational pressure.

3.5. Analysis of the neutrality plot

The analysis of a neutrality plot can provide insights into how natural selection and mutational pressure affect the CUB of genes. Therefore, the neutrality plot was generated between GC12 values and GC3 values (Fig. 5). The analysis revealed a significant positive correlation (r = 0.0476, p < 0.05) between GC12 and GC3 values. the regression line's slope was determined to be 0.2359, suggesting that approximately 23.59% of the observed codon usage bias can be attributed to direct mutation pressure. Conversely, the remaining 76.41% of the bias was determined to be influenced by natural selection. The results of the study suggest that mutation pressure possessed a limited influence on the CUB observed in the IIVs DNA ligase genes. In contrast, the predominant factor shaping the bias was likely natural selection.

3.6. PR2 bias plot analysis

The PR2 bias plot was utilized to evaluate and analyze the effect of mutational pressure and natural selection on the CUB in the DNA ligase genes of IIVs. This plot provided a visual representation of the roles played by these factors in shaping the observed CUB patterns (Fig. 6 ). In the PR2 bias plot, the AT bias was plotted against the GC bias to assess the deviation from the expected A = T and C = G pattern. Interestingly, here, a slight deviation was observed in the PR2 bias plot, indicating a non-equivalence between adenine (A) and thymine (T), as well as between guanine (G) and cytosine (C) at the third codon positions of the DNA ligase genes in IIVs. The analysis revealed that the mean AT bias value was 0.50, indicating an equal preference for A and T nucleotides, while the mean GC bias value was 0.49, indicating a slightly higher tendency for G over C nucleotides within the DNA ligase gene sequences. The results demonstrated a preference for A and G nucleotides (Purines) over T and C nucleotides (Pyrimidines), implying that both mutational pressure and natural selection contribute to the CUB observed in IIVs DNA ligase genes.

3.7. Codon adaptation index (CAI) analysis

CAI is an index utilized to assess the degree of codon usage bias or adaptation of a gene to its host organism. The CAI values were computed for all codons in the IIVs DNA ligase genes using the codon usage data from ten different host organisms (Table 1), including Chilo suppressalis, Armadillidium vulgare, Ochlerotatus taeniorhynchus, Simulium vittatum, Oxycanus dirempta, Helicoverpa zea, Anopheles minimus, Chondrocladia grandis, Litopenaeus vannamei and Cherax quadricarinatus as a reference set. The findings of the present study indicate a tendency towards higher CAI values (> 0.5) in the IIVs DNA ligase genes, suggesting that these genes exhibit a better level of adaptation to their respective host organisms (except for IIV3 MIV052L, IIV25 170R, IIV22 159R, IIV9 109R, IIV22A 166R) (Table 2). The CAI values of IIVs DNA ligase genes exhibited a range of 0.48 to 0.84, with a mean value of 0.62. The CAI value of IIV6 DNA ligase gene in relation to C. suppressalis was 0.84, and was remarkably higher than others.

To further validate the statistically important differences in CAI values, the E-CAI values were calculated for the IIVs DNA ligase genes; their E-CAI values exhibited a range of 0.48 to 0.86, with a mean value of 0.68 (Table 2). The E-CAI value of IIV6 DNA ligase gene was 0.86 (p < 0.05), indicating the adaption of IIV6 DNA ligase gene to its host and revealing that the sequences had normal distribution. Similar results were also found in other IIVs DNA ligase genes.

3.8. Correspondence analysis

To assess the main patterns of variation in codon usage among DNA ligase genes, COA was conducted using the RSCU values. The results of the COA analysis indicated that axis 1 explained 58.74% of the total variation, followed by axis 2 with 14.6%, axis 3 with 4.12%, and axis 4 with 1.02%. These results suggest that the first axis accounts for a major role in explaining the variation in RSCU values, while the second axis contributes to a lesser extent. The higher percentage of variation explained by axis 1 suggests that it captures the most significant patterns and trends in the codon usage data. To gain a deeper understanding of the dispersion of synonymous codon usage patterns, we conducted further analysis by examining the dispersion in the plane defined by the first two principal axes of COA. The data points exhibit a broad distribution across the entire graph (Fig. 7A). When the codons were ordered according to their RSCU values across the two primary axes of COA, it was observed that A- and T-terminated codons were positioned closer to axis 1 compared to C- and G-terminated codons (Fig. 7B).

3.9. Dinucleotide abundance frequency analysis

In order to assess the possible impact of dinucleotide composition on codon usage bias, the relative frequencies of the sixteen dinucleotides were computed for the IIVs DNA ligase genes (Table 4). The results revealed a non-random distribution of relative dinucleotide frequencies in the IIVs DNA ligase genes. The relative frequencies of the dinucleotides AC, CA, CT, GA, and GT were found to be consistent with the expected theoretical frequencies, which are typically close to 1 (mean ± SD = 0.956 ± 0.105, 1.045 ± 0.093, 0.919 ± 0.162, 1.037 ± 0.162 and 0.984 ± 0.112, respectively). None of the dinucleotides were over-represented and one dinucleotide (TA = 0.675 ± 0.139) was under-represented in IIVs DNA ligase genes (Fig. 8). Furthermore, the analysis revealed that 90% of the frequencies among the 16 dinucleotides fell within the normal range of 0.78 to 1.23.

