Analysis of synonymous codon usage in Hepatitis A virus

Hepatitis A virus (HAV), the causative agent of type A viral hepatitis, is an ancient human virus that was first identified in the stools of infected people in 1973 [1]. HAV is a non-enveloped, single-stranded positive-sence RNA virus which belongs to order Picornavirales, family Picornaviridae, the genus Hepatovirus in virus taxonomy [2‐4]. The genome of HAV is approximately 7500 nucleotide in length and contains a large open-reading frame (ORF) encoding a polyprotein in which the major capsid proteins represent the amino-terminal third, with the remainder of the polyprotein comprising a series of nonstructural proteins required for HAV RNA replication: 2B, 2C, 3A, 3B, 3C^pro and 3D^pol. Based on the studies of genetics, HAV was proposed to divide into six different genotypes [5]. However, there is only one known serological group of human HAV [6, 7]. Although HAV causes occasional, dramatic disease outbreaks of acute hepatitis with fatal outcomes in otherwise healthy adults as well as isolated severe cases of hepatitis, it has never been associated with chronic liver disease [8].

As we all know, the genetic code chooses 64 codons to represent 20 standard amino acids and stop signals. These alternative codons for the same amino acid are termed as synonymous codons. Synonymous mutations tend to occur in the third base position, but the cases can be interchanged without altering the primary sequence of the polypeptide product. Some reports indicate that synonymous codons are not chosen equally both within and between genomes [9‐13]. In general, codon usage variation may be the product of natural selection and/or mutation pressure for accurate and efficient translation in various organisms [14‐21]. It is well known that codon usage variation is considered as an indicator of the forces shaping genome evolution. In addition, compared with natural selection, mutation pressure plays an important role in synonymous codon usage pattern in some RNA viruses [18, 22, 23].

Nevertheless, little information about codon usage pattern of HAV genome including the relative synonymous codon usage (RSCU) and codon usage bias (CUB) in the process of its evolution is available. In this study, the key genetic determinants of codon usage index in HAV were examined.

Overtime, there have been more and more features that are unique to HAV within the family Picornaviridae, including its tissue tropism, its virion morphogenesis, its genetic distance from other members of this family, the important details of the processing of the viral polyprotein and the interactions of the virus with host cells [24]. After we analyzed synonymous codon usage in HAV (Table 2), we found that comparing with other viruses of Picornaviridae, such as Coxsackievirus A9 (ENC = 55.6), Enterovirus 71 (ENC = 56.6), Poliovirus type 3 (ENC = 54.2), Rhinovirus type 89 (ENC = 45.9) [23] and Food-and-Mouth Disease virus (mean ENC = 51.53) [21], the ENC values for HAV are a little low (mean ENC = 39.34). Although the ENC values for Coxsackievirus, Enterovirus, Poliovirus and Rhinovirus are not the mean value, it is also suggesting that the overall extent of codon usage bias in HAV genomes is rather high in Picornaviridae. In fact, Sánchez et al. have previously reported that HAV presents a higher codon usage bias than other members of the family, which conveys in the adaptation to use abundant and rare codons [25]. As a result, HAV codon usage has evolved to be complementary to that of human cells, never adopting codons those abundant for the host cell, even in some instances using these abundant codons as rare codons [26].

Since the variation and evolution of virus generally appear in the changes of virus genome composition, compositional constraint was assumed to be closely correlated with the synonymous codon usage pattern [18, 19, 27‐30]. Nucleotide U content was the highest, and the ratio of U₃% was much higher than the other base composition on the third codon position (Table 3), which interpreted why most of the preferentially used codons are U-ended codons (Table 2). Despite the ratio of U₃% was the highest, the major compositional constraint, which shaping the synonymous codon usage pattern of HAV genome, was from the percent of nucleotide A on the third codon position (Table 4). Moreover, two principle axes (ƒ'₁ and ƒ'₂) are not correlated with the other base compositions except nucleotide A (Table 4). This discovery was different from many reports which suggest that C+G compositional constraints were the major factor influencing codon usage bias in virus genome [18, 29, 30]. Therefore, we supposed that the compositional constraint was from not only C+G contents but also A and/or U contents. In addition, we found that A₃% has a remarkable correlation with (C+G)% (Table 3). Hence, we could infer that A₃% could influence the synonymous codon usage pattern through coordinating the contents of (C+G)%. Moreover, each composition was closely correlated with one of the other compositions, and each composition has a striking negative correlation with the other compositions. The (C₃+G₃)% was correlated with all the base compositions especially U and C contents. All these data suggest that there were kinds of complex and fantastic interrelations existing among these base compositions to regulate the codon usage bias. In brief, compositional constraint can indeed determine the variation of synonymous codon usage in virus genome.

Mutational pressure and natural selection are generally thought to be the main factors that account for codon usage variation between genes in different organisms [14‐21]. We wished to determine which should be responsible for the extreme codon usage bias in HAV. In the present study, the mutational pressure was determined to be the more important factor for the codon usage bias in HAV, which is shown in Figure 2, indicating that the codon usage in HAV genome is influenced by the C+G content which is usually assumed to be the result of mutational pressure. Actually, it is previously reported that mutation pressure rather than natural selection is the most important determinant of the codon bias in human RNA viruses [23]. Since mutation rates in RNA viruses are much higher than those in DNA viruses [31], it is understandable that mutational pressure is the major factor of shaping codon usage pattern in the 21 HAV strains included in our study. Despite this, HAV does not appear to undergo the rapid accumulation of genetic changes seen in many RNA viruses. Because HAV exploits a very low translation rate and a very low replication rate to promote and ensure its survival [26, 32], it shows a quite low mutation rate than other members of the family Picornaviridae[24, 33].

Since HAV mutation rate is much lower than other members of the family Picornaviridae, how does it form such a higher codon usage bias than other members of the family? Furthermore, how does it form kinds of trends in codon usage variation among different stains (Shown in Figure 1) in the condition of the similar nucleotide contents (Table 2)? This could be ascribed to the distinct endemicity of HAV, which is speculated from the result of COA. Early comparative studies of the nucleotide sequences of different human HAV strain suggested that sequence correlation could be correlated with the geographical origin of viruses [34, 35]. It is well known that quasispecies dynamics is characterized by continuous generation of variant viral genomes, competition among them, and selection of the fittest mutant distributions in any given environment. As other RNA viruses, HAV exists in vivo as distributions of closely related variant referred to as quasispecies [25, 32]. HAV strains maintained their low rate of accumulating mutations over a long period of time so that it developed specific ecological niches [33]. Because of surviving in different geographical area, different human race and different rounds of replication, the extreme codon usage bias of HAV was established over a long time. Moreover, in the context of a very low mutation rate, the extreme codon usage bias of HAV was conserved so that a distinct endemicity was generated.