The Clustal series of programs are widely used in molecular biology for the multiple alignment of both nucleic acid and protein sequences and for preparing phylogenetic trees. The popularity of the programs depends on a number of factors, including not only the accuracy of the results, but also the robustness, portability and user-friendliness of the programs. New features include NEXUS and FASTA format output, printing range numbers and faster tree calculation. Although, Clustal was originally developed to run on a local computer, numerous Web servers have been set up, notably at the EBI (European Bioinformatics Institute) (http://www.ebi.ac.uk/clustalw/).

The combination of significantly lower cost and increased speed of sequencing has resulted in an explosive growth of data submitted into the primary next-generation sequence data archive, the Sequence Read Archive (SRA). The preservation of experimental data is an important part of the scientific record, and increasing numbers of journals and funding agencies require that next-generation sequence data are deposited into the SRA. The SRA was established as a public repository for the next-generation sequence data and is operated by the International Nucleotide Sequence Database Collaboration (INSDC). INSDC partners include the National Center for Biotechnology Information (NCBI), the European Bioinformatics Institute (EBI) and the DNA Data Bank of Japan (DDBJ). The SRA is accessible at http://www.ncbi.nlm.nih.gov/Traces/sra from NCBI, at http://www.ebi.ac.uk/ena from EBI and at http://trace.ddbj.nig.ac.jp from DDBJ. In this article, we present the content and structure of the SRA, detail our support for sequencing platforms and provide recommended data submission levels and formats. We also briefly outline our response to the challenge of data growth.

A self-organizing map (SOM) was developed as a novel bioinformatics strategy for phylogenetic classification of sequence fragments obtained from pooled genome samples of uncultured microbes in environmental and clinical samples. This phylogenetic classification was possible without either orthologous sequence sets or sequence alignments. We first constructed SOMs for tetranucleotide frequencies in 210,000 5 kb sequence fragments obtained from 1502 prokaryotes for which at least 10 kb of genomic sequence has been deposited in public DNA databases. The sequences could be classified primarily according to phylogenetic groups without information regarding the species. We used the SOM method to classify sequence fragments derived from environmental samples of the Sargasso Sea and of an acidophilic biofilm growing in acid mine drainage. Phylogenetic diversity of the environmental sequences was effectively visualized on a single map. Sequences that were derived from a single genome but cloned independently could be reassociated in silico. G + C% has been used for a long period as a fundamental parameter for phylogenetic classification of microbes, but the G + C% is apparently too simple a parameter to differentiate a wide variety of known species. Oligonucleotide frequency can be used to distinguish the species because oligonucleotide frequencies vary significantly among their genomes.

Autophagy is a process of self-digestion generally observed in eukaryotes and has been shown to play crucial roles for survival under starvation and removal of deleterious substances. Despite great advances that have been made, many problems in mechanisms of autophagy remain unsolved. As a large number of autophagy-related proteins are identified in each species, a database that collects data, identifies their homologs in other species and makes them available will contribute to research advancement. As no such resources exist, we built the Autophagy database (http://tp-apg.genes.nig.ac.jp/autophagy) to provide basics, up-to-date information on relevant literature, and a list of autophagy-related proteins and their homologs in 41 eukaryotes. From the database, the user can search for proteins by keywords or sequences to obtain a wealth of data including functional and structural information and find possible functional homologs of proteins whose functions have been demonstrated in other species. As proteins that bind the phospholipid, phosphatidyl inositol 3-phosphate (PI3P) are essential for autophagy to proceed, we carried out an original analysis to identify probable PI3P-binding proteins, and made the list available from the database. The database is expected to give impetus to further research on autophagy by providing basic and specialized data on the subject.