Job Description Region-Gene Association Graphs Global Controls

Total Page:16

File Type:pdf, Size:1020Kb

Job Description Region-Gene Association Graphs Global Controls Overview News Use GREAT Demo Video How to Cite Help Forum Bejerano Lab, Stanford University GREAT version 3.0.0 current (02/15/2015 to now) Job Description Region-Gene Association Graphs Number of associated genes per region Binned by orientation and distance to TSS Binned by absolute distance to TSS What do these graphs illustrate? Download as PDF. Download as PDF. Download as PDF. Global Controls Global Export Which data is exported by each option? GO Molecular Function (3 terms) Global controls Table controls: Export Shown top rows in this table: 20 Set Term annotation count: Min: 1 Max: Inf Set Visualize this table: [select one] Binom Binom Hyper Hyper Binom Binom Binom Binom Binom Hyper Hyper Hyper Hyper Hyper Hyper Term Term Binom Binom Observed Region Hyper Hyper Observed Term Raw Bonferroni FDR Q- Fold Genome Raw Bonferroni FDR Q- Fold Total Gene Set Name ID Rank Expected Region Set Rank Expected Gene Gene P-Value P-Value Val Enrichment Fraction P-Value P-Value Val Enrichment Genes Coverage Hits Coverage Hits Coverage sequence-specific DNA binding GO:0043565 2 5.7476e- 2.1197e-6 1.0598e- 2.0959 36.2619 76 0.0935 19.59% 2 4.7470e- 1.7507e-13 8.7535e- 3.1263 21.7511 68 697 12.08% 9.76% 10 6 17 14 HMG box domain binding GO:0071837 5 8.0649e- 2.9743e-3 5.9486e- 7.9439 1.2588 10 0.0032 2.58% 9 1.7248e- 6.3610e-2 7.0678e- 10.1193 0.5929 6 19 1.07% 31.58% 7 4 5 3 regulatory region DNA binding GO:0000975 6 7.9757e- 2.9414e-2 4.9024e- 2.0768 20.2232 42 0.0521 10.82% 5 5.4813e- 2.0215e-4 4.0430e- 2.8814 11.4529 33 367 5.86% 8.99% 6 3 8 5 The test set of 388 genomic regions picked 563 (3%) of all 18,041 genes. GO Molecular Function has 3,688 terms covering 15,090 (84%) of all 18,041 genes, and 189,388 term - gene associations. 3,688 ontology terms (100%) were tested using an annotation count range of [1, Inf]. GO Biological Process (17 terms) Global controls Table controls: Export Shown top rows in this table: 20 Set Term annotation count: Min: 1 Max: Inf Set Visualize this table: [select one] Binom Binom Hyper Hyper Binom Binom Binom Binom Binom Hyper Hyper Hyper Hyper Hyper Hyper Term Term Binom Binom Observed Region Hyper Hyper Observed Term Raw Bonferroni FDR Q- Fold Genome Raw Bonferroni FDR Q- Fold Total Gene Set Name ID Rank Expected Region Set Rank Expected Gene Gene P-Value P-Value Val Enrichment Fraction P-Value P-Value Val Enrichment Genes Coverage Hits Coverage Hits Coverage skeletal system development GO:0001501 1 8.8312e- 9.2198e-7 9.2198e- 2.5437 22.8016 58 0.0588 14.95% 2 2.9408e- 3.0702e-12 1.5351e- 3.8962 12.5763 49 403 8.70% 12.16% 11 7 16 12 Binom Binom Hyper Hyper Binom Binom Binom Binom Binom Hyper Hyper Hyper Hyper Hyper Hyper Term Term Binom Binom Observed Region Hyper Hyper Observed Term Raw Bonferroni FDR Q- Fold Genome Raw Bonferroni FDR Q- Fold Total Gene Set Name ID Rank Expected Region Set Rank Expected Gene Gene P-Value P-Value Val Enrichment Fraction P-Value P-Value Val Enrichment Genes Coverage Hits Coverage Hits Coverage embryonic morphogenesis GO:0048598 2 5.2786e- 5.5108e-6 2.7554e- 2.2762 28.5569 65 0.0736 16.75% 4 2.8600e- 2.9858e-11 7.4645e- 3.4063 15.8530 54 508 9.59% 10.63% 10 6 15 12 anterior/posterior pattern specification GO:0009952 3 6.9152e- 7.2195e-6 2.4065e- 3.3730 10.3765 35 0.0267 9.02% 18 2.7401e- 2.8607e-8 1.5893e- 4.7656 6.0853 29 195 5.15% 14.87% 10 6 12 9 embryonic