Abstract Summary: We present a suite of on-line tools to design candidate vaccine proteins, and to assess antigen potential, using coverage of k-mers (as proxies for potential T-cell epitopes) as a metric. The vaccine design tool uses the recently published ‘mosaic’ method to generate protein sequences optimized for coverage of high-frequency k-mers; the coverage-assessment tools facilitate coverage comparisons for any potential antigens. To demonstrate these tools, we designed mosaic protein sets for B-clade HIV-1 Gag, Pol and Nef, and compared them to antigens used in a recent human vaccine trial. Availability: http://hiv.lanl.gov/content/sequence/MOSAIC/ Contact: [email protected] Supplementary information: Supplementary data are available at ftp://ftp-t10.lanl.gov/pub/btk/WebToolsData

BACKGROUND: Jumping alignments have recently been proposed as a strategy to search a given multiple sequence alignment A against a database. Instead of comparing a database sequence S to the multiple alignment or profile as a whole, S is compared and aligned to individual sequences from A. Within this alignment, S can jump between different sequences from A, so different parts of S can be aligned to different sequences from the input multiple alignment. This approach is particularly useful for dealing with recombination events. RESULTS: We developed a jumping profile Hidden Markov Model (jpHMM), a probabilistic generalization of the jumping-alignment approach. Given a partition of the aligned input sequence family into known sequence subtypes, our model can jump between states corresponding to these different subtypes, depending on which subtype is locally most similar to a database sequence. Jumps between different subtypes are indicative of intersubtype recombinations. We applied our method to a large set of genome sequences from human immunodeficiency virus (HIV) and hepatitis C virus (HCV) as well as to simulated recombined genome sequences. CONCLUSION: Our results demonstrate that jumps in our jumping profile HMM often correspond to recombination breakpoints; our approach can therefore be used to detect recombinations in genomic sequences. The recombination breakpoints identified by jpHMM were found to be significantly more accurate than breakpoints defined by traditional methods based on comparing single representative sequences.

MOTIVATION: The hepatitis C virus (HCV) is a significant threat to public health worldwide. The virus is highly variable and evolves rapidly, making it an elusive target for the immune system and for vaccine and drug design. At present, some 30 000 HCV sequences have been published. A central website that provides annotated sequences and analysis tools will be helpful to HCV scientists worldwide. RESULTS: The HCV sequence database collects and annotates sequence data and provides them to the public via a website that contains a user-friendly search interface and a large number of sequence analysis tools, based on the model of the highly regarded Los Alamos HIV database. The HCV sequence database was officially launched in September 2003. Since then, its usage has steadily increased and is now at an average of approximately 280 visits per day from distinct IP addresses. AVAILABILITY: The HCV website can be accessed via http://hcv.lanl.gov and http://hcv-db.org.

Abstract Motivation: The amount of HIV-1 sequence data generated (presently around 42000 sequences, of which more than 22000 are from the V3 region of the viral envelope) presents a challenge for anyone working on the analysis of these data. A major problem is obtaining the region of interest from the stored sequences, which often contain but are not limited to that region. In addition, multiple alignment programs generally cannot deal with the large numbers of sequences that are available for many HIV-1 regions. We set out to provide our users with a tool that will retrieve and create an initial alignment of the HIV sequences that are available for a given genomic region. Results: The MPAlign (Multiple Pairwise Alignment) web interface is a collection of Perl scripts that retrieves sequences from the Los Alamos HIV sequence database based on a number of search parameters. All sequences were pairwise-aligned to a model sequence using the Hidden Markov Model-based program HMMER. The HMMER model is general enough to accommodate virtually all HIV-1 sequences stored in the database. To create a multiple sequence alignment, gaps were inserted into the sequences during retrieval, so that they are aligned to one another. Retrieving and aligning the almost 560 gp120 sequences (\batchmode \documentclass[fleqn,10pt,legalpaper]{article} \usepackage{amssymb} \usepackage{amsfonts} \usepackage{amsmath} \pagestyle{empty} \begin{document} \({\sim}\) \end{document}1500 nt) stored in the database is at least 1500 times faster than a similar Clustal alignment. Availability: At http://www.hiv.lanl.gov/ Contact: Brian Gaschen at [email protected] * To whom correspondence should be addressed.