Phylogeographic differentiation versus transcriptomic adaptation to warm temperatures in Zostera marina, a globally important seagrass.

Populations distributed across a broad thermal cline are instrumental in addressing adaptation to increasing temperatures under global warming. Using a space-for-time substitution design, we tested for parallel adaptation to warm temperatures along two independent thermal clines in Zostera marina, the most widely distributed seagrass in the temperate Northern Hemisphere. A North-South pair of populations was sampled along the European and North American coasts and exposed to a simulated heatwave in a common-garden mesocosm. Transcriptomic responses under control, heat stress and recovery were recorded in 99 RNAseq libraries with ~13 000 uniquely annotated, expressed genes. We corrected for phylogenetic differentiation among populations to discriminate neutral from adaptive differentiation. The two southern populations recovered faster from heat stress and showed parallel transcriptomic differentiation, as compared with northern populations. Among 2389 differentially expressed genes, 21 exceeded neutral expectations and were likely involved in parallel adaptation to warm temperatures. However, the strongest differentiation following phylogenetic correction was between the three Atlantic populations and the Mediterranean population with 128 of 4711 differentially expressed genes exceeding neutral expectations. Although adaptation to warm temperatures is expected to reduce sensitivity to heatwaves, the continued resistance of seagrass to further anthropogenic stresses may be impaired by heat-induced downregulation of genes related to photosynthesis, pathogen defence and stress tolerance.

Dr. Zompo: an online data repository for Zostera marina and Posidonia oceanica ESTs.

As ecosystem engineers, seagrasses are angiosperms of paramount ecological importance in shallow shoreline habitats around the globe. Furthermore, the ancestors of independent seagrass lineages have secondarily returned into the sea in separate, independent evolutionary events. Thus, understanding the molecular adaptation of this clade not only makes significant contributions to the field of ecology, but also to principles of parallel evolution as well. With the use of Dr. Zompo, the first interactive seagrass sequence database presented here, new insights into the molecular adaptation of marine environments can be inferred. The database is based on a total of 14 597 ESTs obtained from two seagrass species, Zostera marina and Posidonia oceanica, which have been processed, assembled and comprehensively annotated. Dr. Zompo provides experimentalists with a broad foundation to build experiments and consider challenges associated with the investigation of this class of non-domesticated monocotyledon systems. Our database, based on the Ruby on Rails framework, is rich in features including the retrieval of experimentally determined heat-responsive transcripts, mining for molecular markers (SSRs and SNPs), and weighted key word searches that allow access to annotation gathered on several levels including Pfam domains, GeneOntology and KEGG pathways. Well established plant genome sites such as The Arabidopsis Information Resource (TAIR) and the Rice Genome Annotation Project are interfaced by Dr. Zompo. With this project, we have initialized a valuable resource for plant biologists in general and the seagrass community in particular. The database is expected to grow together with more data to come in the near future, particularly with the recent initiation of the Zostera genome sequencing project.The Dr. Zompo database is available at http://drzompo.uni-muenster.de/

One billion years of bZIP transcription factor evolution: conservation and change in dimerization and DNA-binding site specificity.

The genomic era has revealed that the large repertoire of observed animal phenotypes is dependent on changes in the expression patterns of a finite number of genes, which are mediated by a plethora of transcription factors (TFs) with distinct specificities. The dimerization of TFs can also increase the complexity of a genetic regulatory network manifold, by combining a small number of monomers into dimers with distinct functions. Therefore, studying the evolution of these dimerizing TFs is vital for understanding how complexity increased during animal evolution. We focus on the second largest family of dimerizing TFs, the basic-region leucine zipper (bZIP), and infer when it expanded and how bZIP DNA-binding and dimerization functions evolved during the major phases of animal evolution. Specifically, we classify the metazoan bZIPs into 19 families and confirm the ancient nature of at least 13 of these families, predating the split of the cnidaria. We observe fixation of a core dimerization network in the last common ancestor of protostomes-deuterostomes. This was followed by an expansion of the number of proteins in the network, but no major dimerization changes in interaction partners, during the emergence of vertebrates. In conclusion, the bZIPs are an excellent model with which to understand how DNA binding and protein interactions of TFs evolved during animal evolution.

The evolution of domain arrangements in proteins and interaction networks.