Table 4

Relative abundance of the 16 dinucleotides in IIVs DNA ligase genes
Dinucleotides	Range	Means ± SD
AA	0.916–1.365	1.187 ± 0.111
AC	0.780–1.128	0.956 ± 0.105
AG	0.583–1.089	0.860 ± 0.153
AT	0.811–1.042	0.877 ± 0.090
CA	0.933–1.207	1.045 ± 0.093
CC	0.664–1.509	1.180 ± 0.279
CG	0.451-1.600	0.880 ± 0.402
CT	0.594–1.083	0.919 ± 0.162
GA	0.841–1.261	1.037 ± 0.162
GC	0.623–1.128	0.824 ± 0.145
GG	0.932–1.422	1.142 ± 0.184
GT	0.813–1.109	0.984 ± 0.112
TA	0.489–0.819	0.675 ± 0.139
TC	0.875–1.485	1.135 ± 0.247
TG	0.988–1.345	1.163 ± 0.118
TT	0.884–1.316	1.205 ± 0.115

For IIV6 DNA ligase gene, the over-represented dinucleotides were GG (1.283) and TT (1.274) while the under-represented dinucleotides were TA (0.780) and CG (0.451). To evaluate the possible impact of under-representation of CG and TA dinucleotides on the codon usage pattern, the RSCU values of the eight codons containing CG (CCG, GCG, TCG, ACG, CGC, CGG, CGT, and CGA) were examined. All codons containing CG were found to be under-represented (RSCU < 0.6), indicating that they were not preferentially utilized in the codon usage pattern. Two (CTA and TAC) of six codons containing TA were under-represented (Table 3). Nevertheless, the RSCU values of the four codons containing TA (TTA, ATA, GTA, and TAT) indicated that these codons were preferentially selected and utilized in the codon usage pattern. Similarly, the impact of over-representation of TT and GG on CUB was investigated by analyzing the RSCU values of the seven codons containing TT (TTT, TTC, TTA, TTG, CTT, ATT, and GTT) and the six codons containing GG (CGG, AGG, GGC, GGA, GGG, and GGT). Out of the seven codons containing TT, five (TTT, TTA, CTT, ATT, and GTT) were found to be over-represented (RSCU > 1.6). This suggests a preference for these specific codons in encoding their relevant amino acids within the DNA ligase genes. Among the six codons containing GG, only one codon (GGA) was found to be over-represented. The findings imply that the CUB of the IIV6 DNA ligase gene can be affected by the frequency of dinucleotides.

3.10. Correlation analysis

To delve deeper into the impact of natural selection or mutational pressure on the CUB within the DNA ligase genes of IIVs, a correlation analysis was conducted. A high correlation value (r) close to 1 indicates that translational selection is the primary factor driving the CUB. On the other hand, a low correlation (approaching 0) indicates that mutation may have a stronger influence compared to translational selection on the CUB [65].

Therefore, Spearman's rank correlation analysis was conducted to examine the relationship between nucleotide compositions (A, T, C, G, and GC), ENC values, and codon composition (A3s, T3s, C3s, G3s, and GC3s) of IIVs DNA ligase genes (Table 5). The results displayed a substantial negative correlation between A or T and C3s, G3s, and GC3s in the IIVs DNA ligase genes. Conversely, a substantial positive correlation was identified between A or T and A3s, T3s. Furthermore, C, G, or GC exhibited a significant negative correlation with A3s and T3s, but a significant positive correlation with C3s, G3s, and GC3s. The ENC values of IIVs DNA ligase genes seemed to show a positive correlation with C3s, G3s, GC3s, while the T3s, A3s have a negative correlation with ENC. The observed relationships strongly indicate the importance of nucleotide composition, influenced by mutational pressure, in determining the codon usage patterns of IIVs DNA ligase genes.

Table 5

Correlation analysis between nucleotide compositions (A%,T%, C%, G%, GC), the ENC values and codon composition ( A3s, T3s, C3s, G3s, and GC3s) of IIVs DNA ligase genes
	A3s	T3s	C3s	G3s	GC3s
A%	0,95041*	0,79614*	-0,91736*	-0,88981*	-0,88981*
T%	0,8331*	0,95173*	-0,88*	-0,88*	-0,90759*
C%	-0,95592*	-0,95592*	1	0,92837*	0,95592*
G%	-0,87724*	-0,80828*	0,79724*	0,88552*	0,86621*
GC	-0.9931*	-0.8831*	0.9491*	0.9546*	0.9546*
ENC	-0,96011*	-0,87758*	0,9216*	0,97112*	0,95461*
The values in the table refer to correlation coefficient “r” values in a correlation analysis.*P-value < 0.05

The correlation analysis conducted on the IIVs DNA ligase genes revealed a significant positive correlation between axis 1 and GC3s, GC, C, G, C3s, G3s, and ENC. Conversely, a significant negative correlation was found between axis 1 and A, T, A3s, and T3s (Table 6). In contrast, axis 2 showed no significant correlations with any nucleotide constraints in the IIVs DNA ligase genes.

