MIRA-Assisted Microarray Analysis, a New Technology for The

Total Page:16

File Type:pdf, Size:1020Kb

MIRA-Assisted Microarray Analysis, a New Technology for The Research Article MIRA-Assisted Microarray Analysis, a New Technology for the Determination of DNA Methylation Patterns, Identifies Frequent Methylation of Homeodomain-Containing Genes in Lung Cancer Cells Tibor Rauch,1 Hongwei Li,1 Xiwei Wu,2 and Gerd P. Pfeifer1 Divisions of 1Biology and 2Biomedical Informatics, Beckman Research Institute of the City of Hope, Duarte, California Abstract hypermethylation generally leads to inactivation of gene expres- We present a straightforward and comprehensive approach sion, this epigenetic alteration is considered to be a key mechanism for DNA methylation analysis in mammalian genomes. The for long-term silencing of tumor suppressor genes. The importance methylated-CpG island recovery assay (MIRA), which is based of promoter methylation in functional inactivation of lung cancer on the high affinity of the MBD2/MBD3L1 complex for suppressor genes is becoming increasingly recognized. It is methylated DNA, has been used to detect cell type–dependent estimated that between 0.5% and 3% of all genes carrying CpG- differences in DNA methylation on a microarray platform. The rich promoter sequences (so-called CpG islands) may be silenced procedure has been verified and applied to identify a series of by DNA methylation in lung cancer (1, 11). This means that there novel candidate lung tumor suppressor genes and potential are most likely several hundred genes that are incapacitated by this DNA methylation markers that contain methylated CpG pathway. Some of these genes may be bona fide tumor suppressor islands. One gene of particular interest was DLEC1, located genes, but in other cases, the methylation event may be a at a commonly deleted area on chromosome 3p22-p21.3, consequence of gene silencing or may somehow be associated with which was frequently methylated in primary lung cancers and tumor formation rather than being a cause of tumorigenesis. melanomas. Among the identified methylated genes, homeo- Several specific genes are methylated in lung cancer, including CDKN2A, RASSF1A, RARb, MGMT, GSTP1, CDH13, APC, DAPK, domain-containing genes were unusually frequent (11 of the TIMP3 top 50 hits) and were targeted on different chromosomes. , and several others (12–16). The methylation frequency These genes included LHX2, LHX4, PAX7, HOXB13, LBX1, SIX2, (the percentage of tumors analyzed that carry methylated alleles) HOXD3, DLX1, HOXD1, ONECUT2, and PAX9. The data show ranges from <10% to >80% but these numbers differ widely that MIRA-assisted microarray analysis has a low false- depending on the histologic type of tumor, the study population, positive rate and has the capacity to catalogue methylated and/or the methods used to assess methylation. To improve the CpG islands on a genome-wide basis. The results support the sensitivity of screening tools for the detection of early lung cancer, hypothesis that cancer-associated DNA methylation events DNA methylation markers have shown great promise (7, 17, 18). do not occur randomly throughout the genome but at least However, many more markers that could have improved specificity some are targeted by specific mechanisms. (Cancer Res 2006; in discriminating tumor from normal tissue and are methylated 66(16): 7939-47) at a high frequency in lung tumors have likely not yet been discovered. Introduction To analyze DNA methylation patterns on a genome-wide scale, several techniques have been developed, but none of them has yet In mammalian cells, the DNA base 5-methylcytosine occurs at ¶ reached wide