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Coevolutionary Analysis

At this point, we’ve walked through the steps to take a set of sequences and obtain a set of COGs with phylogenetic reconstructions for each COG. We’re now ready to look for signals of coevolution, which imply functional associations between COGs. These methods are implemented via the EvoWeaver class in SynExtend, which includes many commonly used methods for detecting coevolutionary patterns.

While the previous steps have only utilized a small subsample of the data, we’re now finally going to work with the complete dataset. This dataset is comprised of the 91 Micrococcus genomes available with assemblies at the Scaffold, Chromosome, or Complete level (link to query). Note that more genomes may become available after this conference; these are all that were available at the time.

We ran the complete pipeline of identifying and annotating genes with DECIPHER, finding COGs with SynExtend, and then creating gene trees for each COG using DECIPHER. The complete data consist of 3,407 distinct COGs. All of this analysis is performed entirely within SynExtend and DECIPHER; no external packages or data are required aside from the input genomes.

We now use the new EvoWeaver class to try to find COGs that show evidence of correlated evolutionary selective pressures, also referred to as ‘coevolutionary signal’.