Search

Search Results

3 results found. Results per page: [ 20 ][ 40 ][ 60 ][ 80 ][ 100 ][ 200 ][ 300 ]

Sort by: [ Publication Date ][ Score ]

Year of publication: [ 2025 ][ 2024 ][ 2023 ][ 2022 ][ 2021 ][ 2020 ][ 2019 ][ 2018 ][ 2017 ][ 2016 ][ 2015 ][ 2014 ][ 2013 ][ 2012 ][ 2011 ][ 2010 ][ 2009 ][ Any ]

Direction: [ Desc ][ Asc ]

• Research Paper Volume 9, Issue 3 pp 803-822

  Age-associated chromatin relaxation is enhanced in Huntington’s disease mice

  Relevance score: 6.231915

  Myungsun Park, Byungkuk Min, Kyuheum Jeon, Sunwha Cho, Jung Sun Park, Jisun Kim, Jeha Jeon, Jinhoi Song, Seokho Kim, Sangkyun Jeong, Hyemyung Seo, Yong-Kook Kang

  Keywords: aging, Huntington’s disease, targeted NGS, epigenetic, chromatin accessibility, Huntingtin (HTT)

  Published in Aging on March 12, 2017

  Show abstract
  Hide abstract

  Expansion of polyglutamine stretch in the huntingtin (HTT) protein is a major cause of Huntington’s disease (HD). The polyglutamine part in HTT interacts with various proteins implicated in epigenetic regulation of genes, suggesting that mutant HTT may disturb the integrity of the epigenetic system. Here, we used a PCRseq-based method to examine expression profile of 395 exonic segments from 260 “epi-driver” genes in splenic T lymphocytes from aged HD mice. We identified 67 exonic segments differentially expressed between young and aged HD mice, most of them upregulated in the aged. Polycomb-repressive complex (PRC)-regulated genes (PRGs) were markedly upregulated in aged HD mice, consistent with downregulation of PRC genes. Epi-driver gene categories of lysine-methylation, lysine-demethylation, arginine-methylation, and PRG showed differential age-associated changes between HD and control. Analyzing the pattern of change in epi-driver gene expressions hinted at an enhanced shift in HD chromatin to a more accessible state with age, which was experimentally demonstrated by DNase-I-hypersensitivity sequencing showing increased chromatin accessibility in HD cells compared to control. We suggest the global change can potentially relieve chromatin-induced repression of many genes, and the unintended expressions of some detrimental proteins could alter T cell function to a greater degree in aged HD mice.

  

  Analysis of gene expression in splenic T cells from mouse models of Huntington’s disease (HD). (A) Illustration of spiking-in neighbor genome PCR (SiNG-PCR) sequencing. (B) Distribution of relative counts of target-gene amplicons in young and aged HD mice. The ratio (M/R) of cDNA counts relative to rat spike-in counts was calculated to measure the expression level of each target amplicon. (C) Principal component analysis (PCA). Both young and aged sample groups are marked using colored circles. (D) Heatmap illustrating Pearson correlation between young and aged group samples. (E) Scatter plot (r = 0.9). Those of amplicons whose negligible expressions in the young group are markedly enhanced in the aged group are circled.

  
  
  

  

  Differentially expressed target sequences (DETSs) in young and aged mouse models of Huntington’s disease (HD). (A) Heatmap of amplicon levels. The heatmap is arbitrarily divided into upper and lower areas, with the former containing highly expressed amplicons from the aged samples. (B) Comparison of DETSs in different functional categories between wild-type and HD samples. The number of DETSs in each category is indicated on the bar. DNA meth, DNA methylation; K-(de)meth, lysine methylation and demethylation; PRC & PRG, Polycomb group proteins and PCR-regulated genes; Deacet, histone deacetylation; Ubiq, ubiquitination. (C) Expression levels of senescence-category DETSs commonly detected in wild-type and HD samples. Error bars, standard deviation.

  
  
  

  

  Increased expression of Polycomb repressive complex (PRC)-regulated genes (PRG) in aged mouse models of Huntington’s disease (HD). (A) The proportion of amplicons in each category that belong to the upper (red) and lower (black) clusters in the heat map shown in Figure 2A. The upper cluster amplicons represent 26% of the total amplicons as indicated by dotted line (red). TSG, tumor suppressor genes. For other abbreviations, refer to the Figure 2 legend. (B-E) Fold difference (log₂) in the amount of PRG amplicons between aged HD vs. young HD (B), between aged HD vs. aged wild-type (wt) (C), between aged wt and young wt (D), and between young HD vs. young wt samples (E). P-values, paired-sample t-test. Error bar, standard error. (F) Comparison of expression levels of Ezh2 in HD and wild type samples. P-value, paired-sample t-test. Error bar, standard deviation. (G) RT-PCR analysis of PRGs. PRGs were randomly chosen, and expression levels were examined in splenic T cells from young (HD_y) and aged HD (HD_o) mice. 18s RNA, loading control.

  
  
  

  

  Comparison of the mean ratios of epi-driver gene expression levels in each category between young and aged samples of Huntington’s disease (HD) mice and control mice. In (A) each bar shows the fold change of epi-driver gene expression levels in each category between aged and young samples. In (B) the mean fold changes, standard deviations (STD), and p-values (paired-sample t-test) between indicated comparisons are represented for the graphs in A. Wo and wy, old and young wild-type samples; Ho and Hy, old and young HD samples.

