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Background Western Kentucky University is a member of a select group of colleges and universities chosen to participate in a national science experiment designed to improve undergraduate science education. To introduce freshman students to authentic research, the Howard Hughes Medical Institute’s Science Education Alliance (HHMI SEA) has implemented an innovative program to introduce genomics into the classroom. The program draws on themes and techniques from biology, microbiology, molecular biology, genomics and bioinformatics. The WKU course is called “Genome Discovery and Exploration” (GDE); WKU Genome Discovery and Exploration Program [http://bioweb.wku.edu/asp/wkungri/]. During the fall semester, students isolate bacterial viruses from the environment and characterize them using a variety of techniques including DNA analysis and electron microscopy. Over the winter break, the complete DNA sequence of one of the viruses isolated by the GDE students is determined. During the spring semester, GDE students learn how use computer programs (e.g. Consed, Glimmer, Genemark, BLAST and Phamerator) to identify all the viral genes and to make genome wide comparisons to identify evolutionary relationships. All course participants and the SEA staff are connected via the internet to share and analyze data, troubleshoot, and discuss results. Near the end of the spring semester, HHMI hosts a research symposium for course faculty and one student from each institution to report on their discoveries and experiences. As unique phages are characterized on campuses nationwide, students will have the opportunity to publish their research for the broader scientific community. This hands-on experience with the tools of Bioinformatics is an outstanding training opportunity and this unique program has helped the WKU Biology Department create an introductory pipeline to research experiences that complements our existing and planned instructional programs and allows freshman to engage in the thrill of discovery.

Background In order to develop treatments or preventive measures for auditory hair cell loss, an understanding of both the process of auditory hair cell regeneration and factors that influence this process, is needed. Our previous microarray analysis showed that growth hormone (GH) was significantly upregulated during zebrafish auditory hair cell regeneration, coupled with cell proliferation [1,2]. We further tested the effects of GH on zebrafish auditory hair cell regeneration by injecting GH after sound exposure and found that GH can efficiently promote post-trauma auditory hair cell regeneration, which may be achieved through stimulating proliferation and suppressing apoptosis [3]. In the current study, we used Next Generation Sequencing (NGS) to examine the possible GH pathways involved in zebrafish auditory hair cell regeneration.

Background Toxoplasmosis, caused by the protozoan parasite Toxoplasma gondii is a major cause of morbidity and mortality in patients with AIDS and an important cause of miscarriage, stillbirth and congenital disease in newborns. Previous studies have provided evidence that dietary supplementation with vitamin E and selenium is harmful during experimental toxoplasmosis in mice, whereas a diet deficient in vitamin E and selenium results in decreased numbers of tissue cysts in the brain and dramatically reduced brain pathology. The overall goal of the present study was to determine the impact of dietary supplementation with antioxidants on gene expression in the brains of non-infected mice and in mice infected with T. gondii using microarray analysis. RNA was isolated from the brains of C57BL/6 mice, and an Agilent Oligo Whole Mouse Genome Microarray (Agilent Technologies, Inc.) was performed. A total of 48 chips were normalized by Z ratios and the Data Driven Harr Fisch Normalization methods. Differentially expressed genes were identified by applying thresholds to identify significant values and the results were compared between the normalization methods. These differentially expressed genes and their respective fold change ratios were used in Ingenuity Pathway Analysis (IPA) software to analyze the pathways involved with these genes.

Material and methods The Wizard007 bacteriophage was isolated from a soil sample taken at N36° 49’36.8” W87° 29’42.5” in Hopkinsville, KY. It was plaque purified on Mycobacterium smegmatis and DNA was isolated using the Promega Wizard DNA purification kit. The DNA was sequenced at the Virginia Commonwealth University by Roche 454 DNA sequencing. The genome quality was confirmed in Consed [1] and found to be 51,034 bp in length. Genes were called from the assembled sequence with a workflow consisting of Glimmer [2], GeneMark [3], tRNAscan [4], and SDFinder to identify potential gene features. Gbrowse [5], Apollo [6], and BLAST [7] were used to call and annotate genes. A 10 base 3’ overhang was found at the ends by ligating the genomic DNA and sequencing a PCR product produced across the ligated ends.

Materials and methods In this study we compared the codon frequencies between the phages that carry tRNA in their genome (Clusters A2, A3, A5, A6, A9, C1, C2, E, J, K1, L1, L2, M) to those phages without tRNA in their genome (Clusters A1, A4, B1, B2, D, F1, G) in order to determine whether the tRNAs being carried by the mycobacteriophages were needed to survive in M. smegmatis. The phages with embedded tRNAs were drawn from http:// phagesdb.org/data/. The coding sequences for the mycobacteriophages were obtained from NCBI GenBank [2]. Codon frequencies were derived for each mycobacteriophage and a BoxWhiskerChart (Figure 1) was made using a program written in Mathematica. To determine which codons may require expression of phage tRNAs, Figure 1 plot regions for phages containing tRNA (red) that show frequencies in excess of those not containing tRNA (blue) have been circled in magenta. Only a few codons meet this criteria: ACT, ATG, CAG***, CGT, GAC**, GAG*, TAC, TAT, TGG. A significant number of mycobacteriophages lay outside the non-tRNA phage boundaries for codons CAG, GAC

The University of Tennessee (UT), the Oak Ridge National Laboratory (ORNL), and the Kentucky Biomedical Research Infrastructure Network (KBRIN), have collaborated over the past eleven years to share research and educational expertise in bioinformatics. One result of this collaboration is the joint sponsorship of an annual regional summit to bring together researchers, educators and students who are interested in bioinformatics from a variety of research and educational institutions. This summit provides unique opportunities for collaboration and forging links between members of the various institutions. This year, the Eleventh Annual UT-ORNL-KBRIN Bioinformatics Summit was held at the Seelbach Hilton Hotel in Louisville, Kentucky from March 30-April 1, 2012. A total of 232 participants pre-registered for the summit, with 126 from various Kentucky institutions and 80 from various Tennessee institutions. A number of additional participants came from universities and research institutions from other states and countries, e.g. University of Arkansas Medical Sciences, Michigan State University, University of Cincinnati, Iowa State University, etc. Eighty-four registrants were faculty, with an additional 68 students, 37 staff, and 32 postdoctoral participants (with 12 undeclared). The conference program consisted of three days of presentations. The first day included a pre-summit of talks by Kentucky researchers and a workshop on Next-Generation Sequencing technologies. The next two days were dedicated to scientific presentations divided into four plenary sessions on Next-Generation Sequencing, Medical Informatics, Metagenomics, and Behavioral and Comparative Genomics. The Medical Informatics session was followed by four short talks, selected from 47 submitted poster abstracts.

* Correspondence: claire.rinehart@wku.edu Department of Biology, Western Kentucky University, Bowling Green, KY, 42101, USA Figure 1 Seven predicted pham 6714 structures superimposed into a single model matching methyltransferase structures. PDB files were rendered using UCSF Chimera (http://www.cgl.ucsf.edu/chimera/). Proteins include MeeZee gp 78, JN243856.1; Backyardigan gp 74, JF704093.1; and ShiLan gp 70, JN020143.1 Kapadia and Rinehart BMC Bioinformatics 2013, 14(Suppl 17):A10 http://www.biomedcentral.com/1471-2105/14/S17/A10