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Sökning: WFRF:(Forrest Alistair R R)

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1.
  • Horie, Masafumi, et al. (författare)
  • Integrative CAGE and DNA Methylation Profiling Identify Epigenetically Regulated Genes in NSCLC
  • 2017
  • Ingår i: Molecular Cancer Research. - : AMER ASSOC CANCER RESEARCH. - 1541-7786 .- 1557-3125. ; 15:10, s. 1354-1365
  • Tidskriftsartikel (refereegranskat)abstract
    • Lung cancer is the leading cause of cancer-related deaths worldwide. The majority of cancer driver mutations have been identified; however, relevant epigenetic regulation involved in tumorigenesis has only been fragmentarily analyzed. Epigenetically regulated genes have a great theranostic potential, especially in tumors with no apparent driver mutations. Here, epigenetically regulated genes were identified in lung cancer by an integrative analysis of promoter-level expression profiles from Cap Analysis of Gene Expression (CAGE) of 16 nonsmall cell lung cancer (NSCLC) cell lines and 16 normal lung primary cell specimens with DNA methylation data of 69 NSCLC cell lines and 6 normal lung epithelial cells. A core set of 49 coding genes and 10 long noncoding RNAs (lncRNA), which are upregulated in NSCLC cell lines due to promoter hypomethylation, was uncovered. Twenty-two epigenetically regulated genes were validated (upregulated genes with hypomethylated promoters) in the adenocarcinoma and squamous cell cancer subtypes of lung cancer using The Cancer Genome Atlas data. Furthermore, it was demonstrated that multiple copies of the REP522 DNA repeat family are prominently upregulated due to hypomethylation in NSCLC cell lines, which leads to cancer-specific expression of lncRNAs, such as RP1-90G24.10, AL022344.4, and PCAT7. Finally, Myeloma Overexpressed (MYEOV) was identified as the most promising candidate. Functional studies demonstrated that MYEOV promotes cell proliferation, survival, and invasion. Moreover, high MYEOV expression levels were associated with poor prognosis. (C) 2017 AACR.
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2.
  • Horie, Masafumi, et al. (författare)
  • Transcriptome analysis of periodontitis-associated fibroblasts by CAGE sequencing identified DLX5 and RUNX2 long variant as novel regulators involved in periodontitis
  • 2016
  • Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 6
  • Tidskriftsartikel (refereegranskat)abstract
    • Periodontitis is affecting over half of the adult population, and represents a major public health problem. Previously, we isolated a subset of gingival fibroblasts (GFs) from periodontitis patients, designated as periodontitis-associated fibroblasts (PAFs), which were highly capable of collagen degradation. To elucidate their molecular profiles, GFs isolated form healthy and periodontitis-affected gingival tissues were analyzed by CAGE-seq and integrated with the FANTOM5 atlas. GFs from healthy gingival tissues displayed distinctive patterns of CAGE profiles as compared to fibroblasts from other organ sites and characterized by specific expression of developmentally important transcription factors such as BARX1, PAX9, LHX8, and DLX5. In addition, a novel long non-coding RNA associated with LHX8 was described. Furthermore, we identified DLX5 regulating expression of the long variant of RUNX2 transcript, which was specifically active in GFs but not in their periodontitis-affected counterparts. Knockdown of these factors in GFs resulted in altered expression of extracellular matrix (ECM) components. These results indicate activation of DLX5 and RUNX2 via its distal promoter represents a unique feature of GFs, and is important for ECM regulation. Down-regulation of these transcription factors in PAFs could be associated with their property to degrade collagen, which may impact on the process of periodontitis.
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3.
  • Hurst, Laurence D., et al. (författare)
  • A simple metric of promoter architecture robustly predicts expression breadth of human genes suggesting that most transcription factors are positive regulators
  • 2014
  • Ingår i: Genome Biology. - : Springer Science and Business Media LLC. - 1465-6906 .- 1474-760X. ; 15:7, s. 413-
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Conventional wisdom holds that, owing to the dominance of features such as chromatin level control, the expression of a gene cannot be readily predicted from knowledge of promoter architecture. This is reflected, for example, in a weak or absent correlation between promoter divergence and expression divergence between paralogs. However, an inability to predict may reflect an inability to accurately measure or employment of the wrong parameters. Here we address this issue through integration of two exceptional resources: ENCODE data on transcription factor binding and the FANTOM5 high-resolution expression atlas. Results: Consistent with the notion that in eukaryotes most transcription factors are activating, the number of transcription factors binding a promoter is a strong predictor of expression breadth. In addition, evolutionarily young duplicates have fewer transcription factor binders and narrower expression. Nonetheless, we find several binders and cooperative sets that are disproportionately associated with broad expression, indicating that models more complex than simple correlations should hold more predictive power. Indeed, a machine learning approach improves fit to the data compared with a simple correlation. Machine learning could at best moderately predict tissue of expression of tissue specific genes. Conclusions: We find robust evidence that some expression parameters and paralog expression divergence are strongly predictable with knowledge of transcription factor binding repertoire. While some cooperative complexes can be identified, consistent with the notion that most eukaryotic transcription factors are activating, a simple predictor, the number of binding transcription factors found on a promoter, is a robust predictor of expression breadth.