Proteins are composed of domains, which are conserved evolutionary units that often also correspond to functional units and can frequently be detected with reasonable reliability using computational methods. Most proteins consist of two or more domains, giving rise to a variety of combinations of domains. Another level of complexity arises because proteins themselves can form complexes with small molecules, nucleic acids and other proteins. The networks of both domain combinations and protein interactions can be conceptualised as graphs, and these graphs can be analysed conveniently by computational methods. In this review we summarise facts and hypotheses about the evolution of domains in multi-domain proteins and protein complexes, and the tools and data resources available to study them.

CADRE: the Central Aspergillus Data REpository.

CADRE is a public resource for housing and analysing genomic data extracted from species of Aspergillus. It arose to enable maintenance of the complete annotated genomic sequence of Aspergillus fumigatus and to provide tools for searching, analysing and visualizing features of fungal genomes. By implementing CADRE using Ensembl, a framework is in place for storing and comparing several genomes: the resource will thus expand by including other Aspergillus genomes (such as Aspergillus nidulans) as they become available. CADRE is accessible at http://www.cadre. man.ac.uk.

BioMiner--modeling, analyzing, and visualizing biochemical pathways and networks.

MOTIVATION: Understanding the biochemistry of a newly sequenced organism is an essential task for post-genomic analysis. Since, however, genome and array data grow much faster than biochemical information, it is necessary to infer reactions by comparative analysis. No integrated and easy to use software tool for this purpose exists as yet. RESULTS: We present a new software system--BioMiner--for analyzing and visualizing biochemical pathways and networks. BioMiner is based on a new comprehensive, extensible and reusable data model--BioCore--which can be used to model biochemical pathways and networks. As a first application we present PathFinder, a new tool predicting biochemical pathways by comparing groups of related organisms based on sequence similarity. We successfully tested PathFinder with a number of experiments, e.g. the well studied glycolysis in bacteria. Additionally, an application called PathViewer for the visualization of metabolic networks is presented. PathViewer is the first application we are aware of which supports the graphical comparison of metabolic networks of different organisms. AVAILABILITY: http://www.zbi.uni-saarland.de/chair/projects/BioMiner SUPPLEMENTARY INFORMATION: Additional information on experimental results can be found on our web site.

Switching from simple to complex oscillations in calcium signaling.

We present a new model for calcium oscillations based on experiments in hepatocytes. The model considers feedback inhibition on the initial agonist receptor complex by calcium and activated phospholipase C, as well as receptor type-dependent self-enhanced behavior of the activated G(alpha) subunit. It is able to show simple periodic oscillations and periodic bursting, and it is the first model to display chaotic bursting in response to agonist stimulations. Moreover, our model offers a possible explanation for the differences in dynamic behavior observed in response to different agonists in hepatocytes.

Modeling evolutionary landscapes: mutational stability, topology, and superfunnels in sequence space.

Random mutations under neutral or near-neutral conditions are studied by considering plausible evolutionary trajectories on "neutral nets"-i.e., collections of sequences (genotypes) interconnected via single-point mutations encoding for the same ground-state structure (phenotype). We use simple exact lattice models for the mapping between sequence and conformational spaces. Densities of states based on model intrachain interactions are determined by exhaustive conformational enumeration. We compare results from two very different interaction schemes to ascertain robustness of the conclusions. In both models, sequences in a majority of neutral nets center around a single "prototype sequence" of maximum mutational stability, tolerating the largest number of neutral mutations. General analytical considerations show that these topologies by themselves lead to higher steady-state evolutionary populations at prototype sequences. On average, native thermodynamic stability increases toward a maximum at the prototype sequence, resulting in funnel-like arrangements of native stabilities in sequence space. These observations offer a unified perspective on sequence design, native stability, and mutational stability of proteins. These principles are generalizable from native stability to any measure of fitness provided that its variation with respect to mutations is essentially smooth.

Application of constraint programming techniques for structure prediction of lattice proteins with extended alphabets.

MOTIVATION: Predicting the ground state of biopolymers is a notoriously hard problem in biocomputing. Model systems, such as lattice proteins, are simple tools and valuable to test and improve new methods. Best known are models with sequences composed from a binary (hydrophobic and polar) alphabet. The major drawback is the degeneracy, i.e. the number of different ground state conformations. RESULTS: We show how recently developed constraint programming techniques can be used to solve the structure prediction problem efficiently for a higher order alphabet. To our knowledge it is the first report of an exact and computationally feasible solution to model proteins of length up to 36 and without resorting to maximally compact states. We further show that degeneracy is reduced by more than one order of magnitude and that ground state conformations are not necessarily compact. Therefore, more realistic protein simulations become feasible with our model.