Table 6

Correlation analysis between A, T, C, G, ENC, A3s,T3s, C3s, G3s, GC3s, GC and the first axis values
	A%	T%	C%	G%	ENC	A3s	T3s	C3s	G3s	GC3s	GC
Axis 1
r	-0,85557*	-0,93664*	0,96561*	0,81543*	0,92857*	-0,9271*	-0,97662*	0,96561*	0,95461*	0,97662*	0.9231*
P	< 0.05	< 0.05	< 0.05	< 0.05	< 0.05	< 0.05	< 0.05	< 0.05	< 0.05	< 0.05	< 0.05
The values in the table refer to correlation coefficient “r” values in a correlation analysis.*P-value < 0.05

Table 7

Correlation analysis among the first axis values, ENC, A3s, T3s, G3s, C3s, GC3s, GC values and the Gravy values
	Axis 1	ENC	A3s	T3s	C3s	G3s	GC3s	GC
Gravy
r	-0,72527*	-0,73626*	0,72902*	0,69051*	-0,71252*	-0,76204*	-0,76754*	-0.7582*
P	< 0.05	< 0.05	< 0.05	< 0.05	< 0.05	< 0.05	< 0.05	< 0.05
The values in the table refer to correlation coefficient “r” values in a correlation analysis.*P-value < 0.05

Aromaticity and hydropathicity can have an impact on the CUB, and their effects may be attributed to natural selection. To determine the role of natural selection on the codon usage of IIVs DNA ligase genes, a correlation analysis was conducted between ENC, A3s, T3s, G3s, C3s, GC3s, GC values, and Gravy values (Tablo 7). The results indicated a positive correlation between Gravy and A3s as well as T3s, while a negative correlation was found between GC, CC3s, G3s, C3s, ENC, and axis 1. However, Aroma has no correlation with axis 1 and other indices. Therefore, the association between hydrophobicity and the codon usage of IIVs DNA ligase genes suggests the impact of natural selection on the pattern of codon usage.

In this study, a extensive analysis of the codon usage patterns of DNA ligase genes in IIV6 and 11 other invertebrate iridoviruses (IIVs) was conducted to gain a more profound insight into the evolutionary processes shaping their genetic composition. There are few studies on CUB of IIV6 [42–44]. 205R is one of 215 ORF of IIV6 genome and encodes the NAD + dependent DNA ligase. So far, NAD+-dependent DNA ligases mentioned in the literature were found exclusively in eubacterial genomes and certain eukaryotic viral DNA genomes [19, 25, 66, 67].

By comparing the conserved sequence motifs/domains, IIV6 DNA ligase differs from bacterial NAD + ligase substantially at the C terminus that it is missing the zinc finger domain (Fig. 1). In this regard, IIV6 DNA ligase is similar to the mimivirus and entomopoxvirus DNA ligases [19, 22, 25]. These studies have reported that ligase activity is not necessarily dependent on the presence of a zinc finger domain.

The bias in codon usage is a significant indication of gene evolution and can be impacted by numerous factors, with natural selection and mutation pressure being the most prevalent influences [68]. The CUB of a gene can be affected by the nucleotide composition within that gene [69]. The analysis of nucleotide content in IIVs DNA ligase genes demonstrated that A is the most prevalent nucleotide, followed by T. This finding aligns with previous studies conducted on other viruses such as Venezuelan equine encephalitis virus [70], Crimean-Congo hemorrhagic fever virus [71], Lumpy skin disease virus [72], Rice tungro bacilliform virus [73] and Canine distemper virus [74].

The GC composition at each position of the codon is considered a reliable index of bias in base composition. The findings of this study indicate that the third codon positions exhibit higher A and T contents compared to G and C. Typically, a higher AT-rich content usually exhibit correlation with the RSCU patterns observed in various viruses. [71, 75, 76]. Consistent with this observation, the RSCU analysis revealed a preference for A or T-end codons, indicating that the protein-coding sequences of IIVs DNA ligase showed a tendency to utilize A/T-ended codons. This suggests that changes in nucleotide composition, influenced by various factors, may significantly contribute to codon usage bias.

Previous studies have suggested that when viruses and their hosts exhibit identical codon usage patterns, it can enhance the efficiency of translating amino acids during protein synthesis. Conversely, variations in codon usage patterns can have an impact on the accurate folding of viral proteins [72, 77–79]. Consistent with these previous studies, our results show that the patterns of codon usage in IIV6 exhibit a high degree of similarity to its host, Chilo suppressalis [70, 80, 81]. Furthermore, prior works have reported significant variations in the codon usage patterns between viruses and their respective hosts [82–84].

It is crucial to comprehend the degree of CUB at the gene level. One commonly used measure to assess this bias is the ENC. The ENC value of a gene exhibits an inverse correlation with its expression level. A lower ENC value is indicative of a stronger bias in codon usage and corresponds to higher levels of gene expression. Conversely, a higher ENC value suggests the utilization of a diverse range of codons that encode amino acids, which is associated with lower levels of gene expression [85]. An ENC value exceeding 35 implies a low CUB [49]. The analysis indicated that the average ENC value for IIVs DNA ligase genes was 45.95, suggesting a low CUB. Identical findings of low codon usage bias were reported in another viruses like SFTSV [86], Zika virus [87], MCV [88], and HCMV [77]. However, our study identified that the IIV6 DNA ligase gene exhibited a stronger codon usage bias compared to the others.

Earlier studies have proposed that a low codon usage bias can enhance viral replication efficiency by reducing conflicts with the translation machinery of the host [41, 89]. The analysis of ENC-GC3 plots is a widely utilized method for investigating CUB in genes across different organisms. In our study, a plot was created by plotting the ENC values of each IIVs DNA ligase gene against the GC3s. The majority of the data points were located below the expected curve and just a few points above it, implying that there are additional factors, like translational selection, besides mutation pressure to influence the CUB of IIVs DNA ligase genes. Earlier studies reported similar results in related plots [40, 73, 90, 91]. While ENC-GC3 plot analysis is widely utilized to measure CUB, it alone is not sufficient to discern the specific contributions of mutation pressure and translational selection [65, 92]. In order to delve deeper into the factors shaping codon usage patterns, neutrality plot analysis and PR2 plot analysis were conducted. The results of these analyses suggest that translational selection may have a significant influence on CUB, which are consistent with prior studies [43, 70, 93]. However, the influence of mutation pressure on CUB in some viruses seems to be greater than that of translational selection [85, 94].