organ development GO:0048568 5 1.8247e- 1.9050e-5 3.8101e- 2.4148 22.7760 55 0.0587 14.18% 20 3.1036e- 3.2401e-8 1.6201e- 3.4333 12.2330 42 392 7.46% 10.71% 9 6 12 9 embryonic organ morphogenesis GO:0048562 6 5.4845e- 5.7258e-5 9.5431e- 2.7034 15.9061 43 0.0410 11.08% 25 1.4103e- 1.4723e-7 5.8893e- 3.9754 8.3010 33 266 5.86% 12.41% 9 6 11 9 regionalization GO:0003002 9 4.0631e- 4.2419e-4 4.7132e- 2.5182 17.0755 43 0.0440 11.08% 30 1.9585e- 2.0447e-7 6.8157e- 3.7385 9.3620 35 300 6.22% 11.67% 8 5 11 9 pattern specification process GO:0007389 13 1.6930e- 1.7675e-3 1.3596e- 2.1457 24.7002 53 0.0637 13.66% 12 7.0261e- 7.3353e-9 6.1127e- 3.4009 13.2316 45 424 7.99% 10.61% 7 4 13 10 skeletal system morphogenesis GO:0048705 28 9.7855e- 1.0216e-2 3.6486e- 2.7370 10.9607 30 0.0282 7.73% 23 9.3387e- 9.7496e-8 4.2390e- 4.6976 5.9605 28 191 4.97% 14.66% 7 4 12 9 embryonic skeletal system morphogenesis GO:0048704 33 2.2968e- 2.3979e-2 7.2664e- 3.6094 5.2640 19 0.0136 4.90% 47 1.9138e- 1.9980e-6 4.2511e- 6.5545 2.7462 18 88 3.20% 20.45% 6 4 10 8 embryonic skeletal system development GO:0048706 41 4.5261e- 4.7252e-2 1.1525e- 2.9918 7.6876 23 0.0198 5.93% 15 1.3688e- 1.4290e-8 9.5269e- 6.2993 3.6512 23 117 4.09% 19.66% 6 3 12 10 ossification GO:0001503 52 1.1910e- 1.2434e-1 2.3912e- 2.6096 9.9634 26 0.0257 6.70% 92 3.7858e- 3.9524e-2 4.2961e- 3.2532 6.1477 20 197 3.55% 10.15% 5 3 6 4 muscle organ development GO:0007517 67 5.3845e- 5.6215e-1 8.3903e- 2.2155 13.5410 30 0.0349 7.73% 111 2.9925e- 3.1241e-1 2.8145e- 2.6704 8.2386 22 264 3.91% 8.33% 5 3 5 3 chondroblast differentiation GO:0060591 69 6.1310e- 6.4007e-1 9.2764e- 41.0115 0.0732 3 0.0002 0.77% 131 1.1812e- 1.0000 9.4136e- 24.0333 0.1248 3 4 0.53% 75.00% 5 3 4 3 negative regulation of myeloid cell GO:0045638 83 1.5678e- 1.0000 1.9720e- 3.6344 3.3018 12 0.0085 3.09% 143 1.5114e- 1.0000 1.1034e- 4.1083 2.4341 10 78 1.78% 12.82% differentiation 4 2 4 2 positive regulation of steroid biosynthetic GO:0010893 89 2.3134e- 1.0000 2.7137e- 9.3321 0.5358 5 0.0014 1.29% 158 3.8036e- 1.0000 2.5133e- 10.6815 0.3745 4 12 0.71% 33.33% process 4 2 4 2 osteoblast development GO:0002076 94 3.2381e- 1.0000 3.5963e- 5.5549 1.2601 7 0.0032 1.80% 148 2.3507e- 1.0000 1.6582e- 8.4327 0.5929 5 19 0.89% 26.32% 4 2 4 2 artery morphogenesis GO:0048844 103 4.8435e- 1.0000 4.9093e- 3.4182 3.2181 11 0.0083 2.84% 172 6.7334e- 1.0000 4.0870e- 4.6731 1.4979 7 48 1.24% 14.58% 4 2 4 2 The test set of 388 genomic regions picked 563 (3%) of all 18,041 genes. GO Biological Process has 10,440 terms covering 15,441 (86%) of all 18,041 genes, and 950,065 term - gene associations. 10,440 ontology terms (100%) were tested using an annotation count range of [1, Inf]. GO Cellular Component (1 term) Global controls Table controls: Export Shown top rows in this table: 20 Set Term annotation count: Min: 1 Max: Inf Set Visualize this table: [select one] Binom Binom Hyper Hyper Binom Binom Binom Binom Binom Hyper Hyper Hyper Hyper Hyper Hyper Term Term Binom Binom Observed Region Hyper Hyper Observed Term Raw Bonferroni FDR Q- Fold Genome Raw Bonferroni FDR Q- Fold Total Gene Set Name ID Rank Expected Region Set Rank Expected Gene Gene P-Value P-Value Val Enrichment Fraction P-Value P-Value Val Enrichment Genes Coverage Hits Coverage Hits Coverage PcG protein complex GO:0031519 4 2.6739e- 3.3825e-2 8.4563e- 5.9780 1.5055 9 0.0039 2.32% 2 2.2406e- 2.8344e-2 1.4172e- 6.5732 1.2171 8 39 1.42% 20.51% 5 3 5 2 The test set of 388 genomic regions picked 563 (3%) of all 18,041 genes. GO Cellular Component has 1,265 terms covering 16,807 (93%) of all 18,041 genes, and 277,316 term - gene associations. 