327 research outputs found

    Fluorescence Intensity Normalisation: Correcting for Time Effects in Large-Scale Flow Cytometric Analysis

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    A next step to interpret the findings generated by genome-wide association studies is to associate molecular quantitative traits with disease-associated alleles. To this end, researchers are linking disease risk alleles with gene expression quantitative trait loci (eQTL). However, gene expression at the mRNA level is only an intermediate trait and flow cytometry analysis can provide more downstream and biologically valuable protein level information in multiple cell subsets simultaneously using freshly obtained samples. Because the throughput of flow cytometry is currently limited, experiments may need to span over several weeks or months to obtain a sufficient sample size to demonstrate genetic association. Therefore, normalisation methods are needed to control for technical variability and compare flow cytometry data over an extended period of time. We show how the use of normalising fluorospheres improves the repeatability of a cell surface CD25-APC mean fluorescence intensity phenotype on CD4+ memory T cells. We investigate two types of normalising beads: broad spectrum and spectrum matched. Lastly, we propose two alternative normalisation procedures that are usable in the absence of normalising beads

    Regulation of otic neurosensory specification by Notch and Wnt signalling: insights from RNA-seq screenings in the embryonic chicken inner ear

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    The Notch and Wnt signalling pathways play key roles in the formation of inner ear sensory organs, but little is known about their transcriptional effectors and targets in this context. Here, we perturbed Notch and Wnt activities in the embryonic chicken otic vesicle using pharmacological treatment or in ovo electroporation of plasmid DNA, and used RNA-Seq to analyse the resulting changes in gene expression. Compared to pharmacological treatments, in ovo electroporation changed the expression of fewer genes, a likely consequence of the variability and mosaicism of transfection. The pharmacological inhibition of Notch activity induced a rapid change in the expression of known effectors of this pathway and genes associated with neurogenesis, consistent with a switch towards an otic neurosensory fate. The Wnt datasets contained many genes associated with a neurosensory biological function, confirming the importance of this pathway for neurosensory specification in the otocyst. Finally, the results of a preliminary gain-of-function screening of selected transcription factors and Wnt signalling components suggest that the endogenous programs of otic neurosensory specification are very robust, and in general unaffected by the overexpression of a single factor. Altogether this work provides new insights into the effectors and candidate targets of the Notch and Wnt pathways in the early developing inner ear and could serve as a useful reference for future functional genomics experiments in the embryonic avian inner ear

    Bayesian test for colocalisation between pairs of genetic association studies using summary statistics.

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    Genetic association studies, in particular the genome-wide association study (GWAS) design, have provided a wealth of novel insights into the aetiology of a wide range of human diseases and traits, in particular cardiovascular diseases and lipid biomarkers. The next challenge consists of understanding the molecular basis of these associations. The integration of multiple association datasets, including gene expression datasets, can contribute to this goal. We have developed a novel statistical methodology to assess whether two association signals are consistent with a shared causal variant. An application is the integration of disease scans with expression quantitative trait locus (eQTL) studies, but any pair of GWAS datasets can be integrated in this framework. We demonstrate the value of the approach by re-analysing a gene expression dataset in 966 liver samples with a published meta-analysis of lipid traits including >100,000 individuals of European ancestry. Combining all lipid biomarkers, our re-analysis supported 26 out of 38 reported colocalisation results with eQTLs and identified 14 new colocalisation results, hence highlighting the value of a formal statistical test. In three cases of reported eQTL-lipid pairs (SYPL2, IFT172, TBKBP1) for which our analysis suggests that the eQTL pattern is not consistent with the lipid association, we identify alternative colocalisation results with SORT1, GCKR, and KPNB1, indicating that these genes are more likely to be causal in these genomic intervals. A key feature of the method is the ability to derive the output statistics from single SNP summary statistics, hence making it possible to perform systematic meta-analysis type comparisons across multiple GWAS datasets (implemented online at http://coloc.cs.ucl.ac.uk/coloc/). Our methodology provides information about candidate causal genes in associated intervals and has direct implications for the understanding of complex diseases as well as the design of drugs to target disease pathways

    A Method to Address Differential Bias in Genotyping in Large-Scale Association Studies

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    In a previous paper we have shown that, when DNA samples for cases and controls are prepared in different laboratories prior to high-throughput genotyping, scoring inaccuracies can lead to differential misclassification and, consequently, to increased false-positive rates. Different DNA sourcing is often unavoidable in large-scale disease association studies of multiple case and control sets. Here, we describe methodological improvements to minimise such biases. These fall into two categories: improvements to the basic clustering methods for identifying genotypes from fluorescence intensities, and use of “fuzzy” calls in association tests in order to make appropriate allowance for call uncertainty. We find that the main improvement is a modification of the calling algorithm that links the clustering of cases and controls while allowing for different DNA sourcing. We also find that, in the presence of different DNA sourcing, biases associated with missing data can increase the false-positive rate. Therefore, we propose the use of “fuzzy” calls to deal with uncertain genotypes that would otherwise be labeled as missing

    RNA-Seq of Huntington's disease patient myeloid cells reveals innate transcriptional dysregulation associated with proinflammatory pathway activation

