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Codon usage bias studies and cluster analysis on emerging bat SARS-related coronaviruses in Yunnan Province, China |
TIAN Ming-ming, WEI Xue-ling, YANG Xing, SONG Xiu-feng, LI Guang-hua, LIU Qi |
Department of Medical Microbiology and Immunology, Integrated Lab of Pathogenic Biology, School of Basic Medicine, Dali University, Dali 671000, China |
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Abstract To explore the codon usage bias of the emerging bat SARS-related coronavirus (SARSr-CoV) in Yunnan Province and its evolutionary relationship with SARS-CoVs and other SARSr-CoVs, we used Lasergene, EMBOSS, CodonW and other biological information software to analyze codon usage bias and cluster analysis of the protein coding sequences of the emerging bat SARSr-CoVs in Yunnan Province, SARS-CoVs, and other SARSr-CoVs. Results showed that the number of effective codons (ENC) of these emerging bat SARSr-CoVs proteins were close to 61, their codon usage bias were weak. The Relative Synonymous Codon Usage (RSCU) analysis showed that the preferred codons of each protein were different, but tending to use the codons ending with A or U. In the choice of preferred codons, these new emerging bat SARSr-CoVs were highly consistent with SARS-CoVs. ENC-Plot, neutral plot analysis and PR2 rule analysis indicated that the natural selection factors mainly influenced the evolution of these emerging bat SARSr-CoVs. Clustering analysis based on codon usage bias indicated that the emerging bat SARSr-CoVs were closely related to SARS-CoVs. In addition, these emerging bat SARSr-CoVs were dispersedly clustered with SARSr-CoVs found in other regions. All of these shown that the new emerging bat SARSr-CoVs in Yunnan have higher degree of similarity to SARS-CoVs and have higher risks of cross species transmission. This further indicated that the bat SARSr-CoVs in Yunnan may be the natural gene reservoir of SARS-CoVs and SARSr-CoVs for other regions from the perspective of codon usage preference.
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Received: 23 April 2018
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Fund:Supported by the National Natural Science Foundation of China (Nos. 81660337 & 81703573) and the Scientific Research Fund of Yunnan Provincial Education Department (No. 2015Y383) |
Corresponding Authors:
Liu Qi, Email: qiliu@aliyun.com
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