CAI analysis is commonly utilized to assess the level of gene expression and evaluate the degree to which viral genes have adapted to their host organisms. Highly expressed genes, which are translated by the host, typically exhibit higher CAI values [95, 96]. In this paper, CAI analysis revealed that IIVs DNA ligase genes show significant adaptation to their hosts, which implying that natural selection contributed to CUB the IIVs DNA ligase genes. These findings are consistent with previous studies that have also reported similar results, highlighting the significance of natural selection in influencing the codon usage patterns of viral genes [97, 98].

COA analysis is conducted to examine the patterns of codon usage based on the RSCU values. The COA analysis indicated that the observed patterns in nucleotide content and codon usage were likely affected by mutation pressure. These findings align with a previous study by Tian et al. (2020) made on Ranavirus, which also suggested the prominent impact of mutation pressure in influencing codon usage patterns.

The abundance of dinucleotides has been found to impact CUB in various organisms, such as RNA and DNA viruses [59, 99]. In this current study, it was examined the relative abundances of 16 dinucleotides to explore their potential effects. We observed that the frequencies of CG and TA dinucleotides in the IIV6 DNA ligase gene were underrepresented among the 16 dinucleotides. Dinucleotide CG is generally underrepresented in most viruses, including Hepatitis C virus, Hepatitis E virus and classical swine fever virus [92, 100, 101]. Moreover, the underrepresentation of CG and TA dinucleotides is considered as a strategy employed by viruses to evade reduce nonsense mutations, the host immune system and prevent cleavage by RNase [102, 103].

Mutation pressure and natural selection are commonly regarded as the primary factors influencing CUB [37, 104]. The impact of mutational pressure on CUB was verified through notably strong correlations observed between the composition of nucleotide and third codon position. Furthermore, the significant correlation between the ENC values and the nucleotide content, as well as the correlation between axis 1 and nucleotide content at the third position, provided further support for the significance of mutational pressure in shaping CUB. Aromaticity (Aroma) and hydropathicity (Gravy) might also be associated with the codon usage patterns of viruses. Correlation analysis demonstrated that there was a relationship between Gravy and codon composition, supporting the role of natural selection to the codon usage of IIVs DNA ligase genes. Previous studies have revealed that aromaticity and hydrophobicity are involved in the formation of codon usage bias in various viruses, including Zika virus, feline calicivirus, and Usutu virus [76, 87, 95].

The findings of this study revealed that the CUB of the IIV6 DNA ligase gene is high. The findings suggest that both natural selection and mutational pressure significantly contribute to the formation of codon usage patterns in IIVs DNA ligase genes. Furthermore, the study indicates that dinucleotide composition and hydrophobicity may exert an influence on the codon usage pattern. These insights enhance our comprehending of the functional mechanisms of the IIV6 DNA ligase gene and the evolution of invertebrate iridoviruses.

Acknowledgements

This work was financially supported by the Recep Tayyip Erdogan University (Project no. FBA-2016-533).

