scholarly journals Codon usage and codon context bias in Xanthophyllomyces dendrorhous

BMC Genomics ◽  
2015 ◽  
Vol 16 (1) ◽  
Author(s):  
Marcelo Baeza ◽  
Jennifer Alcaíno ◽  
Salvador Barahona ◽  
Dionisia Sepúlveda ◽  
Víctor Cifuentes
2017 ◽  
Vol 32 ◽  
pp. 31-39 ◽  
Author(s):  
Ratna Prabha ◽  
Dhananjaya P. Singh ◽  
Swati Sinha ◽  
Khurshid Ahmad ◽  
Anil Rai

Gene Reports ◽  
2021 ◽  
Vol 23 ◽  
pp. 101055 ◽  
Author(s):  
Jayanti Saha ◽  
Sukanya Bhattacharjee ◽  
Monalisha Pal Sarkar ◽  
Barnan Kumar Saha ◽  
Hriday Kumar Basak ◽  
...  

2006 ◽  
Vol 45 (02) ◽  
pp. 163-168 ◽  
Author(s):  
M. Pinheiro ◽  
V. Afreixo ◽  
G. Moura ◽  
A. Freitas ◽  
M. A. S. Santos ◽  
...  

Summary Objectives: Gene sequence features such as codon bias, codon context, and codon expansion (e.g. tri-nucleotide repeats) can be better understood at the genomic scale level by combining statistical methodologies with advanced computer algorithms and data visualization through sophisticated graphical interfaces. This paper presents the ANACONDA system, a bioinformatics application for gene primary structure analysis. Methods: Codon usage tables using absolute metrics and software for multivariate analysis of codon and amino acid usage are available in public databases. However, they do not provide easy computational and statistical tools to carry out detailed gene primary structure analysis on a genomic scale. We propose the usage of several statistical methods – contingency table analysis, residual analysis, multivariate analysis (cluster analysis) – to analyze the codon bias under various aspects (degree of association, contexts and clustering). Results: The developed solution is a software application that provides a user-guided analysis of codon sequences considering several contexts and codon usage on a genomic scale. The utilization of this tool in our molecular biology laboratory is focused on particular genomes, especially those from Saccharomyces cerevisiae, Candida albicansand Escherichia coli. In order to illustrate the applicability and output layouts of the software these species are herein used as examples. Conclusions: The statistical tools incorporated in the system are allowing to obtain global views of important sequence features. It is expected that the results obtained will permit identification of general rules that govern codon context and codon usage in any genome. Additionally, identification of genes containing expanded codons that arise as a consequence of erroneous DNA replication events will permit uncovering new genes associated with human disease.


2015 ◽  
Vol 75-76 ◽  
pp. 57-63 ◽  
Author(s):  
Han Bin Pek ◽  
Maximilian Klement ◽  
Kok Siong Ang ◽  
Bevan Kai-Sheng Chung ◽  
Dave Siak-Wei Ow ◽  
...  

F1000Research ◽  
2020 ◽  
Vol 9 ◽  
pp. 174
Author(s):  
Aikaterini Alexaki ◽  
Jacob Kames ◽  
Gaya K. Hettiarachchi ◽  
John C. Athey ◽  
Upendra K. Katneni ◽  
...  

Ribosome profiling provides the opportunity to evaluate translation kinetics at codon level resolution. Here, we describe ribosome profiling data, generated from two HEK293T cell lines. The ribosome profiling data are composed of Ribo-seq (mRNA sequencing data from ribosome protected fragments) and RNA-seq data (total RNA sequencing). The two HEK293T cell lines each express a version of the F9 gene, both of which are translated into identical proteins in terms of their amino acid sequences. However, these F9 genes vary drastically in their codon usage and predicted mRNA structure. We also provide the pipeline that we used to analyze the data. Further analyzing this dataset holds great potential as it can be used i) to unveil insights into the composition and regulation of the transcriptome, ii) for comparison with other ribosome profiling datasets, iii) to measure the rate of protein synthesis across the proteome and identify differences in elongation rates, iv) to discover previously unidentified translation of peptides, v) to explore the effects of codon usage or codon context in translational kinetics and vi) to investigate cotranslational folding. Importantly, a unique feature of this dataset, compared to other available ribosome profiling data, is the presence of the F9 gene in two very distinct coding sequences.


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