acceptance. Most methods currently available are 5 -CpG dinucleotides and provides the basis for a common mode of labor-intensive and use methylation-sensitive restriction endonu- epigenetic inheritance. Changes in DNA methylation patterns cleases, and thus are limited by the occurrence of the respective occur in a developmental stage– and tissue-specific manner and sites within the target sequence. Another way to find methylated often accompany tumor development, most notably in the form of genes is by using expression microarrays to identify genes CpG island hypermethylation (1–10). During tumorigenesis, both reactivated by treatment with DNA methylation inhibitors (e.g., alleles of a tumor suppressor gene need to be inactivated by geno- ‘5-aza-deoxycytidine; refs. 19–21). This approach is effective but mic changes such as chromosomal deletions or loss-of-function can only be used with cell lines. Recently, genomic tiling and BAC mutations in the coding region of a gene. As an alternative microarrays have been introduced to map methylation patterns mechanism, transcriptional silencing by hypermethylation of CpG (22, 23). These methods are also limited, both in terms of their level islands spanning the promoter regions of tumor suppressor genes of resolution and in terms of the requirements for restriction is a common and important process in carcinogenesis. Because endonuclease recognition sites. An antibody against 5-methylcyto- sine has been used in immunoprecipitation experiments combined with microarrays (6, 23). However, this antibody requires ssDNA for recognition, which is sometimes difficult to achieve in CpG-rich Note: Supplementary data for this article are available at Cancer Research Online DNA regions. Here we describe a new genome-wide DNA (http://cancerres.aacrjournals.org/). Requests for reprints: Gerd P. Pfeifer, Division of Biology, Beckman Research methylation detection method that depends neither on restriction Institute of the City of Hope, 1500 East Duarte Road, Duarte, CA 91010. Phone: 626- endonucleases nor on specific antibodies. This method is based on 301-8853; Fax: 626-358-7703; E-mail: [email protected]. I2006American Association for Cancer Research. the methylated-CpG island recovery assay (MIRA), which we doi:10.1158/0008-5472.CAN-06-1888 previously applied for testing the methylation status of specific www.aacrjournals.org 7939 Cancer Res 2006; 66: (16). August 15, 2006 Downloaded from cancerres.aacrjournals.org on September 23, 2021. © 2006 American Association for Cancer Research. Cancer Research genes (24). It makes use of the high affinity of the MBD2b/MBD3L1 log 2 ratios between the dye swap pairs. Based on our experience, the complex for methylated DNA (24, 25). Here we show that MIRA can combined Lowess and dye swap normalization approach can best reduce be used to analyze the DNA methylation status of a large number of variability. CpG island methylation profiles were determined by ratios genes simultaneously using a microarray approach. between MIRA-enriched and unenriched samples (enrichment factor) for both tumor and normal tissues. The ratios of the enrichment factors between cancer and normal DNA samples will measure the methylation Materials and Methods difference between cancer and normal tissue. To identify the CpG islands MIRA and microarray analysis. DNA obtained from normal human that are differentially methylated between normal and tumor cell DNA, bronchial epithelial (NHBE) cells and from the lung cancer cell line A549 methylation profiles were compared using statistical linear model in was digested with MseI(5¶-TTAA), which produces small (f200-300 bp) LIMMA. For target gene selection, unadjusted