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Expression patterns of protein kinases correlate with gene architecture and evolutionary rates.

Ogurtsov AY, Mariño-Ramírez L, Johnson GR, Landsman D, Shabalina SA, Spiridonov NA - PLoS ONE (2008)

Bottom Line: The primary transcript length of PK genes, similar to other protein coding genes, inversely correlates with gene expression level and expression breadth, which is likely due to the necessity to reduce metabolic costs of transcription for abundant messages.Structure and evolutionary divergence of tissue-specific PK genes is related to the proliferative activity of the tissue where these genes are predominantly expressed.Our data provide evidence that physiological requirements for transcription intensity, ubiquitous expression, and tissue-specific regulation shape gene structure and affect rates of evolution.

View Article: PubMed Central - PubMed

Affiliation: National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, USA.

ABSTRACT

Background: Protein kinase (PK) genes comprise the third largest superfamily that occupy approximately 2% of the human genome. They encode regulatory enzymes that control a vast variety of cellular processes through phosphorylation of their protein substrates. Expression of PK genes is subject to complex transcriptional regulation which is not fully understood.

Principal findings: Our comparative analysis demonstrates that genomic organization of regulatory PK genes differs from organization of other protein coding genes. PK genes occupy larger genomic loci, have longer introns, spacer regions, and encode larger proteins. The primary transcript length of PK genes, similar to other protein coding genes, inversely correlates with gene expression level and expression breadth, which is likely due to the necessity to reduce metabolic costs of transcription for abundant messages. On average, PK genes evolve slower than other protein coding genes. Breadth of PK expression negatively correlates with rate of non-synonymous substitutions in protein coding regions. This rate is lower for high expression and ubiquitous PKs, relative to low expression PKs, and correlates with divergence in untranslated regions. Conversely, rate of silent mutations is uniform in different PK groups, indicating that differing rates of non-synonymous substitutions reflect variations in selective pressure. Brain and testis employ a considerable number of tissue-specific PKs, indicating high complexity of phosphorylation-dependent regulatory network in these organs. There are considerable differences in genomic organization between PKs up-regulated in the testis and brain. PK genes up-regulated in the highly proliferative testicular tissue are fast evolving and small, with short introns and transcribed regions. In contrast, genes up-regulated in the minimally proliferative nervous tissue carry long introns, extended transcribed regions, and evolve slowly.

Conclusions/significance: PK genomic architecture, the size of gene functional domains and evolutionary rates correlate with the pattern of gene expression. Structure and evolutionary divergence of tissue-specific PK genes is related to the proliferative activity of the tissue where these genes are predominantly expressed. Our data provide evidence that physiological requirements for transcription intensity, ubiquitous expression, and tissue-specific regulation shape gene structure and affect rates of evolution.

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Correlations between the level of human-mouse evolutionarily divergence in protein coding and untranslated regions of human PK genes, expression breadth, and the size of pre-mRNA.A. Correlation between non-synonymous divergence, PK expression breadth and the size of pre-mRNA. Breadth of gene expression was estimated as the number of organ and tissue sources of gene-specific ESTs. Data are presented as averages and SEM. B. Correlations between evolutionarily divergence in protein coding regions and UTRs of PK genes.
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pone-0003599-g003: Correlations between the level of human-mouse evolutionarily divergence in protein coding and untranslated regions of human PK genes, expression breadth, and the size of pre-mRNA.A. Correlation between non-synonymous divergence, PK expression breadth and the size of pre-mRNA. Breadth of gene expression was estimated as the number of organ and tissue sources of gene-specific ESTs. Data are presented as averages and SEM. B. Correlations between evolutionarily divergence in protein coding regions and UTRs of PK genes.

Mentions: We analyzed structural features of PK genes associated with breadth of expression (defined as the number of tissues where a gene is expressed). We observed strong negative correlation between the size of pre-mRNA and the number of expressing tissues (R = −0.67, p = 1.22×10−6, Figure 3A). We also found similar correlation for non-PK genes, which was primarily due to smaller size of introns in broadly expressed genes.


