Visualisation and graph-theoretic analysis of a large-scale protein structural interactome

Bolser, Dan; Dafas, Panos; Harrington, Richard; Park, Jong C.; Schroeder, Michael

doi:10.1186/1471-2105-4-45

Cited by 22 publications

(6 citation statements)

References 59 publications

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“…We mapped all genes with signatures of positive selection on coding and cis -regulatory sequences in the TRN (Figure 3 ). We also estimated betweenness for each gene in the TRN; betweenness is a global measure of centrality (Borgatti and Everett, 2006 ) which ranges from 1, indicating most central or at the core of the network, to 0, indicating the outside perimeter or the periphery of the network. We compared the average betweenness of genes with substantial signs of positive (γ > 1) and negative (γ < −1) selection.…”

Section: Resultsmentioning

confidence: 99%

Pleiotropy constrains the evolution of protein but not regulatory sequences in a transcription regulatory network influencing complex social behaviors

et al. 2014

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It is increasingly apparent that genes and networks that influence complex behavior are evolutionary conserved, which is paradoxical considering that behavior is labile over evolutionary timescales. How does adaptive change in behavior arise if behavior is controlled by conserved, pleiotropic, and likely evolutionary constrained genes? Pleiotropy and connectedness are known to constrain the general rate of protein evolution, prompting some to suggest that the evolution of complex traits, including behavior, is fuelled by regulatory sequence evolution. However, we seldom have data on the strength of selection on mutations in coding and regulatory sequences, and this hinders our ability to study how pleiotropy influences coding and regulatory sequence evolution. Here we use population genomics to estimate the strength of selection on coding and regulatory mutations for a transcriptional regulatory network that influences complex behavior of honey bees. We found that replacement mutations in highly connected transcription factors and target genes experience significantly stronger negative selection relative to weakly connected transcription factors and targets. Adaptively evolving proteins were significantly more likely to reside at the periphery of the regulatory network, while proteins with signs of negative selection were near the core of the network. Interestingly, connectedness and network structure had minimal influence on the strength of selection on putative regulatory sequences for both transcription factors and their targets. Our study indicates that adaptive evolution of complex behavior can arise because of positive selection on protein-coding mutations in peripheral genes, and on regulatory sequence mutations in both transcription factors and their targets throughout the network.

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Section: Resultsmentioning

confidence: 99%

Pleiotropy constrains the evolution of protein but not regulatory sequences in a transcription regulatory network influencing complex social behaviors

et al. 2014

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“…expression values obtained by microarray experiments) by coloring nodes. Osprey [4] and PSIMAP [2] are typical examples that have visualized gene/protein interaction networks and their experimental values. However, their examples do not provide an optimal layout of large-scale networks.…”

Section: Visualization Of Biological Networkmentioning

confidence: 99%

A hybrid space-filling and force-directed layout method for visualizing multiple-category graphs

Itoh

Muelder

et al. 2009

2009 IEEE Pacific Visualization Symposium

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Many graphs used in real-world applications consist of nodes belonging to more than one category. We call such graph "multiplecategory graphs". Social networks are typical examples of multiplecategory graphs: nodes are persons, links are friendships, and categories are communities that the persons belong to. It is often helpful to visualize both connectivity and categories of the graphs simultaneously. In this paper, we present a new visualization technique for multiple-category graphs. The technique firstly constructs hierarchical clusters of the nodes based on both connectivity and categories. It then places the nodes by a new hybrid space-filling and force-directed layout algorithm to clearly display both connectivity and category information. We show layout results using our hybrid method and compare it with other methods, and present a case study using an active biological network dataset.

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“…Table 3). Recently, the large-scale protein structural interactome suggested 19 SCOP superfamilies as the most interactive superfamilies [42]. Also interestingly enough, two out of these 19 superfamilies (i.e.…”

Section: Highly Connected Hubs In Functional Similarity Networkmentioning

confidence: 99%

Genome-Wide Analysis of Enzyme Structure-Function Combination Across Three Domains of Life

Zhang¹,

Tang

2007

PPL

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To investigate diverse enzyme structure-function combination (SFC) types in different species, 34 different genome sequences were annotated using the protein catalytic domain database SCOPEC (http://www.enzome.com/enzome/), in which both the structure and function for each entry are known. Annotated enzymes with catalytic domains from the same SCOP superfamily are considered to have an identical structure. Annotated enzymes sharing the identical three-digit EC number are considered to have the same enzymatic function. Results reveal that the different SFC types for enzymes identified in archaea, bacteria and eukaryota are 137, 300 and 313, respectively. About 80% of the SFCs identified in archaea can be consistently found in bacteria and eukaryota species, whereas 28% and 35% combination types in bacteria and eukaryota respectively are unique to their corresponding groups. The number of functions per structure and the number of structures per function for the annotated sequences were measured in different species. Furthermore, a new concept was proposed to represent enzymatic structures as a functional similarity network. Thus, the current study will be helpful to enhance the global view on the evolution of enzymatic structure and function.

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Visualisation and graph-theoretic analysis of a large-scale protein structural interactome

Cited by 22 publications

References 59 publications

Pleiotropy constrains the evolution of protein but not regulatory sequences in a transcription regulatory network influencing complex social behaviors

Pleiotropy constrains the evolution of protein but not regulatory sequences in a transcription regulatory network influencing complex social behaviors

A hybrid space-filling and force-directed layout method for visualizing multiple-category graphs

Genome-Wide Analysis of Enzyme Structure-Function Combination Across Three Domains of Life

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