Mutational Changes Across Pathways for Different Euryarchaeal Lineages

The domain Archaea is in need of additional scientific investigation, so that our understanding of this variety of life may further approach levels of knowledge comparable to the two other domains, Eukarya and Bacteria. The archaeal phylum for which most genomic data exist is Euryarchaeota. This phylum is found both in diverse environments and in association with human and other eukaryotic hosts. We analyze the following question for differentiating Euryarchaeota lineages: as a gene changes in a pathway, do other genes also change in this same pathway? For homologous genes that are shared across the Euryarchaeota, we hypothesize that levels of genetic sequence differences between homologs, that are specific to different phylogenetic groupings, will be clustered based on pathway associations. Furthermore, we expect that pathway associations that are characteristic for different phylogenetic groupings will provide insights on environmental and host adaptations. We examined 113 fully sequenced genomes from the phylum Euryarchaeota, through the use of the Department of Energy Joint Genome Institute Integrated Microbial Genomes and Microbiomes (IMG/M) system. From our analysis, 2529 KEGG Orthology (KO) gene-based functions were identified from 113 fully sequenced genomes of Euryarchaeota, and 173 of these KO functions had full representation across all 113 fully sequenced genomes. These 173 KO functions mapped to 80 different KEGG Pathways, ranging from 1 KO function identified within a specific pathway to 44 KO functions identified within a specific pathway. Almost half of the associatively mapped KEGG Pathways had just a single identified KO function. There were on average 3.5 gene-based functions per pathway (median: 2; SE: 0.074). We investigated the ten pathways with the greatest number of functions, ranging from 8 to 44, which overall related to core metabolic pathways, DNA replication, and protein-coding gene expression. We then evaluated genetic variation across a chosen subset of three genera of Euryarchaeota, each genus of which appeared to have a similar degree of divergence based on distance trees that were generated within IMG/M. We report on those instances consistent with levels of genetic differences that are specific to different phylogenetic groupings, and have furthermore found these levels to be clustered based on pathway associations. This evidence supports a conclusion for how levels of genetic divergence can help to distinguish diverse varieties of Archaea. This finding is guiding us in a future direction for studying how these levels of genetic divergence relate to characteristic phenotypes and adaptations for these genera where, for instance, host association appears to be a factor that modulates levels of genetic differences for some pathways