A Highly Polymorphic Copy Number Variant in the NSF Gene is Associated with Cocaine Dependence

Cocaine dependence is a complex psychiatric disorder involving both genetic and environmental factors. Several neurotransmitter systems mediate cocaine's effects, dependence and relapse, being the components of the neurotransmitter release machinery good candidates for the disorder. Previously, we identified a risk haplotype for cocaine dependence in the NSF gene, encoding the protein N-Ethylmaleimide-Sensitive Factor essential for synaptic vesicle turnover. Here we examined the possible contribution to cocaine dependence of a large copy number variant (CNV) that encompasses part of the NSF gene. We performed a case-control association study in a discovery sample (359 cases and 356 controls) and identified an association between cocaine dependence and the CNV (P=0.013), that was confirmed in the replication sample (508 cases and 569 controls, P=7.1e-03) and in a pooled analysis (P=1.8e-04), with an over-representation of low number of copies in cases. Subsequently, we studied the functional impact of the CNV on gene expression and found thatthe levels of two NSF transcripts were significantly increased in peripheral blood mononuclear cells (PBMC) along with the number of copies of the CNV. These results, together with a previous study from our group, support the role of NSF in the susceptibility to cocaine dependenc

Targeting LIF-mediated paracrine interaction for pancreatic cancer therapy and monitoring.

Pancreatic ductal adenocarcinoma (PDAC) has a dismal prognosis largely owing to inefficient diagnosis and tenacious drug resistance. Activation of pancreatic stellate cells (PSCs) and consequent development of dense stroma are prominent features accounting for this aggressive biology1,2. The reciprocal interplay between PSCs and pancreatic cancer cells (PCCs) not only enhances tumour progression and metastasis but also sustains their own activation, facilitating a vicious cycle to exacerbate tumorigenesis and drug resistance3-7. Furthermore, PSC activation occurs very early during PDAC tumorigenesis8-10, and activated PSCs comprise a substantial fraction of the tumour mass, providing a rich source of readily detectable factors. Therefore, we hypothesized that the communication between PSCs and PCCs could be an exploitable target to develop effective strategies for PDAC therapy and diagnosis. Here, starting with a systematic proteomic investigation of secreted disease mediators and underlying molecular mechanisms, we reveal that leukaemia inhibitory factor (LIF) is a key paracrine factor from activated PSCs acting on cancer cells. Both pharmacologic LIF blockade and genetic Lifr deletion markedly slow tumour progression and augment the efficacy of chemotherapy to prolong survival of PDAC mouse models, mainly by modulating cancer cell differentiation and epithelial-mesenchymal transition status. Moreover, in both mouse models and human PDAC, aberrant production of LIF in the pancreas is restricted to pathological conditions and correlates with PDAC pathogenesis, and changes in the levels of circulating LIF correlate well with tumour response to therapy. Collectively, these findings reveal a function of LIF in PDAC tumorigenesis, and suggest its translational potential as an attractive therapeutic target and circulating marker. Our studies underscore how a better understanding of cell-cell communication within the tumour microenvironment can suggest novel strategies for cancer therapy

The first myriapod genome sequence reveals conservative arthropod gene content and genome organisation in the centipede Strigamia maritima.

