Phylobook: a tool for display, clade annotation and extraction of sequences from molecular phylogenies.

As the volume of sequence data from variable pathogens increases, means of analyzing, annotating and extracting specific taxa for study becomes more difficult. To meet these challenges for datasets with hundreds to thousands of taxa, 'Phylobook' was developed. Starting with a sequence alignment file, Phylobook generates and displays phylogenetic trees adjacent to highlighter plots showing the position of mutations, and allows the user to identify lineages and recombinants, annotate and export selected subsets of sequences for downstream analysis. Accurate lineage assignment, which is difficult to automate, is aided using annotations created by different clustering methods. Phylobook provides web-based display combined with automated clustering and manual editing to allow for expert assessment and correction of lineage assignments and extraction for downstream analysis.

Phylobook generates and displays phylogenetic trees adjacent to highlighter plots showing the position of mutations, allows the user to identify lineages and recombinants, annotate and export selected subsets of sequences for downstream analysis.

Gene expression patterns that correlate with hepatitis C and early progression to fibrosis in liver transplant recipients.

BACKGROUND & AIMS: Liver transplant recipients infected with hepatitis C virus (HCV) develop recurrent hepatitis soon after transplantation and, in some cases, progress to fibrosis within the first 2 years. Our goals were to identify molecular processes influencing the liver disease progression and to find potential gene markers of early fibrosis. METHODS: We performed gene expression profiling on serial liver biopsy specimens obtained from 13 (11 infected and 2 uninfected) transplant recipients within the first year after transplantation at 0, 3, 6, and 12 months. The data were compared with clinical observations and with a gene expression database obtained for 55 nontransplant HCV-infected and uninfected liver samples. RESULTS: We identified several specific gene expression patterns. The first pattern was unique for the transplant recipients regardless of their infection status. The corresponding genes encoded stress response proteins and blood proteins involved in coagulation that were differentially expressed in response to posttransplantation graft recovery. The second pattern was specific to HCV-infected samples and included up-regulation of genes encoding components of the interferon-mediated antiviral response and immune system (antigen presentation, cytotoxic response). This up-regulation pattern was absent or suppressed in the patients who developed early fibrosis, indicating that the disease progression might result from an impaired liver response to infection. Finally, we identified gene expression patterns that were specific for 12-month biopsy specimens in all 4 HCV-infected patients who developed early fibrosis. CONCLUSIONS: The identified gene expression patterns may prove useful for diagnostic and prognostic applications in HCV-infected patients, including predicting early progression to fibrosis.

Virus infection and the interferon response: a global view through functional genomics.

The primary focus of this chapter is on providing an overview of how we use the tools of functional genomics to study virus infection, the interferon response, and the mechanisms by which viruses attenuate or evade this response to ensure successful replication. We provide examples of the types of analyses we perform, experimental design considerations, and the tools and techniques we use for data processing and mining. We have not attempted to provide detailed protocols for performing microarray or proteomics experiments because even individual components of such analyses, for example, techniques for the isolation and amplification of ribonucleic acid, could easily be the subject of an entire chapter. Rather, our goal is to show how data obtained from global gene expression and protein profiling can be used to gain new insights into virus-host interactions, with particular emphasis on the interferon response and its modulation by virus infection.