Solving the gene classification problem with a novel Gene Space approach

Abstract

Genomic organization and its comparative analysis throughout all major kingdoms of life are extensively studied across multiple scales, ranging from individual gene-level analyses to system-wide investigations. This work introduces a novel framework for characterizing genetic architecture through a new integral genomic parameter. We propose the concept of a multidimensional Gene Space to enable holistic quantification of genome organization principles. Gene Space -- a multidimensional space based on the frequencies of nucleotide tokens, such as individual nucleotides, codons, or codon pairs. We demonstrate that in this space, genes from each of the studied microorganism species occupy a limited region, and individual genes from different species can be effectively separated. Consequently, a specific Genome Subspace can be defined for each species, which constrains the organisms evolutionary pathways, thereby determining the constraints on gene optimization for these species. Further in-depth analysis is required to test if it is true for other organisms as well. The Gene Space framework offers a novel and powerful approach for genome analysis at the most basic levels, with promising applications in comparative genomics, evolutionary biology, and gene optimization.