Expression pattern analysis of transcribed HERV sequences is complicated by ex vivo recombination.

BACKGROUND: The human genome comprises numerous human endogenous retroviruses (HERVs) that formed millions of years ago in ancestral species. A number of loci of the HERV-K(HML-2) family are evolutionarily much younger. A recent study suggested an infectious HERV-K(HML-2) variant in humans and other primates. Isolating such a variant from human individuals would be a significant finding for human biology. RESULTS: When investigating expression patterns of specific HML-2 proviruses we encountered HERV-K(HML-2) cDNA sequences without proviral homologues in the human genome, named HERV-KX, that could very well support recently suggested infectious HML-2 variants. However, detailed sequence analysis, using the software RECCO, suggested that HERV-KX sequences were produced by recombination, possibly arising ex vivo, between transcripts from different HML-2 proviral loci. CONCLUSION: As RT-PCR probably will be instrumental for isolating an infectious HERV-K(HML-2) variant, generation of "new" HERV-K(HML-2) sequences by ex vivo recombination seems inevitable. Further complicated by an unknown amount of allelic sequence variation in HERV-K(HML-2) proviruses, newly identified HERV-K(HML-2) variants should be interpreted very cautiously.

Structural and functional comparison of the non-structural protein 4B in flaviviridae.

Flaviviridae are evolutionarily related viruses, comprising the hepatitis C virus (HCV), with the non-structural protein 4B (NS4B) as one of the least characterized proteins. NS4B is located in the endoplasmic reticulum membrane and is assumed to be a multifunctional protein. However, detailed structure information is missing. The hydrophobic nature of NS4B is a major difficulty for many experimental techniques. We applied bioinformatics methods to analyse structural and functional properties of NS4B in different viruses. We distinguish a central non-globular membrane portion with four to five transmembrane regions from an N- and C-terminal part with non-transmembrane helical elements. We demonstrate high similarity in sequence and structure for the C-terminal part within the flaviviridae family. A palmitoylation site contained in the C-terminal part of HCV is equally conserved in GB virus B. Furthermore, we identify and characterize an N-terminal basic leucine zipper (bZIP) motif in HCV, which is suggestive of a functionally important interaction site. In addition, we model the interaction of the bZIP region with the recently identified interaction partner CREB-RP/ATF6beta, a human activating transcription factor involved in ER-stress. In conclusion, the versatile structure, together with functional sites and motifs, possibly enables NS4B to adopt a role as protein hub in the membranous web interaction network of virus and host proteins. Important structural and functional properties of NS4B are predicted with implications for ER-stress response, altered gene expression and replication efficacy.

Recco: recombination analysis using cost optimization.

MOTIVATION: Recombination plays an important role in the evolution of many pathogens, such as HIV or malaria. Despite substantial prior work, there is still a pressing need for efficient and effective methods of detecting recombination and analyzing recombinant sequences. RESULTS: We introduce Recco, a novel fast method that, given a multiple sequence alignment, scores the cost of obtaining one of the sequences from the others by mutation and recombination. The algorithm comes with an illustrative visualization tool for locating recombination breakpoints. We analyze the sequence alignment with respect to all choices of the parameter alpha weighting recombination cost against mutation cost. The analysis of the resulting cost curve yields additional information as to which sequence might be recombinant. On random genealogies Recco is comparable in its power of detecting recombination with the algorithm Geneconv (Sawyer, 1989). For specific relevant recombination scenarios Recco significantly outperforms Geneconv.

Calculating the statistical significance of changes in pathway activity from gene expression data.

We present a statistical approach to scoring changes in activity of metabolic pathways from gene expression data. The method identifies the biologically relevant pathways with corresponding statistical significance. Based on gene expression data alone, only local structures of genetic networks can be recovered. Instead of inferring such a network, we propose a hypothesis-based approach. We use given knowledge about biological networks to improve sensitivity and interpretability of findings from microarray experiments. Recently introduced methods test if members of predefined gene sets are enriched in a list of top-ranked genes in a microarray study. We improve this approach by defining scores that depend on all members of the gene set and that also take pairwise co-regulation of these genes into account. We calculate the significance of co-regulation of gene sets with a nonparametric permutation test. On two data sets the method is validated and its biological relevance is discussed. It turns out that useful measures for co-regulation of genes in a pathway can be identified adaptively. We refine our method in two aspects specific to pathways. First, to overcome the ambiguity of enzyme-to-gene mappings for a fixed pathway, we introduce algorithms for selecting the best fitting gene for a specific enzyme in a specific condition. In selected cases, functional assignment of genes to pathways is feasible. Second, the sensitivity of detecting relevant pathways is improved by integrating information about pathway topology. The distance of two enzymes is measured by the number of reactions needed to connect them, and enzyme pairs with a smaller distance receive a higher weight in the score calculation.