Myriapods (e.g., centipedes and millipedes) display a simple homonomous body plan relative to other arthropods. All members of the class are terrestrial, but they attained terrestriality independently of insects. Myriapoda is the only arthropod class not represented by a sequenced genome. We present an analysis of the genome of the centipede Strigamia maritima. It retains a compact genome that has undergone less gene loss and shuffling than previously sequenced arthropods, and many orthologues of genes conserved from the bilaterian ancestor that have been lost in insects. Our analysis locates many genes in conserved macro-synteny contexts, and many small-scale examples of gene clustering. We describe several examples where S. maritima shows different solutions from insects to similar problems. The insect olfactory receptor gene family is absent from S. maritima, and olfaction in air is likely effected by expansion of other receptor gene families. For some genes S. maritima has evolved paralogues to generate coding sequence diversity, where insects use alternate splicing. This is most striking for the Dscam gene, which in Drosophila generates more than 100,000 alternate splice forms, but in S. maritima is encoded by over 100 paralogues. We see an intriguing linkage between the absence of any known photosensory proteins in a blind organism and the additional absence of canonical circadian clock genes. The phylogenetic position of myriapods allows us to identify where in arthropod phylogeny several particular molecular mechanisms and traits emerged. For example, we conclude that juvenile hormone signalling evolved with the emergence of the exoskeleton in the arthropods and that RR-1 containing cuticle proteins evolved in the lineage leading to Mandibulata. We also identify when various gene expansions and losses occurred. The genome of S. maritima offers us a unique glimpse into the ancestral arthropod genome, while also displaying many adaptations to its specific life history.This work was supported by the following grants: NHGRIU54HG003273 to R.A.G; EU Marie Curie ITN #215781 “Evonet” to M.A.; a Wellcome Trust Value in People (VIP) award to C.B. and Wellcome Trust graduate studentship WT089615MA to J.E.G; Marine rhythms of Life” of the University of Vienna, an FWF (http://www.fwf.ac.at/) START award (#AY0041321) and HFSP (http://www.hfsp.org/) research grant (#RGY0082/2010) to KT-­‐R; MFPL Vienna International PostDoctoral Program for Molecular Life Sciences (funded by Austrian Ministry of Science and Research and City of Vienna, Cultural Department -­‐Science and Research to T.K; Direct Grant (4053034) of the Chinese University of Hong Kong to J.H.L.H.; NHGRI HG004164 to G.M.; Danish Research Agency (FNU), Carlsberg Foundation, and Lundbeck Foundation to C.J.P.G.; U.S. National Institutes of Health R01AI55624 to J.H.W.; Royal Society University Research fellowship to F.M.J.; P.D.E. was supported by the BBSRC via the Babraham Institute;This is the final version of the article. It first appeared from PLOS via http://dx.doi.org/10.1371/journal.pbio.100200

BART: bioinformatics array research tool

Abstract Background Microarray experiments comprise more than half of all series in the Gene Expression Omnibus (GEO). However, downloading and analyzing raw or semi-processed microarray data from GEO is not intuitive and requires manual error-prone analysis and a bioinformatics background. This is due to a lack of standardization in array platform fabrication as well as the lack of a simple interactive tool for clustering, plotting, differential expression testing, and testing for functional enrichment. Results We introduce the Bioinformatics Array Research Tool (BART), an R Shiny web application that automates the microarray download and analysis process across diverse microarray platforms. It provides an intuitive interface, automatically downloads and parses data from GEO, suggests groupings of samples for differential expression testing, performs batch effect correction, outputs quality control plots, converts probe IDs, generates full lists of differentially expressed genes, and performs functional enrichment analysis. We show that BART enables a more comprehensive analysis of a wider range of microarray datasets on GEO by comparing it to four leading online microarray analysis tools. Conclusions BART allows a scientist with no bioinformatics background to extract knowledge from their own microarray data or microarray experiments available from GEO. BART is functional on more microarray experiments and provides more comprehensive analyses than extant microarray analysis tools. BART is hosted on bart.salk.edu, includes a user tutorial, and is available for download from https://bitbucket.org/Luisa_amaral/bart

The Aging Astrocyte Transcriptome from Multiple Regions of the Mouse Brain

Summary: Aging brains undergo cognitive decline, associated with decreased neuronal synapse number and function and altered metabolism. Astrocytes regulate neuronal synapse formation and function in development and adulthood, but whether these properties change during aging, contributing to neuronal dysfunction, is unknown. We addressed this by generating aged and adult astrocyte transcriptomes from multiple mouse brain regions. These data provide a comprehensive RNA-seq database of adult and aged astrocyte gene expression, available online as a resource. We identify astrocyte genes altered by aging across brain regions and regionally unique aging changes. Aging astrocytes show minimal alteration of homeostatic and neurotransmission-regulating genes. However, aging astrocytes upregulate genes that eliminate synapses and partially resemble reactive astrocytes. We further identified heterogeneous expression of synapse-regulating genes between astrocytes from different cortical regions. We find that alterations to astrocytes in aging create an environment permissive to synapse elimination and neuronal damage, potentially contributing to aging-associated cognitive decline. : The aging brain has reduced synapse number and decreased neuronal activity, functions regulated by neighboring astrocytes. Boisvert et al. investigated if aging astrocytes are contributing to these changes and found that aged astrocytes show increased expression of genes for inflammatory and synapse elimination pathways and decreased cholesterol synthesis enzymes. Keywords: astrocyte, synapse, aging, neurodegeneratio

