36 research outputs found

    Altered tumor formation and evolutionary selection of genetic variants in the human MDM4 oncogene

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    A large body of evidence strongly suggests that the p53 tumor suppressor pathway is central in reducing cancer frequency in vertebrates. The protein product of the haploinsufficient mouse double minute 2 (MDM2) oncogene binds to and inhibits the p53 protein. Recent studies of human genetic variants in p53 and MDM2 have shown that single nucleotide polymorphisms (SNPs) can affect p53 signaling, confer cancer risk, and suggest that the pathway is under evolutionary selective pressure (1–4). In this report, we analyze the haplotype structure of MDM4, a structural homolog of MDM2, in several different human populations. Unusual patterns of linkage disequilibrium (LD) in the haplotype distribution of MDM4 indicate the presence of candidate SNPs that may also modify the efficacy of the p53 pathway. Association studies in 5 different patient populations reveal that these SNPs in MDM4 confer an increased risk for, or early onset of, human breast and ovarian cancers in Ashkenazi Jewish and European cohorts, respectively. This report not only implicates MDM4 as a key regulator of tumorigenesis in the human breast and ovary, but also exploits for the first time evolutionary driven linkage disequilibrium as a means to select SNPs of p53 pathway genes that might be clinically relevant

    Single-cell RNA transcriptome landscape of hepatocytes and non-parenchymal cells in healthy and NAFLD mouse liver

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    Nonalcoholic fatty liver disease (NAFLD) is a global health-care problem with limited therapeutic options. To obtain a cellular resolution of pathogenesis, 82,168 single-cell transcriptomes (scRNA-seq) across different NAFLD stages were profiled, identifying hepatocytes and 12 other non-parenchymal cell (NPC) types. scRNA-seq revealed insights into the cellular and molecular mechanisms of the disease. We discovered a dual role for hepatic stellate cells in gene expression regulation and in the potential to trans-differentiate into myofibroblasts. We uncovered distinct expression profiles of Kupffer cells versus monocyte-derived macrophages during NAFLD progression. Kupffer cells showed stronger immune responses, while monocyte-derived macrophages demonstrated a capability for differentiation. Three chimeric NPCs were identified including endothelial-chimeric stellate cells, hepatocyte-chimeric endothelial cells, and endothelial-chimeric Kupffer cells. Our work identified unanticipated aspects of mouse with NAFLD at the single-cell level and advanced the understanding of cellular heterogeneity in NAFLD livers

    Fine-scale detection of population-specific linkage disequilibrium using haplotype entropy in the human genome

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    <p>Abstract</p> <p>Background</p> <p>The creation of a coherent genomic map of recent selection is one of the greatest challenges towards a better understanding of human evolution and the identification of functional genetic variants. Several methods have been proposed to detect linkage disequilibrium (LD), which is indicative of natural selection, from genome-wide profiles of common genetic variations but are designed for large regions.</p> <p>Results</p> <p>To find population-specific LD within small regions, we have devised an entropy-based method that utilizes differences in haplotype frequency between populations. The method has the advantages of incorporating multilocus association, conciliation with low allele frequencies, and independence from allele polarity, which are ideal for short haplotype analysis. The comparison of HapMap SNPs data from African and Caucasian populations with a median resolution size of ~23 kb gave us novel candidates as well as known selection targets. Enrichment analysis for the yielded genes showed associations with diverse diseases such as cardiovascular, immunological, neurological, and skeletal and muscular diseases. A possible scenario for a selective force is discussed. In addition, we have developed a web interface (ENIGMA, available at <url>http://gibk21.bse.kyutech.ac.jp/ENIGMA/index.html</url>), which allows researchers to query their regions of interest for population-specific LD.</p> <p>Conclusion</p> <p>The haplotype entropy method is powerful for detecting population-specific LD embedded in short regions and should contribute to further studies aiming to decipher the evolutionary histories of modern humans.</p

    Butyrophilin-like 2 regulates site-specific adaptations of intestinal γδ intraepithelial lymphocytes

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    Tissue-resident γδ intraepithelial lymphocytes (IELs) orchestrate innate and adaptive immune responses to maintain intestinal epithelial barrier integrity. Epithelia-specific butyrophilin-like (Btnl) molecules induce perinatal development of distinct Vγ TCR+ IELs, however, the mechanisms that control γδ IEL maintenance within discrete intestinal segments are unclear. Here, we show that Btnl2 suppressed homeostatic proliferation of γδ IELs preferentially in the ileum. High throughput transcriptomic characterization of site-specific Btnl2-KO γδ IELs reveals that Btnl2 regulated the antimicrobial response module of ileal γδ IELs. Btnl2 deficiency shapes the TCR specificities and TCRγ/δ repertoire diversity of ileal γδ IELs. During DSS-induced colitis, Btnl2-KO mice exhibit increased inflammation and delayed mucosal repair in the colon. Collectively, these data suggest that Btnl2 fine-tunes γδ IEL frequencies and TCR specificities in response to site-specific homeostatic and inflammatory cues. Hence, Btnl-mediated targeting of γδ IEL development and maintenance may help dissect their immunological functions in intestinal diseases with segment-specific manifestations

    A Potential Role for Shed Soluble Major Histocompatibility Class I Molecules as Modulators of Neurite Outgrowth

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    The neurobiological activities of classical major histocompatibility class I (MHCI) molecules are just beginning to be explored. To further examine MHCI's actions during the formation of neuronal connections, we cultured embryonic mouse retina explants a short distance from wildtype thalamic explants, or thalami from transgenic mice (termed “NSE-Db”) whose neurons express higher levels of MHCI. While retina neurites extended to form connections with wildtype thalami, we were surprised to find that retina neurite outgrowth was very stunted in regions proximal to NSE-Db thalamic explants, suggesting that a diffusible factor from these thalami inhibited retina neurite outgrowth. It has been long known that MHCI-expressing cells release soluble forms of MHCI (sMHCI) due to the shedding of intact MHCI molecules, as well as the alternative exon splicing of its heavy chain or the action proteases which cleave off it's transmembrane anchor. We show that the diffusible inhibitory factor from the NSE-Db thalami is sMHCI. We also show that COS cells programmed to express murine MHCI release sMHCI that inhibits neurite outgrowth from nearby neurons in vitro. The neuroinhibitory effect of sMHCI could be blocked by lowering cAMP levels, suggesting that the neuronal MHCI receptor's signaling mechanism involves a cyclic nucleotide-dependent pathway. Our results suggest that MHCI may not only have neurobiological activity in its membrane-bound form, it may also influence local neurons as a soluble molecule. We discuss the involvement of complement proteins in generating sMHCI and new theoretical models of MHCI's biological activities in the nervous system

    Pan-cancer analysis of whole genomes

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    Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe

    Noise regularization removes correlation artifacts in single-cell RNA-seq data preprocessing

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    In this study, we benchmarked five representative single-cell RNA-sequencing data-preprocessing methods with a focus on their influence in inferring gene-gene expression correlations. We found that substantial correlation artifacts have been introduced during the preprocessing steps due to data oversmoothing, raising the issue that correlation computed from these preprocessed data may not be reliable and should be treated with caution. We then proposed a noise-regularization method to penalize the oversmoothed data, which can effectively eliminate the artifacts while retaining the majority of the true correlations. The regularized correlations can be further applied to construct gene-gene correlation networks, which is helpful for obtaining mechanistic insights into the complex biological systems
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