1,265 ontology terms (100%) were tested using an annotation count range of [1, Inf]. Mouse Phenotype (20+ terms) Global controls Table controls: Export Shown top rows in this table: 20 Set Term annotation count: Min: 1 Max: Inf Set Visualize this table: [select one] Binom Binom Hyper Hyper Binom Binom Binom Binom Binom Hyper Hyper Hyper Hyper Hyper Hyper Term Term Binom Binom Observed Region Hyper Hyper Observed Term Raw Bonferroni FDR Q- Fold Genome Raw Bonferroni FDR Q- Fold Total Gene Set Name ID Rank Expected Region Set Rank Expected Gene Gene P-Value P-Value Val Enrichment Fraction P-Value P-Value Val Enrichment Genes Coverage Hits Coverage Hits Coverage thoracic vertebral transformation MP:0004618 1 4.4458e- 3.5202e-10 3.5202e- 11.9222 1.5098 18 0.0039 4.64% 17 6.0629e- 4.8006e-7 2.8239e- 8.9012 1.6852 15 54 2.66% 27.78% 14 10 11 8 abnormal sternebra morphology MP:0004322 2 2.7539e- 2.1806e-7 1.0903e- 6.5333 3.2143 21 0.0083 5.41% 22 2.4197e- 1.9159e-6 8.7088e- 8.1469 1.8412 15 59 2.66% 25.42% 11 7 10 8 abnormal rib development MP:0002823 3 2.8995e- 2.2958e-7 7.6527e- 11.9491 1.1716 14 0.0030 3.61% 126 4.7384e- 3.7518e-1 2.9776e- 7.0097 0.9986 7 32 1.24% 21.88% 11 8 5 3 abnormal cervical vertebrae morphology MP:0003048 4 4.5629e- 3.6129e-6 9.0323e- 4.4541 5.8374 26 0.0150 6.70% 12 1.0731e- 8.4969e-8 7.0808e- 6.0254 3.6512 22 117 3.91% 18.80% 10 7 11 9 abnormal vertebrae morphology MP:0000137 5 5.8125e- 4.6024e-6 9.2047e- 2.6774 18.3013 49 0.0472 12.63% 9 3.5959e- 2.8472e-8 3.1636e- 3.5506 11.2656 40 361 7.10% 11.08% 10 7 12 9 vertebral transformation MP:0003036 6 7.7012e- 6.0978e-6 1.0163e- 5.4186 3.8756 21 0.0100 5.41% 35 3.8747e- 3.0680e-5 8.7657e- 5.4933 3.2767 18 105 3.20% 17.14% 10 6 9 7 abnormal rib morphology MP:0000150 7 8.4592e- 6.6980e-6 9.5686e- 3.0860 12.6378 39 0.0326 10.05% 30 1.1165e- 8.8401e-6 2.9467e- 3.7321 7.7705 29 249 5.15% 11.65% 10 7 9 7 abnormal thoracic cage morphology MP:0004624 8 9.3369e- 7.3929e-6 9.2412e- 2.6059 19.1869 50 0.0495 12.89% 8 2.5109e- 1.9881e-8 2.4851e- 3.6649 10.6415 39 341 6.93% 11.44% 10 7 12 9 abnormal sternum morphology MP:0000157 9 1.1460e- 9.0737e-6 1.0082e- 3.0522 12.7775 39 0.0329 10.05% 13 1.1043e- 8.7435e-8 6.7258e- 4.5111 6.4286 29 206 5.15% 14.08% 9 6 11 9 abnormal presacral vertebrae morphology MP:0000459 10 1.4313e- 1.1333e-5 1.1333e- 3.2783 10.6764 35 0.0275 9.02% 14 1.2473e- 9.8759e-8 7.0542e- 4.4893 6.4598 29 207 5.15% 14.01% 9 6 11 9 abnormal rib attachment MP:0004625 11 3.4050e- 2.6961e-5 2.4510e- 4.7393 4.6421 22 0.0120 5.67% 28 7.1791e- 5.6844e-6 2.0302e- 6.0716
Recommended publications
  • Differential Expression Profile Prioritization of Positional Candidate Glaucoma Genes the GLC1C Locus
    LABORATORY SCIENCES Differential Expression Profile Prioritization of Positional Candidate Glaucoma Genes The GLC1C Locus Frank W. Rozsa, PhD; Kathleen M. Scott, BS; Hemant Pawar, PhD; John R. Samples, MD; Mary K. Wirtz, PhD; Julia E. Richards, PhD Objectives: To develop and apply a model for priori- est because of moderate expression and changes in tization of candidate glaucoma genes. expression. Transcription factor ZBTB38 emerges as an interesting candidate gene because of the overall expres- Methods: This Affymetrix GeneChip (Affymetrix, Santa sion level, differential expression, and function. Clara, Calif) study of gene expression in primary cul- ture human trabecular meshwork cells uses a positional Conclusions: