5 results on '"Marka, van Blitterswijk"'
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2. Additional file 1: of Extensive transcriptomic study emphasizes importance of vesicular transport in C9orf72 expansion carriers
- Author
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Dickson, Dennis, Baker, Matthew, Jackson, Jazmyne, Mariely DeJesus-Hernandez, NiCole Finch, Shulan Tian, Heckman, Michael, Pottier, Cyril, Gendron, Tania, Murray, Melissa, Yingxue Ren, Reddy, Joseph, Graff-Radford, Neill, Boeve, Bradley, Petersen, Ronald, Knopman, David, Josephs, Keith, Petrucelli, Leonard, Bjรถrn Oskarsson, Sheppard, John, Asmann, Yan, Rademakers, Rosa, and Marka Van Blitterswijk more...
- Abstract
Figure S1 a Module-trait relationships are presented for patients with an expanded C9orf72 repeat and patients without this repeat (C9Plus vs. C9Minus). b For patients with an expansion and control subjects (C9Plus vs. Control), module-trait relationships are plotted. These plots are generated with weighted gene co-expression network analysis (WGCNA) to find groups of genes that go up (red) or down (blue) together. A unique color has been assigned to each of these groups, also called a module. Correlations and p-values are shown for variables of interest, including disease group (C9Plus, C9Minus, and/or Control; arrow), neurons, microglia, astrocytes, oligodendrocytes, endothelial cells, RNA integrity number (RIN), age at death, sex, and plate. The strongest correlations (brightest colors) are observed for cell types. Notably, both module-trait relationship plots are based on residuals obtained without adjustment for cell-type-specific markers. Figure S2 a With adjustment for cell-type-specific markers, a cluster dendrogram is shown for C9orf72 expansion carriers and control subjects. b For the same comparison, a cluster dendrogram is displayed without adjustment for cell-type-specific markers. The branches in these dendrograms correspond to specific modules. A unique color has been assigned to each of these modules. Additionally, variables of interest are included, such as the disease group, neurons, microglia, astrocytes, oligodendrocytes, endothelial cells, RNA integrity number (RIN), age at death, sex, and plate. High levels are shown in red and low levels in blue. After adjustment, no striking differences are observed based on cell type; without adjustment, however, modules appear to be associated with certain cell types (e.g., turquoise and neurons). Figure S3 a For patients harboring a C9orf72 repeat expansion and those without this expansion (C9Plus vs. C9Minus; module membership > 0.6 and significance < 1.0E-05), a gene network is displayed. b A gene network is visualized when examining expansion carriers and controls (C9Plus vs. Control; module membership > 0.6 and significance < 1.0E-05). In these network plots, the connectivity of each gene is represented by the size of its node, the module to which it has been assigned by its color, and the strength of the correlation by the thickness of its edges; the C9orf72 gene is denoted by an arrow. Of note, the plots in this figure have been generated without adjustment for cell-type-specific markers. Figure S4 a-d Trends are displayed for patients carrying a C9orf72 repeat expansion. a The first plot shows VEGFA and age at onset. b CDKL1 and C9orf72 expansion size are shown in the second plot. c The third plot displays EEF2K and poly(GP) levels. In these three plots, the solid blue line denotes the linear regression line, while each individual is represented by a solid dark grey circle. d The last plot shows SGSM3 levels and survival after onset, when comparing the bottom 50% (solid salmon line) to the top 50% (solid turquoise line). These plots have been created using residuals unadjusted for differences in cellular composition. Figure S5 a-h The expression levels of VEGFA, CDKL1, EEF2K, and SGSM3 are shown for all disease groups: patients with a C9orf72 repeat expansion (C9Plus), patients without this expansion (C9Minus), and control subjects (Control), both with and without adjustment for cell-type-specific markers. For each box plot, the median is represented by a solid black line, and each box spans the interquartile range (IQR; 25th percentile to 75th percentile). Figure S6 a-h This figure displays the correlation between our expression assays (relative expression) and RNA sequencing data (residuals). a-b The first two plots show correlations for VEGFA, either with or without adjustment for cell-type-specific markers. c-d The next two plots visualize correlations for CDKL1, both with and without adjustment for cellular composition. e-f EEF2K is displayed on the next plots, again with and without adjustment for surrogate markers. g-h The last two plots show correlations for SGSM3 with and without adjustment for cellular composition. For each of these plots, the solid blue line denotes the linear regression line, while each individual is represented by a solid dark grey circle. (PDF 2894 kb) more...