P values were set at a level fragments and generally cuts outside of CpG islands. Linkers (upper of 0.05, and the fold change between cancer MIRA/Input versus normal strand sequence, 5¶-TAGAATTCAGATCTCCCG-3¶; lower strand sequence, MIRA/Input (difference factor) was set at >2. Direct comparison of MIRA- 3¶-CTTAAGTCTAGAGGGCCCAGTGGCG-5¶) were ligated to the MseI- enriched fractions from tumor and normal tissue DNA provided digested DNA and enrichment of the methylated fraction was done by independent confirmation for the methylation differences observed MIRA as previously described (24). Briefly, 1 Ag of purified GST-tagged although the latter analysis may be affected by differences in gene copy MBD2b protein and 1 Ag of purified His-tagged MBD3L1 protein were numbers between normal and tumor tissue. preincubated and bound to a glutathione sepharose CL-4B matrix DNA methylation analysis using combined bisulfite restriction (Amersham Biosciences, Piscataway, NJ). The plasmids used to produce analysis and bisulfite sequencing. DNA was isolated from cell lines or these proteins are available on request. This matrix was incubated with 500 frozen tumors and matched normal tissue by standard phenol-chloroform ng of MseI-cut and linker-ligated genomic DNA in 400 AL of a binding extraction and ethanol precipitation. Non–small-cell lung carcinoma tumor reaction mixture [10 mmol/L Tris-HCl (pH 7.5), 50 mmol/L NaCl, 1 mmol/L tissue samples and matching normal tissues removed with surgery were EDTA, 1 mmol/L DTT, 3 mmol/L MgCl2, 0.1% Triton-X100, 5% glycerol, obtained from the frozen tumor bank of the City of Hope National Medical 25 Ag/mL bovine serum albumin, and 1.25 Ag/mL sonicated JM110 (dcm Center. The combined bisulfite restriction analysis (COBRA) assays were minus) bacterial DNA] for 240 minutes at 4jC on a rocking platform. After done using the method of Xiong and Laird (28). DNA was treated with washing the pelletted sepharose beads thrice with binding buffer containing sodium bisulfite and purified as described (24). PCR primers for 700 mmol/L NaCl, the methylated DNA–enriched genomic DNA fraction amplification of specific targets in bisulfite-treated DNA are listed in was eluted by addition of guanidinium hydrochloride–containing buffer and Supplementary Table S1. For sequence analysis, the PCR products
Recommended publications
  • Six3 Overexpression Initiates the Formation of Ectopic Retina
    Downloaded from genesdev.cshlp.org on October 6, 2021 - Published by Cold Spring Harbor Laboratory Press RESEARCH COMMUNICATION in the developing eye and ventral forebrain. Recently, in Six3 overexpression initiates Drosophila a member of the Six subclass of homeobox the formation of ectopic retina genes, optix, has been isolated, which by sequence com- parison of the homeobox appears to be the ortholog of Felix Loosli, Sylke Winkler, Six3 (Toy et al. 1998). Functional analysis of optix, how- 1 and Joachim Wittbrodt ever, has not yet been reported. In medaka fish (Oryzias latipes) Six3 is expressed in Sonderforschungsbereich (SFB) Junior Group, Institute for Human Genetics, University of Go¨ ttingen, c/o the anterior-most neuroectoderm at gastrula stages and Max-Planck-Institute (MPI) for Biophysical Chemistry, Am later in the developing retina (Loosli et al. 1998). Mosaic Fassberg, 37077 Go¨ttingen, Germany misexpression of mouse Six3 in small clones, in response to injected plasmid DNA, resulted in the formation of The homeobox gene sine oculis (so) is essential for visual ectopic lenses in the region of the otic vesicle, suggesting system formation in Drosophila. A vertebrate member a decisive role for Six3 during vertebrate lens develop- of the so/Six gene family, Six3, is expressed in the devel- ment (Oliver et al. 1996). Considering the expression of oping eye and forebrain. Injection of Six3 RNA into Six3 in the retinal primordia and the essential role of a medaka fish embryos causes ectopic Pax6 and Rx2 ex- Drosophila homolog, so,inDrosophila eye develop- pression in midbrain and cerebellum, resulting in the ment, we investigated a potential role of Six3 in early formation of ectopic retinal primordia.
