NAR Genomics and BioinformaticsGenomicsPeer-reviewed journal article
Mapping the Inter- and Intra-genic Codon Usage Landscape in Homo sapiens
Maahil ArshadiD, Matthew Uchmanowicz, Vanshika Rana, Brett TrostiD, Stephen W. SchereriD, Muhammad Arshad RafiqiD
Abstract
Although the genetic code is degenerate, codon selection is non-random and reflects significant functional constraints. Codon usage bias (CUB) acts as a layer of post-transcriptional regulation, influencing mRNA stability, translation kinetics, and co-translational protein folding. While CUB is well-characterized in unicellular organisms, its regulatory scope and functional consequences in humans remain complex and less defined. Our study offers a comprehensive evaluation of human codon usage. We report that genes exhibiting the strongest codon bias are enriched in high-stoichiometry biological processes, such as skin development and oxygen/carbon dioxide transport, and harbor significantly fewer synonymous variants than expected ({rho} = -0.24, p < 2.2 x 10-16). Furthermore, we find that codon optimization is spatially regulated: it is significantly more pronounced in structured protein domains compared to intrinsically disordered regions (IDRs) (Cliffs {Delta}= 0.26, p < 2.2 x 10-16). Consistent with translational selection, the most frequently used codons are supported by higher tRNA gene copy numbers ({rho} = 0.49, p < 6.4 x 10-4). Finally, by correcting for GC3 content, we reveal that the apparent correlation between ENC and adaptation indices (CAI/tAI) vanishes, allowing us to disentangle mutational pressure from translational selection. Collectively, our findings position codon usage bias as a central, evolutionarily conserved regulator of translation and protein folding in humans. Our results provide a comprehensive and integrated view of intergenic and intragenic codon usage bias in humans, reinforcing the biological relevance of synonymous codon choice in shaping translational dynamics and protein biogenesis. This provides a refined framework for interpreting synonymous variation and guiding functional genomics.
- organism: human
- assay: DNA methylation
- assay: whole-genome sequencing
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 0
- FWCI
- 0.00
- Field percentile
- 10th percentile
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