A novel algorithm for alignment of multiple PPI networks based on simulated annealing

Background

To infer gene regulatory networks (GRNs) from gene-expression data is still a fundamental and challenging problem in systems biology. Several existing algorithms formulate GRNs inference as a regression problem and obtain the network with an ensemble strategy. Recent studies on data driven dynamic network construction provide us a new perspective to solve the regression problem.

Results

In this study, we propose a data driven dynamic network construction method to infer gene regulatory network (D3GRN), which transforms the regulatory relationship of each target gene into functional decomposition problem and solves each sub problem by using the Algorithm for Revealing Network Interactions (ARNI). To remedy the limitation of ARNI in constructing networks solely from the unit level, a bootstrapping and area based scoring method is taken to infer the final network. On DREAM4 and DREAM5 benchmark datasets, D3GRN performs competitively with the state-of-the-art algorithms in terms of AUPR.

Conclusions

We have proposed a novel data driven dynamic network construction method by combining ARNI with bootstrapping and area based scoring strategy. The proposed method performs well on the benchmark datasets, contributing as a competitive method to infer gene regulatory networks in a new perspective.

     

Measurement of the Girth of Coniferous Trees at Braemar in 1894

ABSTRACT

Background: Plant communities are usually characterised by species composition and abundance, but also underlie a multitude of complex interactions that we have only recently started unveiling. Yet, we are still far from understanding ecological and evolutionary processes shaping the network-level organisation of plant diversity, and to what extent these processes are specific to certain spatial scales or environments.

Aims: Understanding the systemic mechanisms of plant–plant network assembly and their consequences for diversity patterns.

Methods: We review recent methods and results of plant–plant networks.

Results: We synthetize how plant–plant networks can help us to: (a) assess how competition and facilitation may balance each other through the network; (b) analyse the role of plant–plant interactions beyond pairwise competition in structuring plant communities, and (c) forecast the ecological implications of complex species dependencies. We discuss pros and cons, assumptions and limitations of different approaches used for inferring plant–plant networks.

Conclusions: We propose novel opportunities for advancing plant ecology by using ecological networks that encompass different ecological levels and spatio-temporal scales, and incorporate more biological information. Embracing networks of interactions among plants can shed new light on mechanisms driving evolution and ecosystem functioning, helping us to mitigate diversity loss.     

Evolution of gene regulatory networks controlling body plan development

Evolutionary change in animal morphology results from alteration of the functional organization of the gene regulatory networks (GRNs) that control development of the body plan. A major mechanism of evolutionary change in GRN structure is alteration of cis-regulatory modules that determine regulatory gene expression. Here we consider the causes and consequences of GRN evolution. Although some GRN subcircuits are of great antiquity, other aspects are highly flexible and thus in any given genome more recent. This mosaic view of the evolution of GRN structure explains major aspects of evolutionary process, such as hierarchical phylogeny and discontinuities of paleontological change.     

Heritability: the link between development and the microevolution of molar tooth form

Abstract

The developmental gene expression, morphogenesis, and population variation in mammalian molar teeth has become increasingly well understood, providing a model system for synthesizing evolution and developmental genetics. In this study, we estimated additive genetic covariances in molar shape (G) using parent-offspring regression in Cryptotis parva, the Least Shrew. We found that crown shape had an overall h² value of 0.34 (±0.08), with higher heritabilities in molar cusps than notches. We compared the genetic covariances to phenotypic (P) and environmental (E) covariances, and to the covariances in crown features expected from the enamel knot developmental cascade (D). We found that G and D were not strongly correlated and that major axes of G (evolutionary lines of least resistance) are better predictors of evolutionary divergences in soricines than is D. We conclude that the enamel knot cascade does impose constraints on the evolution of molar shape, but that it is so permissive that the divergences among soricines (whose last common ancestor lived about 14 million years ago) do not fully explore its confines. Over tens of millions of years, G will be a better predictor of the major axes of evolution in molar shape than D.     