    [Show full text]
  • Table S1 the Four Gene Sets Derived from Gene Expression Profiles of Escs and Differentiated Cells
    Table S1 The four gene sets derived from gene expression profiles of ESCs and differentiated cells Uniform High Uniform Low ES Up ES Down EntrezID GeneSymbol EntrezID GeneSymbol EntrezID GeneSymbol EntrezID GeneSymbol 269261 Rpl12 11354 Abpa 68239 Krt42 15132 Hbb-bh1 67891 Rpl4 11537 Cfd 26380 Esrrb 15126 Hba-x 55949 Eef1b2 11698 Ambn 73703 Dppa2 15111 Hand2 18148 Npm1 11730 Ang3 67374 Jam2 65255 Asb4 67427 Rps20 11731 Ang2 22702 Zfp42 17292 Mesp1 15481 Hspa8 11807 Apoa2 58865 Tdh 19737 Rgs5 100041686 LOC100041686 11814 Apoc3 26388 Ifi202b 225518 Prdm6 11983 Atpif1 11945 Atp4b 11614 Nr0b1 20378 Frzb 19241 Tmsb4x 12007 Azgp1 76815 Calcoco2 12767 Cxcr4 20116 Rps8 12044 Bcl2a1a 219132 D14Ertd668e 103889 Hoxb2 20103 Rps5 12047 Bcl2a1d 381411 Gm1967 17701 Msx1 14694 Gnb2l1 12049 Bcl2l10 20899 Stra8 23796 Aplnr 19941 Rpl26 12096 Bglap1 78625 1700061G19Rik 12627 Cfc1 12070 Ngfrap1 12097 Bglap2 21816 Tgm1 12622 Cer1 19989 Rpl7 12267 C3ar1 67405 Nts 21385 Tbx2 19896 Rpl10a 12279 C9 435337 EG435337 56720 Tdo2 20044 Rps14 12391 Cav3 545913 Zscan4d 16869 Lhx1 19175 Psmb6 12409 Cbr2 244448 Triml1 22253 Unc5c 22627 Ywhae 12477 Ctla4 69134 2200001I15Rik 14174 Fgf3 19951 Rpl32 12523 Cd84 66065 Hsd17b14 16542 Kdr 66152 1110020P15Rik 12524 Cd86 81879 Tcfcp2l1 15122 Hba-a1 66489 Rpl35 12640 Cga 17907 Mylpf 15414 Hoxb6 15519 Hsp90aa1 12642 Ch25h 26424 Nr5a2 210530 Leprel1 66483 Rpl36al 12655 Chi3l3 83560 Tex14 12338 Capn6 27370 Rps26 12796 Camp 17450 Morc1 20671 Sox17 66576 Uqcrh 12869 Cox8b 79455 Pdcl2 20613 Snai1 22154 Tubb5 12959 Cryba4 231821 Centa1 17897
    [Show full text]
  • Supplemental Materials ZNF281 Enhances Cardiac Reprogramming
    Supplemental Materials ZNF281 enhances cardiac reprogramming by modulating cardiac and inflammatory gene expression Huanyu Zhou, Maria Gabriela Morales, Hisayuki Hashimoto, Matthew E. Dickson, Kunhua Song, Wenduo Ye, Min S. Kim, Hanspeter Niederstrasser, Zhaoning Wang, Beibei Chen, Bruce A. Posner, Rhonda Bassel-Duby and Eric N. Olson Supplemental Table 1; related to Figure 1. Supplemental Table 2; related to Figure 1. Supplemental Table 3; related to the “quantitative mRNA measurement” in Materials and Methods section. Supplemental Table 4; related to the “ChIP-seq, gene ontology and pathway analysis” and “RNA-seq” and gene ontology analysis” in Materials and Methods section. Supplemental Figure S1; related to Figure 1. Supplemental Figure S2; related to Figure 2. Supplemental Figure S3; related to Figure 3. Supplemental Figure S4; related to Figure 4. Supplemental Figure S5; related to Figure 6. Supplemental Table S1. Genes included in human retroviral ORF cDNA library. Gene Gene Gene Gene Gene Gene Gene Gene Symbol Symbol Symbol Symbol Symbol Symbol Symbol Symbol AATF BMP8A CEBPE CTNNB1 ESR2 GDF3 HOXA5 IL17D ADIPOQ BRPF1 CEBPG CUX1 ESRRA GDF6 HOXA6 IL17F ADNP BRPF3 CERS1 CX3CL1 ETS1 GIN1 HOXA7 IL18 AEBP1 BUD31 CERS2 CXCL10 ETS2 GLIS3 HOXB1 IL19 AFF4 C17ORF77 CERS4 CXCL11 ETV3 GMEB1 HOXB13 IL1A AHR C1QTNF4 CFL2 CXCL12 ETV7 GPBP1 HOXB5 IL1B AIMP1 C21ORF66 CHIA CXCL13 FAM3B GPER HOXB6 IL1F3 ALS2CR8 CBFA2T2 CIR1 CXCL14 FAM3D GPI HOXB7 IL1F5 ALX1 CBFA2T3 CITED1 CXCL16 FASLG GREM1 HOXB9 IL1F6 ARGFX CBFB CITED2 CXCL3 FBLN1 GREM2 HOXC4 IL1F7
