Regulatory sites for splicing in human basal ganglia are enriched for disease-relevant information

Genome-wide association studies have generated an increasing number of common genetic variants associated with neurological and psychiatric disease risk. An improved understanding of the genetic control of gene expression in human brain is vital considering this is the likely modus operandum for many causal variants. However, human brain sampling complexities limit the explanatory power of brain-related expression quantitative trait loci (eQTL) and allele-specific expression (ASE) signals. We address this, using paired genomic and transcriptomic data from putamen and substantia nigra from 117 human brains, interrogating regulation at different RNA processing stages and uncovering novel transcripts. We identify disease-relevant regulatory loci, find that splicing eQTLs are enriched for regulatory information of neuron-specific genes, that ASEs provide cell-specific regulatory information with evidence for cellular specificity, and that incomplete annotation of the brain transcriptome limits interpretation of risk loci for neuropsychiatric disease. This resource of regulatory data is accessible through our web server, http://braineacv2.inf.um.es/

Identification of candidate Parkinson disease genes by integrating genome-wide association study, expression, and epigenetic data sets

Importance Substantial genome-wide association study (GWAS) work in Parkinson disease (PD) has led to the discovery of an increasing number of loci shown reliably to be associated with increased risk of disease. Improved understanding of the underlying genes and mechanisms at these loci will be key to understanding the pathogenesis of PD. Objective To investigate what genes and genomic processes underlie the risk of sporadic PD. Design and Setting This genetic association study used the bioinformatic tools Coloc and transcriptome-wide association study (TWAS) to integrate PD case-control GWAS data published in 2017 with expression data (from Braineac, the Genotype-Tissue Expression [GTEx], and CommonMind) and methylation data (derived from UK Parkinson brain samples) to uncover putative gene expression and splicing mechanisms associated with PD GWAS signals. Candidate genes were further characterized using cell-type specificity, weighted gene coexpression networks, and weighted protein-protein interaction networks. Main Outcomes and Measures It was hypothesized a priori that some genes underlying PD loci would alter PD risk through changes to expression, splicing, or methylation. Candidate genes are presented whose change in expression, splicing, or methylation are associated with risk of PD as well as the functional pathways and cell types in which these genes have an important role. Results Gene-level analysis of expression revealed 5 genes (WDR6 [OMIM 606031], CD38 [OMIM 107270], GPNMB [OMIM 604368], RAB29 [OMIM 603949], and TMEM163 [OMIM 618978]) that replicated using both Coloc and TWAS analyses in both the GTEx and Braineac expression data sets. A further 6 genes (ZRANB3 [OMIM 615655], PCGF3 [OMIM 617543], NEK1 [OMIM 604588], NUPL2 [NCBI 11097], GALC [OMIM 606890], and CTSB [OMIM 116810]) showed evidence of disease-associated splicing effects. Cell-type specificity analysis revealed that gene expression was overall more prevalent in glial cell types compared with neurons. The weighted gene coexpression performed on the GTEx data set showed that NUPL2 is a key gene in 3 modules implicated in catabolic processes associated with protein ubiquitination and in the ubiquitin-dependent protein catabolic process in the nucleus accumbens, caudate, and putamen. TMEM163 and ZRANB3 were both important in modules in the frontal cortex and caudate, respectively, indicating regulation of signaling and cell communication. Protein interactor analysis and simulations using random networks demonstrated that the candidate genes interact significantly more with known mendelian PD and parkinsonism proteins than would be expected by chance. Conclusions and Relevance Together, these results suggest that several candidate genes and pathways are associated with the findings observed in PD GWAS studies

Identification of genetic variants associated with Huntington's disease progression: a genome-wide association study