Moving towards a better understanding of iterative evolution: an example from the late Silurian Monograptidae (Graptolithina) of the Baltic Basin

Iterative evolution has proved a difficult evolutionary phenomenon to study and interpret. Inferences of causality vary from study to study and quantitatively based phylogenetic reconstruction has never been attempted. In an effort to better understand iterative evolution we employed stratocladistics, gap analysis and disparity analysis to study the case of the Monograptidae in the aftermath of the late Silurian Cyrtograptus lundgreni extinction event. Our combination of gap analytical and stratocladistic techniques allowed us to elucidate the evolutionary relationships between the studied taxa. Based on our stratocladistic results we recommend the generic reassignment of five monograptid taxa. The stratocladistic results, in conjunction with morphological disparity analysis suggest the presence of a persistent developmental potential for the emergence of iteratively evolving characters. This persistent potential appears to be limited by extrinsic ecological constraints, which would have relaxed in the aftermath of the C. lundgreni extinction event. Our findings indicate that iterative evolution in the late Silurian Monograptidae is a product of the interaction of both intrinsic and extrinsic constraints on the acquisition of the iteratively evolving character, with the exact causality being dependent on the particular character.     

Evo-devo: Hydra raises its Noggin

Noggin, along with other secreted bone morphogenetic protein (BMP) inhibitors, plays a crucial role in neural induction and neural tube patterning as well as in somitogenesis, cardiac morphogenesis and formation of the skeleton in vertebrates. The BMP signalling pathway is one of the seven fundamental pathways that drive embryonic development and pattern formation in animals. Understanding its evolutionary origin and role in pattern formation is, therefore, important to evolutionary developmental biology (evo-devo). We have studied the evolutionary origin of BMP–Noggin antagonism in hydra, which is a powerful diploblastic model to study evolution of pattern-forming mechanisms because of the unusual cellular dynamics during its pattern formation and its remarkable ability to regenerate. We cloned and characterized the noggin gene from hydra and found it to exhibit considerable similarity with its orthologues at the amino acid level. Microinjection of hydra Noggin mRNA led to duplication of the dorsoventral axis in Xenopus embryos, demonstrating its functional conservation across the taxa. Our data, along with those of others, indicate that the evolutionarily conserved antagonism between BMP and its inhibitors predates bilateral divergence. This article reviews the various roles of Noggin in different organisms and some of our recent work on hydra Noggin in the context of evolution of developmental signalling pathways.     

Metabolic stasis in an ancient symbiosis: genome-scale metabolic networks from two Blattabacterium cuenoti strains,primary endosymbionts of cockroaches

Background

Cockroaches are terrestrial insects that strikingly eliminate waste nitrogen as ammonia instead of uric acid. Blattabacterium cuenoti (Mercier 1906) strains Bge and Pam are the obligate primary endosymbionts of the cockroaches Blattella germanica and Periplaneta americana, respectively. The genomes of both bacterial endosymbionts have recently been sequenced, making possible a genome-scale constraint-based reconstruction of their metabolic networks. The mathematical expression of a metabolic network and the subsequent quantitative studies of phenotypic features by Flux Balance Analysis (FBA) represent an efficient functional approach to these uncultivable bacteria.

Results

We report the metabolic models of Blattabacterium strains Bge (iCG238) and Pam (iCG230), comprising 296 and 289 biochemical reactions, associated with 238 and 230 genes, and 364 and 358 metabolites, respectively. Both models reflect both the striking similarities and the singularities of these microorganisms. FBA was used to analyze the properties, potential and limits of the models, assuming some environmental constraints such as aerobic conditions and the net production of ammonia from these bacterial systems, as has been experimentally observed. In addition, in silico simulations with the iCG238 model have enabled a set of carbon and nitrogen sources to be defined, which would also support a viable phenotype in terms of biomass production in the strain Pam, which lacks the first three steps of the tricarboxylic acid cycle. FBA reveals a metabolic condition that renders these enzymatic steps dispensable, thus offering a possible evolutionary explanation for their elimination. We also confirm, by computational simulations, the fragility of the metabolic networks and their host dependence.