    [Show full text]
  • Genome-Wide DNA Methylation Analysis of KRAS Mutant Cell Lines Ben Yi Tew1,5, Joel K
    www.nature.com/scientificreports OPEN Genome-wide DNA methylation analysis of KRAS mutant cell lines Ben Yi Tew1,5, Joel K. Durand2,5, Kirsten L. Bryant2, Tikvah K. Hayes2, Sen Peng3, Nhan L. Tran4, Gerald C. Gooden1, David N. Buckley1, Channing J. Der2, Albert S. Baldwin2 ✉ & Bodour Salhia1 ✉ Oncogenic RAS mutations are associated with DNA methylation changes that alter gene expression to drive cancer. Recent studies suggest that DNA methylation changes may be stochastic in nature, while other groups propose distinct signaling pathways responsible for aberrant methylation. Better understanding of DNA methylation events associated with oncogenic KRAS expression could enhance therapeutic approaches. Here we analyzed the basal CpG methylation of 11 KRAS-mutant and dependent pancreatic cancer cell lines and observed strikingly similar methylation patterns. KRAS knockdown resulted in unique methylation changes with limited overlap between each cell line. In KRAS-mutant Pa16C pancreatic cancer cells, while KRAS knockdown resulted in over 8,000 diferentially methylated (DM) CpGs, treatment with the ERK1/2-selective inhibitor SCH772984 showed less than 40 DM CpGs, suggesting that ERK is not a broadly active driver of KRAS-associated DNA methylation. KRAS G12V overexpression in an isogenic lung model reveals >50,600 DM CpGs compared to non-transformed controls. In lung and pancreatic cells, gene ontology analyses of DM promoters show an enrichment for genes involved in diferentiation and development. Taken all together, KRAS-mediated DNA methylation are stochastic and independent of canonical downstream efector signaling. These epigenetically altered genes associated with KRAS expression could represent potential therapeutic targets in KRAS-driven cancer. Activating KRAS mutations can be found in nearly 25 percent of all cancers1.
    [Show full text]
  • Predicting Clinical Response to Treatment with a Soluble Tnf-Antagonist Or Tnf, Or a Tnf Receptor Agonist
    (19) TZZ _ __T (11) EP 2 192 197 A1 (12) EUROPEAN PATENT APPLICATION (43) Date of publication: (51) Int Cl.: 02.06.2010 Bulletin 2010/22 C12Q 1/68 (2006.01) (21) Application number: 08170119.5 (22) Date of filing: 27.11.2008 (84) Designated Contracting States: (72) Inventor: The designation of the inventor has not AT BE BG CH CY CZ DE DK EE ES FI FR GB GR yet been filed HR HU IE IS IT LI LT LU LV MC MT NL NO PL PT RO SE SI SK TR (74) Representative: Habets, Winand Designated Extension States: Life Science Patents AL BA MK RS PO Box 5096 6130 PB Sittard (NL) (71) Applicant: Vereniging voor Christelijk Hoger Onderwijs, Wetenschappelijk Onderzoek en Patiëntenzorg 1081 HV Amsterdam (NL) (54) Predicting clinical response to treatment with a soluble tnf-antagonist or tnf, or a tnf receptor agonist (57) The invention relates to methods for predicting a clinical response to a therapy with a soluble TNF antagonist, TNF or a TNF receptor agonist and a kit for use in said methods. EP 2 192 197 A1 Printed by Jouve, 75001 PARIS (FR) EP 2 192 197 A1 Description [0001] The invention relates to methods for predicting a clinical response to a treatment with a soluble TNF antagonist, with TNF or a TNF receptor agonist using expression levels of genes of the Type I INF pathway and a kit for use in said 5 methods. In another aspect, the invention relates to a method for evaluating a pharmacological effect of a treatment with a soluble TNF antagonist, TNF or a TNF receptor agonist.
