109 research outputs found

    Maml1 acts cooperatively with Gli proteins to regulate Sonic hedgheog signaling pathway

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    Sonic hedgehog (Shh) signaling is essential for proliferation of cerebellar granule cell progenitors (GCPs) and its misregulation is linked to various disorders, including cerebellar cancer medulloblastoma. The effects of Shh pathway are mediated by the Gli family of transcription factors, which controls the expression of a number of target genes, including Gli1. Here, we identify Mastermind-like 1 (Maml1) as a novel regulator of the Shh signaling since it interacts with Gli proteins, working as a potent transcriptional coactivator. Notably, Maml1 silencing results in a significant reduction of Gli target genes expression, with a negative impact on cell growth of NIH3T3 and Patched1−/− mouse embryonic fibroblasts (MEFs), bearing a constitutively active Shh signaling. Remarkably, Shh pathway activity results severely compromised both in MEFs and GCPs deriving from Maml1−/− mice with an impairment of GCPs proliferation and cerebellum development. Therefore Maml1−/− phenotype mimics aspects of Shh pathway deficiency, suggesting an intrinsic requirement for Maml1 in cerebellum development. The present study shows a new role for Maml1 as a component of Shh signaling, which plays a crucial role in both development and tumorigenesis

    gganatogram: An R package for modular visualisation of anatograms and tissues based on ggplot2 [version 1; referees: 2 approved]

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    Displaying data onto anatomical structures is a convenient technique to quickly observe tissue related information. However, drawing tissues is a complex task that requires both expertise in anatomy and the arts. While web based applications exist for displaying gene expression on anatograms, other non-genetic disciplines lack similar tools. Moreover, web based tools often lack the modularity associated with packages in programming languages, such as R. Here I present gganatogram, an R package used to plot modular species anatograms based on a combination of the graphical grammar of ggplot2 and the publicly available anatograms from the Expression Atlas. This combination allows for quick and easy, modular, and reproducible generation of anatograms. Using only one command and a data frame with tissue name, group, colour, and value, this tool enables the user to visualise specific human and mouse tissues with desired colours, grouped by a variable, or displaying a desired value, such as gene-expression, pharmacokinetics, or bacterial load across selected tissues. I hope that this tool will be useful by the wider community in biological sciences. Community members are welcome to submit additional anatograms, which can be incorporated into the package. A stable version gganatogram has been deposited to neuroconductor, and a development version can be found on github/jespermaag/gganatogram

    Navigating in vitro bioactivity data by investigating available resources using model compounds.

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    The number of chemical compounds and associated experimental data in public databases is growing, but presently there is no simple way to access these data in a quick and synoptic manner. Instead, data are fragmented across different resources and interested parties need to invest invaluable time and effort to navigate these systems

    A systematic analysis of orphan cyclins reveals CNTD2 as a new oncogenic driver in lung cancer

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    As lung cancer has increased to the most common cause of cancer death worldwide, prognostic biomarkers and effective targeted treatments remain lacking despite advances based on patients' stratification. Multiple core cyclins, best known as drivers of cell proliferation, are commonly deregulated in lung cancer where they may serve as oncogenes. The recent expansion of the cyclin family raises the question whether new members might play oncogenic roles as well. Here, we investigated the protein levels of eight atypical cyclins in lung cancer cell lines and formalin-fixed and paraffin-embedded (FFPE) human tumors, as well as their functional role in lung cancer cells. Of the new cyclins evaluated, CNTD2 was significantly overexpressed in lung cancer compared to adjacent normal tissue, and exhibited a predominant nuclear location. CNTD2 overexpression increased lung cancer cell viability, Ki-67 intensity and clonogenicity and promoted lung cancer cell migration. Accordingly, CNTD2 enhanced tumor growth in vivo on A549 xenograft models. Finally, the analysis of gene expression data revealed a high correlation between elevated levels of CNTD2 and decreased overall survival in lung cancer patients. Our results reveal CNTD2 as a new oncogenic driver in lung cancer, suggesting value as a prognostic biomarker and therapeutic target in this disease

    Intron and gene size expansion during nervous system evolution

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    © The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in McCoy, M. J., & Fire, A. Z. Intron and gene size expansion during nervous system evolution. BMC Genomics, 21(1), (2020): 360, doi:10.1186/s12864-020-6760-4.Background The evolutionary radiation of animals was accompanied by extensive expansion of gene and genome sizes, increased isoform diversity, and complexity of regulation. Results Here we show that the longest genes are enriched for expression in neuronal tissues of diverse vertebrates and of invertebrates. Additionally, we show that neuronal gene size expansion occurred predominantly through net gains in intron size, with a positional bias toward the 5â€Č end of each gene. Conclusions We find that intron and gene size expansion is a feature of many genes whose expression is enriched in nervous systems. We speculate that unique attributes of neurons may subject neuronal genes to evolutionary forces favoring net size expansion. This process could be associated with tissue-specific constraints on gene function and/or the evolution of increasingly complex gene regulation in nervous systems.This study was supported by the following programs, grants, and fellowships: 2018 Grass Fellowship in Neuroscience (Grass Foundation), 2019 Whitman Fellowship at the Marine Biological Laboratory, and the Stanford Genomics Training Program (5T32HG000044–22; PI: M. Snyder) to MJM, and R01GM37706/R35GM130366 to AZF. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

    gganatogram: An R package for modular visualisation of anatograms and tissues based on ggplot2 [version 2; referees: 2 approved]

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    Displaying data onto anatomical structures is a convenient technique to quickly observe tissue related information. However, drawing tissues is a complex task that requires both expertise in anatomy and the arts. While web based applications exist for displaying gene expression on anatograms, other non-genetic disciplines lack similar tools. Moreover, web based tools often lack the modularity associated with packages in programming languages, such as R. Here I present gganatogram, an R package used to plot modular species anatograms based on a combination of the graphical grammar of ggplot2 and the publicly available anatograms from the Expression Atlas. This combination allows for quick and easy, modular, and reproducible generation of anatograms. Using only one command and a data frame with tissue name, group, colour, and  value, this tool enables the user to visualise specific human and mouse tissues with desired colours, grouped by a variable, or displaying a desired value, such as gene-expression, pharmacokinetics, or bacterial load across selected tissues. gganatogram consists of 5 highly annotated organisms, male/female human/mouse, and a cell anatogram. It further consists of 24 other less annotated organisms from the animal and plant kingdom. I hope that this tool will be useful by the wider community in biological sciences. Community members are welcome to submit additional anatograms, which can be incorporated into the package. A stable version gganatogram has been deposited to neuroconductor, and a development version can be found on github/jespermaag/gganatogram. An interactive shiny app of gganatogram can be found on https://jespermaag.shinyapps.io/gganatogram/, which allows for non-R users to create anatograms
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