Background Huntington's disease is caused by a CAG repeat expansion in the huntingtin gene, HTT. Age at onset has been used as a quantitative phenotype in genetic analysis looking for Huntington's disease modifiers, but is hard to define and not always available. Therefore, we aimed to generate a novel measure of disease progression and to identify genetic markers associated with this progression measure. Methods We generated a progression score on the basis of principal component analysis of prospectively acquired longitudinal changes in motor, cognitive, and imaging measures in the 218 indivduals in the TRACK-HD cohort of Huntington's disease gene mutation carriers (data collected 2008–11). We generated a parallel progression score using data from 1773 previously genotyped participants from the European Huntington's Disease Network REGISTRY study of Huntington's disease mutation carriers (data collected 2003–13). We did a genome-wide association analyses in terms of progression for 216 TRACK-HD participants and 1773 REGISTRY participants, then a meta-analysis of these results was undertaken. Findings Longitudinal motor, cognitive, and imaging scores were correlated with each other in TRACK-HD participants, justifying use of a single, cross-domain measure of disease progression in both studies. The TRACK-HD and REGISTRY progression measures were correlated with each other (r=0·674), and with age at onset (TRACK-HD, r=0·315; REGISTRY, r=0·234). The meta-analysis of progression in TRACK-HD and REGISTRY gave a genome-wide significant signal (p=1·12 × 10−10) on chromosome 5 spanning three genes: MSH3, DHFR, and MTRNR2L2. The genes in this locus were associated with progression in TRACK-HD (MSH3 p=2·94 × 10−8 DHFR p=8·37 × 10−7 MTRNR2L2 p=2·15 × 10−9) and to a lesser extent in REGISTRY (MSH3 p=9·36 × 10−4 DHFR p=8·45 × 10−4 MTRNR2L2 p=1·20 × 10−3). The lead single nucleotide polymorphism (SNP) in TRACK-HD (rs557874766) was genome-wide significant in the meta-analysis (p=1·58 × 10−8), and encodes an aminoacid change (Pro67Ala) in MSH3. In TRACK-HD, each copy of the minor allele at this SNP was associated with a 0·4 units per year (95% CI 0·16–0·66) reduction in the rate of change of the Unified Huntington's Disease Rating Scale (UHDRS) Total Motor Score, and a reduction of 0·12 units per year (95% CI 0·06–0·18) in the rate of change of UHDRS Total Functional Capacity score. These associations remained significant after adjusting for age of onset. Interpretation The multidomain progression measure in TRACK-HD was associated with a functional variant that was genome-wide significant in our meta-analysis. The association in only 216 participants implies that the progression measure is a sensitive reflection of disease burden, that the effect size at this locus is large, or both. Knockout of Msh3 reduces somatic expansion in Huntington's disease mouse models, suggesting this mechanism as an area for future therapeutic investigation

Data of the DENV-1 strains isolated and sequenced in this study.

<p>Data of the DENV-1 strains isolated and sequenced in this study.</p

Plaque mean area of DENV-1 isolates.

<p>Plaque mean area of DENV-1 isolates.</p

Inferred spread obtained by a discrete phylogeographic analysis of DENV-1 genotype V.

<p>The KML file for visualization in Google Earth is available as a supplementary dataset (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0111017#pone.0111017.s005" target="_blank">Video S1</a>).</p

Viral RNA copies and NS1 production.

<p>Biological properties of imported (A and C) and local isolates (B and D). Viral loads are expressed as log copy/µL (A and B), points are mean values of two independent experiments. The SD are not seen in some of the points because they fall inside the symbol. NS1 production is expressed as absorbance at 450 nm/cut-off value (SR = sample ratio) (C and D). Dpi: days post-infection.</p

Bayesian skyline plot for DENV-1 genotype V.

<p>The population size of DENV-1 genotype V (Y axis) vs time in years (X axis) is shown. Ninety-percent highest probability densities are considered.</p

Location of non-synonymous changes in the polyprotein of DENV-1 strains in relation to the reference sequence FGA/89.