    [Show full text]
  • Association of Gene Ontology Categories with Decay Rate for Hepg2 Experiments These Tables Show Details for All Gene Ontology Categories
    Supplementary Table 1: Association of Gene Ontology Categories with Decay Rate for HepG2 Experiments These tables show details for all Gene Ontology categories. Inferences for manual classification scheme shown at the bottom. Those categories used in Figure 1A are highlighted in bold. Standard Deviations are shown in parentheses. P-values less than 1E-20 are indicated with a "0". Rate r (hour^-1) Half-life < 2hr. Decay % GO Number Category Name Probe Sets Group Non-Group Distribution p-value In-Group Non-Group Representation p-value GO:0006350 transcription 1523 0.221 (0.009) 0.127 (0.002) FASTER 0 13.1 (0.4) 4.5 (0.1) OVER 0 GO:0006351 transcription, DNA-dependent 1498 0.220 (0.009) 0.127 (0.002) FASTER 0 13.0 (0.4) 4.5 (0.1) OVER 0 GO:0006355 regulation of transcription, DNA-dependent 1163 0.230 (0.011) 0.128 (0.002) FASTER 5.00E-21 14.2 (0.5) 4.6 (0.1) OVER 0 GO:0006366 transcription from Pol II promoter 845 0.225 (0.012) 0.130 (0.002) FASTER 1.88E-14 13.0 (0.5) 4.8 (0.1) OVER 0 GO:0006139 nucleobase, nucleoside, nucleotide and nucleic acid metabolism3004 0.173 (0.006) 0.127 (0.002) FASTER 1.28E-12 8.4 (0.2) 4.5 (0.1) OVER 0 GO:0006357 regulation of transcription from Pol II promoter 487 0.231 (0.016) 0.132 (0.002) FASTER 6.05E-10 13.5 (0.6) 4.9 (0.1) OVER 0 GO:0008283 cell proliferation 625 0.189 (0.014) 0.132 (0.002) FASTER 1.95E-05 10.1 (0.6) 5.0 (0.1) OVER 1.50E-20 GO:0006513 monoubiquitination 36 0.305 (0.049) 0.134 (0.002) FASTER 2.69E-04 25.4 (4.4) 5.1 (0.1) OVER 2.04E-06 GO:0007050 cell cycle arrest 57 0.311 (0.054) 0.133 (0.002)
    [Show full text]
  • Transient Activation of Meox1 Is an Early Component of the Gene
    View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Access to Research and Communications Annals 1 Transient activation of Meox1 is an early component of the gene 2 regulatory network downstream of Hoxa2. 3 4 Pavel Kirilenko1, Guiyuan He1, Baljinder Mankoo2, Moises Mallo3, Richard Jones4, 5 5 and Nicoletta Bobola1,* 6 7 (1) School of Dentistry, Faculty of Medical and Human Sciences, University of 8 Manchester, Manchester, UK. 9 (2) Randall Division of Cell and Molecular Biophysics, King's College London, UK. 10 (3) Instituto Gulbenkian de Ciência, Oeiras, Portugal. 11 (4) Genetic Medicine, Manchester Academic Health Science Centre, Central 12 Manchester University Hospitals NHS Foundation Trust, Manchester, UK. 13 (5) Present address: Department of Biology, University of York, York, UK. 14 15 Running title: Hoxa2 activates Meox1 expression. 16 Keywords: Meox1, Hoxa2, homeodomain, development, mouse 17 *Words Count: Material and Methods: 344; Introduction, Results and Discussion: 18 3679 19 19 * Author for correspondence at: AV Hill Building The University of Manchester Manchester M13 9PT United Kingdom Phone: (+44) 161 3060642 E-mail: [email protected] 1 Abstract 2 Hox genes encode transcription factors that regulate morphogenesis in all animals 3 with bilateral symmetry. Although Hox genes have been extensively studied, their 4 molecular function is not clear in vertebrates, and only a limited number of genes 5 regulated by Hox transcription factors have been identified. Hoxa2 is required for 6 correct development of the second branchial arch, its major domain of expression. 7 We now show that Meox1 is genetically downstream from Hoxa2 and is a direct 8 target.
