SUMMARY: A number of methods have been devised to address the need for targeted genomic resequencing. One of these methods, region-specific extraction (RSE) is characterized by the capture of long DNA fragments (15-20 kb) by magnetic beads, after enzymatic extension of oligonucleotides hybridized to selected genomic regions. Facilitating the selection of the most appropriate capture oligos for targeting a region of interest, satisfying the properties of temperature (Tm) and entropy (ΔG), while minimizing the formation of primer-dimers in a pooled experiment, is therefore necessary. Manual design and selection of oligos becomes very challenging, complicated by factors such as length of the target region and number of targeted regions. Here we describe, AnthOligo, a web-based application developed to optimally automate the process of generation of oligo sequences used to target and capture the continuum of large and complex genomic regions. Apart from generating oligos for RSE, this program may have wider applications in the design of customizable internal oligos to be used as baits for gene panel analysis or even probes for large-scale comparative genomic hybridization array processes. AnthOligo was tested by capturing the Major Histocompatibility Complex (MHC) of a random sample.The application provides users with a simple interface to upload an input file in BED format and customize parameters for each task. The task of probe design in AnthOligo commences when a user uploads an input file and concludes with the generation of a result-set containing an optimal set of region-specific oligos. AnthOligo is currently available as a public web application with URL: http://antholigo.chop.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MOTIVATION: RNA-Seq (also called whole-transcriptome sequencing) is an emerging technology that uses the capabilities of next-generation sequencing to detect and quantify entire transcripts. One of its important applications is the improvement of existing genome annotations. RNA-Seq provides rapid, comprehensive and cost-effective tools for the discovery of novel genes and transcripts compared with expressed sequence tag (EST), which is instrumental in gene discovery and gene sequence determination. The rat is widely used as a laboratory disease model, but has a less well-annotated genome as compared with humans and mice. In this study, we incorporated deep RNA-Seq data from three rat tissues-bone marrow, brain and kidney-with EST data to improve the annotation of the rat genome. RESULTS: Our analysis identified 32 197 transcripts, including 13 461 known transcripts, 13 934 novel isoforms and 4802 new genes, which almost doubled the numbers of transcripts in the current public rat genome database (rn5). Comparisons of our predicted protein-coding gene sets with those in public datasets suggest that RNA-Seq significantly improves genome annotation and identifies novel genes and isoforms in the rat. Importantly, the large majority of novel genes and isoforms are supported by direct evidence of RNA-Seq experiments. These predicted genes were integrated into the Rat Genome Database (RGD) and can serve as an important resource for functional studies in the research community. AVAILABILITY AND IMPLEMENTATION: The predicted genes are available at http://rgd.mcw.edu.

MOTIVATION: New sequencing technologies have accelerated research on prokaryotic genomes and have made genome sequencing operations outside major genome sequencing centers routine. However, no off-the-shelf solution exists for the combined assembly, gene prediction, genome annotation and data presentation necessary to interpret sequencing data. The resulting requirement to invest significant resources into custom informatics support for genome sequencing projects remains a major impediment to the accessibility of high-throughput sequence data. RESULTS: We present a self-contained, automated high-throughput open source genome sequencing and computational genomics pipeline suitable for prokaryotic sequencing projects. The pipeline has been used at the Georgia Institute of Technology and the Centers for Disease Control and Prevention for the analysis of Neisseria meningitidis and Bordetella bronchiseptica genomes. The pipeline is capable of enhanced or manually assisted reference-based assembly using multiple assemblers and modes; gene predictor combining; and functional annotation of genes and gene products. Because every component of the pipeline is executed on a local machine with no need to access resources over the Internet, the pipeline is suitable for projects of a sensitive nature. Annotation of virulence-related features makes the pipeline particularly useful for projects working with pathogenic prokaryotes. AVAILABILITY AND IMPLEMENTATION: The pipeline is licensed under the open-source GNU General Public License and available at the Georgia Tech Neisseria Base (http://nbase.biology.gatech.edu/). The pipeline is implemented with a combination of Perl, Bourne Shell and MySQL and is compatible with Linux and other Unix systems.