Geographical codon usage biases in prokaryotes - Pham, Loan (My University, 2025)
Despite the rapid extension of microbial genomics, the impact of environmental variables in affecting the distribution and variability of prokaryotic (archaeal and bacterial) genes is still little understood and a key shortcoming in area. The genome hypothesis proposed by Grantham in 1980 provides a foundation for understanding internal evolutionary dynamics. However, it does not account for spatial and ecological variations across diverse microbiomes. Building on this, we propose the geospatial genome hypothesis, which integrates geospatial and environmental factors as external forces to shape prokaryotic genomes. We hypothesize that both ecological and microbial community selection forces modulate the codon usage of prokaryotes. In this study, we merged genomics data and environmental metadata of prokaryotes from the Joint Genome Institution public database, analyzing the global patterns of GC content and codon usage bias. The results revealed distinct trends in Guanine+Citosine (GC) content across environmental conditions and a latitudinal gradient. Prokaryotes show contrasting latitudinal patterns in GC content, with bacteria having higher GC content in higher-latitude and terrestrial environments, while archaeal GC content peaks in equatorial and marine regions. Additionally, we find similarity in codon usage biases among samples inhabiting ecologically similar environments, suggesting local adaptation. Thus, in agreement with the geospatial genome hypothesis, both internal and external forces have influence to shape the GC and codon usage in prokaryotes. Overall, this study underscores the importance of genomic composition in signaling and predicting prokaryotes ecological adaptation in changing environments, highlighting the importance in integrating ecological perspective in understanding microbial genome evolution.
Keywords: Evolutionary genomics, microbial genomics, Codon usage, GC content, genome hypothesis, environmental and geographical adaptation, geospatial genome hypothesis