Genome Network Project: An Integrated Genomic Platform

With the objective of elucidating the structure of gene interactions in the human genome, the Genome Network Project has generated a vast quantity of experimental data, mainly focusing on transcriptional control and transcription-factor related protein-protein interactions (PPI). This data has been collected and organized into the Genome Network Platform ("http://genomenetwork.nig.ac.jp/":http://genomenetwork.nig.ac.jp/) at the National Institute of Genetics. Expression data was obtained through CAGE (Cap Analysis Gene Expression), qRT-PCR, tiling array, microarray and short RNA analysis, while PPI information was gathered through yeast two hybrid (Y2H), mammalian two hybrid (M2H) and _in vitro_ virus (IVV) methods. The Genome Network Platform Viewer provides an integrated user interface to the complete database, including services of gene search, whole genome browsing, PPI network viewer, and expression profile analysis. Our platform represents an extremely useful resource for researchers in the field of genomics, and provides access to high quality data through the combination of intuitive browsing and visualization capabilities

DDBJ working on evaluation and classification of bacterial genes in INSDC

DNA Data Bank of Japan (DDBJ) () newly collected and released 12 927 184 entries or 13 787 688 598 bases in the period from July 2005 to June 2006. The released data contain honeybee expressed sequence tags (ESTs), re-examined and re-annotated complete genome data of Escherichia coli K-12 W3110, medaka WGS and human MGA. We also systematically evaluated and classified the genes in the complete bacterial genomes submitted to the International Nucleotide Sequence Database Collaboration (INSDC, ) that is composed of DDBJ, EMBL Bank and GenBank. The examination and classification selected 557 000 genes as reliable ones among all the bacterial genes predicted by us

Why Do Hubs Tend to Be Essential in Protein Networks?

The protein–protein interaction (PPI) network has a small number of highly connected protein nodes (known as hubs) and many poorly connected nodes. Genome-wide studies show that deletion of a hub protein is more likely to be lethal than deletion of a non-hub protein, a phenomenon known as the centrality-lethality rule. This rule is widely believed to reflect the special importance of hubs in organizing the network, which in turn suggests the biological significance of network architectures, a key notion of systems biology. Despite the popularity of this explanation, the underlying cause of the centrality-lethality rule has never been critically examined. We here propose the concept of essential PPIs, which are PPIs that are indispensable for the survival or reproduction of an organism. Our network analysis suggests that the centrality-lethality rule is unrelated to the network architecture, but is explained by the simple fact that hubs have large numbers of PPIs, therefore high probabilities of engaging in essential PPIs. We estimate that ~ 3% of PPIs are essential in the yeast, accounting for ~ 43% of essential genes. As expected, essential PPIs are evolutionarily more conserved than nonessential PPIs. Considering the role of essential PPIs in determining gene essentiality, we find the yeast PPI network functionally more robust than random networks, yet far less robust than the potential optimum. These and other findings provide new perspectives on the biological relevance of network structure and robustness

Two different classes of co-occurring motif pairs found by a novel visualization method in human promoter regions

<p>Abstract</p> <p>Background</p> <p>It is essential in modern biology to understand how transcriptional regulatory regions are composed of <it>cis</it>-elements, yet we have limited knowledge of, for example, the combinational uses of these elements and their positional distribution.</p> <p>Results</p> <p>We predicted the positions of 228 known binding motifs for transcription factors in phylogenetically conserved regions within -2000 and +1000 bp of transcriptional start sites (TSSs) of human genes and visualized their correlated non-overlapping occurrences. In the 8,454 significantly correlated motif pairs, two major classes were observed: 248 pairs in Class 1 were mainly found around TSSs, whereas 4,020 Class 2 pairs appear at rather arbitrary distances from TSSs. These classes are distinct in a number of aspects. First, the positional distribution of the Class 1 constituent motifs shows a single peak near the TSSs, whereas Class 2 motifs show a relatively broad distribution. Second, genes that harbor the Class 1 pairs are more likely to be CpG-rich and to be expressed ubiquitously than those that harbor Class 2 pairs. Third, the 'hub' motifs, which are used in many different motif pairs, are different between the two classes. In addition, many of the transcription factors that correspond to the Class 2 hub motifs contain domains rich in specific amino acids; these domains may form disordered regions important for protein-protein interaction.</p> <p>Conclusion</p> <p>There exist at least two classes of motif pairs with respect to TSSs in human promoters, possibly reflecting compositional differences between promoters and enhancers. We anticipate that our visualization method may be useful for the further characterisation of promoters.</p

The evolutionary position of nematodes

BACKGROUND: The complete genomes of three animals have been sequenced by global research efforts: a nematode worm (Caenorhabditis elegans), an insect (Drosophila melanogaster), and a vertebrate (Homo sapiens). Remarkably, their relationships have yet to be clarified. The confusion concerns the enigmatic position of nematodes. Traditionally, nematodes have occupied a basal position, in part because they lack a true body cavity. However, the leading hypothesis now joins nematodes with arthropods in a molting clade, Ecdysozoa, based on data from several genes. RESULTS: We tested the Ecdysozoa hypothesis with analyses of more than 100 nuclear protein alignments, under conditions that would expose biases, and found that it was not supported. Instead, we found significant support for the traditional hypothesis, Coelomata. Our result is robust to different rates of sequence change among genes and lineages, different numbers of taxa, and different species of nematodes. CONCLUSION: We conclude that insects (arthropods) are genetically and evolutionarily closer to humans than to nematode worms