CladeOScope: functional interactions through the prism of clade-wise co-evolution

Abstract

Mapping co-evolved genes via phylogenetic profiling (PP) is a powerful approach to uncover functional interactions between genes and to associate them with pathways. Despite many successful endeavors, the understanding of co-evolutionary signals in eukaryotes remains partial. Our hypothesis is that ‘Clades’, branches of the tree of life (e.g. primates and mammals), encompass signals that cannot be detected by PP using all eukaryotes. As such, integrating information from different clades should reveal local co-evolution signals and improve function prediction. Accordingly, we analyzed 1028 genomes in 66 clades and demonstrated that the co-evolutionary signal was scattered across clades. We showed that functionally related genes are frequently co-evolved in only parts of the eukaryotic tree and that clades are complementary in detecting functional interactions within pathways. We examined the non-homologous end joining pathway and the UFM1 ubiquitin-like protein pathway and showed that both demonstrated distinguished co-evolution patterns in specific clades. Our research offers a different way to look at co-evolution across eukaryotes and points to the importance of modular co-evolution analysis. We developed the ‘CladeOScope’ PP method to integrate information from 16 clades across over 1000 eukaryotic genomes and is accessible via an easy to use web server at http://cladeoscope.cs.huji.ac.il.

Switch of Bacteria Community Under Oxygen Depletion in Sediment of Bohai Sea

“…Recent investigations on functional potential prediction of bacteria by employing PICRUSt2 in different environments, including soils (Toole et al, 2021), seawater (Xue et al, 2021), marine sediment (Su et al, 2018) are in help to decipher the detailed function variations successfully. In addition, benefiting from the function prediction of bacteria from the 16S rRNA gene sequences solely, diverse unknown microbes could be identified phylogenetically (Tsaban et al, 2021). With the unique contribution of each clade to Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways are developed, PICRUSt2 prediction is increasingly applied in microbial ecology studies.…”

Expanding the MECP2 network using comparative genomics reveals potential therapeutic targets for Rett syndrome

“…genes that are either conserved or lost as a group) are functionally related, often belonging to the same pathway ( Sherill-Rofe et al, 2019 ; Tabach et al, 2013a ; Tabach et al, 2013b ; Schwartz et al, 2013 ). We have shown that both across-clade and within-clade measures of co-evolution can be informative, and thus we computed NPPs both across all eukaryotes ( Figure 1A and Figure 1—figure supplement 1A ) and within mammals ( Figure 1B and Figure 1—figure supplement 1B ) as described previously ( Sherill-Rofe et al, 2019 ; Bloch et al, 2020 ; Tsaban et al, 2021 ; Braun et al, 2020 ).…”

“…We used the pipeline we described in Tsaban et al, 2021 to calculate the Normalized Phylogenetic Profile (NPP) of 1028 eukaryotic species and rank genes based on their evolutionary similarity to MECP2. Briefly, 20,192 human proteins (one representative protein sequence per gene) were downloaded from UniProt reference proteomes (June 2018 release) ( Bateman and UniProt Consortium, 2019 ).…”

“…can provide complementary evidence, and is especially informative for genes with multiple functions that show complex or recent evolution ( Sherill-Rofe et al, 2019 ). We recently incorporated a clade-specific analysis into our Normalized Phylogenetic Profile (NPP) software pipeline ( Tsaban et al, 2021 ), which is used for all the analyses in this study. We have used several functional databases including CORUM ( Ruepp et al, 2008 ), KEGG ( Kanehisa and Goto, 2000 ), and REACTOME ( Jassal et al, 2020 ) to validate the NPP method and show that it recovers known protein complexes and pathways with higher specificity and sensitivity than other phylogenetic methods ( Bloch et al, 2020 ; Tsaban et al, 2021 ).…”

Inverse Potts model improves accuracy of phylogenetic profiling

“…Phylogenetic profiling is one such analysis method. In this method, when two ortholog groups (OGs) have similar occurrence patterns among species in a table of OGs, the two OGs are presumed to be functionally related ( Kensche et al , 2008 ; Moi et al , 2020 ; Niu et al , 2017 ; Pellegrini et al , 1999 ; Stupp et al , 2021 ; Tremblay et al , 2021 ; Tsaban et al , 2021 ). Although phylogenetic profiling was first proposed to detect protein–protein interactions, this method in principle captures any functional relationships between genes.…”