Conflict of interest The author declares no confict of interest

Chinchar VG, Hick P, Ince IA et al (2017) ICTV virus taxonomy profile: Iridoviridae. J Gen Virol 98:890–891. https://doi.org/10.1099/jgv.0.000818
Chinchar VG, Duffus ALJ (2019) Molecular and ecological studies of a virus family (Iridoviridae) infecting invertebrates and ectothermic vertebrates. Viruses 11
Rosa GM, Ayala Botto G, Mitra AT et al (2022) Invasive fish disrupt host-pathogen dynamics leading to amphibian declines. Biol Conserv 276. https://doi.org/10.1016/j.biocon.2022.109785
Williams T (2008) Natural invertebrate hosts of iridoviruses (Iridoviridae). Neotrop Entomol 37:615–632. https://doi.org/10.1590/s1519-566x2008000600001
Arulmoorthy MP, Vijayan R, Sinduja K et al (2022) Infection with Decapod iridescent virus 1: an emerging disease in shrimp culture. Arch Microbiol 204
Canuti M, Large G, Verhoeven JTP, Dufour SC (2022) A Novel Iridovirus Discovered in Deep-Sea Carnivorous Sponges. https://doi.org/10.3390/v14081595. Viruses 14:
Kleespies RG, Tidona CA, Darai G (1999) Characterization of a New Iridovirus Isolated. from Crickets and Investigations on the Host Range
Hernández O, Maldonado G, Williams T (2000) An epizootic of patent iridescent virus disease in multiple species of blackflies in Chiapas, Mexico. https://doi.org/10.1046/j.1365-2915.2000.00258.x. Med Vet Entomol 14:
Gregory CR, Latimer KS, Pennick KE et al (2006) Novel iridovirus in a nautilus (Nautilus spp). J Vet Diagnostic Investig 18. https://doi.org/10.1177/104063870601800213
Tang KFJ, Redman RM, Pantoja CR et al (2007) Identification of an iridovirus in Acetes erythraeus (Sergestidae) and the development of in situ hybridization and PCR method for its detection. J Invertebr Pathol 96. https://doi.org/10.1016/j.jip.2007.05.006
Lehman IR (1974) DNA ligase: Structure, mechanism, and function. Science (80-) 186:. https://doi.org/10.1126/science.186.4166.790
Doherty AJ, Suh SW (2000) Structural and mechanistic conservation in DNA ligases. Nucleic Acids Res. https://doi.org/10.1093/nar/28.21.4051. 28:
Timson DJ, Singleton MR, Wigley DB (2000) DNA ligases in the repair and replication of DNA. Mutat Res - DNA Repair. https://doi.org/10.1016/S0921-8777(00)00033-1. 460:
Wilkinson A, Day J, Bowater R (2001) Bacterial DNA ligases. Mol Microbiol 40:1241–1248. https://doi.org/10.1046/j.1365-2958.2001.02479.x
Shuman S, Lima CD (2004) The polynucleotide ligase and RNA capping enzyme superfamily of covalent nucleotidyltransferases. Curr Opin Struct Biol 14
Ellenberger T, Tomkinson AE (2008) Eukaryotic DNA ligases: Structural and functional insights. Annu Rev Biochem 77
Martin IV, Macneill SA (2002) Protein family review ATP-dependent DNA ligases. Genome Biol 3
Williamson A, Hjerde E, Kahlke T (2016) Analysis of the distribution and evolution of the ATP-dependent DNA ligases of bacteria delineates a distinct phylogenetic group “Lig E. Mol Microbiol 99. https://doi.org/10.1111/mmi.13229
Sriskanda V, Moyer RW, Shuman S (2001) NAD+-dependent DNA Ligase Encoded by a Eukaryotic Virus. J Biol Chem 276. https://doi.org/10.1074/jbc.M105643200
Zhao A, Gray FC, MacNeill SA (2006) ATP- and NAD+-dependent DNA ligases share an essential function in the halophilic archaeon Haloferax volcanii. Mol Microbiol 59. https://doi.org/10.1111/j.1365-2958.2005.04975.x
Poidevin L, MacNeill SA (2006) Biochemical characterisation of LigN, an NAD+-dependent DNA ligase from the halophilic euryarchaeon Haloferax volcanii that displays maximal in vitro activity at high salt concentrations. BMC Mol Biol 7. https://doi.org/10.1186/1471-2199-7-44
Benarroch D, Shuman S (2006) Characterization of mimivirus NAD+-dependent DNA ligase. https://doi.org/10.1016/j.virol.2006.04.032. Virology 353:
Borrel G, Harris HMB, Tottey W et al (2012) Genome sequence of “candidatus methanomethylophilus alvus” Mx1201, a methanogenic archaeon from the human gut belonging to a seventh order of methanogens. J Bacteriol 194. https://doi.org/10.1128/JB.01867-12
Spang A, Saw JH, Jørgensen SL et al (2015) Complex archaea that bridge the gap between prokaryotes and eukaryotes. Nature 521. https://doi.org/10.1038/nature14447
Lu J, Tong J, Feng H et al (2004) Unique ligation properties of eukaryotic NAD+-dependent DNA ligase from Melanoplus sanguinipes entomopoxvirus. Biochim Biophys Acta - Proteins Proteomics. https://doi.org/10.1016/j.bbapap.2004.06.008. 1701:
Jakob NJ, Darai G (2002) Molecular anatomy of Chilo iridescent virus genome and the evolution of viral genes. Virus Genes 25. https://doi.org/10.1023/A:1020984210358
Eaton HE, Metcalf J, Penny E et al (2007) Comparative genomic analysis of the family Iridoviridae: Re-annotating and defining the core set of iridovirus genes. Virol J 4. https://doi.org/10.1186/1743-422X-4-11
Jakob NJ, Müller K, Bahr U, Darai G (2001) Analysis of the first complete DNA sequence of an invertebrate iridovirus: Coding strategy of the genome of Chilo iridescent virus. Virology 286. https://doi.org/10.1006/viro.2001.0963
D’Costa SM, Yao HJ, Bilimoria SL (2004) Transcriptional mapping in Chilo iridescent virus infections. Arch Virol 149:723–742. https://doi.org/10.1007/s00705-003-0232-4
Ince IA, Boeren SA, van Oers MM et al (2010) Proteomic analysis of Chilo iridescent virus. https://doi.org/10.1016/j.virol.2010.05.038. Virology 405:
Dizman YA, Demirbag Z, Ince IA, Nalcacioglu R (2012) Transcriptomic analysis of Chilo iridescent virus immediate early promoter. Virus Res 167. https://doi.org/10.1016/j.virusres.2012.05.025
Ince IA, Özcan K, Vlak JM, van Oers MM (2013) Temporal classification and mapping of non-polyadenylated transcripts of an invertebrate iridovirus. J Gen Virol 94. https://doi.org/10.1099/vir.0.046359-0
Dizman YA, Muratoglu H, Sandalli C et al (2016) Chilo iridescent virus (CIV) ORF 012L encodes a protein with both exonuclease and endonuclease functions. Arch Virol 161:3029–3037. https://doi.org/10.1007/s00705-016-3007-4
İnce İA, Pijlman GP, Vlak JM, van Oers MM (2017) Hairpin structures with conserved sequence motifs determine the 3′ ends of non-polyadenylated invertebrate iridovirus transcripts. Virology 511. https://doi.org/10.1016/j.virol.2017.06.026