Conclusions

The minimized Blattabacterium metabolic networks are surprisingly similar in strains Bge and Pam, after 140 million years of evolution of these endosymbionts in separate cockroach lineages. FBA performed on the reconstructed networks from the two bacteria helps to refine the functional analysis of the genomes enabling us to postulate how slightly different host metabolic contexts drove their parallel evolution.

     

Scalable optimal Bayesian classification of single-cell trajectories under regulatory model uncertainty

Background

Biological networks describes the mechanisms which govern cellular functions. Temporal networks show how these networks evolve over time. Studying the temporal progression of network topologies is of utmost importance since it uncovers how a network evolves and how it resists to external stimuli and internal variations. Two temporal networks have co-evolving subnetworks if the evolving topologies of these subnetworks remain similar to each other as the network topology evolves over a period of time. In this paper, we consider the problem of identifying co-evolving subnetworks given a pair of temporal networks, which aim to capture the evolution of molecules and their interactions over time. Although this problem shares some characteristics of the well-known network alignment problems, it differs from existing network alignment formulations as it seeks a mapping of the two network topologies that is invariant to temporal evolution of the given networks. This is a computationally challenging problem as it requires capturing not only similar topologies between two networks but also their similar evolution patterns.

Results

We present an efficient algorithm, Tempo, for solving identifying co-evolving subnetworks with two given temporal networks. We formally prove the correctness of our method. We experimentally demonstrate that Tempo scales efficiently with the size of network as well as the number of time points, and generates statistically significant alignments—even when evolution rates of given networks are high. Our results on a human aging dataset demonstrate that Tempo identifies novel genes contributing to the progression of Alzheimer’s, Huntington’s and Type II diabetes, while existing methods fail to do so.

Conclusions

Studying temporal networks in general and human aging specifically using Tempo enables us to identify age related genes from non age related genes successfully. More importantly, Tempo takes the network alignment problem one huge step forward by moving beyond the classical static network models.

     

The Hsp90 Capacitor,Developmental Remodeling,and Evolution: The Robustness of Gene Networks and the Curious Evolvability of Metamorphosis

ABSTRACT

Genetic capacitors moderate expression of heritable variation and provide a novel mechanism for rapid evolution. The prototypic genetic capacitor, Hsp90, interfaces stress responses, developmental networks, trait thresholds and expression of wide-ranging morphological changes in Drosophila and other organisms. The Hsp90 capacitor hypothesis, that stress-sensitive storage and release of genetic variation through Hsp90 facilitates adaptive evolution in unpredictable environments, has been challenged by the belief that Hsp90-buffered variation is unconditionally deleterious. Here we review recent results supporting the Hsp90 capacitor hypothesis, highlighting the heritability, selectability, and potential evolvability of Hsp90-buffered traits. Despite a surprising bias toward morphological novelty and typically invariable quantitative traits, Hsp90-buffered changes are remarkably modular, and can be selected to high frequency independent of the expected negative side-effects or obvious correlated changes in other, unselected traits. Recent dissection of cryptic signal transduction variation involved in one Hsp90-buffered trait reveals potentially dozens of normally silent polymorphisms embedded in cell cycle, differentiation and growth control networks. Reduced function of Hsp90 substrates during environmental stress would destabilize robust developmental processes, relieve developmental constraints and plausibly enables genetic network remodeling by abundant cryptic alleles. We speculate that morphological transitions controlled by Hsp90 may fuel the incredible evolutionary lability of metazoan life-cycles.     

Evolution of protein complexes by duplication of homomeric interactions

Background  

Cellular functions are accomplished by the concerted actions of functional modules. The mechanisms driving the emergence and evolution of these modules are still unclear. Here we investigate the evolutionary origins of protein complexes, modules in physical protein-protein interaction networks.