Intravital imaging of fluorescent markers and FRET probes by DNA tattooing

Background  

Advances in fluorescence microscopy and mouse transgenesis have made it possible to image molecular events in living animals. However, the generation of transgenic mice is a lengthy process and intravital imaging requires specialized knowledge and equipment. Here, we report a rapid and undemanding intravital imaging method using generally available equipment.     

Cubic exact solutions for the estimation of pairwise haplotype frequencies: implications for linkage disequilibrium analyses and a web tool 'CubeX'

Background  

The frequency of a haplotype comprising one allele at each of two loci can be expressed as a cubic equation (the 'Hill equation'), the solution of which gives that frequency. Most haplotype and linkage disequilibrium analysis programs use iteration-based algorithms which substitute an estimate of haplotype frequency into the equation, producing a new estimate which is repeatedly fed back into the equation until the values converge to a maximum likelihood estimate (expectation-maximisation).     

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.     

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.