Yesilyurt A, Demirbag Z, van Oers MM, Nalcacioglu R (2020) Conserved motifs in the invertebrate iridescent virus 6 (IIV6) genome regulate virus transcription. J Invertebr Pathol 177. https://doi.org/10.1016/j.jip.2020.107496
Gencer D, Yesilyurt A, Ozsahin E et al (2023) Identification of the potential matrix protein of invertebrate iridescent virus 6 (IIV6). J Invertebr Pathol 197. https://doi.org/10.1016/j.jip.2023.107885
Butt AM, Nasrullah I, Tong Y (2014) Genome-wide analysis of codon usage and influencing factors in chikungunya viruses. PLoS ONE 9. https://doi.org/10.1371/journal.pone.0090905
Ikemura T (1985) Codon usage and tRNA content in unicellular and multicellular organisms. Mol Biol Evol 2:13–34. https://doi.org/10.1093/oxfordjournals.molbev.a040335
Parvathy ST, Udayasuriyan V, Bhadana V (2022) Codon usage bias. Mol Biol Rep 49:539–565. https://doi.org/10.1007/s11033-021-06749-4
Bera BC, Virmani N, Kumar N et al (2017) Genetic and codon usage bias analyses of polymerase genes of equine influenza virus and its relation to evolution. BMC Genomics 18. https://doi.org/10.1186/s12864-017-4063-1
Butt AM, Nasrullah I, Qamar R, Tong Y (2016) Evolution of codon usage in Zika virus genomes is host and vector specific. Emerg Microbes Infect 5. https://doi.org/10.1038/emi.2016.106
Tsai CT, Lin CH, Chang CY (2007) Analysis of codon usage bias and base compositional constraints in iridovirus genomes. Virus Res 126. https://doi.org/10.1016/j.virusres.2007.03.001
Tian H, Hu Q mu, Xiao H et al (2020) bing, Genetic and codon usage bias analyses of major capsid protein gene in Ranavirus. Infect Genet Evol 84:. https://doi.org/10.1016/j.meegid.2020.104379
Zhao R, Gu C, Zou X et al (2022) Comparative genomic analysis reveals new evidence of genus boundary for family Iridoviridae and explores qualified hallmark genes. Comput Struct Biotechnol J 20. https://doi.org/10.1016/j.csbj.2022.06.049
Puigbò P, Bravo IG, Garcia-Vallve S (2008) CAIcal: A combined set of tools to assess codon usage adaptation. Biol Direct 3. https://doi.org/10.1186/1745-6150-3-38
Karniychuk UU (2016) Analysis of the synonymous codon usage bias in recently emerged enterovirus D68 strains. Virus Res 223. https://doi.org/10.1016/j.virusres.2016.06.015
Sharp PM, Li WH (1986) Codon usage in regulatory genes in Escherichia coli does not reflect selection for “rare” codons. Nucleic Acids Res 14. https://doi.org/10.1093/nar/14.19.7737
Wong EHM, Smith DK, Rabadan R et al (2010) Codon usage bias and the evolution of influenza A viruses. Codon Usage Biases of Influenza Virus. BMC Evol Biol 10. https://doi.org/10.1186/1471-2148-10-253
Wright F (1990) The “effective number of codons” used in a gene. Gene 87. https://doi.org/10.1016/0378-1119(90)90491-9
Comeron JM, Aguadé M (1998) An evaluation of measures of synonymous codon usage bias. J Mol Evol 47:268–274
Hartl DL, Moriyama EN, Sawyer SA (1994) Selection intensity for codon bias. Genetics 138. https://doi.org/10.1093/genetics/138.1.227
Montaña-Lozano P, Balaguera-Reina SA, Prada-Quiroga CF (2023) Comparative analysis of codon usage of mitochondrial genomes provides evolutionary insights into reptiles. Gene 851. https://doi.org/10.1016/j.gene.2022.146999
Sueoka N (1988) Directional mutation pressure and neutral molecular evolution. Proc Natl Acad Sci U S A 85. https://doi.org/10.1073/pnas.85.8.2653
Sueoka N (1992) Directional mutation pressure, selective constraints, and genetic equilibria. J Mol Evol 34. https://doi.org/10.1007/BF00182387
Sueoka N (1995) Intrastrand parity rules of DNA base composition and usage biases of synonymous codons. J Mol Evol 40. https://doi.org/10.1007/BF00163236
Sueoka N (1999) Two aspects of DNA base composition: G + C content and translation- coupled deviation from intra-strand rule of A = T and G = C. J Mol Evol 49. https://doi.org/10.1007/PL00006534
Clarke RT, Greenacre MJ (1985) Theory and Applications of Correspondence Analysis. J Anim Ecol 54. https://doi.org/10.2307/4399
Zhang J, Wang M, Liu WQ et al (2011) Analysis of codon usage and nucleotide composition bias in polioviruses. Virol J. https://doi.org/10.1186/1743-422X-8-146. 8:
Kariin S, Burge C (1995) Dinucleotide relative abundance extremes: a genomic signature. Trends Genet 11
Burge C, Campbell AM, Karlin S (1992) Over- and under-representation of short oligonucleotides in DNA sequences. Proc Natl Acad Sci U S A 89. https://doi.org/10.1073/pnas.89.4.1358
Lobry JR, Gautier C (1994) Hydrophobicity, expressivity and aromaticity are the major trends of amino-acid usage in 999 escherichia coli chromosome-encoded genes. Nucleic Acids Res 22. https://doi.org/10.1093/nar/22.15.3174
Lee JY, Chang C, Song HK et al (2000) Crystal structure of NAD+-dependent DNA ligase: Modular architecture and functional implications. EMBO J 19. https://doi.org/10.1093/emboj/19.5.1119
Shuman S (1995) Vaccinia Virus DNA Ligase: Specificity, Fidelity, and Inhibition. Biochemistry 34:. https://doi.org/10.1021/bi00049a029
Sriskanda V, Shuman S (2002) Conserved residues in domain Ia are required for the reaction of Escherichia coli DNA ligase with NAD+. J Biol Chem 277. https://doi.org/10.1074/jbc.M111164200
Wang H, Liu S, Zhang B, Wei W (2016) Analysis of synonymous codon usage bias of zika virus and its adaption to the hosts. PLoS ONE 11. https://doi.org/10.1371/journal.pone.0166260
Chauleau M, Shuman S (2016) Kinetic mechanism and fidelity of nick sealing by Escherichia coli NAD+-dependent DNA ligase (LigA). Nucleic Acids Res 44:2298–2309. https://doi.org/10.1093/nar/gkw049
Kaczmarek FS, Zaniewski RP, Gootz TD et al (2001) Cloning and functional characterization of an NAD+-dependent DNA ligase from Staphylococcus aureus. J Bacteriol 183:3016–3024. https://doi.org/10.1128/JB.183.10.3016-3024.2001
Zhang X, Cai Y, Zhai X et al (2018) Comprehensive analysis of codon usage on rabies virus and other lyssaviruses. Int J Mol Sci 19. https://doi.org/10.3390/ijms19082397
Jenkins GM, Holmes EC (2003) The extent of codon usage bias in human RNA viruses and its evolutionary origin. Virus Res 92. https://doi.org/10.1016/S0168-1702(02)00309-X
Wang H, Liu S, Lv Y, Wei W (2023) Codon usage bias of Venezuelan equine encephalitis virus and its host adaption. Virus Res 328. https://doi.org/10.1016/j.virusres.2023.199081
