DBTBS: a database of Bacillus subtilis promoters and transcription factors

With the completion of the determination of its entire genome sequence, one of the next major targets of Bacillus subtilis genomics is to clarify the whole gene regulatory network. To this end, the results of systematic experiments should be compared with the rich source of individual experimental results accumulated so far. Thus, we constructed a database of the upstream regulatory information of B.subtilis (DBTBS). The current version was constructed by surveying 291 references and contains information on 90 binding factors and 403 promoters. For each promoter, all of its known cis-elements are listed according to their positions, while these cis-elements are aligned to illustrate their consensus sequence for each transcription factor. All probable transcription factors coded in the genome were classified with the Pfam motifs. Using this database, we compared the character of B.subtilis promoters with that of Escherichia coli promoters. Our database is accessible at http://elmo.ims.u-tokyo.ac.jp/dbtbs/.

Delineating developmental and metabolic pathways in vivo by expression profiling using the RIKEN set of 18,816 full-length enriched mouse cDNA arrays

We have systematically characterized gene expression patterns in 49 adult and embryonic mouse tissues by using cDNA microarrays with 18,816 mouse cDNAs. Cluster analysis defined sets of genes that were expressed ubiquitously or in similar groups of tissues such as digestive organs and muscle. Clustering of expression profiles was observed in embryonic brain, postnatal cerebellum, and adult olfactory bulb, reflecting similarities in neurogenesis and remodeling. Finally, clustering genes coding for known enzymes into 78 metabolic pathways revealed a surprising coordination of expression within each pathway among different tissues. On the other hand, a more detailed examination of glycolysis revealed tissue-specific differences in profiles of key regulatory enzymes. Thus, by surveying global gene expression by using microarrays with a large number of elements, we provide insights into the commonality and diversity of pathways responsible for the development and maintenance of the mammalian body plan.

Global survey of genetic variation in CCR5, RANTES, and MIP-1α: Impact on the epidemiology of the HIV-1 pandemic

Expression of CC chemokine receptor 5 (CCR5), the major coreceptor for HIV-1 cell entry, and its ligands (e.g., RANTES and MIP-1α) is widely regarded as central to the pathogenesis of HIV-1 infection. By surveying nearly 3,000 HIV+ and HIV− individuals from worldwide populations for polymorphisms in the genes encoding RANTES, MIP-1α, and CCR5, we show that the evolutionary histories of human populations have had a significant impact on the distribution of variation in these genes, and that this may be responsible, in part, for the heterogeneous nature of the epidemiology of the HIV-1 pandemic. The varied distribution of RANTES haplotypes (AC, GC, and AG) associated with population-specific HIV-1 transmission- and disease-modifying effects is a striking example. Homozygosity for the AC haplotype was associated with an increased risk of acquiring HIV-1 as well as accelerated disease progression in European Americans, but not in African Americans. Yet, the prevalence of the ancestral AC haplotype is high in individuals of African origin, but substantially lower in non-Africans. In a Japanese cohort, AG-containing RANTES haplotype pairs were associated with a delay in disease progression; however, we now show that their contribution to HIV-1 pathogenesis and epidemiology in other parts of the world is negligible because the AG haplotype is infrequent in non-Far East Asians. Thus, the varied distribution of RANTES, MIP-1α, and CCR5 haplotype pairs and their population-specific phenotypic effects on HIV-1 susceptibility and disease progression results in a complex pattern of biological determinants of HIV-1 epidemiology. These findings have important implications for the design, assessment, and implementation of effective HIV-1 intervention and prevention strategies.

New trends in natural language processing: statistical natural language processing.

The field of natural language processing (NLP) has seen a dramatic shift in both research direction and methodology in the past several years. In the past, most work in computational linguistics tended to focus on purely symbolic methods. Recently, more and more work is shifting toward hybrid methods that combine new empirical corpus-based methods, including the use of probabilistic and information-theoretic techniques, with traditional symbolic methods. This work is made possible by the recent availability of linguistic databases that add rich linguistic annotation to corpora of natural language text. Already, these methods have led to a dramatic improvement in the performance of a variety of NLP systems with similar improvement likely in the coming years. This paper focuses on these trends, surveying in particular three areas of recent progress: part-of-speech tagging, stochastic parsing, and lexical semantics.

Comparative expressed-sequence-tag analysis of differential gene expression profiles in PC-12 cells before and after nerve growth factor treatment.

Nerve growth factor-induced differentiation of adrenal chromaffin PC-12 cells to a neuronal phenotype involves alterations in gene expression and represents a model system to study neuronal differentiation. We have used the expressed-sequence-tag approach to identify approximately 600 differentially expressed mRNAs in untreated and nerve growth factor-treated PC-12 cells that encode proteins with diverse structural and biochemical functions. Many of these mRNAs encode proteins belonging to cellular pathways not previously known to be regulated by nerve growth factor. Comparative expressed-sequence-tag analysis provides a basis for surveying global changes in gene-expression patterns in response to biological signals at an unprecedented scale, is a powerful tool for identifying potential interactions between different cellular pathways, and allows the gene-expression profiles of individual genes belonging to a particular pathway to be followed.