Tower 1978

1978 yearbook of Westbrook College in Portland, Maine.https://dune.une.edu/wchc_yearbooks/1007/thumbnail.jp

Pyrénées et océan : organe des stations thermales et des bains de mer desservant tout le littoral et la chaîne des Pyrénées, chronique mondaine du baigneur et du touriste... ["puis" journal des intérêts économiques des Pyrénées et du Sud-Ouest : organe officiel de la Fédération des syndicats d'initiative du Sud-Ouest]

15 décembre 19121912/12/15 (N327).Appartient à l’ensemble documentaire : Aquit1Appartient à l’ensemble documentaire : MidiPyren

Additional file 9: of Transcriptome sequencing reveals thousands of novel long non-coding RNAs in B cell lymphoma

DLBCL sample subtype classification. Data showing the classification of the 104 primary DLBCL subtypes as ABC or GCB. (XLSX 37 kb

Spreading of aberrant methylation to neighboring probesets in the ABC samples.

<p>(A) A schematic representation of how the genome was divided into blocks of genes to study spreading of altered DNA methylation. (B–C) Analysis of spreading of aberrant methylation within genomic neighborhoods. Loci “<i>i</i>” represent probesets that are significantly hypo- (black) or hyper-methylated (grey) in lymphoma samples compared to normal tissues, and loci “<i>i</i>±<i>j</i>” represent both the (<i>i</i>+<i>j</i>)-th and (<i>i</i>−<i>j</i>)-th neighbors of those probesets. For instance, when we focused on probeset #10 (i.e. <i>i</i> = 10), we analyzed spreading of aberrant methylation at probesets #5, 6, 7, 8, 9, 11, 12, 13, 14 and 15. Panel B displays the change in methylation states while panel C shows the change in IQR (variability between samples).</p

Genome-wide patterns of aberrant methylation.

<p>(A) Graphical explanation of how the distribution of M-scores and IQR are transformed into violin distribution plots to enable more efficient visualization and comparison on intra- and inter-sample variability. (B) Distribution of the methylation score (M-score, left) and inter-quartile ranges (IQR, right) at probesets in centromeric, telomeric, and intermediate regions for normal and diseased tissues. Bar width is proportional to the number of data points, and the colors are the same as in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003137#pgen-1003137-g001" target="_blank">Figure 1A</a>. (C) Distributions of M-score (left) and IQR (right) are shown for gene-poor, gene-rich, and intermediate regions.</p

Genomic localization of transcriptional regulators and AICDA associates with sites of aberrant DNA methylation.

<p>(A–D) Methylation heterogeneity of promoters of genes that are targets of master regulators. The panels display the distribution of methylation scores (M-scores) for promoters of target genes of (A) BCL6, (B) MYC, (C) EZH2, and (D) AICDA. (E) A schematic overview showing targeted abnormal promoter methylation by master regulators such as MYC, BCL6, EZH2 and AICDA in the lymphoma subtypes.</p

The insulator factor CTCF prevents spreading of aberrant methylation.

<p>(A) Methylation heterogeneity depends on the density of CTCF-binding sites. Methylation state (M-score, left) and inter-sample methylation variation (IQR, right) are shown for CTCF-BS-poor, CTCF-BS-rich, and intermediate regions. (B) Spreading of aberrant methylation from genomic position “<i>i</i>” to “<i>i</i>±1” (i.e. two neighboring sites) when at least one CTCF-BS is present (black vertical dotted line) and when no CTCF-BS is present (light grey vertical dotted line) between “<i>i</i>” and “<i>i</i>±1”, for aberrant hypo-methylation (two left panels) and aberrant hyper-methylation (two right panels). The presence of CTCF-BS more efficiently restricts the spreading of aberrant hypo-methylation. (C) A schematic overview showing spreading of abnormal methylation in the absence of CTCF-binding sites in genomic neighborhood.</p

Genes associated with aberrant DNA methylation patterns B-cell lymphoma.

<p>(A) List of genes potentially associated with aberrant methylation patterns in DLBCL. Boxplots visualize the distribution of Pearson correlation coefficients of primary variable (expression level of a candidate gene) and the fitted variables (ΔM of promoters). The numbers on top represent the summarized quantity R², i.e. statistical variance in the fitted variable explained by the primary variable (in percent). See <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003137#pgen.1003137.s035" target="_blank">Text S1</a>, Module 7 for more details. Statistically significant R² values (p&lt;0.05) are marked with an asterisk. (B) List of the top 10 genes with highest R² the unbiased genome-wide analysis. See <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003137#pgen.1003137.s035" target="_blank">Text S1</a>, Module 7 for more details.</p

The extent of DNA methylation aberration is predictive of patient survival.

<p>(A) Phylogenetic tree, as estimated based on the correlation of group-averaged M-scores. Departure from normal methylation patterns is correlated with disease severity of the lymphoma samples. (B–C) Kaplan-Meier curves for risk groups defined according to their methylation distance score (i.e. distance from normal B-cells), which reflects how different a sample's methylation profile is from that of NBC or NGC, for all DLBCL (GCB and ABC) samples. (B) Multivariate analysis with the International Prognostic Index (IPI) and distance to NBC. (C) Only IPI.</p

DNA methylation and gene expression relationships display subtype-specific differences.

<p>CpG islands and shores across the genome were categorized into those located upstream from a transcription start site (TSS), overlapping a TSS or located downstream from a TSS. Boxplots are plotted that illustrate the maximum DNA methylation levels at CpGs within these CpG islands and CpG shores for the top 15th percentile expressed genes (right) and the bottom 15th percentile expressed genes (left). Each row shows a representative sample for each type: Normal bone marrow (top); IDH-mut AML (middle) and MLLr AML (bottom). In all sample types CpG islands overlapping a TSS displayed lower methylation levels in highly expressed genes and higher methylation levels in genes that were expressed at low levels. In MLLr AMLs this relationship between expression and methylation levels further extended into CpG shores, and was also observed at CpG islands and shores upstream and downstream from the TSS. IDH-mut AMLs, and to a lesser degree NBM samples, displayed higher methylation levels at CpG shores of genes with high expression levels, while low methylation levels were observed at these shores for genes expressed at low levels.</p