Rahman SU, Yao X, Li X et al (2018) Analysis of codon usage bias of Crimean-Congo hemorrhagic fever virus and its adaptation to hosts. Infect Genet Evol 58. https://doi.org/10.1016/j.meegid.2017.11.027
Rahman SU, Abdullah M, Khan AW et al (2022) A detailed comparative analysis of codon usage bias in Alongshan virus. Virus Res 308. https://doi.org/10.1016/j.virusres.2021.198646
Nguyen TH, Wang D, Rahman SU et al (2021) Analysis of codon usage patterns and influencing factors in rice tungro bacilliform virus. Infect Genet Evol 90. https://doi.org/10.1016/j.meegid.2021.104750
Wang X, Xu W, Fan K et al (2020) Codon usage bias in the H gene of canine distemper virus. Microb Pathog 149. https://doi.org/10.1016/j.micpath.2020.104511
Tyagi A, Nagar V (2022) Genome dynamics, codon usage patterns and influencing factors in Aeromonas hydrophila phages. Virus Res 320. https://doi.org/10.1016/j.virusres.2022.198900
Zang M, He W, Du F et al (2017) Analysis of the codon usage of the ORF2 gene of feline calicivirus. Infect Genet Evol 54:54–59. https://doi.org/10.1016/j.meegid.2017.06.013
Hu C, Chen J, Ye L et al (2014) Codon usage bias in human cytomegalovirus and its biological implication. https://doi.org/10.1016/j.gene.2014.05.018. Gene 545:
Cristina J, Moreno P, Moratorio G, Musto H (2015) Genome-wide analysis of codon usage bias in Ebolavirus. Virus Res 196. https://doi.org/10.1016/j.virusres.2014.11.005
Sexton NR, Ebel GD (2019) Effects of arbovirus multi-host life cycles on dinucleotide and codon usage patterns. Viruses 11
Chantawannakul P, Cutler RW (2008) Convergent host-parasite codon usage between honeybee and bee associated viral genomes. J Invertebr Pathol 98. https://doi.org/10.1016/j.jip.2008.02.016
Tyagi A, Singh NK, Gurtler V, Karunasagar I (2016) Bioinformatics analysis of codon usage patterns and influencing factors in Penaeus monodon nudivirus. Arch Virol 161. https://doi.org/10.1007/s00705-015-2689-3
Yao X, Fan Q, Yao B et al (2020) Codon Usage Bias Analysis of Bluetongue Virus Causing Livestock Infection. Front Microbiol 11. https://doi.org/10.3389/fmicb.2020.00655
Jiang L, Zhang Q, Xiao S, Si F (2022) Deep decoding of codon usage strategies and host adaption preferences of soybean mosaic virus. Int J Biol Macromol 222. https://doi.org/10.1016/j.ijbiomac.2022.09.179
Pu F, Wang R, Yang X et al (2023) Nucleotide and codon usage biases involved in the evolution of African swine fever virus: A comparative genomics analysis. J Basic Microbiol. https://doi.org/10.1002/jobm.202200624
Wang H, Meng T, Wei W (2018) Analysis of synonymous codon usage bias in helicase gene from Autographa californica multiple nucleopolyhedrovirus. Genes and Genomics 40. https://doi.org/10.1007/s13258-018-0689-x
Zu Z, Lin H, Hu Y et al (2022) The genetic evolution and codon usage pattern of severe fever with thrombocytopenia syndrome virus. Infect Genet Evol 99. https://doi.org/10.1016/j.meegid.2022.105238
Tao J, Yao H (2020) Comprehensive analysis of the codon usage patterns of polyprotein of Zika virus. Prog Biophys Mol Biol 150. https://doi.org/10.1016/j.pbiomolbio.2019.05.001
Nair RR, Mohan M, Rudramurthy GR et al (2021) Strategies and Patterns of Codon Bias in Molluscum Contagiosum Virus. https://doi.org/10.3390/pathogens10121649. Pathogens 10:
Nasrullah I, Butt AM, Tahir S et al (2015) Genomic analysis of codon usage shows influence of mutation pressure, natural selection, and host features on Marburg virus evolution. BMC Evol Biol 15:1–15. https://doi.org/10.1186/s12862-015-0456-4
Zhou Y, Chen X, Ushijima H, Frey TK (2012) Analysis of base and codon usage by rubella virus. Arch Virol 157. https://doi.org/10.1007/s00705-012-1243-9
Sun J, Zhao W, Wang R et al (2020) Analysis of the codon usage pattern of HA and NA genes of H7N9 influenza A virus. Int J Mol Sci 21. https://doi.org/10.3390/ijms21197129
Patil SS, Indrabalan UB, Suresh KP, Shome BR (2021) Analysis of codon usage bias of classical swine fever virus. https://doi.org/10.14202/vetworld.2021.1450-1458. Vet World 14:
Yu X, Gao K, Pi M et al (2021) Phylogenetic and codon usage analysis for replicase and capsid genes of porcine circovirus 3. Vet Res Commun 45. https://doi.org/10.1007/s11259-021-09816-0
Das M, Kumar S (2018) Analysis of codon usage pattern of infectious laryngotracheitis virus immunogenic glycoproteins and its biological implications. Infect Genet Evol. https://doi.org/10.1016/j.meegid.2018.04.009. 62:
Zhou J, Xing Y, Zhou Z, Wang S (2023) A comprehensive analysis of Usutu virus (USUV) genomes revealed lineage-specific codon usage patterns and host adaptations. Front Microbiol 13. https://doi.org/10.3389/fmicb.2022.967999
Mioduser O, Goz E, Tuller T (2017) Significant differences in terms of codon usage bias between bacteriophage early and late genes: A comparative genomics analysis. BMC Genomics 18. https://doi.org/10.1186/s12864-017-4248-7
Suresh KP, Indrabalan UB, Shreevatsa B et al (2023) Evaluation of codon usage patterns and molecular evolution dynamics in Japanese encephalitis virus: An integrated bioinformatics approach. Infect Genet Evol 109. https://doi.org/10.1016/j.meegid.2023.105410
Qi X, Wei C, Li Y et al (2020) The characteristic of the synonymous codon usage and phylogenetic analysis of hepatitis B virus. Genes and Genomics 42. https://doi.org/10.1007/s13258-020-00932-w
Simón D, Cristina J, Musto H (2022) An overview of dinucleotide and codon usage in all viruses. Arch Virol 167. https://doi.org/10.1007/s00705-022-05454-2
Li B, Wu H, Miao Z et al (2022) Codon Usage of Hepatitis E Viruses: A Comprehensive Analysis. Front Microbiol 13. https://doi.org/10.3389/fmicb.2022.938651
Lobo FP, Mota BEF, Pena SDJ et al (2009) Virus-host coevolution: Common patterns of nucleotide motif usage in Flaviviridae and their hosts. PLoS ONE 4. https://doi.org/10.1371/journal.pone.0006282
Cheng X, Virk N, Chen W et al (2013) CpG Usage in RNA Viruses: Data and Hypotheses. PLoS ONE 8. https://doi.org/10.1371/journal.pone.0074109
Dorn A, Kippenberger S (2008) Clinical application of CpG-, non-CpG-, and antisense oligodeoxynucleotides as immunomodulators. Curr Opin Mol Ther 10
Khandia R, Khan AA, Karuvantevida N et al (2023) Insights into Synonymous Codon Usage Bias in Hepatitis C Virus and Its Adaptation to Hosts. Pathogens 12. https://doi.org/10.3390/pathogens12020325

