Locating and sequencing of the E3 and neighbouring regions in bovine advenovirus type 2

Adenoviruses are nonenveloped icosahedral shaped particles. The double stranded DNA viral genome is divided into 5 major early transcription units, designated E1 A, E1 B, and E2 to E4, which are expressed in a regulated manner soon after infection. The gene products of the early region 3 (E3), shown to be nonessential for viral replication in vitro, are believed to be involved in counteracting host immunosurveillance. In order to sequence the E3 region of Bovine adenovirus type 2 (BAV2) it was necessary to determine the restriction map for the plasmid pEA48. A physical restriction endonuclease map for BamHl, Clal, Eco RI, Hindlll, Kpnl, Pstt, Sail, and Xbal was constructed. The DNA insert in pEA48 was determined to be viral in origin using Southern hybridization. A human adenovirus type 5 recombinant plasmid, containing partial DNA fragments of the two transcription units L4 and L5 that lie just outside the E3, was used to localize this region. The recombinant plasmid pEA was subcloned to facilitate sequencing. The DNA sequences between 74.8 and 90.5 map units containing the E3, the hexon associated protein (pVIII), and the fibre gene were determined. Homology comparison revealed that the genes for the hexon associated pV11I and the fibre protein are conserved. The last 70 amino acids of the BAV2 pV11I were the most conserved, showing a similarity of 87 percent with Ad2 pV1I1. A comparison between the predicted amino acid sequences of BAV2 and Ad40, Ad41 , Ad2 and AdS, revealed that they have an identical secondary structure consisting of a tail, a shaft and a knob. The shaft is composed of 22, 15 amino acid motifs, with periodic glycines and hydrophobic residues. The E3 region was found to consist of about 2.3 Kbp and to encode four proteins that were greater than 60 amino acids. However, these four open reading frames did not show significant homology to any other known adenovirus DNA or protein sequence.

A Multi-Objective Genetic Algorithm with Side Effect Machines for Motif Discovery

Understanding the machinery of gene regulation to control gene expression has been one of the main focuses of bioinformaticians for years. We use a multi-objective genetic algorithm to evolve a specialized version of side effect machines for degenerate motif discovery. We compare some suggested objectives for the motifs they find, test different multi-objective scoring schemes and probabilistic models for the background sequence models and report our results on a synthetic dataset and some biological benchmarking suites. We conclude with a comparison of our algorithm with some widely used motif discovery algorithms in the literature and suggest future directions for research in this area.

Improving Short DNA Sequence Alignment with Parallel Computing

Variations in different types of genomes have been found to be responsible for a large degree of physical diversity such as appearance and susceptibility to disease. Identification of genomic variations is difficult and can be facilitated through computational analysis of DNA sequences. Newly available technologies are able to sequence billions of DNA base pairs relatively quickly. These sequences can be used to identify variations within their specific genome but must be mapped to a reference sequence first. In order to align these sequences to a reference sequence, we require mapping algorithms that make use of approximate string matching and string indexing methods. To date, few mapping algorithms have been tailored to handle the massive amounts of output generated by newly available sequencing technologies. In otrder to handle this large amount of data, we modified the popular mapping software BWA to run in parallel using OpenMPI. Parallel BWA matches the efficiency of multithreaded BWA functions while providing efficient parallelism for BWA functions that do not currently support multithreading. Parallel BWA shows significant wall time speedup in comparison to multithreaded BWA on high-performance computing clusters, and will thus facilitate the analysis of genome sequencing data.

THE ASSOCIATION OF SEQUENCE OF HIRING PRACTICE AND BIOPHYSICAL COMPONENTS IN SCREENING PROBATIONARY FIREFIGHTERS

Variation in hiring procedures occurs within fire service human resource departments. In this study, City 1 and City 2 applicants were required to pass their biophysical assessments prior to being hired as firefighters at the beginning and end of the screening process, respectively. City 1 applicants demonstrated significantly lower resting heart rate (RHR), resting diastolic blood pressure (RDBP), body fat% (BF) and higher z-scores for BF, trunk flexibility (TF) and overall clinical assessment (p<0.05). Regression analysis found that age and conducting the biophysical assessment at the end of the screening process explained poorer biophysical assessment results in BF% (R2=21%), BF z-score (R2=22%), TF z-score (R2=10%) and overall clinical assessment z-score (R2=7%). Each of RHR (OR=1.06, CI=1.01-1.10), RDBP (OR=1.05, CI=1.00-1.11) and BF% (OR=1.20, CI=1.07-1.37) increased the odds of being a City 2 firefighter (p<0.05). Biophysical screening at the end of the hiring process may result in the hiring of a less healthy firefighter.

Complete Genome Sequence of Erwinia amylovora Bacteriophage

The complete genome of an Erwinia amylovora bacteriophage, vB_EamM_Ea35-70 (Ea35-70), is 271,084 bp, encodes 318 putative proteins, and contains one tRNA. Comparative analysis with other Myoviridae genomes suggests that Ea35-70 is related to the Phikzlikevirus genus within the family Myoviridae, since 26% of Ea35-70 proteins share homology to proteins in Pseudomonas phage φKZ.