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. 2013 Sep 23;8(9):e74109.
doi: 10.1371/journal.pone.0074109. eCollection 2013.

CpG usage in RNA viruses: data and hypotheses

Xiaofei Cheng  1 , Nasar Virk, Wei Chen, Shuqin Ji, Shuxian Ji, Yuqiang Sun, Xiaoyun Wu
Affiliations

CpG usage in RNA viruses: data and hypotheses

Xiaofei Cheng et al. PLoS One. .

Abstract

CpG repression in RNA viruses has been known for decades, but a reasonable explanation has not yet been proposed to explain this phenomenon. In this study, we calculated the CpG odds ratio of all RNA viruses that have available genome sequences and analyzed the correlation with their genome polarity, base composition, synonymous codon usage, phylogenetic relationship, and host. The results indicated that the viral base composition, synonymous codon usage and host selection were the dominant factors that determined the CpG bias in RNA viruses. CpG usage variation between the different viral groups was caused by different combinations of these pressures, which also differed from each other in strength. The consistent under-representation of CpG usage in -ssRNA viruses is determined predominantly by base composition, which may be a consequence of the U/A preferred mutation bias of -ssRNA viruses, whereas the CpG usage of +ssRNA viruses is affected greatly by their hosts. As a result, most +ssRNA viruses mimic their hosts' CpG usage. Unbiased CpG usage in dsRNA viruses is most likely a result of their dsRNA genome, which allows the viruses to escape from the host-driven CpG elimination pressure. CpG was under-represented in all reverse-transcribing viruses (RT viruses), suggesting that DNA methylation is an important factor affecting the CpG usage of retroviruses. However, vertebrate-infecting RT viruses may also suffer host' CpG elimination pressure that also acts on +ssRNA viruses, which results in further under-representation of CpG in the vertebrate-infecting RT viruses.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. CpG usage pattern of RNA viruses.
The y-axis depicts the number of viruses with the specific CpGO/E values given on the x-axis.
Figure 2
Figure 2. The influence of GC content on viral CpG usage.
(A) Correlation between CpG odds ratios and GC contents of RNA viruses. (B) CpG usage variation between the four groups of RNA viruses. CpGO/E distribution range of each viral group is shown by yellow dots, and the mean CpGO/E value of each viral group is indicated by the purple bar. The standard deviations of the mean CpGO/E values are also indicated. (C) Correlation between the mean CpGO/E and mean GC content values. (D) Correlation between the CpGO/E and CpGO/E _CDS values.
Figure 3
Figure 3. CpG usage pattern of RNA viruses within coding region.
(A–D) Distribution of CpG at the three locations in the coding regions of −ssRNA, RT, dsRNA, and +ssRNA viruses, respectively.
Figure 4
Figure 4. +ssRNA viruses mimic the CpG usage of their respective host.
Correlation between +ssRNA viral and host's mean CpGO/E (A), mean CpGO/E _CDS_12 (B), mean CpGO/E _CDS_23 (C), and mean CpGO/E _CDS_31 (D). The abbreviations at the bottom of each chart (B, F, I, P, and V) represent bacteria or bacterial-infecting +ssRNA viruses, fungi or fungus-infecting +ssRNA, invertebrates or invertebrate-infecting +ssRNA viruses, plants or plant-infecting +ssRNA viruses, and vertebrates or vertebrate-infecting +ssRNA viruses, respectively.
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Publication types

Grants and funding

This study was supported by the Natural Science Foundation of China (Project No. 31101417 and 31101415) and the Natural Science Foundation of Zhejiang Province (Project No: Y3110175 and Y3110277). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.