Analysis of synonymous codon usage bias of Lassa virus

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.

Authors

Institutions

Publication Details

Journal
Virus Research
Published
2025-01-29
DOI
https://doi.org/10.1016/j.virusres.2025.199528
Citations
2
Primary Topic
Viral Infections and Outbreaks Research
Type
article
Field-Weighted Citation Impact
2.79

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Analysis of synonymous codon usage bias of Lassa virus

Hassan Ur Rehman, Kotb A. Attia, May Alrashed, Huiying Liang et al.
2 citations
Virus Research
Viral Infections and Outbreaks Research
2.79
article

Analysis of synonymous codon usage bias of Lassa virus

Hassan Ur Rehman, Kotb A. Attia, May Alrashed, Huiying Liang, Siddiq Ur Rahman, Ubaid Ullah, Yikui Hu
article en
2 citations

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.

Virus ResearchVol. 353
King Saud University (SA), Khushal Khan Khattak University Karak
King Saud University, Natural Science Foundation of Hubei Province
Openalex Percentile: Top 13%
Viral Infections and Outbreaks Research
2.79
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Analysis of synonymous codon usage bias of Lassa virus — Hassan Ur Rehman, Kotb A. Attia, et al. · Virus Research (2025) | TGRS Research Map | TGRS