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The gene-specific codon counting database: a genome-based catalog of one-, two-, three-, four- and five-codon combinations present in Saccharomyces cerevisiae genes.

Tumu S, Patil A, Towns W, Dyavaiah M, Begley TJ - Database (Oxford) (2012)

Bottom Line: Using our developed Gene-Specific Codon Counting Database, we have identified extreme codon runs in specific genes.We have also demonstrated that specific codon combinations or usage patterns are over-represented in genes whose corresponding proteins belong to ribosome or translation-associated biological processes.Our resulting database provides a mineable list of multi-codon data and can be used to identify unique sequence runs and codon usage patterns in individual and functionally linked groups of genes.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science, University at Albany, State University of New York, Albany, NY 12222, USA.

ABSTRACT
A codon consists of three nucleotides and functions during translation to dictate the insertion of a specific amino acid in a growing peptide or, in the case of stop codons, to specify the completion of protein synthesis. There are 64 possible single codons and there are 4096 double, 262 144 triple, 16 777 216 quadruple and 1 073 741 824 quintuple codon combinations available for use by specific genes and genomes. In order to evaluate the use of specific single, double, triple, quadruple and quintuple codon combinations in genes and gene networks, we have developed a codon counting tool and employed it to analyze 5780 Saccharomyces cerevisiae genes. We have also developed visualization approaches, including codon painting, combination and bar graphs, and have used them to identify distinct codon usage patterns in specific genes and groups of genes. Using our developed Gene-Specific Codon Counting Database, we have identified extreme codon runs in specific genes. We have also demonstrated that specific codon combinations or usage patterns are over-represented in genes whose corresponding proteins belong to ribosome or translation-associated biological processes. Our resulting database provides a mineable list of multi-codon data and can be used to identify unique sequence runs and codon usage patterns in individual and functionally linked groups of genes.

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GSCC visual output demonstrating codon combinations in YEF3. Bar graphs (A–D) of single, double, triple, and quadruple codon combinations in the YEF3 gene, respectively. Each bar represents a codon. When the user places the mouse pointer over the each bar (codon) in GSCC, it shows the quantitated values of the codon. In all the graphs, the bars are sorted in the descending order of (actual–expected frequency). Codon painting (E) takes user input information, consisting of individual codons or codon runs, and highlights these occurrences in the gene sequence.
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bas002-F2: GSCC visual output demonstrating codon combinations in YEF3. Bar graphs (A–D) of single, double, triple, and quadruple codon combinations in the YEF3 gene, respectively. Each bar represents a codon. When the user places the mouse pointer over the each bar (codon) in GSCC, it shows the quantitated values of the codon. In all the graphs, the bars are sorted in the descending order of (actual–expected frequency). Codon painting (E) takes user input information, consisting of individual codons or codon runs, and highlights these occurrences in the gene sequence.

Mentions: In the context of Figure 2, we use bar graphs to display the number of individual codons as well as all two-, three- and four-codon combinations found in YEF3. In the displayed bar graphs, each bar corresponds to one codon or codon combination from the selected gene. In all the bar graphs, the bars are sorted in the descending order of Actual frequency minus Expected frequency for each codon or codon combination found in the target gene. The y-axis represents the number of times the specified codon was identified in the target gene and the x-axis represents the rank order for that specified codon or codon combination, as it relates to the difference in actual minus expected frequency. We have not been able to display the names for all the codon or codon combinations on the x-axis because of the character length; however, users can place the mouse pointer on each bar to retrieve specific details (sequence, actual and expected frequency) for each codon or codon combination. Since for each gene there are 64 or 4096 or 262 144 or 16 77 216 or 1 073 741 824 potential codons or combinations, specific to 1, 2, 3, 4 or 5 codons in a row, we cannot show all the codon combinations simultaneously on the screen using bar graphs; we have limited the user to 30 bars at a time on the screen. The user can employ the horizontal scroll bar to methodically analyze all codon combinations in a gene sequence. Figure 2 illustrates the key features of the bar graphs using YEF3 as an example.Figure 2


The gene-specific codon counting database: a genome-based catalog of one-, two-, three-, four- and five-codon combinations present in Saccharomyces cerevisiae genes.

