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Updated: Jun 1, 2025

Unbiased Deep Sequencing of RNA Viruses from Clinical Samples
Published on: July 2, 2016
Analysis of synonymous codon usage bias of Lassa virus
Siddiq Ur Rahman1, Yikui Hu2, Hassan Ur Rehman3
1Medical Big Data Center, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong Province 510080, PR China; Department of Computer Science & Bioinformatics, Khushal Khan Khattak University, Karak, Khyber Pakhtunkhwa, 27200, Pakistan.
Abstract:
Lassa virus genome consists of two single-stranded, negative-sense RNA segments that lie in the genus Arenavirus. The disease associated with the Lassa virus is distributed all over the world, with approximately 3,000,000-5,000,000 infections diagnosed annually in West Africa. It shows high health risks to the human being. Previous research used the evolutionary time scale and adaptive evolution to describe the Lassa virus population pattern. However, it is still unclear how the Lassa virus takes advantage of synonymous codons. In this study, we analyzed the codon usage bias in 162 Lassa virus strains by calculating and comparing the nucleotide contents, effective number of codons (ENC), codon adaptation index (CAI), relative synonymous codon usage (RSCU), and others. The results disclosed that LASV strains are rich in A/T. The average ENC value indicated a low codon usage bias in LASVs. The ENC-plot, neutrality plot and parity rule 2 plot demonstrated that, besides mutational pressure, other factors like natural selection also contributed to codon usage bias. This study is significant because it described the pattern of codon usage in the genomes of the Lassa viruses and provided the information needed for a fundamental evolutionary study of them.
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