A Drosophila model of Pontocerebellar Hypoplasia reveals a critical role for the RNA exosome in neurons.

The RNA exosome is an evolutionarily-conserved ribonuclease complex critically important for precise processing and/or complete degradation of a variety of cellular RNAs. The recent discovery that mutations in genes encoding structural RNA exosome subunits cause tissue-specific diseases makes defining the role of this complex within specific tissues critically important. Mutations in the RNA exosome component 3 (EXOSC3) gene cause Pontocerebellar Hypoplasia Type 1b (PCH1b), an autosomal recessive neurologic disorder. The majority of disease-linked mutations are missense mutations that alter evolutionarily-conserved regions of EXOSC3. The tissue-specific defects caused by these amino acid changes in EXOSC3 are challenging to understand based on current models of RNA exosome function with only limited analysis of the complex in any multicellular model in vivo. The goal of this study is to provide insight into how mutations in EXOSC3 impact the function of the RNA exosome. To assess the tissue-specific roles and requirements for the Drosophila ortholog of EXOSC3 termed Rrp40, we utilized tissue-specific RNAi drivers. Depletion of Rrp40 in different tissues reveals a general requirement for Rrp40 in the development of many tissues including the brain, but also highlight an age-dependent requirement for Rrp40 in neurons. To assess the functional consequences of the specific amino acid substitutions in EXOSC3 that cause PCH1b, we used CRISPR/Cas9 gene editing technology to generate flies that model this RNA exosome-linked disease. These flies show reduced viability; however, the surviving animals exhibit a spectrum of behavioral and morphological phenotypes. RNA-seq analysis of these Drosophila Rrp40 mutants reveals increases in the steady-state levels of specific mRNAs and ncRNAs, some of which are central to neuronal function. In particular, Arc1 mRNA, which encodes a key regulator of synaptic plasticity, is increased in the Drosophila Rrp40 mutants. Taken together, this study defines a requirement for the RNA exosome in specific tissues/cell types and provides insight into how defects in RNA exosome function caused by specific amino acid substitutions that occur in PCH1b can contribute to neuronal dysfunction.

NanoStringDiff: a novel statistical method for differential expression analysis based on NanoString nCounter data.

The advanced medium-throughput NanoString nCounter technology has been increasingly used for mRNA or miRNA differential expression (DE) studies due to its advantages including direct measurement of molecule expression levels without amplification, digital readout and superior applicability to formalin fixed paraffin embedded samples. However, the analysis of nCounter data is hampered because most methods developed are based on t-tests, which do not fit the count data generated by the NanoString nCounter system. Furthermore, data normalization procedures of current methods are either not suitable for counts or not specific for NanoString nCounter data. We develop a novel DE detection method based on NanoString nCounter data. The method, named NanoStringDiff, considers a generalized linear model of the negative binomial family to characterize count data and allows for multifactor design. Data normalization is incorporated in the model framework through data normalization parameters, which are estimated from positive controls, negative controls and housekeeping genes embedded in the nCounter system. We propose an empirical Bayes shrinkage approach to estimate the dispersion parameter in the model and a likelihood ratio test to identify differentially expressed genes. Simulations and real data analysis demonstrate that the proposed method performs better than existing methods.