Tumu S, Patil A, Towns W, Dyavaiah M, Begley TJ - Database (Oxford) (2012)

GSCC visual output demonstrating codon combinations in YEF3. Bar graphs (A–D) of single, double, triple, and quadruple codon combinations in the YEF3 gene, respectively. Each bar represents a codon. When the user places the mouse pointer over the each bar (codon) in GSCC, it shows the quantitated values of the codon. In all the graphs, the bars are sorted in the descending order of (actual–expected frequency). Codon painting (E) takes user input information, consisting of individual codons or codon runs, and highlights these occurrences in the gene sequence.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC3275765&req=5

bas002-F2: GSCC visual output demonstrating codon combinations in YEF3. Bar graphs (A–D) of single, double, triple, and quadruple codon combinations in the YEF3 gene, respectively. Each bar represents a codon. When the user places the mouse pointer over the each bar (codon) in GSCC, it shows the quantitated values of the codon. In all the graphs, the bars are sorted in the descending order of (actual–expected frequency). Codon painting (E) takes user input information, consisting of individual codons or codon runs, and highlights these occurrences in the gene sequence.
Mentions: In the context of Figure 2, we use bar graphs to display the number of individual codons as well as all two-, three- and four-codon combinations found in YEF3. In the displayed bar graphs, each bar corresponds to one codon or codon combination from the selected gene. In all the bar graphs, the bars are sorted in the descending order of Actual frequency minus Expected frequency for each codon or codon combination found in the target gene. The y-axis represents the number of times the specified codon was identified in the target gene and the x-axis represents the rank order for that specified codon or codon combination, as it relates to the difference in actual minus expected frequency. We have not been able to display the names for all the codon or codon combinations on the x-axis because of the character length; however, users can place the mouse pointer on each bar to retrieve specific details (sequence, actual and expected frequency) for each codon or codon combination. Since for each gene there are 64 or 4096 or 262 144 or 16 77 216 or 1 073 741 824 potential codons or combinations, specific to 1, 2, 3, 4 or 5 codons in a row, we cannot show all the codon combinations simultaneously on the screen using bar graphs; we have limited the user to 30 bars at a time on the screen. The user can employ the horizontal scroll bar to methodically analyze all codon combinations in a gene sequence. Figure 2 illustrates the key features of the bar graphs using YEF3 as an example.Figure 2

Bottom Line: Using our developed Gene-Specific Codon Counting Database, we have identified extreme codon runs in specific genes.We have also demonstrated that specific codon combinations or usage patterns are over-represented in genes whose corresponding proteins belong to ribosome or translation-associated biological processes.Our resulting database provides a mineable list of multi-codon data and can be used to identify unique sequence runs and codon usage patterns in individual and functionally linked groups of genes.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science, University at Albany, State University of New York, Albany, NY 12222, USA.

ABSTRACT
A codon consists of three nucleotides and functions during translation to dictate the insertion of a specific amino acid in a growing peptide or, in the case of stop codons, to specify the completion of protein synthesis. There are 64 possible single codons and there are 4096 double, 262 144 triple, 16 777 216 quadruple and 1 073 741 824 quintuple codon combinations available for use by specific genes and genomes. In order to evaluate the use of specific single, double, triple, quadruple and quintuple codon combinations in genes and gene networks, we have developed a codon counting tool and employed it to analyze 5780 Saccharomyces cerevisiae genes. We have also developed visualization approaches, including codon painting, combination and bar graphs, and have used them to identify distinct codon usage patterns in specific genes and groups of genes. Using our developed Gene-Specific Codon Counting Database, we have identified extreme codon runs in specific genes. We have also demonstrated that specific codon combinations or usage patterns are over-represented in genes whose corresponding proteins belong to ribosome or translation-associated biological processes. Our resulting database provides a mineable list of multi-codon data and can be used to identify unique sequence runs and codon usage patterns in individual and functionally linked groups of genes.

Show MeSH