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Results for “phylome”

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A phylogenomic approach to microbial evolution.

To study the origin and evolution of biochemical pathways in microorganisms, we have developed methods and software for automatic, large-scale reconstructions of phylogenetic relationships. We define the complete set of phylogenetic trees derived from the proteome of an organism as the phylome and introduce the term phylogenetic connection as a concept that describes the relative relationships between taxa in a tree. A query system has been incorporated into the system so as to allow searches for defined categories of trees within the phylome. As a complement, we have developed the pyphy system for visualising the results of complex queries on phylogenetic connections, genomic locations and functional assignments in a graphical format. Our phylogenomics approach, which links phylogenetic information to the flow of biochemical pathways within and among microbial species, has been used to examine more than 8000 phylogenetic trees from seven microbial genomes. The results have revealed a rich web of phylogenetic connections. However, the separation of Bacteria and Archaea into two separate domains remains robust.

Computational Biology↗

Newly Developed Structure-Based Methods Do Not Outperform Standard Sequence-Based Methods for Large-Scale Phylogenomics.

Recent developments in protein structure prediction have allowed the use of this previously limited source of information at genome-wide scales. It has been proposed that the use of structural information may offer advantages over sequences in phylogenetic reconstruction, due to their slower rate of evolution and direct correlation to function. Here, we examined how recently developed methods for structure-based homology search and tree reconstruction compare with current state-of-the-art sequence-based methods in reconstructing genome-wide collections of gene phylogenies (i.e. phylomes). While structure-based methods can be useful in specific scenarios, we found that their current performance does not justify using the newly developed structure-based methods as a default choice in large-scale phylogenetic studies. On the one hand, the best performing sequence-based tree reconstruction methods still outperform structure-based methods for this task. On the other hand, structure-based homology detection methods provide larger lists of candidate homologs, as previously reported. However, this comes at the expense of missing hits identified by sequence-based methods, as well as providing sets of homolog candidates with higher fractions of false positives. These insights help to guide the use of structural data in comparative genomics and highlight the need to continue improving structure-based approaches. Our pipeline is fully reproducible and has been implemented in a Snakemake workflow. This will facilitate a continuous assessment of future improvements of structure-based tools in the AlphaFold era.

Phylogeny↗