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Biology subjects

Begley, U.

Publications and source records attributed to Begley, U..

2 recordsLinked to original sources

Oncogenes have the most distinct codon biases in the genome and codon signatures that oppose tumor suppressor genes

Oncogenes and tumor-suppressor genes play opposing roles in cancer biology to promote and restrict growth, respectively. Codon usage patterns interface with tRNA modifications to control translation, leading to gene-specific codon signatures with regulatory potential. As such, codon-biased translational regulation has been identified as a driver of proliferation and drug resistance in multiple cancers. We used advanced codon analytics methods to characterize and compare codon usage bias in oncogenes and tumor suppressor genes (TSGs) from humans and mice at group and gene-specific levels. We demonstrate that human oncogenes exhibit a distinct and opposing codon usage pattern to TSGs. This phenomenon is also present in mice but with less distinct oncogene bias relative to humans. Further comparison to 447 gene ontology groups demonstrated that human oncogenes have the most distinct codon usage patterns in the genome, while also highlighting that codon bias can separate functionally related genes and pathways from other biological processes. Using gene-specific codon analytics, we determined that human oncogenes have two types of extreme codon bias: a large group (N = 43) over-using G/C ending (GC3) codons and a smaller group (N = 12) over-using A/U (AU3) ending codons. While GC3 bias has been linked to increased translation in general, the AU3 finding suggests that genetic, environmental, or stress-related signals could drive the translation of this small group of oncogenes. The less extreme bias observed in mouse oncogenes and tumor suppressors likely underscores species-specific differences in oncogenic translation programs. Together, our findings highlight codon usage bias as a potential determinant of oncogene expression, provide a framework for ontology-based codon analysis, and uncover on species-specific differences in oncogene translation and codon usage biases.

cancer biology↗

Genes and Pathways Comprising the Human and Mouse ORFeomes Display Distinct Codon Bias Signatures that Can Regulate Protein Levels

Arginine, glutamic acid and selenocysteine based codon bias has been shown to regulate the translation of specific mRNAs for proteins that participate in stress responses, cell cycle and transcriptional regulation. Defining codon-bias in gene networks has the potential to identify other pathways under translational control. Here we have used computational methods to analyze the ORFeome of all unique human (19,711) and mouse (22,138) open-reading frames (ORFs) to characterize codon-usage and codon-bias in genes and biological processes. We show that ORFeome-wide clustering of gene-specific codon frequency data can be used to identify ontology-enriched biological processes and gene networks, with developmental and immunological programs well represented for both humans and mice. We developed codon over-use ontology mapping and hierarchical clustering to identify multi-codon bias signatures in human and mouse genes linked to signaling, development, mitochondria and metabolism, among others. The most distinct multi-codon bias signatures were identified in human genes linked to skin development and RNA metabolism, and in mouse genes linked to olfactory transduction and ribosome, highlighting species-specific pathways potentially regulated by translation. Extreme codon bias was identified in genes that included transcription factors and histone variants. We show that re-engineering extreme usage of C- or U-ending codons for aspartic acid, asparagine, histidine and tyrosine in the transcription factors CEBPB and MIER1, respectively, significantly regulates protein levels. Our study highlights that multi-codon bias signatures can be linked to specific biological pathways and that extreme codon bias with regulatory potential exists in transcription factors for immune response and development. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=140 SRC="FIGDIR/small/636209v1_ufig1.gif" ALT="Figure 1"> View larger version (45K): org.highwire.dtl.DTLVardef@de9969org.highwire.dtl.DTLVardef@29e1dforg.highwire.dtl.DTLVardef@1abfebcorg.highwire.dtl.DTLVardef@e119b6_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