Only1geneintheGLC1C interval fits our differential expression profile model for prioritization of model for differential expression under multiple glau- candidate genes within the GLC1C genetic inclusion in- coma risk conditions. The use of multiple prioritization terval. models resulted in filtering 7 candidate genes of higher interest out of the 41 known genes in the region. Results: Sixteen genes were expressed under all condi- tions within the GLC1C interval. TMEM22 was the only Clinical Relevance: This study identified a small sub- gene within the interval with differential expression in set of genes that are most likely to harbor mutations that the same direction under both conditions tested. Two cause glaucoma linked to GLC1C. genes, ATP1B3 and COPB2, are of interest in the con- text of a protein-misfolding model for candidate selec- tion. SLC25A36, PCCB, and FNDC6 are of lesser inter- Arch Ophthalmol. 2007;125:117-127 IGH PREVALENCE AND PO- identification of additional GLC1C fami- tential for severe out- lies7,18-20 who provide optimal samples for come combine to make screening candidate genes for muta- adult-onset primary tions.7,18,20 The existence of 2 distinct open-angle glaucoma GLC1C haplotypes suggests that muta- (POAG) a significant public health prob- tions will not be limited to rare descen- H1 lem.
    [Show full text]
  • Differential Expression Profile Prioritization of Positional Candidate Glaucoma Genes the GLC1C Locus
    LABORATORY SCIENCES Differential Expression Profile Prioritization of Positional Candidate Glaucoma Genes The GLC1C Locus Frank W. Rozsa, PhD; Kathleen M. Scott, BS; Hemant Pawar, PhD; John R. Samples, MD; Mary K. Wirtz, PhD; Julia E. Richards, PhD Objectives: To develop and apply a model for priori- est because of moderate expression and changes in tization of candidate glaucoma genes. expression. Transcription factor ZBTB38 emerges as an interesting candidate gene because of the overall expres- Methods: This Affymetrix GeneChip (Affymetrix, Santa sion level, differential expression, and function. Clara, Calif) study of gene expression in primary cul- ture human trabecular meshwork cells uses a positional Conclusions: Only1geneintheGLC1C interval fits our differential expression profile model for prioritization of model for differential expression under multiple glau- candidate genes within the GLC1C genetic inclusion in- coma risk conditions. The use of multiple prioritization terval. models resulted in filtering 7 candidate genes of higher interest out of the 41 known genes in the region. Results: Sixteen genes were expressed under all condi- tions within the GLC1C interval. TMEM22 was the only Clinical Relevance: This study identified a small sub- gene within the interval with differential expression in set of genes that are most likely to harbor mutations that the same direction under both conditions tested. Two cause glaucoma linked to GLC1C. genes, ATP1B3 and COPB2, are of interest in the con- text of a protein-misfolding model for candidate selec- tion. SLC25A36, PCCB, and FNDC6 are of lesser inter- Arch Ophthalmol. 2007;125:117-127 IGH PREVALENCE AND PO- identification of additional GLC1C fami- tential for severe out- lies7,18-20 who provide optimal samples for come combine to make screening candidate genes for muta- adult-onset primary tions.7,18,20 The existence of 2 distinct open-angle glaucoma GLC1C haplotypes suggests that muta- (POAG) a significant public health prob- tions will not be limited to rare descen- H1 lem.