  
  
  

  

  Analysis of age-associated pattern of change in epi-driver gene expressions in Huntington’s disease mice. Fold changes were measured for the epi-driver gene amplicons in the categories of acetylation (A), lysine (K) methylation (B), K demethylation (C), Polycomb-repressive complex (PRC, C), and DNA methylation (D). In B-D, amplicons are differentially marked according to their modification effects on chromatin accessibility: open circles indicate increased accessibility; solid circles indicate reduced accessibility; and grey circles for cases involving either increased or reduced accessibility. (E) Summary of the upward (Δ) or downward (∇) change in expression of epi-driver genes in each category. ‘-‘ indicate no significant change. Ho and Hy, old and young HD samples.

  
  
  

  

  DNase-I hypersensitive site profiling in aged Huntington’s disease (HD) and wild-type splenic cells. (A) Scatter plot of DNase-I hypersensitive (DHS) read counts (log₂) between HD and wt around transcription start site (TSS). DHS reads ± 2 kb around TSSs were counted. Colored dots (orange for HD-high and green for wt-high) indicate DHSs reads with 2-fold or more count differences. (B) Heatmaps of DHS signals around TSSs (± 2 kb) in HD and wt mice. DHS signals were clustered by the k-means algorithm (k = 2). Sites are ordered by DHS signal intensity around TSS. (C-D) Read count distribution around TSSs (± 2 kb, left) and the mean DHS signal density around TSSs (± 300 bp, right) in cluster-1 (C) and cluster-2 (D). (E) Comparison of DHS signal density at PRG TSSs between HD and wt samples. Shown are the proportions of PRGs with HD-high (orange) and wt-high (gray) DHS signals. Of the 16 PRGs, 15 PRGs belong to cluster-2 and 10 (63%) have denser signals in HD sample than in wt.

  
  
  

• Research Paper Volume 8, Issue 4 pp 636-641

  Quantification of global mitochondrial DNA methylation levels and inverse correlation with age at two CpG sites

  Relevance score: 7.27856

  Shakhawan K. Mawlood, Lynn Dennany, Nigel Watson, John Dempster, Benjamin S. Pickard

  Keywords: mitochondrial DNA, epigenetics, ageing, age prediction, Illumina NGS

  Published in Aging on February 17, 2016

  Show abstract
  Hide abstract

  Mammalian ageing features biological attrition evident at cellular, genetic and epigenetic levels. Mutation of mitochondrial DNA, and nuclear DNA methylation changes are well established correlates of ageing. The methylation of mitochondrial DNA (mtDNA) is a new and incompletely described phenomenon with unknown biological control and significance. Here we describe the bisulphite sequencing of mtDNA from 82 individuals aged 18‐91 years. We detected low and variable levels of mtDNA methylation at 54 of 133 CpG sites interrogated. Regression analysis of methylation levels at two CpG sites (M1215 and M1313) located within the 12S ribosomal RNA gene showed an inverse correlation with subject age suggesting their utility as epigenetic markers of ageing.

  

  Mean methylation levels at 54 CpG sites across the mitochondrial genome (category labels denote reference base position). While methylation levels are typically 2‐6%, considerable inter‐individual variation was observed, indicated by minimum and maximum range bars. CpG sites within the 12S RNA gene are highlighted.

  
  
  

  

  Methylation levels (expressed as a fraction) at two CpG sites within the 12S RNA gene, M1215 (a) and M1313 (b), correlate with age and can be used to construct an accurate predictive model (c) using Pearson's correlation.

  
  
  

• Research Paper pp undefined-undefined

  Comparison of the mutation patterns between tumor tissue and cell-free DNA in stage IV gastric cancer

  Relevance score: 7.54044

  Ching-Yun Kung, Wen-Liang Fang, Yi-Ping Hung, Kuo-Hung Huang, Ming-Huang Chen, Yee Chao, Shih-Chieh Lin, Anna Fen-Yau Li, Su-Shun Lo, Chew-Wun Wu

  Keywords: tumor DNA, cfDNA, NGS, sensitivity, specificity

  Published in Aging on Invalid Date

  Show abstract
  Hide abstract

  Compared to stage I–III gastric cancer (GC), the level of cell-free DNA (cfDNA) was significantly higher in stage IV GC. The mutation patterns of different metastatic patterns between cfDNA and tumor DNA in stage IV GC have not yet been reported. We used next-generation sequencing (NGS) to analyze cfDNA and tumor DNA in 56 stage IV GC patients. Tumor DNA and cfDNA were analyzed using a 29-gene NGS panel. In tumor samples, the most commonly mutated gene was TP53 (64%), followed by ARID1A (62%), KMT2C (60%) and KMT2D (58%). In cfDNA samples, the most commonly mutated genes were FAT4 (19%) and MACF1 (19%), followed by KMT2D (18%), ARID1A (14%) and LRP1B (14%). The concordance of mutation patterns in these 29 genes was 42.0% between cfDNA and tumor DNA. A specificity of 100% was found when using the mutation status of cfDNA to predict mutations in tumor samples. The sensitivity of the mutation status of cfDNA to predict mutation in tumor samples was highest in FAT4 (88.9%), followed by MACF1 (80%), CDH1 (75%) and PLB1 (75%). For cfDNA with PLB1 mutations, patients were more likely to develop distant lymphatic metastasis than peritoneal metastasis. Patients with multiple-site metastases had significantly more mutated spots than patients with single-site metastasis. Due to the high sensitivity and specificity of some genes in the prediction of mutation in tumor samples, monitoring the mutation pattern of cfDNA may be useful in the stage IV GC treatment.