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The relationship between proteome size, structural disorder and organism complexity.

ABSTRACT: BACKGROUND: Sequencing the genomes of the first few eukaryotes created the impression that gene number shows no correlation with organism complexity, often referred to as the G-value paradox. Several attempts have previously been made to resolve this paradox, citing multifunctionality of proteins, alternative splicing, microRNAs or non-coding DNA. As intrinsic protein disorder has been linked with complex responses to environmental stimuli and communication between cells, an additional possibility is that structural disorder may effectively increase the complexity of species. RESULTS: We revisited the G-value paradox by analyzing many new proteomes whose complexity measured with their number of distinct cell types is known. We found that complexity and proteome size measured by the total number of amino acids correlate significantly and have a power function relationship. We systematically analyzed numerous other features in relation to complexity in several organisms and tissues and found: the fraction of protein structural disorder increases significantly between prokaryotes and eukaryotes but does not further increase over the course of evolution; the number of predicted binding sites in disordered regions in a proteome increases with complexity; the fraction of protein disorder, predicted binding sites, alternative splicing and protein-protein interactions all increase with the complexity of human tissues. CONCLUSIONS: We conclude that complexity is a multi-parametric trait, determined by interaction potential, alternative splicing capacity, tissue-specific protein disorder and, above all, proteome size. The G-value paradox is only apparent when plants are grouped with metazoans, as they have a different relationship between complexity and proteome size.

SUBMITTER: Schad E

PROVIDER: S-EPMC3334615 | biostudies-literature | 2011

REPOSITORIES: biostudies-literature

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The relationship between proteome size, structural disorder and organism complexity.

Schad Eva E Tompa Peter P Hegyi Hedi H

Genome biology 20111219 12

<h4>Background</h4>Sequencing the genomes of the first few eukaryotes created the impression that gene number shows no correlation with organism complexity, often referred to as the G-value paradox. Several attempts have previously been made to resolve this paradox, citing multifunctionality of proteins, alternative splicing, microRNAs or non-coding DNA. As intrinsic protein disorder has been linked with complex responses to environmental stimuli and communication between cells, an additional po ...[more]

PMID: 22182830

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Project description:The importance of unstructured biology has quickly grown during the last decades accompanying the explosion of the number of experimentally resolved protein structures. The idea that structural disorder might be a novel mechanism of protein interaction is widespread in the literature, although the number of statistically significant structural studies supporting this idea is surprisingly low. At variance with previous works, our conclusions rely exclusively on a large-scale analysis of all the 134337 X-ray crystallographic structures of the Protein Data Bank averaged over clusters of almost identical protein sequences. In this work, we explore the complexity of the organisation of all the interaction interfaces observed when a protein lies in alternative complexes, showing that interfaces progressively add up in a hierarchical way, which is reflected in a logarithmic law for the size of the union of the interface regions on the number of distinct interfaces. We further investigate the connection of this complexity with different measures of structural disorder: the standard missing residues and a new definition, called "soft disorder", that covers all the flexible and structurally amorphous residues of a protein. We show evidences that both the interaction interfaces and the soft disordered regions tend to involve roughly the same amino-acids of the protein, and preliminary results suggesting that soft disorder spots those surface regions where new interfaces are progressively accommodated by complex formation. In fact, our results suggest that structurally disordered regions not only carry crucial information about the location of alternative interfaces within complexes, but also about the order of the assembly. We verify these hypotheses in several examples, such as the DNA binding domains of P53 and P73, the C3 exoenzyme, and two known biological orders of assembly. We finally compare our measures of structural disorder with several disorder bioinformatics predictors, showing that these latter are optimised to predict the residues that are missing in all the alternative structures of a protein and they are not able to catch the progressive evolution of the disordered regions upon complex formation. Yet, the predicted residues, when not missing, tend to be characterised as soft disordered regions.

Project description:UnlabelledWe consider the problem of biological complexity via a projection of protein-coding genes of complex organisms onto the functional space of the proteome. The latter can be defined as a set of all functions committed by proteins of an organism. Alternative splicing (AS) allows an organism to generate diverse mature RNA transcripts from a single mRNA strand and thus it could be one of the key mechanisms of increasing of functional complexity of the organism's proteome and a driving force of biological evolution. Thus, the projection of transcription units (TU) and alternative splice-variant (SV) forms onto proteome functional space could generate new types of relational networks (e.g. SV-protein function networks, SFN) and lead to discoveries of novel evolutionarily conservative functional modules. Such types of networks might provide new reliable characteristics of organism complexity and a better understanding of the evolutionary integration and plasticity of interconnection of genome-transcriptome-proteome functions.ResultsWe use the InterPro and UniProt databases to attribute descriptive features (keywords) to protein sequences. UniProt database includes a controlled and curated vocabulary of specific descriptors or keywords. The keywords have been assigned to a protein sequence via conserved domains or via similarity with annotated sequences. Then we consider the unique combinations of keywords as the protein functional labels (FL), which characterize the biological functions of the given protein and construct the contingency tables and graphs providing the projections of transcription units (TU) and alternative splice-variants (SV) onto all FL of the proteome of a given organism. We constructed SFNs for organisms with different evolutionary history and levels of complexity, and performed detailed statistical parameterization of the networks.ConclusionsThe application of the algorithm to organisms with different evolutionary history and level of biological complexity (nematode, fruit fly, vertebrata) reveals that the parameters describing SFN correlate with the complexity of a given organism. Using statistical analysis of the links of the functional networks, we propose new features of evolution of protein function acquisition. We reveal a group of genes and corresponding functions, which could be attributed to an early conservative part of the cellular machinery essential for cell viability and survival. We identify and provide characteristics of functional switches in the polyform group of TUs in different organisms. Based on comparison of mouse and human SFNs, a role of alternative splicing as a necessary source of evolution towards more complex organisms is demonstrated. The entire set of FL across many organisms could be used as a draft of the catalogue of the functional space of the proteome world.

Project description:BackgroundHow genome complexity affects organismal phenotypic complexity is a fundamental question in evolutionary developmental biology. Previous studies proposed various contributing factors of genome complexity and tried to find the connection between genomic complexity and organism complexity. However, a general model to answer this question is lacking. Here, we introduce a 'two-level' model for the realization of genome complexity at phenotypic level.ResultsFive representative species across Protostomia and Deuterostomia were involved in this study. The intrinsic gene properties contributing to genome complexity were classified into two generalized groups: the complexity and age degree of both protein-coding and noncoding genes. We found that young genes tend to be simpler; however, the mid-age genes, rather than the oldest genes, show the highest proportion of high complexity. Complex genes tend to be utilized preferentially in each stage of embryonic development, with maximum representation during the late stage of organogenesis. This trend is mainly attributed to mid-age complex genes. In contrast, young genes tend to be expressed in specific spatiotemporal states. An obvious correlation between the time point of the change in over- and under-representation and the order of gene age was observed, which supports the funnel-like model of the conservation pattern of development. In addition, we found some probable causes for the seemingly contradictory 'funnel-like' or 'hourglass' model.ConclusionsThese results indicate that complex and young genes contribute to organismal complexity at two different levels: Complex genes contribute to the complexity of individual proteomes in certain states, whereas young genes contribute to the diversity of proteomes in different spatiotemporal states. This conclusion is valid across the five species investigated, indicating it is a conserved model across Protostomia and Deuterostomia. The results in this study also support 'funnel-like model' from a new viewpoint and explain why there are different evo-devo relation models.

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The relationship between proteome size, structural disorder and organism complexity.

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The relationship between proteome size, structural disorder and organism complexity.

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