Conservation of regulatory elements between two species of Drosophila

Background  

One of the important goals in the post-genomic era is to determine the regulatory elements within the non-coding DNA of a given organism's genome. The identification of functional cis-regulatory modules has proven difficult since the component factor binding sites are small and the rules governing their arrangement are poorly understood. However, the genomes of suitably diverged species help to predict regulatory elements based on the generally accepted assumption that conserved blocks of genomic sequence are likely to be functional. To judge the efficacy of strategies that prefilter by sequence conservation it is important to know to what extent the converse assumption holds, namely that functional elements common to both species will fall within these conserved blocks. The recently completed sequence of a second Drosophila species provides an opportunity to test this assumption for one of the experimentally best studied regulatory networks in multicellular organisms, the body patterning of the fly embryo.     

Identification of tissue-specific cis-regulatory modules based on interactions between transcription factors

Background  

Evolutionary conservation has been used successfully to help identify cis-acting DNA regions that are important in regulating tissue-specific gene expression. Motivated by increasing evidence that some DNA regulatory regions are not evolutionary conserved, we have developed an approach for cis-regulatory region identification that does not rely upon evolutionary sequence conservation.     

A new protein binding pocket similarity measure based on comparison of clouds of atoms in 3D: application to ligand prediction

Background  

Predicting which molecules can bind to a given binding site of a protein with known 3D structure is important to decipher the protein function, and useful in drug design. A classical assumption in structural biology is that proteins with similar 3D structures have related molecular functions, and therefore may bind similar ligands. However, proteins that do not display any overall sequence or structure similarity may also bind similar ligands if they contain similar binding sites. Quantitatively assessing the similarity between binding sites may therefore be useful to propose new ligands for a given pocket, based on those known for similar pockets.     

Vertebrate DM domain proteins bind similar DNA sequences and can heterodimerize on DNA

Background:  

The DM domain is a zinc finger-like DNA binding motif first identified in the sexual regulatory proteins Doublesex (DSX) and MAB-3, and is widely conserved among metazoans. DM domain proteins regulate sexual differentiation in at least three phyla and also control other aspects of development, including vertebrate segmentation. Most DM domain proteins share little similarity outside the DM domain. DSX and MAB-3 bind partially overlapping DNA sequences, and DSX has been shown to interact with DNA via the minor groove without inducing DNA bending. DSX and MAB-3 exhibit unusually high DNA sequence specificity relative to other minor groove binding proteins. No detailed analysis of DNA binding by the seven vertebrate DM domain proteins, DMRT1-DMRT7 has been reported, and thus it is unknown whether they recognize similar or diverse DNA sequences.     

An arthropod <Emphasis Type="Italic">cis-</Emphasis>regulatory element functioning in sensory organ precursor development dates back to the Cambrian

Background  

An increasing number of publications demonstrate conservation of function of cis-regulatory elements without sequence similarity. In invertebrates such functional conservation has only been shown for closely related species. Here we demonstrate the existence of an ancient arthropod regulatory element that functions during the selection of neural precursors. The activity of genes of the achaete-scute (ac-sc) family endows cells with neural potential. An essential, conserved characteristic of proneural genes is their ability to restrict their own activity to single or a small number of progenitor cells from their initially broad domains of expression. This is achieved through a process called lateral inhibition. A regulatory element, the sensory organ precursor enhancer (SOPE), is required for this process. First identified in Drosophila, the SOPE contains discrete binding sites for four regulatory factors. The SOPE of the Drosophila asense gene is situated in the 5' UTR.     

Seed selection strategy in global network alignment without destroying the entire structures of functional modules

Background

Network alignment is one of the most common biological network comparison methods. Aligning protein-protein interaction (PPI) networks of different species is of great important to detect evolutionary conserved pathways or protein complexes across species through the identification of conserved interactions, and to improve our insight into biological systems. Global network alignment (GNA) problem is NP-complete, for which only heuristic methods have been proposed so far. Generally, the current GNA methods fall into global heuristic seed-and-extend approaches. These methods can not get the best overall consistent alignment between networks for the opinionated local seed. Furthermore These methods are lost in maximizing the number of aligned edges between two networks without considering the original structures of functional modules.

Methods

We present a novel seed selection strategy for global network alignment by constructing the pairs of hub nodes of networks to be aligned into multiple seeds. Beginning from every hub seed and using the membership similarity of nodes to quantify to what extent the nodes can participate in functional modules associated with current seed topologically we align the networks by modules. By this way we can maintain the functional modules are not damaged during the heuristic alignment process. And our method is efficient in resolving the fatal problem of most conventional algorithms that the initialization selected seeds have a direct influence on the alignment result. The similarity measures between network nodes (e.g., proteins) include sequence similarity, centrality similarity, and dynamic membership similarity and our algorithm can be called Multiple Hubs-based Alignment (MHA).

Results

When applying our seed selection strategy to several pairs of real PPI networks, it is observed that our method is working to strike a balance, extending the conserved interactions while maintaining the functional modules unchanged. In the case study, we assess the effectiveness of MHA on the alignment of the yeast and fly PPI networks. Our method outperforms state-of-the-art algorithms at detecting conserved functional modules and retrieves in particular 86% more conserved interactions than IsoRank.

Conclusions

We believe that our seed selection strategy will lead us to obtain more topologically and biologically similar alignment result. And it can be used as the reference and complement of other heuristic methods to seek more meaningful alignment results.