Distribution of transfer RNA genes in thePisum sativum chloroplast DNA

Purified chloroplast tRNAs were isolated fromPisum sativum leaves and radioactively labeled at their 3′ end using tRNA nucleotidyl transferase and α³²P-labeled CTP. Pea ctDNA was fragmented using a number of restriction endonucleases and hybridized with thein vitro labeled chloroplast tRNAs by DNA transfer method. Genes for tRNAs have been found to be dispersed throughout the chloroplast genome. A closer analysis of the several hybrid regions using recombinant DNA plasmids have shown that tRNA genes are localized in the chloroplast genome in both single and multiple arrangements. Two dimensional gel electrophoresis of total ct tRNA have identified 36 spots. All of them have been found to hybridize withPisum sativum ctDNA. Using recombinant clones, 30 of the tRNA spots have been mapped inPisum sativum ctDNA.     

Darkling Beetles (Alphitobius diaperinus) and Their Larvae as Potential Vectors for the Transfer of Campylobacter jejuni and Salmonella enterica Serovar Paratyphi B Variant Java between Successive Broiler Flocks

Broiler flocks often become infected with Campylobacter and Salmonella, and the exact contamination routes are still not fully understood. Insects like darkling beetles and their larvae may play a role in transfer of the pathogens between consecutive cycles. In this study, several groups of beetles and their larvae were artificially contaminated with a mixture of Salmonella enterica serovar Paratyphi B Variant Java and three C. jejuni strains and kept for different time intervals before they were fed to individually housed chicks. Most inoculated insects were positive for Salmonella and Campylobacter just before they were fed to the chicks. However, Campylobacter could not be isolated from insects that were kept for 1 week before they were used to mimic an empty week between rearing cycles. All broilers fed insects that were inoculated with pathogens on the day of feeding showed colonization with Campylobacter and Salmonella at levels of 50 to 100%. Transfer of both pathogens by groups of insects that were kept for 1 week before feeding to the chicks was also observed, but at lower levels. Naturally contaminated insects that were collected at a commercial broiler farm colonized broilers at low levels as well. In conclusion, the fact that Salmonella and Campylobacter can be transmitted via beetles and their larvae to flocks in successive rearing cycles indicates that there should be intensive control programs for exclusion of these insects from broiler houses.     

Revealing pancrustacean relationships: Phylogenetic analysis of ribosomal protein genes places Collembola (springtails) in a monophyletic Hexapoda and reinforces the discrepancy between mitochondrial and nuclear DNA markers

Background  

In recent years, several new hypotheses on phylogenetic relations among arthropods have been proposed on the basis of DNA sequences. One of the challenged hypotheses is the monophyly of hexapods. This discussion originated from analyses based on mitochondrial DNA datasets that, due to an unusual positioning of Collembola, suggested that the hexapod body plan evolved at least twice. Here, we re-evaluate the position of Collembola using ribosomal protein gene sequences.     

Ranking non-synonymous single nucleotide polymorphisms based on disease concepts

As the number of non-synonymous single nucleotide polymorphisms (nsSNPs) identified through whole-exome/whole-genome sequencing programs increases, researchers and clinicians are becoming increasingly reliant upon computational prediction algorithms designed to prioritize potential functional variants for further study. A large proportion of existing prediction algorithms are ‘disease agnostic’ but are nevertheless quite capable of predicting when a mutation is likely to be deleterious. However, most clinical and research applications of these algorithms relate to specific diseases and would therefore benefit from an approach that discriminates between functional variants specifically related to that disease from those which are not. In a whole-exome/whole-genome sequencing context, such an approach could substantially reduce the number of false positive candidate mutations. Here, we test this postulate by incorporating a disease-specific weighting scheme into the Functional Analysis through Hidden Markov Models (FATHMM) algorithm. When compared to traditional prediction algorithms, we observed an overall reduction in the number of false positives identified using a disease-specific approach to functional prediction across 17 distinct disease concepts/categories. Our results illustrate the potential benefits of making disease-specific predictions when prioritizing candidate variants in relation to specific diseases. A web-based implementation of our algorithm is available at http://fathmm.biocompute.org.uk.