    [Show full text]
  • Supplementary Data
    Supplementary Figure 1 Supplementary Figure 2 CCR-10-3244.R1 Supplementary Figure Legends Supplementary Figure 1. B-Myb is overexpressed in primary AML blasts and B-CLL cells. Baseline B-Myb mRNA levels were determined by quantitative RT-PCR, after normalization to the level of housekeeping gene, in primary B-CLL (n=10) and AML (n=5) patient samples, and in normal CD19+ (n=5) and CD34+ (n=4) cell preparations. Each sample was determined in triplicate. Horizontal bars are median, upper and lower edges of box are 75th and 25th percentiles, lines extending from box are 10th and 90th percentiles. Supplementary Figure 2. Cytotoxicity by Nutlin-3 and Chlorambucil used alone or in combination in leukemic cells. The p53wild-type EHEB and SKW6.4 cells lines, and the p53mutated BJAB cell line were exposed to Nutlin-3 or Chlorambucil used either alone or in combination. (Nutl.+Chlor.). In A, upon treatment with Nutlin-3 or Chlorambucil, used either alone (both at 10 μM) or in combination (Nutl.+Chlor.), induction of apoptosis was quantitatively evaluated by Annexin V/PI staining, while E2F1 and pRb protein levels were analyzed by Western blot. Tubulin staining is shown as loading control. The average combination index (CI) values (analyzed by the method of Chou and Talalay) for effects of Chlorambucil+Nutlin-3 on cell viability are shown. ED indicates effect dose. In B, levels of B-Myb and E2F1 mRNA were analyzed by quantitative RT- PCR. Results are expressed as fold of B-Myb and E2F1 modulation in cells treated for 24 hours as indicated, with respect to the control untreated cultures set to 1 (hatched line).
    [Show full text]
  • Dendritic Cell Maturation Transcription Factor E2F1 Suppresses
    Transcription Factor E2F1 Suppresses Dendritic Cell Maturation Fang Fang, Yan Wang, Rui Li, Ying Zhao, Yang Guo, Ming Jiang, Jie Sun, Yang Ma, Zijia Ren, Zhigang Tian, Feng This information is current as Wei, De Yang and Weihua Xiao of September 29, 2021. J Immunol 2010; 184:6084-6091; Prepublished online 26 April 2010; doi: 10.4049/jimmunol.0902561 http://www.jimmunol.org/content/184/11/6084 Downloaded from References This article cites 40 articles, 21 of which you can access for free at: http://www.jimmunol.org/content/184/11/6084.full#ref-list-1 http://www.jimmunol.org/ Why The JI? Submit online. • Rapid Reviews! 30 days* from submission to initial decision • No Triage! Every submission reviewed by practicing scientists • Fast Publication! 4 weeks from acceptance to publication by guest on September 29, 2021 *average Subscription Information about subscribing to The Journal of Immunology is online at: http://jimmunol.org/subscription Permissions Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html Email Alerts Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts The Journal of Immunology is published twice each month by The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2010 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. The Journal of Immunology Transcription Factor E2F1 Suppresses Dendritic Cell Maturation Fang Fang,*,1 Yan Wang,*,1 Rui Li,* Ying Zhao,* Yang Guo,* Ming Jiang,* Jie Sun,* Yang Ma,* Zijia Ren,* Zhigang Tian,* Feng Wei,† De Yang,†,‡ and Weihua Xiao* Transcription factor E2F1 has been largely studied as a promoter of S-phase transition in the cell cycle and as a regulator of ap- optosis.
    [Show full text]
  • 1 Supplementary Information for Acetylated Histone H3K56 Interacts
    Supplementary Information for Acetylated histone H3K56 interacts with Oct4 to promote mouse embryonic stem cell pluripotency Table of contents Supplementary Figures 1-4 and Figure Legends Supplementary Methods Cell culture Plasmid construction and transfection ChIP-Sequencing ChIP-Seq data analysis K-means clustering Co-immunoprecipitation assay In vivo peptide pull-down assay Flag-immunoprecipitation assay In vitro peptide pull-down assay Mononucleosome immunoprecipitation Western blot Quantitative PCR Gel mobility shift assay Supplementary Tables 1-8 Supplementary References 1 Supplementary Figures and Legends 0 1 %&'() %&'() *(+, *(+, !"#$ !"#$ -./01&" -./01&" 023 ()*+ 023 ,'-+ . / %&'() %&'() *(+, *(+, !"#$ !"#$ -./01&" -./01&" 023 !"#$% 023 !$&"' Supplementary Figure 1. The distribution of ChIP-Seq signals for NSO and H3K56ac at Cluster 1 regions. (A-D) Enrichment patterns of Nanog, Sox2 and Oct4 (NSO) and H3K56ac at Oct4 (also known as Pou5f1) (A), Klf4 (B), Nanog (C), and Nodal (D) gene loci are shown by University of California, Santa Cruz (UCSC) genome browser. 2 !"#$%&$"'($)*+($,- . F&G-(%5+# F&G-(%5+: F&G-(%5+; F&G-(%5+2 2!! 2!! 2!! 2!! ;!! ;!! ;!! ;!! :!! :!! :!! :!! #!! #!! #!! #!! A50B)&%+0B+C;D"E'/ <05='&>)%,+?*%5'@%+ ! ! ! ! 92 9: ! : 2 92 9: ! : 2 92 9: ! : 2 92 9: ! : 2 $%&'()*%+,)-('./%+(0+ $%&'()*%+,)-('./%+(0+ $%&'()*%+,)-('./%+(0+ $%&'()*%+,)-('./%+(0+ 1/(2+3%'4+/%.(%5-+6478 1/(2+3%'4+/%.(%5-+6478 1/(2+3%'4+/%.(%5-+6478 1/(2+3%'4+/%.(%5-+6478 / F&G-(%5+# F&G-(%5+: F&G-(%5+; F&G-(%5+2 #"! #"! #"! #"! #!! #!! #!! #!!
