Completion of the genome sequence of Lettuce necrotic yellows virus, type species of the genus Cytorhabdovirus

We completed the genome sequence of Lettuce necrotic yellows virus (LNYV) by determining the nucleotide sequences of the 4a (putative phosphoprotein), 4b, M (matrix protein), G (glycoprotein) and L (polymerase) genes. The genome consists of 12,807 nucleotides and encodes six genes in the order 3' leader-N-4a(P)-4b-M-G-L-5' trailer. Sequences were derived from clones of a cDNA library from LNYV genomic RNA and from fragments amplified using reverse transcription-polymerase chain reaction. The 4a protein has a low isoelectric point characteristic for rhabdovirus phosphoproteins. The 4b protein has significant sequence similarities with the movement proteins of capillo- and trichoviruses and may be involved in cell-to-cell movement. The putative G protein sequence contains a predicted 25 amino acids signal peptide and endopeptidase cleavage site, three predicted glycosylation sites and a putative transmembrane domain. The deduced L protein sequence shows similarities with the L proteins of other plant rhabdoviruses and contains polymerase module motifs characteristic for RNA-dependent RNA polymerases of negative-strand RNA viruses. Phylogenetic analysis of this motif among rhabdoviruses placed LNYV in a group with other sequenced cytorhabdoviruses, most closely related to Strawberry crinkle virus. (c) 2005 Elsevier B.V. All rights reserved.

GONOME: measuring correlations between GO terms and genomic positions

Background: Current methods to find significantly under- and over-represented gene ontology (GO) terms in a set of genes consider the genes as equally probable balls in a bag, as may be appropriate for transcripts in micro-array data. However, due to the varying length of genes and intergenic regions, that approach is inappropriate for deciding if any GO terms are correlated with a set of genomic positions. Results: We present an algorithm - GONOME - that can determine which GO terms are significantly associated with a set of genomic positions given a genome annotated with (at least) the starts and ends of genes. We show that certain GO terms may appear to be significantly associated with a set of randomly chosen positions in the human genome if gene lengths are not considered, and that these same terms have been reported as significantly over-represented in a number of recent papers. This apparent over-representation disappears when gene lengths are considered, as GONOME does. For example, we show that, when gene length is taken into account, the term development is not significantly enriched in genes associated with human CpG islands, in contradiction to a previous report. We further demonstrate the efficacy of GONOME by showing that occurrences of the proteosome-associated control element (PACE) upstream activating sequence in the S. cerevisiae genome associate significantly to appropriate GO terms. An extension of this approach yields a whole-genome motif discovery algorithm that allows identification of many other promoter sequences linked to different types of genes, including a large group of previously unknown motifs significantly associated with the terms 'translation' and 'translational elongation'. Conclusion: GONOME is an algorithm that correctly extracts over-represented GO terms from a set of genomic positions. By explicitly considering gene size, GONOME avoids a systematic bias toward GO terms linked to large genes. Inappropriate use of existing algorithms that do not take gene size into account has led to erroneous or suspect conclusions. Reciprocally GONOME may be used to identify new features in genomes that are significantly associated with particular categories of genes.

Identifying sequence regions undergoing conformational change via predicted continuum secondary structure

Motivation: Conformational flexibility is essential to the function of many proteins, e.g. catalytic activity. To assist efforts in determining and exploring the functional properties of a protein, it is desirable to automatically identify regions that are prone to undergo conformational changes. It was recently shown that a probabilistic predictor of continuum secondary structure is more accurate than categorical predictors for structurally ambivalent sequence regions, suggesting that such models are suited to characterize protein flexibility. Results: We develop a computational method for identifying regions that are prone to conformational change directly from the amino acid sequence. The method uses the entropy of the probabilistic output of an 8-class continuum secondary structure predictor. Results for 171 unique amino acid sequences with well-characterized variable structure (identified in the 'Macromolecular movements database') indicate that the method is highly sensitive at identifying flexible protein regions, but false positives remain a problem. The method can be used to explore conformational flexibility of proteins (including hypothetical or synthetic ones) whose structure is yet to be determined experimentally.

SCORPION2: A database for structure-function analysis of scorpion toxins

Scorpion toxins are important experimental tools for characterization of vast array of ion channels and serve as scaffolds for drug design. General public database entries contain limited annotation whereby rich structure-function information from mutation studies is typically not available. SCORPION2 contains more than 800 records of native and mutant toxin sequences enriched with binding affinity and toxicity information, 624 three-dimensional structures and some 500 references. SCORPION2 has a set of search and prediction tools that allow users to extract and perform specific queries: text searches of scorpion toxin records, sequence similarity search, extraction of sequences, visualization of scorpion toxin structures, analysis of toxic activity, and functional annotation of previously uncharacterized scorpion toxins. The SCORPION2 database is available at http://sdmc.i2r.a-star.edu.sg/scorpion/. (c) 2006 Elsevier Ltd. All rights reserved.

Sequencing a new target genome: The Boophilus microplus (Acari : Ixodidae) genome project

The southern cattle tick, Boophilus microplus (Canestrini), causes annual economic losses in the hundreds of millions of dollars to cattle producers throughout the world, and ranks as the most economically important tick from a global perspective. Control failures attributable to the development of pesticide resistance have become commonplace, and novel control technologies are needed. The availability of the genome sequence will facilitate the development of these new technologies, and we are proposing sequencing to a 4-6X draft coverage. Many existing biological resources are available to facilitate a genome sequencing project, including several inbred laboratory tick strains, a database of approximate to 45,000 expressed sequence tags compiled into a B. microplus Gene Index, a bacterial artificial chromosome (BAC) library, an established B. microplus cell line, and genomic DNA suitable for library synthesis. Collaborative projects are underway to map BACs and cDNAs to specific chromosomes and to sequence selected BAC clones. When completed, the genome sequences from the cow, B. microphis, and the B. microphis-borne pathogens Babesia bovis and Anaplasma marginale will enhance studies of host-vector-pathogen systems. Genes involved in the regeneration of amputated tick limbs and transitions through developmental stages are largely unknown. Studies of these and other interesting biological questions will be advanced by tick genome sequence data. Comparative genomics offers the prospect of new insight into many, perhaps all, aspects of the biology of ticks and the pathogens they transmit to farm animals and people. The B. microplus genome sequence will fill a major gap in comparative genomics: a sequence from the Metastriata lineage of ticks. The purpose of the article is to synergize interest in and provide rationales for sequencing the genome of B. microplus and for publicizing currently available genomic resources for this tick.