Evolutionary Stratification of Codon Usage Bias In Plants Arises from GC3 Composition and Translational Optimization
Codon usage bias is a fundamental genomic characteristic that prefers non-random preferential use of synonymous codons. It is a major determinant of translational efficiency, gene regulation, and molecular evolution. However, the evolutionary bias and functional relevance of codon usage bias across the plant lineage is poorly defined and yet to understand what are the major factors responsible for relative synonymous codon usage (RSCU) in genomes and how codon usage bias influences the gene regulation, molecular evolution genomes. A genome-wide codon usage bias study of coding DNA sequences of 262 plant genome was conducted. It encompassed more than 4.6 billion codons from > 11 million coding sequences. Relative synonymous codon usage, codon adaptation index, codon-anticodon mapping, effective number of codon (ENC)-GC3, GC1,2-GC3, parity rule 2 (PR2-bias), molecular economy, and machine learning approaches were used for the study. It was found that codon usage bias was strongly non-random and exhibited a clear phylogenetic structuring. The higher plants favoured A/T-ending, whereas early-diverging lineages were enriched in G/C-ending codons. Analysis of RSCU, codon adaptation index, and codon-anticodon pairing indicated that translational selection is mediated by tRNA availability, contributing sustainability to these molecular patterns. Machine-learning approaches identified a small subset of codons having outsized influence on genome-wide codon usage landscapes. Further studies revealed the presence of robust inverse relationships between the effective number of codons and GC content at synonymous third positions. Neutrality analysis revealed approximately 61% of variation was driven by mutational pressure, tempered by selective constraints. Phylogenetic reconstruction showed a progressive relaxation of codon bias from algae to angiosperms while maintaining a conserved molecular economy cost of [~] 30 ATP per codon across the lineages. The study revealed codon usage bias is lineage-specific evolutionary conserved trait governed by mutation, selection, and translational optimization. Research HighlightsO_LILargest genome-wide study of codon usage in the plant kingdom, covering approximately 4.6 billion codons from 262 plant species that covers algae to angiosperms. C_LIO_LIShowed non-random AT-based codon usage with lineage-specific pattern where higher GC-ending codons are found in the lower plants and AT-ending codons in the higher plants. C_LIO_LIGC3-associated mutational pressure was the primary driver of codon usage bias, with approximately 61% of the variation explained by mutation. C_LIO_LIGC3 showed an inverse relationship with effective number of codons (ENC), establishing the role of GC3 as major axis of evolutionary divergence. C_LIO_LITranslational selection and codon adaptation shaped the genome-wide codon and amino acid usage. C_LIO_LICodon anticodon co-evolution is shaped by lineage-specific optimization driven by tRNA anticodon availability C_LIO_LIApproximately 30 ATPs/codon are required as translational energy cost, revealing strong evolutionary constraints on molecular economy. C_LI Author SummaryAlthough the genetic code is degenerate, synonymous codons are not used universally across the entire genome. Although codon bias is determined as one of the major determinants of translation and molecular evolution, its genome-wide evolutionary architecture across the plant kingdom still remains unresolved. Here the author presented a large and comprehensive analysis of genome-wide codon usage bias across the plant kingdom by integrating more than 4.6 billion codons from over 11 million sequences and 262 plant species. We found that codon usage bias is deeply conserved through the evolutionary stratification that tracks the plant phylogeny. The early diverging lineages algae and bryophytes preferred GC-ending codons, while higher plants preferred AT-ending codons. GC3 composition was found to play a major role towards divergence of codon usage, while mutational pressure played approximately 61% of genome-wide variation. Translational selection also added to the lineage-specific constraints. By integrating codon-anticodon mapping, codon-adaptation index, and machine-learning approaches, it was found that translational optimization is tightly regulated by tRNA availability. A small subset of codons showed disproportionate influence on the global codon usage landscape. Although there is extensive diversification in genome composition and codon preference, plants still showed a conserved energetic investment of approximately 30 ATP per codon. This indicates a strong conserved evolutionary constraint of translational economy. Collectively, the study demonstrates that codon usage bias is a property that is both evolutionarily conserved and dependent on lineage. These findings are resulted from the interplay between mutation, selection, and translational optimization. The study provides a comprehensive framework towards understanding the evolution of synonymous codon usage in plants and offers future efforts in evolutionary genomics, synthetic biology, and transgene design.