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Tissue-specific differences in human transfer RNA expression.

Dittmar KA, Goodenbour JM, Pan T - PLoS Genet. (2006)

Bottom Line: We found tissue-specific differences in the expression of individual tRNA species, and tRNAs decoding amino acids with similar chemical properties exhibited coordinated expression in distinct tissue types.Relative tRNA abundance exhibits a statistically significant correlation to the codon usage of a collection of highly expressed, tissue-specific genes in a subset of tissues or tRNA isoacceptors.Our findings demonstrate the existence of tissue-specific expression of tRNA species that strongly implicates a role for tRNA heterogeneity in regulating translation and possibly additional processes in vertebrate organisms.

View Article: PubMed Central - PubMed

Affiliation: Department of Biochemistry and Molecular Biology, University of Chicago, Chicago, Illinois, United States of America.

ABSTRACT
Over 450 transfer RNA (tRNA) genes have been annotated in the human genome. Reliable quantitation of tRNA levels in human samples using microarray methods presents a technical challenge. We have developed a microarray method to quantify tRNAs based on a fluorescent dye-labeling technique. The first-generation tRNA microarray consists of 42 probes for nuclear encoded tRNAs and 21 probes for mitochondrial encoded tRNAs. These probes cover tRNAs for all 20 amino acids and 11 isoacceptor families. Using this array, we report that the amounts of tRNA within the total cellular RNA vary widely among eight different human tissues. The brain expresses higher overall levels of nuclear encoded tRNAs than every tissue examined but one and higher levels of mitochondrial encoded tRNAs than every tissue examined. We found tissue-specific differences in the expression of individual tRNA species, and tRNAs decoding amino acids with similar chemical properties exhibited coordinated expression in distinct tissue types. Relative tRNA abundance exhibits a statistically significant correlation to the codon usage of a collection of highly expressed, tissue-specific genes in a subset of tissues or tRNA isoacceptors. Our findings demonstrate the existence of tissue-specific expression of tRNA species that strongly implicates a role for tRNA heterogeneity in regulating translation and possibly additional processes in vertebrate organisms.

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Linear Correlation of Relative tRNA Abundance to Codon Usage of Tissue-Specific Genes that Are Expressed at High LevelsThe r- and p-values are indicated in each graph.(A) Liver/brain, all data points. Excluding the two outlying data points (circled) gives a linear fit with r = 0.78, p < 0.0001, and a slope of 1.0 ± 0.2. Inclusion of these two data points gives a linear fit with r = 0.62, p = 0.00098, and a slope of 0.8 ± 0.2.(B) Three individual isoacceptors across all five tissues show linear correlation with r = 0.90 to 0.94 and p = 0.016 to 0.039.(C) Two sets of four tRNAArg isoacceptors in liver and thymus show linear correlation with r = 0.93 and 0.97 and p = 0.067 and 0.033, respectively.
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pgen-0020221-g004: Linear Correlation of Relative tRNA Abundance to Codon Usage of Tissue-Specific Genes that Are Expressed at High LevelsThe r- and p-values are indicated in each graph.(A) Liver/brain, all data points. Excluding the two outlying data points (circled) gives a linear fit with r = 0.78, p < 0.0001, and a slope of 1.0 ± 0.2. Inclusion of these two data points gives a linear fit with r = 0.62, p = 0.00098, and a slope of 0.8 ± 0.2.(B) Three individual isoacceptors across all five tissues show linear correlation with r = 0.90 to 0.94 and p = 0.016 to 0.039.(C) Two sets of four tRNAArg isoacceptors in liver and thymus show linear correlation with r = 0.93 and 0.97 and p = 0.067 and 0.033, respectively.

Mentions: We attempted to find potential correlations between the codon usage of tissue-specifically expressed genes to the relative tRNA abundance among these tissues (Figure 4). In bacteria and yeast, correlations of the abundance of tRNA isoacceptors to codon usage are derived primarily from genes that are translated at high levels (e.g., ribosomal proteins). Adapting this strategy, thresholds were algorithmically established to determine the top 13 to 43 tissue-specific transcripts according to the Human GeneAtlas GNF1H gcRMA dataset at http://symatlas.gnf.org/SymAtlas [2]. Gene sequences for the most highly expressed tissue-specific transcripts were then compiled and analyzed for codon content at http://bioinformatics.org/sms [34]. Some gene information was not included due to ambiguity of data or nomenclature. Table 2 lists the tissue-specific threshold expression levels used for this analysis and the tabulated gene and codon counts. The dataset contains 7,737 to 21,163 codons for six tissues: brain, liver, testis, ovary, thymus, and lymph node (we were unable to carry out this analysis for vulva and spleen). To mimic the relative tRNA abundance measurements, the raw codon count is normalized to the total number of codons in every tissue, and the sum of each normalized codon count from nonbrain tissues is divided by the sum of the same count from brain (Tables S5 and S6).


