Projection of gene-protein networks to the functional space of the proteome and its application to analysis of organism complexity

Abstract

We 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.

Correcting for Differential Transcript Coverage Reveals a Strong Relationship between Alternative Splicing and Organism Complexity

“…Indeed, a previous study that generated relational networks for seven species associated the number of functions in a proteome with the number of polyform transcriptional units in the genome, those that produce protein isoforms with different functional assignments (which are strongly associated with the levels of splicing). Various properties of these networks (such as the number of nodes) were found to be strongly associated with organism complexity, suggesting a link between splicing and both multifunctionality and multicellularity ( Kanapin et al 2010 ).…”

The plausible reason why the length of 5' untranslated region is unrelated to organismal complexity

“…However, as we discussed earlier, 5'UTR is not the only regulatory element in the genome. For example, non-coding RNA-mediated gene regulations [ 30 - 32 ], nonsense-mediated decay [ 33 ], the lengths and interactions of protein coding sequences [ 34 ], and 3'UTRs may all contribute to regulatory complexity [ 11 ]. To be sure, 5'UTRs represent only part of the complicated machinery of eukaryotic gene regulations.…”

An Analysis of Cumulative Selection and Random Drift in the Evolutionary Origination of Novel Protein Motifs

“…Perhaps one of the most interesting and challenging issues in molecular biology and evolution is in accounting for the origins of the highly conserved protein motifs/domains that are at the heart of virtually all cellular activities, and which contribute to organismal complexity [1]. These syntactically specific and distinctive amino acid sequences comprise the key functional units that define the nature and behavior of gene products.…”