32 research outputs found

    The Local Edge Machine: inference of dynamic models of gene regulation

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    We present a novel approach, the Local Edge Machine, for the inference of regulatory interactions directly from time-series gene expression data. We demonstrate its performance, robustness, and scalability on in silico datasets with varying behaviors, sizes, and degrees of complexity. Moreover, we demonstrate its ability to incorporate biological prior information and make informative predictions on a well-characterized in vivo system using data from budding yeast that have been synchronized in the cell cycle. Finally, we use an atlas of transcription data in a mammalian circadian system to illustrate how the method can be used for discovery in the context of large complex networks.Department of Applied Mathematic

    α-Synuclein interacts with lipoproteins in plasma

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    Parkinson’s disease (PD) is an age-related neurodegenerative disorder characterized by dopaminergic neural cell death in the substantia nigra of the brain and α-synuclein (α-syn) accumulation in Lewy bodies. α-Syn can be detected in blood and is a potential biomarker for PD. It has been shown recently that α-syn can pass through the blood-brain barrier (BBB), but the mechanism is not yet understood. We hypothesized that α-syn could interact with lipoproteins, and in association with these particles, could pass through the BBB. Here, we show that apoE, apoJ, and apoA1, but not apoB, were co-immunocaptured along with α-syn from human blood plasma, suggesting that α-syn is associated with high density lipoproteins (HDL). This association was also supported by experiments involving western blotting of plasma fractions separated by gel filtration,which revealed that α-syn was found in fractions identified as HDL. Interestingly, we could also detect α-syn and ApoJ in the intermediate fraction between HDL and LDL, referred to as lipoprotein (a) (Lp(a)), which has an important role in cholesterol metabolism. Overall, the results provide best support for the hypothesis that α-syn interacts with HDL, and this has potential implications for transport of α-syn from the brain to peripheral blood, across the BBB

    Guidelines for Genome-Scale Analysis of Biological Rhythms

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    Genome biology approaches have made enormous contributions to our understanding of biological rhythms, particularly in identifying outputs of the clock, including RNAs, proteins, and metabolites, whose abundance oscillates throughout the day. These methods hold significant promise for future discovery, particularly when combined with computational modeling. However, genome-scale experiments are costly and laborious, yielding “big data” that are conceptually and statistically difficult to analyze. There is no obvious consensus regarding design or analysis. Here we discuss the relevant technical considerations to generate reproducible, statistically sound, and broadly useful genome-scale data. Rather than suggest a set of rigid rules, we aim to codify principles by which investigators, reviewers, and readers of the primary literature can evaluate the suitability of different experimental designs for measuring different aspects of biological rhythms. We introduce CircaInSilico, a web-based application for generating synthetic genome biology data to benchmark statistical methods for studying biological rhythms. Finally, we discuss several unmet analytical needs, including applications to clinical medicine, and suggest productive avenues to address them

    Guidelines for Genome-Scale Analysis of Biological Rhythms

    Get PDF
    Genome biology approaches have made enormous contributions to our understanding of biological rhythms, particularly in identifying outputs of the clock, including RNAs, proteins, and metabolites, whose abundance oscillates throughout the day. These methods hold significant promise for future discovery, particularly when combined with computational modeling. However, genome-scale experiments are costly and laborious, yielding ‘big data’ that is conceptually and statistically difficult to analyze. There is no obvious consensus regarding design or analysis. Here we discuss the relevant technical considerations to generate reproducible, statistically sound, and broadly useful genome scale data. Rather than suggest a set of rigid rules, we aim to codify principles by which investigators, reviewers, and readers of the primary literature can evaluate the suitability of different experimental designs for measuring different aspects of biological rhythms. We introduce CircaInSilico, a web-based application for generating synthetic genome biology data to benchmark statistical methods for studying biological rhythms. Finally, we discuss several unmet analytical needs, including applications to clinical medicine, and suggest productive avenues to address them

    PSMD11 modulates circadian clock function through PER and CRY nuclear translocation.

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    The molecular circadian clock is regulated by a transcriptional translational feedback loop. However, the post-translational control mechanisms are less understood. The NRON complex is a large ribonucleoprotein complex, consisting of a lncRNA and several proteins. Components of the complex play a distinct role in regulating protein phosphorylation, synthesis, stability, and translocation in cellular processes. This includes the NFAT and the circadian clock pathway. PSMD11 is a component of the NRON complex and a lid component of the 26S proteasome. Among the PSMD family members, PSMD11 has a more specific role in circadian clock function. Here, we used cell and biochemical approaches and characterized the role of PSMD11 in regulating the stability and nuclear translocation of circadian clock proteins. We used size exclusion chromatography to enrich the NRON complex in the cytosolic and nuclear fractions. More specifically, PSMD11 knockdown affected the abundance of PER2 and CRY2 proteins and the nuclear translocation of CRY1. This changed the relative abundance of CRY1 and CRY2 in the nucleus. Thus, this work defines the role of PSMD11 in the NRON complex regulating the nuclear translocation of circadian repressors, thereby enabling cellular circadian oscillations

    Novel COCH mutation in a family with autosomal dominant late onset sensorineural hearing impairment and tinnitus

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    This report describes a three generation family with late onset bilateral sensorineural hearing impairment (BLSNHI) and tinnitus in which a novel mutation in the COCH gene was identified after a genome-wide linkage approach. The COCH gene is one of the few genes clinically examined when investigating the etiology of autosomal dominant late onset hearing impairment. Initially mutations in the COCH gene were only reported in exons 4 and 5, coding for the LCCL protein domain. More recently, additional mutations have been identified in exon 12, the only mutations identified outside of the LCCL domain. Currently clinical genetic testing for the COCH gene primarily focuses on identifying mutations in these three exons. In this study, we identify a novel mutation in the COCH gene in exon 11, which, like the exon 12 mutations, falls within the vWFA2 protein domain. This finding reinforces the need for clinical genetic screening of the COCH gene to be expanded beyond the current limited exon screening, as there is now more evidence to support that mutations in other areas of this gene are also causative of a similar form of late onset BLSNHI. (C) 2013 Elsevier Inc. All rights reserved
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