Tissue-specific differences in human transfer RNA expression.

Dittmar KA, Goodenbour JM, Pan T - PLoS Genet. (2006)

Linear Correlation of Relative tRNA Abundance to Codon Usage of Tissue-Specific Genes that Are Expressed at High LevelsThe r- and p-values are indicated in each graph.(A) Liver/brain, all data points. Excluding the two outlying data points (circled) gives a linear fit with r = 0.78, p < 0.0001, and a slope of 1.0 ± 0.2. Inclusion of these two data points gives a linear fit with r = 0.62, p = 0.00098, and a slope of 0.8 ± 0.2.(B) Three individual isoacceptors across all five tissues show linear correlation with r = 0.90 to 0.94 and p = 0.016 to 0.039.(C) Two sets of four tRNAArg isoacceptors in liver and thymus show linear correlation with r = 0.93 and 0.97 and p = 0.067 and 0.033, respectively.
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pgen-0020221-g004: Linear Correlation of Relative tRNA Abundance to Codon Usage of Tissue-Specific Genes that Are Expressed at High LevelsThe r- and p-values are indicated in each graph.(A) Liver/brain, all data points. Excluding the two outlying data points (circled) gives a linear fit with r = 0.78, p < 0.0001, and a slope of 1.0 ± 0.2. Inclusion of these two data points gives a linear fit with r = 0.62, p = 0.00098, and a slope of 0.8 ± 0.2.(B) Three individual isoacceptors across all five tissues show linear correlation with r = 0.90 to 0.94 and p = 0.016 to 0.039.(C) Two sets of four tRNAArg isoacceptors in liver and thymus show linear correlation with r = 0.93 and 0.97 and p = 0.067 and 0.033, respectively.
Mentions: We attempted to find potential correlations between the codon usage of tissue-specifically expressed genes to the relative tRNA abundance among these tissues (Figure 4). In bacteria and yeast, correlations of the abundance of tRNA isoacceptors to codon usage are derived primarily from genes that are translated at high levels (e.g., ribosomal proteins). Adapting this strategy, thresholds were algorithmically established to determine the top 13 to 43 tissue-specific transcripts according to the Human GeneAtlas GNF1H gcRMA dataset at http://symatlas.gnf.org/SymAtlas [2]. Gene sequences for the most highly expressed tissue-specific transcripts were then compiled and analyzed for codon content at http://bioinformatics.org/sms [34]. Some gene information was not included due to ambiguity of data or nomenclature. Table 2 lists the tissue-specific threshold expression levels used for this analysis and the tabulated gene and codon counts. The dataset contains 7,737 to 21,163 codons for six tissues: brain, liver, testis, ovary, thymus, and lymph node (we were unable to carry out this analysis for vulva and spleen). To mimic the relative tRNA abundance measurements, the raw codon count is normalized to the total number of codons in every tissue, and the sum of each normalized codon count from nonbrain tissues is divided by the sum of the same count from brain (Tables S5 and S6).

Bottom Line: We found tissue-specific differences in the expression of individual tRNA species, and tRNAs decoding amino acids with similar chemical properties exhibited coordinated expression in distinct tissue types.Relative tRNA abundance exhibits a statistically significant correlation to the codon usage of a collection of highly expressed, tissue-specific genes in a subset of tissues or tRNA isoacceptors.Our findings demonstrate the existence of tissue-specific expression of tRNA species that strongly implicates a role for tRNA heterogeneity in regulating translation and possibly additional processes in vertebrate organisms.

View Article: PubMed Central - PubMed

Affiliation: Department of Biochemistry and Molecular Biology, University of Chicago, Chicago, Illinois, United States of America.

ABSTRACT
Over 450 transfer RNA (tRNA) genes have been annotated in the human genome. Reliable quantitation of tRNA levels in human samples using microarray methods presents a technical challenge. We have developed a microarray method to quantify tRNAs based on a fluorescent dye-labeling technique. The first-generation tRNA microarray consists of 42 probes for nuclear encoded tRNAs and 21 probes for mitochondrial encoded tRNAs. These probes cover tRNAs for all 20 amino acids and 11 isoacceptor families. Using this array, we report that the amounts of tRNA within the total cellular RNA vary widely among eight different human tissues. The brain expresses higher overall levels of nuclear encoded tRNAs than every tissue examined but one and higher levels of mitochondrial encoded tRNAs than every tissue examined. We found tissue-specific differences in the expression of individual tRNA species, and tRNAs decoding amino acids with similar chemical properties exhibited coordinated expression in distinct tissue types. Relative tRNA abundance exhibits a statistically significant correlation to the codon usage of a collection of highly expressed, tissue-specific genes in a subset of tissues or tRNA isoacceptors. Our findings demonstrate the existence of tissue-specific expression of tRNA species that strongly implicates a role for tRNA heterogeneity in regulating translation and possibly additional processes in vertebrate organisms.

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