    [Show full text]
  • Differential Action on Transcriptional Programs Related to Cell Cycle Control and Immune Function
    Oncogene (2007) 26, 6307–6318 & 2007 Nature Publishing Group All rights reserved 0950-9232/07 $30.00 www.nature.com/onc ORIGINAL ARTICLE Loss of the retinoblastoma tumor suppressor: differential action on transcriptional programs related to cell cycle control and immune function MP Markey1, J Bergseid2, EE Bosco1, K Stengel1,HXu3,4, CN Mayhew1, SJ Schwemberger6, WA Braden1, Y Jiang2, GF Babcock5,6, AG Jegga3,4, BJ Aronow3,4, MF Reed5, JYJ Wang2 and ES Knudsen1 1Department of Cell and Cancer Biology, University of Cincinnati, Cincinnati, OH, USA; 2Department of Medicine, Moores Cancer Center, University of California San Diego, La Jolla, CA, USA; 3Department of Pediatrics, University of Cincinnati, Cincinnati, OH, USA; 4Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA; 5Department of Surgery, University of Cincinnati, Cincinnati, OH, USA and 6Shriners Hospital, Cincinnati, OH, USA Functional inactivation of the retinoblastoma tumor genes involved in immune function was readily observed suppressor gene product (RB) is a common event in with disruption of the LXCXE-binding function of RB. human cancers. Classically, RB functions to constrain Thus, these studies demonstrate that RB plays a cellular proliferation, and loss of RB is proposed to significant role in both the positive and negative regula- facilitate the hyperplastic proliferation associated with tions of transcriptional programs and indicate that loss of tumorigenesis. To understand the repertoire of regulatory RB has distinct biological effects related to both cell cycle processes governed by RB, two models of RB loss were control and immune function. utilized to perform microarray analysis. In murine Oncogene (2007) 26, 6307–6318; doi:10.1038/sj.onc.1210450; embryonic fibroblasts harboring germline loss of RB, published online 23 April 2007 there was a striking deregulation of gene expression, wherein distinct biological pathways were altered.
    [Show full text]
  • Mouse Tfdp2 Knockout Project (CRISPR/Cas9)
    https://www.alphaknockout.com Mouse Tfdp2 Knockout Project (CRISPR/Cas9) Objective: To create a Tfdp2 knockout Mouse model (C57BL/6J) by CRISPR/Cas-mediated genome engineering. Strategy summary: The Tfdp2 gene (NCBI Reference Sequence: NM_001184706 ; Ensembl: ENSMUSG00000032411 ) is located on Mouse chromosome 9. 13 exons are identified, with the ATG start codon in exon 4 and the TAA stop codon in exon 13 (Transcript: ENSMUST00000034982). Exon 6~9 will be selected as target site. Cas9 and gRNA will be co-injected into fertilized eggs for KO Mouse production. The pups will be genotyped by PCR followed by sequencing analysis. Note: Exon 6 starts from about 10.91% of the coding region. Exon 6~9 covers 36.71% of the coding region. The size of effective KO region: ~9861 bp. The KO region does not have any other known gene. Page 1 of 9 https://www.alphaknockout.com Overview of the Targeting Strategy Wildtype allele 5' gRNA region gRNA region 3' 1 6 7 8 9 13 Legends Exon of mouse Tfdp2 Knockout region Page 2 of 9 https://www.alphaknockout.com Overview of the Dot Plot (up) Window size: 15 bp Forward Reverse Complement Sequence 12 Note: The 2000 bp section upstream of Exon 6 is aligned with itself to determine if there are tandem repeats. No significant tandem repeat is found in the dot plot matrix. So this region is suitable for PCR screening or sequencing analysis. Overview of the Dot Plot (down) Window size: 15 bp Forward Reverse Complement Sequence 12 Note: The 2000 bp section downstream of Exon 9 is aligned with itself to determine if there are tandem repeats.