- Published
- 2019
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3. Additional file 1: of TMEM106B haplotypes have distinct gene expression patterns in aged brain
- Author
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Yingxue Ren, Marka Van Blitterswijk, Allen, Mariet, Carrasquillo, Minerva, Reddy, Joseph, Wang, Xue, Beach, Thomas, Dickson, Dennis, Ertekin-Taner, Nilüfer, Asmann, Yan, and Rademakers, Rosa
- Subjects
lipids (amino acids, peptides, and proteins) ,sense organs - Abstract
Table S1. Tissue samples available and selected for inclusion in this study. Table S2. DEGS in TCX. Positive fold change represents higher gene expression in SS than TT. Negative fold change represents lower gene expression in SS than TT. Table S3. DEGS in CER. Positive fold change represents higher gene expression in SS than TT. Negative fold change represents lower gene expression in SS than TT. Table S4. Overlapping genes between TCX and CER based on top 500 genes with |FC| ≥ 1.2 ranked by unadjusted p value. Table S5. Enrichment of modules for their respective DEG signatures. Table S6. Significant modules identified in the TCX and CER matched cases. Table S7. Significant modules identified in separate disease groups in TCX and CER. Table S8. Significant modules identified in the TCX and CER controls. (DOCX 54 kb) more...
- Published
- 2018
- Full Text
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4. Additional file 1: of Long-read sequencing across the C9orf72 â GGGGCCâ repeat expansion: implications for clinical use and genetic discovery efforts in human disease
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Ebbert, Mark, Farrugia, Stefan, Sens, Jonathon, Jansen-West, Karen, Gendron, Tania, Prudencio, Mercedes, McLaughlin, Ian, Bowman, Brett, Seetin, Matthew, Mariely DeJesus-Hernandez, Jackson, Jazmyne, Brown, Patricia, Dickson, Dennis, Marka Van Blitterswijk, Rademakers, Rosa, Petrucelli, Leonard, and Fryer, John more...
- Subjects
3. Good health - Abstract
Figure S1. Repeat-containing plasmids have a large repeat size distribution. Figure S2. Sanger sequencing confirms the SCA36 repeat plasmid contains at least 37 repeats. Figure S3. Individual Sequel and MinION read(s) across the C9orf72 repeat region aligned to the reference genome and hand curated. Data S1. RS II consensus sequence in the C9-774 repeat region is 99.77% accurate, when compared to the plasmid reference sequence. Data S2. MinION consensus sequence in the C9-774 repeat region is 26.55% accurate, when compared to the plasmid reference sequence. Data S3. MinION read covering the non-pathogenic allele. Data S4. Sequel read covering the non-pathogenic allele. Data S5. Sequel read that did not extend through repeat, but contains approximately 30 repeats. Data S6. Sequel read covering approximately 69 repeats. Data S7. Sequel read that did not extend through the repeat, but contains approximately 912 repeats. Data S8. Sequel read covering 1324-repeat allele. Data S9. PacBio Sequel consensus sequence by Long Amplicon Analysis (LAA2). Data S10. Plasmid backbones used to separate reads. Data S11. Sequences adjacent to the C9orf72 repeat region used to identify on-target reads from the PacBio No-Amp Targeted Sequencing approach. (DOCX 3982 kb) more...
5. Additional file 1: of Long-read sequencing across the C9orf72 â GGGGCCâ repeat expansion: implications for clinical use and genetic discovery efforts in human disease
- Author
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Ebbert, Mark, Farrugia, Stefan, Sens, Jonathon, Jansen-West, Karen, Gendron, Tania, Prudencio, Mercedes, McLaughlin, Ian, Bowman, Brett, Seetin, Matthew, Mariely DeJesus-Hernandez, Jackson, Jazmyne, Brown, Patricia, Dickson, Dennis, Marka Van Blitterswijk, Rademakers, Rosa, Petrucelli, Leonard, and Fryer, John more...
- Subjects
3. Good health - Abstract
Figure S1. Repeat-containing plasmids have a large repeat size distribution. Figure S2. Sanger sequencing confirms the SCA36 repeat plasmid contains at least 37 repeats. Figure S3. Individual Sequel and MinION read(s) across the C9orf72 repeat region aligned to the reference genome and hand curated. Data S1. RS II consensus sequence in the C9-774 repeat region is 99.77% accurate, when compared to the plasmid reference sequence. Data S2. MinION consensus sequence in the C9-774 repeat region is 26.55% accurate, when compared to the plasmid reference sequence. Data S3. MinION read covering the non-pathogenic allele. Data S4. Sequel read covering the non-pathogenic allele. Data S5. Sequel read that did not extend through repeat, but contains approximately 30 repeats. Data S6. Sequel read covering approximately 69 repeats. Data S7. Sequel read that did not extend through the repeat, but contains approximately 912 repeats. Data S8. Sequel read covering 1324-repeat allele. Data S9. PacBio Sequel consensus sequence by Long Amplicon Analysis (LAA2). Data S10. Plasmid backbones used to separate reads. Data S11. Sequences adjacent to the C9orf72 repeat region used to identify on-target reads from the PacBio No-Amp Targeted Sequencing approach. (DOCX 3982 kb) more...
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