Five annotated genomes of Mycoplasma hyorhinis were analyzed for clarifying evolutionary dynamics driving the overall codon usage pattern. Information entropy used for estimating nucleotide usage pattern at the gene level indicates that multiple evolutionary dynamics participate in forcing nucleotide usage bias at every codon position. Moreover, nucleotide usage bias directly contributes to synonymous codon usage biases with two different extremes. The overrepresented codons tended to have A/T in the third codon position, and the underrepresented codons strongly used G/C in the third position. Furthermore, correspondence analysis and neutrality plot reflect an obvious interplay between mutation pressure and natural selection mediating codon usage in M. hyorhinis genome. Due to significant bias in usages between A/T and G/C at the gene level, different selective forces have been proposed to contribute to codon usage preference in M. hyorhinis genome, including nucleotide composition constraint derived from mutation pressure, translational selection involved in natural selection, and strand-specific mutational bias represented by different nucleotide skew index. The systemic analyses of codon usage for M. hyorhinis can enable us to better understand the mechanisms of evolution in this species.
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http://dx.doi.org/10.1002/jobm.202000592 | 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
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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.
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