TreeDom: a graphical web tool for analysing domain architecture evolution

Haider, Christian; Kavic, Marina; Sonnhammer, Erik L. L.

doi:10.1093/bioinformatics/btw140

Cited by 4 publications

(3 citation statements)

References 10 publications

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“…A few of these tools allow domain architecture evolution analysis by visualizing each protein's domain architecture along a protein sequence tree. An example is the web tool TreeDom [96] which, given a protein domain family and an anchor sequence, fetches the family from Pfam and builds a tree with the nearest neighbors of the anchor sequence. An example output from TreeDom is shown in Fig.…”

Section: Online Domain Database Resourcesmentioning

confidence: 99%

“…The RAMPAGE/RADS tools [95] make use of domain assignments for rapid homology searching. DoMosaics [92] is a software TreeDom http://treedom.sbc.su.se/ Graphical web tool for analyzing domain architecture evolution using Pfam [96] tool that can act as a wrapper for domain annotation tools, allowing detailed visualization and analysis of domain architectures, as does DomArch [97]. The DAAC algorithm [98] explicitly transfers functional annotation to query sequences based on domain architectural similarity to annotated homologs, as does FACT [93].…”

Section: Online Domain Database Resourcesmentioning

confidence: 99%

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Evolution of Protein Domain Architectures

Forslund¹,

Kaduk²,

Sonnhammer³

2019

Methods in Molecular Biology

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This chapter reviews current research on how protein domain architectures evolve. We begin by summarizing work on the phylogenetic distribution of proteins, as this will directly impact which domain architectures can be formed in different species. Studies relating domain family size to occurrence have shown that they generally follow power law distributions, both within genomes and larger evolutionary groups. These findings were subsequently extended to multi-domain architectures. Genome evolution models that have been suggested to explain the shape of these distributions are reviewed, as well as evidence for selective pressure to expand certain domain families more than others. Each domain has an intrinsic combinatorial propensity, and the effects of this have been studied using measures of domain versatility or promiscuity. Next, we study the principles of protein domain architecture evolution and how these have been inferred from distributions of extant domain arrangements. Following this, we review inferences of ancestral domain architecture and the conclusions concerning domain architecture evolution mechanisms that can be drawn from these. Finally, we examine whether all known cases of a given domain architecture can be assumed to have a single common origin (monophyly) or have evolved convergently (polyphyly). We end by a discussion of some available tools for computational analysis or exploitation of protein domain architectures and their evolution.

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Section: Online Domain Database Resourcesmentioning

confidence: 99%

Section: Online Domain Database Resourcesmentioning

confidence: 99%

Evolution of Protein Domain Architectures

Forslund¹,

Kaduk²,

Sonnhammer³

2019

Methods in Molecular Biology

View full text Add to dashboard Cite

show abstract

“…Several studies [2][3][4][5][6][7][8][9][10][11][12][13][14][15][16] have demonstrated the power of molecular evolution and phylogenetic analysis in determining molecular functions of such proteins. There are many individual tools [17][18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36] for protein sequence similarity searches or ortholog detection, delineating co-occurring domains (domain architectures), and building multiple sequence alignments and phylogenetic trees. However, there is a paucity of unified software or web frameworks that effectively integrate these approaches to comprehensively characterize proteins and help discern function by exhaustively identifying all members of relevant protein families (including remote homologs), mapping domains/domain-architectures, and tracing their phyletic spread across lineages.…”

mentioning

confidence: 99%

MolEvolvR: A web-app for characterizing proteins using molecular evolution and phylogeny

Burke

Chen

Sosinski

et al. 2022

Preprint

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Studying proteins through the lens of evolution can help identify conserved features and lineage-specific variants, and potentially, their functions. MolEvolvR (http://jravilab.org/molevolvr) is a web-app that enables researchers to run a general-purpose computational workflow for characterizing the molecular evolution and phylogeny of their proteins of interest. The web-app accepts input in multiple formats: protein/domain sequences, homologous proteins, or domain scans. MolEvolvR returns detailed homolog data, along with dynamic graphical summaries, e.g., MSA, phylogenetic trees, domain architectures, domain proximity networks, phyletic spreads, and co-occurrence patterns across lineages. Thus, MolEvolvR provides a powerful, easy-to-use interface for computational protein characterization.

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Proteome-Scale Detection of Differential Conservation Patterns at Protein and Subprotein Levels with BLUR

Defosset

Nevers

Ripp

et al. 2020

Genome Biology and Evolution

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In the multi-omics era, comparative genomics studies based on gene repertoire comparison are increasingly used to investigate evolutionary histories of species, to study genotype-phenotype relations, species adaptation to various environments, or to predict gene function using phylogenetic profiling. However, comparisons of orthologs have highlighted the prevalence of sequence plasticity among species, showing the benefits of combining protein and sub-protein levels of analysis to allow for a more comprehensive study of genotype/phenotype correlations. In this article, we introduce a new approach called BLUR (Blast Unexpected Ranking), capable of detecting genotype divergence or specialization between two related clades at different levels: gain/loss of proteins but also of sub-protein regions. These regions can correspond to known domains, uncharacterized regions, or even small motifs. Our method was created to allow two types of research strategies: (1) the comparison of two groups of species with no previous knowledge, with the aim of predicting phenotype differences or specializations between close species or (2) the study of specific phenotypes by comparing species that present the phenotype of interest with species that do not. We designed a website to facilitate the use of BLUR with a possibility of in-depth analysis of the results with various tools, such as functional enrichments, protein-protein interaction networks, and multiple sequence alignments. We applied our method to the study of two different biological pathways and to the comparison of several groups of close species, all with very promising results. BLUR is freely available at http://lbgi.fr/blur/

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TreeDom: a graphical web tool for analysing domain architecture evolution

Abstract: Erik.Sonnhammer@scilifelab.se.

Cited by 4 publications

References 10 publications

Evolution of Protein Domain Architectures

Evolution of Protein Domain Architectures

MolEvolvR: A web-app for characterizing proteins using molecular evolution and phylogeny

Proteome-Scale Detection of Differential Conservation Patterns at Protein and Subprotein Levels with BLUR

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