    [Show full text]
  • Identification of a Substrate-Targeting Domain in Cyclin E Necessary for Phosphorylation of the Retinoblastoma Protein
    Proc. Natl. Acad. Sci. USA Vol. 95, pp. 2535–2540, March 1998 Medical Sciences Identification of a substrate-targeting domain in cyclin E necessary for phosphorylation of the retinoblastoma protein BETH L. KELLY,KAREN G. WOLFE, AND JAMES M. ROBERTS* Fred Hutchinson Cancer Research Center, Division of Basic Sciences, 1124 Columbia Street, Seattle, WA 98104 Communicated by Charles J. Sherr, St. Jude Children’s Research Hospital, Memphis, TN, December 19, 1997 (received for review August 1, 1997) ABSTRACT Considerable advances have been made in express cyclin E (18, 19). This observation implies that under characterizing the cyclins and cyclin-dependent kinases certain conditions cyclin E can be the limiting target of (CDKs) that are necessary for progression through the cell E2F-activated gene transcription. cycle, but there has been relatively lesser success in identifying It is not understood how cyclin E–CDK2 catalyzes the G1 to the specific biochemical pathways and cell cycle events that S phase transition. At present, all that is known is that the S are directly under CDK control. To identify physiologically phase promoting function of cyclin E is at least in part significant CDK substrates we generated mutations in cyclin independent of Rb. Microinjection of antibodies directed E that altered the ability of the cyclin to direct the cyclin–CDK against cyclin E arrest both Rb-positive and Rb-negative cell holoenzyme to specific in vivo substrates. We show that one of lines in G1 (5). One non-Rb substrate of cyclin E–CDK2 is these mutations defines a domain in cyclin E necessary for p27Kip1, an inhibitor of CDKs.
    [Show full text]
  • Differential Requirement for Dimerization Partner DP Between
    www.nature.com/scientificreports OPEN Diferential requirement for dimerization partner DP between E2F-dependent activation of tumor Received: 18 December 2017 Accepted: 31 January 2018 suppressor and growth-related Published: xx xx xxxx genes Hideyuki Komori1, Yasuko Goto2, Kenta Kurayoshi2, Eiko Ozono3, Ritsuko Iwanaga4, Andrew P. Bradford 5, Keigo Araki2 & Kiyoshi Ohtani2 The transcription factor E2F plays crucial roles in cell proliferation and tumor suppression by activating growth-related genes and pro-apoptotic tumor suppressor genes, respectively. It is generally accepted that E2F binds to target sequences with its heterodimeric partner DP. Here we show that, while knockdown of DP1 expression inhibited ectopic E2F1- or adenovirus E1a-induced expression of the CDC6 gene and cell proliferation, knockdown of DP1 and DP2 expression did not afect ectopic E2F1- or E1a-induced expression of the tumor suppressor ARF gene, an upstream activator of the tumor suppressor p53, activation of p53 or apoptosis. These observations suggest that growth related and pro-apoptotic E2F targets are regulated by distinct molecular mechanisms and contradict the threshold model, which postulates that E2F activation of pro-apoptotic genes requires a higher total activity of activator E2Fs, above that necessary for E2F-dependent activation of growth-related genes. E2F family proteins (E2F1-E2F5) form heterodimeric complexes with DP family proteins (DP1 and DP2), gen- erating E2F transcriptional activity that regulates expression of growth-related target genes1–3. E2F activity is regulated by retinoblastoma (RB) family proteins (pRB, p107 and p130) during the cell cycle. RB family proteins directly bind to and inactivate E2F in the resting state. Normal growth signals, such as serum stimulation of fbroblasts, induce phosphorylation of RB family proteins by cyclin-dependent kinases (CDKs), resulting in an increase in E2F transcriptional activity, activation of the growth-related target genes, and subsequent cell cycle progression1–3.
    [Show full text]
  • Building an Automated Classification of DNA-Binding Protein Domains
    Vol. 18 Suppl. 2 2002 BIOINFORMATICS Pages S192–S201 Building an automated classification of DNA-binding protein domains Julia V. Ponomarenko 1, Philip E. Bourne 2 and Ilya N. Shindyalov 3,∗ 1Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, 10 Lavrentyeva Ave., Novosibirsk, 630090, Russia, 2Department of Downloaded from https://academic.oup.com/bioinformatics/article/18/suppl_2/S192/190705 by guest on 27 September 2021 Pharmacology and San Diego Supercomputer Center and 3San Diego Supercomputer Center, University of California San Diego, 9500 Gilman Drive, CA 92093-0505, La Jolla, USA Received on April 8, 2002; accepted on June 15, 2002 ABSTRACT by Luscombe et al. (2000). These complexes were Intensive growth in 3D structure data on DNA-protein classified into eight different structural/functional groups complexes as reflected in the Protein Data Bank containing a total of 54 structural families. Initial assign- (PDB) demands new approaches to the annotation and ment of proteins into eight groups was done manually characterization of these data and will lead to a new un- followed by detailed classification into structural families. derstanding of critical biological processes involving these The SSAP method of structural alignment (Orengo and data. These data and those from other protein structure Taylor, 1996) was used to assist in proper classification classifications will become increasingly important for the of individual proteins. Even though this classification modeling of complete proteomes. We propose a fully can be considered a standard, it is now far behind the automated classification of DNA-binding protein domains number of DNA-protein complexes available in the PDB.
