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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http://dx.doi.org/10.1016/j.virusres.2025.199528 | DOI Listing |
Virus Evol
January 2025
Hemostasis Branch 1, Division of Hemostasis, Office of Plasma Protein Therapeutics CMC, Office of Therapeutic Products, Center for Biologics Evaluation and Research, Food and Drug Administration, 10903 New Hampshire Ave, Silver Spring, MD 20993, USA.
A consistent area of interest since the beginning of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has been the sequence composition of the virus and how it has changed over time. Many resources have been developed for the storage and analysis of SARS-CoV-2 data, such as GISAID (Global Initiative on Sharing All Influenza Data), NCBI, Nextstrain, and outbreak.info.
View Article and Find Full Text PDFNucleic Acids Res
January 2025
School of Biological Sciences, University of Edinburgh, Edinburgh, EH9 3JH, United Kingdom.
The growing demand for biological products drives many efforts to maximize expression of heterologous proteins. Advances in high-throughput sequencing can produce data suitable for building sequence-to-expression models with machine learning. The most accurate models have been trained on one-hot encodings, a mechanism-agnostic representation of nucleotide sequences.
View Article and Find Full Text PDFWorld J Microbiol Biotechnol
January 2025
Shandong Provincial Key Laboratory of Water Pollution Control and Resource Reuse, School of Environmental Science and Engineering, Shandong University, 72 Binhai Road, Jimo, Qingdao, 266237, China.
Catabolic plasmids are critical factors in the degradation of recalcitrant xenobiotics, such as dioxins. Understanding the persistence and evolution of native catabolic plasmids is pivotal for controlling their function in microbial remediation. Here, we track the fitness and evolution of Rhodococcus sp.
View Article and Find Full Text PDFInt J Mol Sci
January 2025
Department of Neurosurgical Engineering and Translational Neuroscience, Graduate School of Medicine, Tohoku University, Sendai 980-8575, Japan.
Int J Mol Sci
January 2025
School of Life Sciences, Nanchang University, Nanchang 330031, China.
is a fully mycoheterotrophic orchid that lacks both leaves and roots, belonging to the genus in the subtribe Calypsoinae. In this study, we assembled and annotated its mitochondrial genome (397,867 bp, GC content: 42.70%), identifying 55 genes, including 37 protein-coding genes (PCGs), 16 tRNAs, and 2 rRNAs, and conducted analyses of relative synonymous codon usage (RSCU), repeat sequences, horizontal gene transfers (HGTs), and gene selective pressure (dN/dS).
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