    [Show full text]
  • SUPPLEMENTARY MATERIAL Bone Morphogenetic Protein 4 Promotes
    www.intjdevbiol.com doi: 10.1387/ijdb.160040mk SUPPLEMENTARY MATERIAL corresponding to: Bone morphogenetic protein 4 promotes craniofacial neural crest induction from human pluripotent stem cells SUMIYO MIMURA, MIKA SUGA, KAORI OKADA, MASAKI KINEHARA, HIROKI NIKAWA and MIHO K. FURUE* *Address correspondence to: Miho Kusuda Furue. Laboratory of Stem Cell Cultures, National Institutes of Biomedical Innovation, Health and Nutrition, 7-6-8, Saito-Asagi, Ibaraki, Osaka 567-0085, Japan. Tel: 81-72-641-9819. Fax: 81-72-641-9812. E-mail: [email protected] Full text for this paper is available at: http://dx.doi.org/10.1387/ijdb.160040mk TABLE S1 PRIMER LIST FOR QRT-PCR Gene forward reverse AP2α AATTTCTCAACCGACAACATT ATCTGTTTTGTAGCCAGGAGC CDX2 CTGGAGCTGGAGAAGGAGTTTC ATTTTAACCTGCCTCTCAGAGAGC DLX1 AGTTTGCAGTTGCAGGCTTT CCCTGCTTCATCAGCTTCTT FOXD3 CAGCGGTTCGGCGGGAGG TGAGTGAGAGGTTGTGGCGGATG GAPDH CAAAGTTGTCATGGATGACC CCATGGAGAAGGCTGGGG MSX1 GGATCAGACTTCGGAGAGTGAACT GCCTTCCCTTTAACCCTCACA NANOG TGAACCTCAGCTACAAACAG TGGTGGTAGGAAGAGTAAAG OCT4 GACAGGGGGAGGGGAGGAGCTAGG CTTCCCTCCAACCAGTTGCCCCAAA PAX3 TTGCAATGGCCTCTCAC AGGGGAGAGCGCGTAATC PAX6 GTCCATCTTTGCTTGGGAAA TAGCCAGGTTGCGAAGAACT p75 TCATCCCTGTCTATTGCTCCA TGTTCTGCTTGCAGCTGTTC SOX9 AATGGAGCAGCGAAATCAAC CAGAGAGATTTAGCACACTGATC SOX10 GACCAGTACCCGCACCTG CGCTTGTCACTTTCGTTCAG Suppl. Fig. S1. Comparison of the gene expression profiles of the ES cells and the cells induced by NC and NC-B condition. Scatter plots compares the normalized expression of every gene on the array (refer to Table S3). The central line
    [Show full text]
  • Supplementary Material
    BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any reliance Supplemental material placed on this supplemental material which has been supplied by the author(s) J Neurol Neurosurg Psychiatry Page 1 / 45 SUPPLEMENTARY MATERIAL Appendix A1: Neuropsychological protocol. Appendix A2: Description of the four cases at the transitional stage. Table A1: Clinical status and center proportion in each batch. Table A2: Complete output from EdgeR. Table A3: List of the putative target genes. Table A4: Complete output from DIANA-miRPath v.3. Table A5: Comparison of studies investigating miRNAs from brain samples. Figure A1: Stratified nested cross-validation. Figure A2: Expression heatmap of miRNA signature. Figure A3: Bootstrapped ROC AUC scores. Figure A4: ROC AUC scores with 100 different fold splits. Figure A5: Presymptomatic subjects probability scores. Figure A6: Heatmap of the level of enrichment in KEGG pathways. Kmetzsch V, et al. J Neurol Neurosurg Psychiatry 2021; 92:485–493. doi: 10.1136/jnnp-2020-324647 BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any reliance Supplemental material placed on this supplemental material which has been supplied by the author(s) J Neurol Neurosurg Psychiatry Appendix A1. Neuropsychological protocol The PREV-DEMALS cognitive evaluation included standardized neuropsychological tests to investigate all cognitive domains, and in particular frontal lobe functions. The scores were provided previously (Bertrand et al., 2018). Briefly, global cognitive efficiency was evaluated by means of Mini-Mental State Examination (MMSE) and Mattis Dementia Rating Scale (MDRS). Frontal executive functions were assessed with Frontal Assessment Battery (FAB), forward and backward digit spans, Trail Making Test part A and B (TMT-A and TMT-B), Wisconsin Card Sorting Test (WCST), and Symbol-Digit Modalities test.
    [Show full text]
  • Transcriptional and Post-Transcriptional Regulation of ATP-Binding Cassette Transporter Expression
    Transcriptional and Post-transcriptional Regulation of ATP-binding Cassette Transporter Expression by Aparna Chhibber DISSERTATION Submitted in partial satisfaction of the requirements for the degree of DOCTOR OF PHILOSOPHY in Pharmaceutical Sciences and Pbarmacogenomies in the Copyright 2014 by Aparna Chhibber ii Acknowledgements First and foremost, I would like to thank my advisor, Dr. Deanna Kroetz. More than just a research advisor, Deanna has clearly made it a priority to guide her students to become better scientists, and I am grateful for the countless hours she has spent editing papers, developing presentations, discussing research, and so much more. I would not have made it this far without her support and guidance. My thesis committee has provided valuable advice through the years. Dr. Nadav Ahituv in particular has been a source of support from my first year in the graduate program as my academic advisor, qualifying exam committee chair, and finally thesis committee member. Dr. Kathy Giacomini graciously stepped in as a member of my thesis committee in my 3rd year, and Dr. Steven Brenner provided valuable input as thesis committee member in my 2nd year. My labmates over the past five years have been incredible colleagues and friends. Dr. Svetlana Markova first welcomed me into the lab and taught me numerous laboratory techniques, and has always been willing to act as a sounding board. Michael Martin has been my partner-in-crime in the lab from the beginning, and has made my days in lab fly by. Dr. Yingmei Lui has made the lab run smoothly, and has always been willing to jump in to help me at a moment’s notice.
