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Evidence for a Strong Correlation Between Transcription Factor Protein Disorder and Organismic Complexity.

ABSTRACT: Studies of diverse phylogenetic lineages reveal that protein disorder increases in concert with organismic complexity but that differences nevertheless exist among lineages. To gain insight into this phenomenology, we analyzed all of the transcription factor (TF) families for which sequences are known for 17 species spanning bacteria, yeast, algae, land plants, and animals and for which the number of different cell types has been reported in the primary literature. Although the fraction of disordered residues in TF sequences is often moderately or poorly correlated with organismic complexity as gauged by cell-type number (r2??0.8). Furthermore, the correlation between the fraction of disordered residues and cell-type number becomes stronger when confined to the TF families participating in cell cycle, cell size, cell division, cell differentiation, or cell proliferation, and other important developmental processes. The data also indicate that evolutionarily simpler organisms allow for the detection of subtle differences in the conserved IDRs of TFs as well as changes in variable IDRs, which can influence the DNA recognition and multifunctionality of TFs through direct or indirect mechanisms. Although strong correlations cannot be taken as evidence for cause-and-effect relationships, we interpret our data to indicate that increasing TF disorder likely was an important factor contributing to the evolution of organismic complexity and not merely a concurrent unrelated effect of increasing organismic complexity.

SUBMITTER: Yruela I

PROVIDER: S-EPMC5434936 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature

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Evidence for a Strong Correlation Between Transcription Factor Protein Disorder and Organismic Complexity.

Yruela Inmaculada I Oldfield Christopher J CJ Niklas Karl J KJ Dunker A Keith AK

Genome biology and evolution 20170501 5

Studies of diverse phylogenetic lineages reveal that protein disorder increases in concert with organismic complexity but that differences nevertheless exist among lineages. To gain insight into this phenomenology, we analyzed all of the transcription factor (TF) families for which sequences are known for 17 species spanning bacteria, yeast, algae, land plants, and animals and for which the number of different cell types has been reported in the primary literature. Although the fraction of disor ...[more]

PMID: 28430951

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Project description:BackgroundUp to now, limited researches focused on the association between transcription factor 7-like 2 gene (TF7L2) gene single nucleotide polymorphisms (SNPs) and breast cancer (BC) risk. The aim of this study was to evaluate the associations between TF7L2 and BC risk in Chinese Han population.MethodsLogistic regression model was used to test the correlation between polymorphisms and BC risk. Strength of association was evaluated by odds ratio (OR) and 95% confidence interval (CI). Generalized multifactor dimensionality reduction (GMDR) was applied to analyze the SNP-SNP and gene-environment interaction.ResultsLogistic regression analysis indicated that the BC risk was obviously higher in carriers of rs1225404 polymorphism C allele than that in TT genotype carriers (TC or CC versus TT), adjusted OR (95%CI) =1.40 (1.09-1.72). Additionally, we also discovered that people with rs7903146- T allele had an obviously higher risk of BC than people with CC allele (CT or TT versus CC), adjusted OR (95%CI) =1.44 (1.09-1.82). GMDR model was used to research the effect of interaction among 4 SNPs and environmental factors on BC risk. We discovered an important two-locus model (p = 0.0100) including rs1225404 and abdominal obesity, suggesting a potential gene-environment correlation between rs1225404 and abdominal obesity. In general, the cross-validation consistency of two-locus model was 10 of 10, and the testing accuracy was 0.632. Compared with subjects with normal waist circumference (WC) value and rs1225404 TT genotype, abdominal obese subjects with rs1225404 TC or CC genotype had the highest BC risk. After covariate adjustment, OR (95%CI) was 2.23 (1.62-2.89). Haplotype analysis indicated that haplotype containing rs1225404-T and rs7903146-C alleles were associated with higher BC risk.ConclusionsC allele of rs1225404 and T allele of rs7903146, interaction between rs1225404 and abdominal obesity, rs1225404-T and rs7903146-C haplotype were all related to increased BC risk.

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.

Dataset Information

Evidence for a Strong Correlation Between Transcription Factor Protein Disorder and Organismic Complexity.

Publications

Evidence for a Strong Correlation Between Transcription Factor Protein Disorder and Organismic Complexity.

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