<p>Polar and non-polar amino acids are coded as follows: hydrophobic in pink (Ala, Phe, Ile, Leu, Met, Pro, Val, Trp); polar but uncharged in light blue (Cys, Gly, Asn, Gln, Ser, Thr, Tyr); negatively charged in gray (Asp, Glu); and positively charged in red (His, Lys, Arg).</p

Two recombinant human interferon-beta 1a pharmaceutical preparations produce a similar transcriptional response determined using whole genome microarray analysis

Objectives: Recombinant human interferon-beta (IFN-b) is a well-established treatment for multiple sclerosis (MS). The regulatory process for marketing authorization of biosimilars is currently under debate in certain countries. In the EU, EMEA has clearly defined the process including overarching and product-specific guidelines, which includes clinical testing. Biosimilarity needs to be based on comparability criteria, including at least molecular characterization, biological activity relevant for the therapeutic effect and relative bioavailability (“bioequivalence”). In the case of such complex diseases as MS, where the effect of treatment is not so directly measurable, in vitro tools can provide additional data to support comparability. Genomic microarrays assays might be useful to compare multisource biopharmaceuticals. The aim of the present study was to compare the pharmacodynamic genomic effects (in terms of transcriptional regulation) of two recombinant human IFN-β1a preparations on lymphocytes of multiple sclerosis patients using a whole genome microarray assay. Methods: We performed an ex vivo whole genome expression profiling of the effect of two preparations of IFN-β1a on non-adherent mononuclears from five relapsing-remitting MS patients analyzing microarrays (CodeLink™ Human Whole Genome). Patients blood was drawn, PBMCs isolated and cultured in three different conditions: culture medium (control), 1,000 U/ml of IFN-β1a (BLA- (STOFERON™, Bio Sidus) and 1,000 U/ml of IFN-β1a (REBIF™, Serono) RNA was purified from non-adherent cells (mostly lymphocytes), amplified and hybridized. Raw data were generated by CodeLink™ proprietary software. Data normalization, quality control and analysis of differential gene expression between treatments were done using linear model for microarray data. Functional annotation analysis of IFN-β1a MS treatment transcription was done using DAVID. Results: Out of the approximately 45,000 human sequences examined, no evidence of differential regulation was found when both treatments were compared (minimum adjusted p-value > 0.999). The IFN-β1a effect differentially regulated the expression of 868 genes. The expression of standard markers such as GTP cyclohidrolase, MxA, and OAS isoenzymes A and B changed as a consequence of the action of IFN-β1a. Conclusions: This exhaustive and highly sensitive assay did not show differences in the genomic expression profile of these two products under the assayed experimental conditions. These results suggest that this technology might be useful for the initial comparison of biosimilars, being part of a comprehensive comparability program that includes clinical testing.Fil: Sterin Prync, Aída Edith. Bio Sidus S.A.; ArgentinaFil: Yankilevich, Patricio. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Bio Sidus S.A.; ArgentinaFil: Barrero, Paola Roxana. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Gobierno de la Ciudad de Buenos Aires. Hospital General de Niños "Ricardo Gutiérrez"; ArgentinaFil: Bello, R.. Bio Sidus S.A.; ArgentinaFil: Marangunich, L.. Bio Sidus S.A.; ArgentinaFil: Vidal, A.. Bio Sidus S.A.; ArgentinaFil: Criscuolo, M.. Bio Sidus S.A.; ArgentinaFil: Benasayag, L.. Centro Neurológico Integral ; ArgentinaFil: Famulari, A. L.. Fundación Argentina contra las Enfermedades Neurológicas del Envejecimiento; ArgentinaFil: Domínguez, R. O.. Fundación Argentina contra las Enfermedades Neurológicas del Envejecimiento; ArgentinaFil: Kauffman, Marcelo Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Biología Celular y Neurociencia "Prof. Eduardo de Robertis". Universidad de Buenos Aires. Facultad de Medicina. Instituto de Biología Celular y Neurociencia; Argentina. Bio Sidus S.A.; ArgentinaFil: Diez, Roberto Alejandro. Bio Sidus S.A.; Argentin