    [Show full text]
  • MIRA-Assisted Microarray Analysis, a New Technology for The
    Research Article MIRA-Assisted Microarray Analysis, a New Technology for the Determination of DNA Methylation Patterns, Identifies Frequent Methylation of Homeodomain-Containing Genes in Lung Cancer Cells Tibor Rauch,1 Hongwei Li,1 Xiwei Wu,2 and Gerd P. Pfeifer1 Divisions of 1Biology and 2Biomedical Informatics, Beckman Research Institute of the City of Hope, Duarte, California Abstract hypermethylation generally leads to inactivation of gene expres- We present a straightforward and comprehensive approach sion, this epigenetic alteration is considered to be a key mechanism for DNA methylation analysis in mammalian genomes. The for long-term silencing of tumor suppressor genes. The importance methylated-CpG island recovery assay (MIRA), which is based of promoter methylation in functional inactivation of lung cancer on the high affinity of the MBD2/MBD3L1 complex for suppressor genes is becoming increasingly recognized. It is methylated DNA, has been used to detect cell type–dependent estimated that between 0.5% and 3% of all genes carrying CpG- differences in DNA methylation on a microarray platform. The rich promoter sequences (so-called CpG islands) may be silenced procedure has been verified and applied to identify a series of by DNA methylation in lung cancer (1, 11). This means that there novel candidate lung tumor suppressor genes and potential are most likely several hundred genes that are incapacitated by this DNA methylation markers that contain methylated CpG pathway. Some of these genes may be bona fide tumor suppressor islands. One gene of particular interest was DLEC1, located genes, but in other cases, the methylation event may be a at a commonly deleted area on chromosome 3p22-p21.3, consequence of gene silencing or may somehow be associated with which was frequently methylated in primary lung cancers and tumor formation rather than being a cause of tumorigenesis.
    [Show full text]
  • Rapid Evolution of Mammalian X-Linked Testis-Expressed Homeobox Genes
    Copyright 2004 by the Genetics Society of America DOI: 10.1534/genetics.103.025072 Rapid Evolution of Mammalian X-Linked Testis-Expressed Homeobox Genes Xiaoxia Wang and Jianzhi Zhang1 Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, Michigan 48109 Manuscript received November 26, 2003 Accepted for publication February 11, 2004 ABSTRACT Homeobox genes encode transcription factors that function in various developmental processes and are usually evolutionarily conserved in their sequences. However, two X-chromosome-linked testis-expressed homeobox genes, one from rodents and the other from fruit flies, are known to evolve rapidly under positive Darwinian selection. Here we report yet another case, from primates. TGIFLX is an X-linked homeobox gene that originated by retroposition of the autosomal gene TGIF2, most likely in a common ancestor of rodents and primates. While TGIF2 is ubiquitously expressed, TGIFLX is exclusively expressed in adult testis. A comparison of the TGIFLX sequences among 16 anthropoid primates revealed a signifi- cantly higher rate of nonsynonymous nucleotide substitution (dN) than synonymous substitution (dS), strongly suggesting the action of positive selection. Although the high dN/dS ratio is most evident outside ف the homeobox, the homeobox has a dN/dS of 0.89 and includes two codons that are likely under selection. Furthermore, the rate of radical amino acid substitutions that alter amino acid charge is significantly greater than that of conservative substitutions, suggesting that the selection promotes diversity of the protein charge profile. More interestingly, an analysis of 64 orthologous homeobox genes from humans and mice shows substantially higher rates of amino acid substitution in X-linked testis-expressed genes than in other genes.
    [Show full text]