Synonymous codon usage and context analysis of genes associated with pancreatic cancer

Analysis of the Compositional Features and Codon Usage Pattern of Genes Involved in Human Autophagy

Autophagy plays an intricate role in paradigmatic human pathologies such as cancer, and neurodegenerative, cardiovascular, and autoimmune disorders. Autophagy regulation is performed by a set of autophagy-related (ATG) genes, first recognized in yeast genome and subsequently identified in other species, including humans. Several other genes have been identified to be involved in the process of autophagy either directly or indirectly. Studying the codon usage bias (CUB) of genes is crucial for understanding their genome biology and molecular evolution. Here, we examined the usage pattern of nucleotide and synonymous codons and the influence of evolutionary forces in genes involved in human autophagy. The coding sequences (CDS) of the protein coding human autophagy genes were retrieved from the NCBI nucleotide database and analyzed using various web tools and software to understand their nucleotide composition and codon usage pattern. The effective number of codons (ENC) in all genes involved in human autophagy ranges between 33.26 and 54.6 with a mean value of 45.05, indicating an overall low CUB. The nucleotide composition analysis of the autophagy genes revealed that the genes were marginally rich in GC content that significantly influenced the codon usage pattern. The relative synonymous codon usage (RSCU) revealed 3 over-represented and 10 under-represented codons. Both natural selection and mutational pressure were the key forces influencing the codon usage pattern of the genes involved in human autophagy.

Pan-cancer analyses of synonymous mutations based on tissue-specific codon optimality

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Developed tissue-specific codon optimality in 29 human tissues.

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Applied these to analyze synonymous mutations in ∼10,000 tumor and normal samples.

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Synonymous mutations frequently increase optimal codons in most cancer types.

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Synonymous mutations frequently increase optimal codons cell cycle-related genes.

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Frequency of optimal codon gain relates to proliferation, DDR deficiency, and survival.

Codon optimality has been demonstrated to be an important determinant of mRNA stability and expression levels in multiple model organisms and human cell lines. However, tissue-specific codon optimality has not been developed to investigate how codon optimality is usually perturbed by somatic synonymous mutations in human cancers. Here, we determined tissue-specific codon optimality in 29 human tissues based on mRNA expression data from the Genotype-Tissue Expression project. We found that optimal codons were associated with differentiation, whereas non-optimal codons were correlated with proliferation. Furthermore, codons biased toward differentiation displayed greater tissue specificity in codon optimality, and the tissue specificity of codon optimality was primarily present in amino acids with high degeneracy of the genetic code. By applying tissue-specific codon optimality to somatic synonymous mutations in 8532 tumor samples across 24 cancer types and to those in 416 normal cells across six human tissues, we found that synonymous mutations frequently increased optimal codons in tumor cells and cancer-related genes (e.g., genes involved in cell cycle). Furthermore, an elevated frequency of optimal codon gain was found to promote tumor cell proliferation in three cancer types characterized by DNA damage repair deficiency and could act as a prognostic biomarker for patients with triple-negative breast cancer. In summary, this study profiled tissue-specific codon optimality in human tissues, revealed alterations in codon optimality caused by synonymous mutations in human cancers, and highlighted the non-negligible role of optimal codon gain in tumorigenesis and therapeutics.