DOI: 10.5061/dryad.p8cz8w9rd
title: The Community Coevolution Model with application to the study of evolutionary relationships between genes based on phylogenetic profiles

description: Organismal traits can evolve in a coordinated way, with correlated
 patterns of gains and losses reflecting important evolutionary
 associations. Discovering these associations can reveal important
 information about the functional and ecological linkages among traits.
 Phylogenetic profiles treat individual genes as traits distributed across
 sets of genomes and can provide a fine-grained view of the genetic
 underpinnings of evolutionary processes in a set of genomes. Phylogenetic
 profiling has been used to identify genes that are functionally linked,
 and to identify common patterns of lateral gene transfer in
 microorganisms. However, comparative analysis of phylogenetic profiles and
 other trait distributions should take into account the phylogenetic
 relationships among the organisms under consideration. Here we propose the
 Community Coevolution Model (CCM), a new coevolutionary model to analyze
 the evolutionary associations among traits, with a focus on phylogenetic
 profiles. In the CCM, traits are considered to evolve as a community with
 interactions, and the transition rate for each trait depends on the
 current states of other traits. Surpassing other comparative methods for
 pairwise trait analysis, CCM has the additional advantage of being able to
 examine multiple traits as a community to reveal more dependency
 relationships. We also develop a simulation procedure to generate
 phylogenetic profiles with correlated evolutionary patterns that can be
 used as benchmark data for evaluation purposes. A simulation study
 demonstrates that CCM is more accurate than other methods including the
 Jaccard Index and three tree-aware methods. The parameterization of CCM
 makes the interpretation of the relations between genes more direct, which
 leads to Darwin's scenario being identified easily based on the
 estimated parameters. We show that CCM is more efficient and fits real
 data better than other methods resulting in higher likelihood scores with
 fewer parameters. An examination of 3786 phylogenetic profiles across a
 set of 659 bacterial genomes highlights linkages between genes with common
 functions, including many patterns that would not have been identified
 under a non-phylogenetic model of common distribution. We also applied the
 CCM to 44 proteins in the well-studied Mitochondrial Respiratory Complex I
 and recovered associations that mapped well onto the structural
 associations that exist in the complex.
description: The Community Coevolution Model (CCM), is a new coevolutionary
 model to analyze the evolutionary associations among binary
 traits. <em>Supplementary Figures and Tables
 files:</em> Supplementary Figures and
 Tables Table
 S3_Predictions_Unannotated_Genes_LZ The
 files contain the figures and tables that are mentioned in the CCM
 paper. <em>LZ data sets:</em>
 Data file: phylogenetic tree (LZ)
 Data file: profile matrix (LZ) 
 The draft assembly of the bacterium “Lachnospiraceae bacterium
 3-1-57FAACT1” (abbreviated as LZ), was isolated from a biopsy retrieved
 from the transverse colon of a female Crohn’s Disease patient at the time
 of colonoscopy (Liu et al. 2018). 658 completed and draft genomes from
 class Clostridia were retrieved from the National Center for Biotechnology
 Information (NCBI) for the comparative analysis of LZ. The phylogenetic
 tree was built through the AMPHORA2 pipeline (Wu and Scott 2012) and
 RAxML-HPC (Stamatakis 2006) using their concatenated, conserved protein
 sequences and another set of eight outgroup genomes from class Bacilli and
 phyla Actinobacteria and Proteobacteria were used for rooting. The
 phylogenetic profiles were constructed by comparing the complete set of LZ
 against all other genomes using rapsearch (Ye et al. 2011).
description: Supplementary Figures and Tables  (.pdf)
 Table S3_Predictions_Unannotated_Genes_LZ (.csv)
 Data file: phylogenetic tree (LZ)  (.nex)
 Data file: profile matrix (LZ) (.csv) 
 The tree files (.nex, .nwk) can be opened with FigTree ,
 the online tool iTOL ,
 etc. For more details, please refer to the README
 file.