Complete loss of H3K9 methylation dissolves mouse heterochromatin organization

Histone H3K9 methylation (H3K9me) states define repressed chromatin in eukaryotic cells. Here the authors reveal complete loss of all H3K9me in mammalian cells through successive deletion of H3K9 methyltransferase genes that results in the dissolution of heterochromatin and the derepression of nearly all repeat families

Discovering single nucleotide variants and indels from bulk and single-cell ATAC-seq

Genetic variants and de novo mutations in regulatory regions of the genome are typically discovered by whole-genome sequencing (WGS), however WGS is expensive and most WGS reads come from non-regulatory regions. The Assay for Transposase-Accessible Chromatin (ATAC-seq) generates reads from regulatory sequences and could potentially be used as a low-cost 'capture' method for regulatory variant discovery, but its use for this purpose has not been systematically evaluated. Here we apply seven variant callers to bulk and single-cell ATAC-seq data and evaluate their ability to identify single nucleotide variants (SNVs) and insertions/deletions (indels). In addition, we develop an ensemble classifier, VarCA, which combines features from individual variant callers to predict variants. The Genome Analysis Toolkit (GATK) is the best-performing individual caller with precision/recall on a bulk ATAC test dataset of 0.92/0.97 for SNVs and 0.87/0.82 for indels within ATAC-seq peak regions with at least 10 reads. On bulk ATAC-seq reads, VarCA achieves superior performance with precision/recall of 0.99/0.95 for SNVs and 0.93/0.80 for indels. On single-cell ATAC-seq reads, VarCA attains precision/recall of 0.98/0.94 for SNVs and 0.82/0.82 for indels. In summary, ATAC-seq reads can be used to accurately discover non-coding regulatory variants in the absence of whole-genome sequencing data and our ensemble method, VarCA, has the best overall performance

The RNA-Binding Protein NONO Coordinates Hepatic Adaptation to Feeding

The mechanisms by which feeding and fasting drive rhythmic gene expression for physiological adaptation to daily rhythm in nutrient availability are not well understood. Here we show that, upon feeding, the RNA-binding protein NONO accumulates within speckle-like structures in liver cell nuclei. Combining RNA-immunoprecipitation and sequencing (RIP-seq), we find that an increased number of RNAs are bound by NONO after feeding. We further show that NONO binds and regulates the rhythmicity of genes involved in nutrient metabolism post-transcriptionally. Finally, we show that disrupted rhythmicity of NONO target genes has profound metabolic impact. Indeed, NONO-deficient mice exhibit impaired glucose tolerance and lower hepatic glycogen and lipids. Accordingly, these mice shift from glucose storage to fat oxidation, and therefore remain lean throughout adulthood. In conclusion, our study demonstrates that NONO post-transcriptionally coordinates circadian mRNA expression of metabolic genes with the feeding/fasting cycle, thereby playing a critical role in energy homeostasis

Scripps Genome ADVISER: Annotation and Distributed Variant Interpretation SERver

<div><p>Interpretation of human genomes is a major challenge. We present the Scripps Genome ADVISER (SG-ADVISER) suite, which aims to fill the gap between data generation and genome interpretation by performing holistic, in-depth, annotations and functional predictions on all variant types and effects. The SG-ADVISER suite includes a de-identification tool, a variant annotation web-server, and a user interface for inheritance and annotation-based filtration. SG-ADVISER allows users with no bioinformatics expertise to manipulate large volumes of variant data with ease – without the need to download large reference databases, install software, or use a command line interface. SG-ADVISER is freely available at genomics.scripps.edu/ADVISER.</p></div

ADVISER Class Performance.

<p>SG-ADVISER Classification performance. The Ingenuity Clinical Assessment considers variants classified as Known Pathogenic or Likely Pathogenic by Ingenuity. The default Ingenuity allele frequency threshold of 3% plus damaging predictions by SIFT and/or Polyphen were used to simulate less confident variant classification tranches in Ingenuity.</p><p>ADVISER Class Performance.</p