    [Show full text]
  • Differential Gene Expression Induced by Verteporfin in Endometrial
    www.nature.com/scientificreports OPEN Diferential gene expression induced by Verteporfn in endometrial cancer cells Received: 12 July 2018 Lisa Gahyun Bang1, Venkata Ramesh Dasari2, Dokyoon Kim1,3 & Radhika P. Gogoi 2,4 Accepted: 7 February 2019 Endometrial cancer (EMCA) is a clinically heterogeneous disease. Previously, we tested the efcacy Published: xx xx xxxx of Verteporfn (VP) in EMCA cells and observed cytotoxic and anti-proliferative efects. In this study, we analyzed RNA sequencing data to investigate the comprehensive transcriptomic landscape of VP treated Type 1 EMCA cell lines, including HEC-1-A and HEC-1-B. There were 549 genes with diferential expression of two-fold or greater and P < 0.05 after false discovery rate correction for the HEC-1-B cell line. Positive regulation of TGFβ1 production, regulation of lipoprotein metabolic process, cell adhesion, endodermal cell diferentiation, formation and development, and integrin mediated signaling pathway were among the signifcantly associated terms. A functional enrichment analysis of diferentially expressed genes after VP treatment revealed extracellular matrix organization Gene Ontology as the most signifcant. CDC23 and BUB1B, two genes crucially involved in mitotic checkpoint progression, were found to be the pair with the best association from STRING among diferentially expressed genes in VP treated HEC-1-B cells. Our in vivo results indicate that subcutaneous tumors in mice were regressed after VP treatment by inhibiting cell cycle pathway proteins. The present study revealed multiple key genes of pathological signifcance in EMCA, thereby improving our understanding of molecular profles of EMCA cells. Endometrial cancer (EMCA) is a clinically heterogeneous disease.
    [Show full text]
  • Realtime Ready Plate Layout Human Cell Cycle Regulation Panel, 96
    For life science research only. FOR IN VITRO USE ONLY. Human Cell Cycle Regulation Panel, 96 Panel of prevalidated qPCR assays for gene expression profiling of human genes involved in cell cycle regulation Cat. No. 05 339 359 001 2 plates, each containing 96 assays Version November 2008 N Store at +2 to +8°C N Store protected from light! Plate Layout 123456789101112 A 1 2 3 4 5 6 7 8 9 10 11 12 ABL 1 ANAPC2 ANAPC4 ATM ATR BAX BCCIP BCL2 BIRC5 BRCA1 BRCA2 CCNA2 B 13 14 15 16 17 18 19 20 21 22 23 24 CCNB1 CCNB2 CCNC CCND1 CCND2 CCND3 CCNE1 CCNE2 CCNF CCNG1 CCNG2 CCNH C 25 26 27 28 29 30 31 32 33 34 35 36 CCNT1 CCNT2 CDC14A CDC16 CDC2 CDC20 CDC25A CDC25B CDC25C CDC34 CDK2 CDK4 D 37 38 39 40 41 42 43 44 45 46 47 48 CDK5R1 CDK6 CDK7 CDK8 CDKN1A CDKN1B CDKN2A CDKN2B CDKN3 CHEK1 CHEK2 CKS1B E 49 50 51 52 53 54 55 56 57 58 59 60 CKS2 CUL1 CUL2 CUL3 E2F1 E2F2 E2F3 E2F4 E2F5 E2F6 GADD45A GTF2H1 F 61 62 63 64 65 66 67 68 69 70 71 72 GTSE1 JUN KNTC1 KPNA2 LGALS3 MAD2L1 MAD2L2 MCM2 MCM3 MYC PCNA PLK1 G 73 74 75 76 77 78 79 80 81 82 83 84 RAD1 RAD17 RAD51 RAD9A RB1 RBL1 RBL2 SKP2 TFDP1 TFDP2 TP53 WEE1 H 85 86 87 88 89 90 91 92 93 94 95 96 ACTB B2M GAPDH HPRT1 RPL13A 18S YWHAZ RT+ RT+ RT+ RT- RT- H1 – H7: Reference genes H8 – H10: RT positive control H11 – H12: RT minus control Sample Details No.
    [Show full text]