WWW access to the SYSTERS protein sequence cluster set.

SUMMARY: We present a Web server where the SYSTERS cluster set of the non-redundant protein database consisting of sequences from SWISS-PROT and PIR is being made available for querying and browsing. The cluster set can be searched with a new sequence using the SSMAL search tool. Additionally, a multiple alignment is generated for each cluster and annotated with domain information from the Pfam protein family database. AVAILABILITY: The server address is http://www.dkfz-heidelberg.de/tbi/services/cluster/ systersform

Computational approaches to identify leucine zippers.

The leucine zipper is a dimerization domain occurring mostly in regulatory and thus in many oncogenic proteins. The leucine repeat in the sequence has been traditionally used for identification, however with poor reliability. The coiled coil structure of a leucine zipper is required for dimerization and can be predicted with reasonable accuracy by existing algorithms. We exploit this fact for identification of leucine zippers from sequence alone. We present a program, 2ZIP, which combines a standard coiled coil prediction algorithm with an approximate search for the characteristic leucine repeat. No further information from homologues is required for prediction. This approach improves significantly over existing methods, especially in that the coiled coil prediction turns out to be highly informative and avoids large numbers of false positives. Many problems in predicting zippers or assessing prediction results stem from wrong sequence annotations in the database.

How are model protein structures distributed in sequence space?

The figure-to-structure maps for all uniquely folding sequences of short hydrophobic polar (HP) model proteins on a square lattice is analyzed to investigate aspects considered relevant to evolution. By ranking structures by their frequencies, few very frequent and many rare structures are found. The distribution can be empirically described by a generalized Zipf's law. All structures are relatively compact, yet the most compact ones are rare. Most sequences falling to the same structure belong to "neutral nets." These graphs in sequence space are connected by point mutations and centered around prototype sequences, which tolerate the largest number (up to 55%) of neutral mutations. Profiles have been derived from these homologous sequences. Frequent structures conserve hydrophobic cores only while rare ones are sensitive to surface mutations as well. Shape space covering, i.e., the ability to transform any structure into most others with few point mutations, is very unlikely. It is concluded that many characteristic features of the sequence-to-structure map of real proteins, such as the dominance of few folds, can be explained by the simple HP model. In analogy to protein families, nets are dense and well separated in sequence space. Potential implications in better understanding the evolution of proteins and applications to improving database searches are discussed.

Exploring the fitness landscapes of lattice proteins.

We present methods to investigate the sequence to structure relation for proteins. We use random structures of HP-type lattice models as a coarse grained model to study generic properties of biopolymers. To circumvent the computational limitations imposed by most lattice protein folding algorithms we apply a simple and fast deterministic approximation algorithm with a tunable accuracy. We investigate ensemble properties such as the conditional probability to find structures with a certain similarity at a given distance of the underlying sequence for various alphabets. Our results suggest that the structure landscapes for lattice proteins are generally very rugged, while larger alphabets fine tune the folding process and smoothen the map. This implies a simplification for evolutionary strategies. The applied methods appear to be helpful in the study of the complex interplay between folding strategies, energy functions and alphabets. Possible implications to the investigation of evolutionary strategies or the optimization of biopolymers are discussed.

Structure formation of biopolymers is complex, their evolution may be simple.

Evolutionary strategies depend on the ability of evolving entities to conserve acquired features and to quickly adapt to new requirements as well. We use computer simulations of simplified exact biopolymers models to investigate the influence of mutations on structure formation. Our computations on large ensembles of random RNA secondary structures show that the sequence to structure mapping is ideally suited for evolutionary optimisation under point mutations: from any random structure it is not far to any target and yet most mutations will preserve the structure. The aim of this paper is to discuss the analogies as well as some recently developed methods to apply our approach to proteins: there we use Dill's HP - model of lattice proteins and apply a novel fast and efficient folding rule. There are remarkable similarities as both landscapes are rugged and structure formation largely depends on local interactions such that it is possible to accomplish a characterisation of the mapping similar to the RNA case.