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4.
  • Hurst, Laurence D., et al. (författare)
  • The Constrained Maximal Expression Level Owing to Haploidy Shapes Gene Content on the Mammalian X Chromosome
  • 2015
  • Ingår i: PLoS biology. - : Public Library of Science (PLoS). - 1544-9173 .- 1545-7885. ; 13:12
  • Tidskriftsartikel (refereegranskat)abstract
    • X chromosomes are unusual in many regards, not least of which is their nonrandom gene content. The causes of this bias are commonly discussed in the context of sexual antagonism and the avoidance of activity in the male germline. Here, we examine the notion that, at least in some taxa, functionally biased gene content may more profoundly be shaped by limits imposed on gene expression owing to haploid expression of the X chromosome. Notably, if the X, as in primates, is transcribed at rates comparable to the ancestral rate (per promoter) prior to the X chromosome formation, then the X is not a tolerable environment for genes with very high maximal net levels of expression, owing to transcriptional traffic jams. We test this hypothesis using The Encyclopedia of DNA Elements (ENCODE) and data from the Functional Annotation of the Mammalian Genome (FANTOM5) project. As predicted, the maximal expression of human X-linked genes is much lower than that of genes on autosomes: on average, maximal expression is three times lower on the X chromosome than on autosomes. Similarly, autosome-to-X retroposition events are associated with lower maximal expression of retrogenes on the X than seen for X-to-autosome retrogenes on autosomes. Also as expected, X-linked genes have a lesser degree of increase in gene expression than autosomal ones (compared to the human/Chimpanzee common ancestor) if highly expressed, but not if lowly expressed. The traffic jam model also explains the known lower breadth of expression for genes on the X (and the Z of birds), as genes with broad expression are, on average, those with high maximal expression. As then further predicted, highly expressed tissue-specific genes are also rare on the X and broadly expressed genes on the X tend to be lowly expressed, both indicating that the trend is shaped by the maximal expression level not the breadth of expression per se. Importantly, a limit to the maximal expression level explains biased tissue of expression profiles of X-linked genes. Tissues whose tissue-specific genes are very highly expressed (e.g., secretory tissues, tissues abundant in structural proteins) are also tissues in which gene expression is relatively rare on the X chromosome. These trends cannot be fully accounted for in terms of alternative models of biased expression. In conclusion, the notion that it is hard for genes on the Therian X to be highly expressed, owing to transcriptional traffic jams, provides a simple yet robustly supported rationale of many peculiar features of X's gene content, gene expression, and evolution.
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5.
  • Ravasi, Timothy, et al. (författare)
  • An Atlas of Combinatorial Transcriptional Regulation in Mouse and Man
  • 2010
  • Ingår i: CELL. - : Elsevier BV. - 0092-8674 .- 1097-4172. ; 140:5, s. 744-752
  • Tidskriftsartikel (refereegranskat)abstract
    • Combinatorial interactions among transcription factors are critical to directing tissue-specific gene expression. To build a global atlas of these combinations, we have screened for physical interactions among the majority of human and mouse DNA-binding transcription factors (TFs). The complete networks contain 762 human and 877 mouse interactions. Analysis of the networks reveals that highly connected TFs are broadly expressed across tissues, and that roughly half of the measured interactions are conserved between mouse and human. The data highlight the importance of TF combinations for determining cell fate, and they lead to the identification of a SMAD3/FLI1 complex expressed during development of immunity. The availability of large TF combinatorial networks in both human and mouse will provide many opportunities to study gene regulation, tissue differentiation, and mammalian evolution.
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6.
  • Yu, Nancy Yiu-Lin, et al. (författare)
  • Complementing tissue characterization by integrating transcriptome profiling from the Human Protein Atlas and from the FANTOM5 consortium
  • 2015
  • Ingår i: Nucleic Acids Research. - : Oxford University Press (OUP). - 0305-1048 .- 1362-4962. ; 43:14, s. 6787-6798
  • Tidskriftsartikel (refereegranskat)abstract
    • Understanding the normal state of human tissue transcriptome profiles is essential for recognizing tissue disease states and identifying disease markers. Recently, the Human Protein Atlas and the FANTOM5 consortium have each published extensive transcriptome data for human samples using Illumina-sequenced RNA-Seq and Heliscope-sequenced CAGE. Here, we report on the first large-scale complex tissue transcriptome comparison between full-length versus 5'-capped mRNA sequencing data. Overall gene expression correlation was high between the 22 corresponding tissues analyzed (R > 0.8). For genes ubiquitously expressed across all tissues, the two data sets showed high genome-wide correlation (91% agreement), with differences observed for a small number of individual genes indicating the need to update their gene models. Among the identified single-tissue enriched genes, up to 75% showed consensus of 7-fold enrichment in the same tissue in both methods, while another 17% exhibited multiple tissue enrichment and/or high expression variety in the other data set, likely dependent on the cell type proportions included in each tissue sample. Our results show that RNA-Seq and CAGE tissue transcriptome data sets are highly complementary for improving gene model annotations and highlight biological complexities within tissue transcriptomes. Furthermore, integration with image-based protein expression data is highly advantageous for understanding expression specificities for many genes.
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  • Resultat 1-6 av 6

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