Manduca sexta, known as the tobacco hornworm or Carolina sphinx moth, is a lepidopteran insect that is used extensively as a model system for research in insect biochemistry, physiology, neurobiology, development, and immunity. One important benefit of this species as an experimental model is its extremely large size, reaching more than 10 g in the larval stage. M. sexta larvae feed on solanaceous plants and thus must tolerate a substantial challenge from plant allelochemicals, including nicotine. We report the sequence and annotation of the M. sexta genome, and a survey of gene expression in various tissues and developmental stages. The Msex_1.0 genome assembly resulted in a total genome size of 419.4 Mbp. Repetitive sequences accounted for 25.8% of the assembled genome. The official gene set is comprised of 15,451 protein-coding genes, of which 2498 were manually curated. Extensive RNA-seq data from many tissues and developmental stages were used to improve gene models and for insights into gene expression patterns. Genome wide synteny analysis indicated a high level of macrosynteny in the Lepidoptera. Annotation and analyses were carried out for gene families involved in a wide spectrum of biological processes, including apoptosis, vacuole sorting, growth and development, structures of exoskeleton, egg shells, and muscle, vision, chemosensation, ion channels, signal transduction, neuropeptide signaling, neurotransmitter synthesis and transport, nicotine tolerance, lipid metabolism, and immunity. This genome sequence, annotation, and analysis provide an important new resource from a well-studied model insect species and will facilitate further biochemical and mechanistic experimental studies of many biological systems in insects.

The Arabidopsis Co-expression Tool, ACT, ranks the genes across a large microarray dataset according to how closely their expression follows the expression of a query gene. A database stores pre-calculated co-expression results for approximately 21,800 genes based on data from over 300 arrays. These results can be corroborated by calculation of co-expression results for user-defined sub-sets of arrays or experiments from the NASC/GARNet array dataset. Clique Finder (CF) identifies groups of genes which are consistently co-expressed with each other across a user-defined co-expression list. The parameters can be altered easily to adjust cluster size and the output examined for optimal inclusion of genes with known biological roles. Alternatively, a Scatter Plot tool displays the correlation coefficients for all genes against two user-selected queries on a scatter plot which can be useful for visual identification of clusters of genes with similar r-values. User-input groups of genes can be highlighted on the scatter plots. Inclusion of genes with known biology in sets of genes identified using CF and Scatter Plot tools allows inferences to be made about the roles of the other genes in the set and both tools can therefore be used to generate short lists of genes for further characterization. ACT is freely available at www.Arabidopsis.leeds.ac.uk/ACT.

Background: Overlapping transcripts in antisense orientation have the potential to form double-stranded RNA (dsRNA), a substrate for a number of different RNA-modification pathways. One prominent route for dsRNA is its breakdown by Dicer enzyme complexes into small RNAs, a pathway that is widely exploited by RNA interference technology to inactivate defined genes in transgenic lines. The significance of this pathway for endogenous gene regulation remains unclear. Results: We have examined transcription data for overlapping gene pairs in Arabidopsis thaliana. On the basis of an analysis of transcripts with coding regions, we find the majority of overlapping gene pairs to be convergently overlapping pairs (COPs), with the potential for dsRNA formation. In all tissues, COP transcripts are present at a higher frequency compared to the overall gene pool. The probability that both the sense and antisense copy of a COP are co-transcribed matches the theoretical value for coexpression under the assumption that the expression of one partner does not affect the expression of the other. Among COPs, we observe an over-representation of spliced (intron-containing) genes (90%) and of genes with alternatively spliced transcripts. For loci where antisense transcripts overlap with sense transcript introns, we also find a significant bias in favor of alternative splicing and variation of polyadenylation. Conclusion: The results argue against a predominant RNA degradation effect induced by dsRNA formation. Instead, our data support alternative roles for dsRNAs. They suggest that at least for a subgroup of COPs, antisense expression may induce alternative splicing or polyadenylation.

Cancer is one of the four major non‑communicable diseases (NCD), responsible for ~14.6% of all human deaths. Currently, there are >100 different known types of cancer and >500 genes involved in cancer. Ongoing research efforts have been focused on cancer etiology and therapy. As a result, there is an exponential growth of cancer‑associated data from diverse resources, such as scientific publications, genome‑wide association studies, gene expression experiments, gene‑gene or protein‑protein interaction data, enzymatic assays, epigenomics, immunomics and cytogenetics, stored in relevant repositories. These data are complex and heterogeneous, ranging from unprocessed, unstructured data in the form of raw sequences and polymorphisms to well‑annotated, structured data. Consequently, the storage, mining, retrieval and analysis of these data in an efficient and meaningful manner pose a major challenge to biomedical investigators. In the current review, we present the central, publicly accessible databases that contain data pertinent to cancer, the resources available for delivering and analyzing information from these databases, as well as databases dedicated to specific types of cancer. Examples for this wealth of cancer‑related information and bioinformatic tools have also been provided.

The TOPS database holds topological descriptions of protein structures. These compact and highly abstract descriptions reduce the protein fold to a sequence of Secondary Structure Elements (SSEs) and three sets of pairwise relationships between them, hydrogen bonds relating parallel and anti- parallel beta strands, spatial adjacencies relating neighbouring SSEs, and the chiralities of selected supersecondary structures, including connections in betaalphabeta units and between parallel alpha helices. The database is used as a resource for visualizing folding topologies, fast topological pattern searching and structure comparison. Here, significant enhancements to the TOPS database are described. The topological description has been enhanced to include packing relationships between helices, which significantly improves the description of protein folds with little beta strand content. Further, the topological description has been annotated with sequence information. The query interfaces to the database have been improved and the new version can be found at http://www.tops.leeds.ac.uk/.

The discovery of therapeutic miRNAs is one of the most exciting challenges for pharmaceutical companies. Since the first miRNA was discovered in 1993, our knowledge of miRNA biology has grown considerably. Many studies have demonstrated that miRNA expression is dysregulated in many diseases, making them appealing tools for novel therapeutic approaches. This review aims to discuss miRNA biogenesis and function, as well as highlight strategies for delivering miRNA agents, presenting viral, non-viral, and exosomic delivery as therapeutic approaches for different cancer types. We also consider the therapeutic role of microRNA-mediated drug repurposing in cancer therapy.