Expression patterns of protein kinases correlate with gene architecture and evolutionary rates.

Ogurtsov AY, Mariño-Ramírez L, Johnson GR, Landsman D, Shabalina SA, Spiridonov NA - PLoS ONE (2008)

Correlations between the level of human-mouse evolutionarily divergence in protein coding and untranslated regions of human PK genes, expression breadth, and the size of pre-mRNA.A. Correlation between non-synonymous divergence, PK expression breadth and the size of pre-mRNA. Breadth of gene expression was estimated as the number of organ and tissue sources of gene-specific ESTs. Data are presented as averages and SEM. B. Correlations between evolutionarily divergence in protein coding regions and UTRs of PK genes.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2572838&req=5

pone-0003599-g003: Correlations between the level of human-mouse evolutionarily divergence in protein coding and untranslated regions of human PK genes, expression breadth, and the size of pre-mRNA.A. Correlation between non-synonymous divergence, PK expression breadth and the size of pre-mRNA. Breadth of gene expression was estimated as the number of organ and tissue sources of gene-specific ESTs. Data are presented as averages and SEM. B. Correlations between evolutionarily divergence in protein coding regions and UTRs of PK genes.
Mentions: We analyzed structural features of PK genes associated with breadth of expression (defined as the number of tissues where a gene is expressed). We observed strong negative correlation between the size of pre-mRNA and the number of expressing tissues (R = −0.67, p = 1.22×10−6, Figure 3A). We also found similar correlation for non-PK genes, which was primarily due to smaller size of introns in broadly expressed genes.

Bottom Line: The primary transcript length of PK genes, similar to other protein coding genes, inversely correlates with gene expression level and expression breadth, which is likely due to the necessity to reduce metabolic costs of transcription for abundant messages.Structure and evolutionary divergence of tissue-specific PK genes is related to the proliferative activity of the tissue where these genes are predominantly expressed.Our data provide evidence that physiological requirements for transcription intensity, ubiquitous expression, and tissue-specific regulation shape gene structure and affect rates of evolution.

View Article: PubMed Central - PubMed

Affiliation: National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, USA.

ABSTRACT

Background: Protein kinase (PK) genes comprise the third largest superfamily that occupy approximately 2% of the human genome. They encode regulatory enzymes that control a vast variety of cellular processes through phosphorylation of their protein substrates. Expression of PK genes is subject to complex transcriptional regulation which is not fully understood.

Principal findings: Our comparative analysis demonstrates that genomic organization of regulatory PK genes differs from organization of other protein coding genes. PK genes occupy larger genomic loci, have longer introns, spacer regions, and encode larger proteins. The primary transcript length of PK genes, similar to other protein coding genes, inversely correlates with gene expression level and expression breadth, which is likely due to the necessity to reduce metabolic costs of transcription for abundant messages. On average, PK genes evolve slower than other protein coding genes. Breadth of PK expression negatively correlates with rate of non-synonymous substitutions in protein coding regions. This rate is lower for high expression and ubiquitous PKs, relative to low expression PKs, and correlates with divergence in untranslated regions. Conversely, rate of silent mutations is uniform in different PK groups, indicating that differing rates of non-synonymous substitutions reflect variations in selective pressure. Brain and testis employ a considerable number of tissue-specific PKs, indicating high complexity of phosphorylation-dependent regulatory network in these organs. There are considerable differences in genomic organization between PKs up-regulated in the testis and brain. PK genes up-regulated in the highly proliferative testicular tissue are fast evolving and small, with short introns and transcribed regions. In contrast, genes up-regulated in the minimally proliferative nervous tissue carry long introns, extended transcribed regions, and evolve slowly.

Conclusions/significance: PK genomic architecture, the size of gene functional domains and evolutionary rates correlate with the pattern of gene expression. Structure and evolutionary divergence of tissue-specific PK genes is related to the proliferative activity of the tissue where these genes are predominantly expressed. Our data provide evidence that physiological requirements for transcription intensity, ubiquitous expression, and tissue-specific regulation shape gene structure and affect rates of evolution.

Show MeSH
Related in: MedlinePlus