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    Innate immune activation beyond the central nervous system is emerging as a vital component of the pathogenesis of neurodegeneration. Huntington’s disease (HD) is a fatal neurodegenerative disorder caused by a CAG repeat expansion in the huntingtin gene. The systemic innate immune system is thought to act as a modifier of disease progression; however, the molecular mechanisms remain only partially understood. Here we use RNA-sequencing to perform whole transcriptome analysis of primary monocytes from thirty manifest HD patients and thirty-three control subjects, cultured with and without a proinflammatory stimulus. In contrast with previous studies that have required stimulation to elicit phenotypic abnormalities, we demonstrate significant transcriptional differences in HD monocytes in their basal, unstimulated state. This includes previously undetected increased resting expression of genes encoding numerous proinflammatory cytokines, such as IL6. Further pathway analysis revealed widespread resting enrichment of proinflammatory functional gene sets, while upstream regulator analysis coupled with Western blotting suggests that abnormal basal activation of the NFOEB pathway plays a key role in mediating these transcriptional changes. That HD myeloid cells have a proinflammatory phenotype in the absence of stimulation is consistent with a priming effect of mutant huntingtin, whereby basal dysfunction leads to an exaggerated inflammatory response once a stimulus is encountered. These data advance our understanding of mutant huntingtin pathogenesis, establish resting myeloid cells as a key source of HD immune dysfunction, and further demonstrate the importance of systemic immunity in the potential treatment of HD and the wider study of neurodegeneration

    CHiCAGO: robust detection of DNA looping interactions in Capture Hi-C data.

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    Capture Hi-C (CHi-C) is a method for profiling chromosomal interactions involving targeted regions of interest, such as gene promoters, globally and at high resolution. Signal detection in CHi-C data involves a number of statistical challenges that are not observed when using other Hi-C-like techniques. We present a background model and algorithms for normalisation and multiple testing that are specifically adapted to CHi-C experiments. We implement these procedures in CHiCAGO ( http://regulatorygenomicsgroup.org/chicago ), an open-source package for robust interaction detection in CHi-C. We validate CHiCAGO by showing that promoter-interacting regions detected with this method are enriched for regulatory features and disease-associated SNPs

    Statistical independence of the colocalized association signals for type 1 diabetes and RPS26 gene expression on chromosome 12q13

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    Following the recent success of genome-wide association studies in uncovering disease-associated genetic variants, the next challenge is to understand how these variants affect downstream pathways. The most proximal trait to a disease-associated variant, most commonly a single nucleotide polymorphism (SNP), is differential gene expression due to the cis effect of SNP alleles on transcription, translation, and/or splicing gene expression quantitative trait loci (eQTL). Several genome-wide SNP–gene expression association studies have already provided convincing evidence of widespread association of eQTLs. As a consequence, some eQTL associations are found in the same genomic region as a disease variant, either as a coincidence or a causal relationship. Cis-regulation of RPS26 gene expression and a type 1 diabetes (T1D) susceptibility locus have been colocalized to the 12q13 genomic region. A recent study has also suggested RPS26 as the most likely susceptibility gene for T1D in this genomic region. However, it is still not clear whether this colocalization is the result of chance alone or if RPS26 expression is directly correlated with T1D susceptibility, and therefore, potentially causal. Here, we derive and apply a statistical test of this hypothesis. We conclude that RPS26 expression is unlikely to be the molecular trait responsible for T1D susceptibility at this locus, at least not in a direct, linear connection

    Deficiency of the zinc finger protein ZFP106 causes motor and sensory neurodegeneration

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    Acknowledgements We are indebted to Jim Humphries, JennyCorrigan, LizDarley, Elizabeth Joynson, Natalie Walters, Sara Wells and the whole necropsy, histology, genotyping and MLC ward 6 teams at MRC Harwell for excellent technical assistance. We thank the staff of the WTSI Illumina Bespoke Team for the RNA-seq data, the Sanger Mouse Genetics Project for the initial mouse characterization and Dr David Adams for critical reading of the manuscript. We also thank KOMP for the mouse embryonic stem cells carrying the knockout first promoter-less allele (tm1a(KOMP)Wtsi) within Zfp016. Conflict of Interest statement. None declared. Funding This work was funded by the UK Medical Research Council (MRC) to A.A.-A. and a Motor Neurone Disease Association (MNDA) project grant to A.A.-A. and EMCF. D.L.H.B. is a Wellcome Trust Senior Clinical Scientist Fellow and P.F. is a MRC/MNDA Lady Edith Wolfson Clinician Scientist Fellow. Funding to pay the Open Access publication charges for this article was provided by the MRC grant number: MC_UP_A390_1106.Peer reviewedPublisher PD

    A Transcriptomic Signature of the Hypothalamic Response to Fasting and BDNF Deficiency in Prader-Willi Syndrome.

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    Transcriptional analysis of brain tissue from people with molecularly defined causes of obesity may highlight disease mechanisms and therapeutic targets. We performed RNA sequencing of hypothalamus from individuals with Prader-Willi syndrome (PWS), a genetic obesity syndrome characterized by severe hyperphagia. We found that upregulated genes overlap with the transcriptome of mouse Agrp neurons that signal hunger, while downregulated genes overlap with the expression profile of Pomc neurons activated by feeding. Downregulated genes are expressed mainly in neuronal cells and contribute to neurogenesis, neurotransmitter release, and synaptic plasticity, while upregulated, predominantly microglial genes are involved in inflammatory responses. This transcriptional signature may be mediated by reduced brain-derived neurotrophic factor expression. Additionally, we implicate disruption of alternative splicing as a potential molecular mechanism underlying neuronal dysfunction in PWS. Transcriptomic analysis of the human hypothalamus may identify neural mechanisms involved in energy homeostasis and potential therapeutic targets for weight loss
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