Download PDF

Version 1

posted

You are reading this latest preprint version

Codon usage bias analysis of the gene encoding NAD+-dependent DNA ligase protein of invertebrate iridescent virus 6

Status:

Version 1

Abstract

Figures

1. Introduction

2. Materials and Methods

2.1. Bioinformatics analysis

2.2. Nucleotide composition analysis

2.3. Relative synonymous codon usage (RSCU) analysis

2.4. Effective number of codons (ENC) analysis

2.5. ENC-GC3s plot analysis

2.6. Neutrality plot analysis

2.7. Parity rule 2 (PR2) plot analysis

2.8. Codon adaptation index (CAI) analysis

2.9. Correspondence analysis (COA)

2.10. Relative dinucleotide abundance analysis

2.11. General average hydropathicity (Gravy) and aromaticity (Aroma) analysis

2.12. Statistical analysis

3. Results

3.1. Conserved domain structure analysis of IIV6 DNA ligase

3.2. Compositional analysis in IIVs DNA ligase gene

3.3. RSCU analysis

3.4. Analysis of the effective number of codons (ENC) and ENC plot

3.5. Analysis of the neutrality plot

3.6. PR2 bias plot analysis

3.7. Codon adaptation index (CAI) analysis

3.8. Correspondence analysis

3.9. Dinucleotide abundance frequency analysis

3.10. Correlation analysis

4. Discussion

5. Conclusions

Declarations

References

Status:

Version 1