Three-Dimensional Imaging of Drosophila melanogaster

The major hindrance to imaging the intact adult Drosophila is that the dark exoskeleton makes it impossible to image through the cuticle. We have overcome this obstacle and describe a method whereby the internal organs of adult Drosophila can be imaged in 3D by bleaching and clearing the adult and then imaging using a technique called optical projection tomography (OPT). The data is displayed as 2D optical sections and also in 3D to provide detail on the shape and structure of the adult anatomy.We have used OPT to visualize in 2D and 3D the detailed internal anatomy of the intact adult Drosophila. In addition this clearing method used for OPT was tested for imaging with confocal microscopy. Using OPT we have visualized the size and shape of neurodegenerative vacuoles from within the head capsule of flies that suffer from age-related neurodegeneration due to a lack of ADAR mediated RNA-editing. In addition we have visualized tau-lacZ expression in 2D and 3D. This shows that the wholemount adult can be stained without any manipulation and that this stain penetrates well as we have mapped the localization pattern with respect to the internal anatomy.We show for the first time that the intact adult Drosophila can be imaged in 3D using OPT, also we show that this method of clearing is also suitable for confocal microscopy to image the brain from within the intact head. The major advantage of this is that organs can be represented in 3D in their natural surroundings. Furthermore optical sections are generated in each of the three planes and are not prone to the technical limitations that are associated with manual sectioning. OPT can be used to dissect mutant phenotypes and to globally map gene expression in both 2D and 3D

Systematic identification of abundant A-to-I editing sites in the human transcriptome

RNA editing by members of the double-stranded RNA-specific ADAR family leads to site-specific conversion of adenosine to inosine (A-to-I) in precursor messenger RNAs. Editing by ADARs is believed to occur in all metazoa, and is essential for mammalian development. Currently, only a limited number of human ADAR substrates are known, while indirect evidence suggests a substantial fraction of all pre-mRNAs being affected. Here we describe a computational search for ADAR editing sites in the human transcriptome, using millions of available expressed sequences. 12,723 A-to-I editing sites were mapped in 1,637 different genes, with an estimated accuracy of 95%, raising the number of known editing sites by two orders of magnitude. We experimentally validated our method by verifying the occurrence of editing in 26 novel substrates. A-to-I editing in humans primarily occurs in non-coding regions of the RNA, typically in Alu repeats. Analysis of the large set of editing sites indicates the role of editing in controlling dsRNA stability.Comment: Pre-print version. See http://dx.doi.org/10.1038/nbt996 for a reprin

Regulation of Na+/K+ ATPase Transport Velocity by RNA Editing

Editing of Na+/K+ ATPase mRNAs modulates the Na+/K+ pump's turnover rate by selectively targeting the release of the final sodium to the outside

Identifying RNA editing sites using RNA sequencing data alone

We show that RNA editing sites can be called with high confidence using RNA sequencing data from multiple samples across either individuals or species, without the need for matched genomic DNA sequence. We identified many previously unidentified editing sites in both humans and Drosophila; our results nearly double the known number of human protein recoding events. We also found that human genes harboring conserved editing sites within Alu repeats are enriched for neuronal functions

A systematic study of genetic algorithms with genotype editing

Abstract. This paper continues our systematic study of an RNAediting computational model of Genetic Algorithms (GA). This model is constructed based on several genetic editing characteristics that are gleaned from the RNA editing system as observed in several organisms. We have expanded the traditional Genetic Algorithm with artificial editing mechanisms as proposed in [11] and [12]. The incorporation of editing mechanisms, which stochastically alter the information encoded in the genotype, provides a means for artificial agents with genetic descriptions to gain greater phenotypic plasticity, which may be environmentally regulated. The systematic study of this artificial genotype editing model has shed some light into the evolutionary implications of RNA editing and how to select proper genotype editors to design more robust GAs. Our results also show promising applications to complex real-world problems. We expect that the framework here developed will both facilitate determining the evolutionary role of RNA editing in biology, and advance the current state of research in Evolutionary Computation.