A Novel Missense Mutation in HSF4 Causes Autosomal-Dominant
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Missense Mutations of MADH4: Characterization of the Mutational Hot Spot and Functional Consequences in Human Tumors
Vol. 10, 1597–1604, March 1, 2004 Clinical Cancer Research 1597 Featured Article Missense Mutations of MADH4: Characterization of the Mutational Hot Spot and Functional Consequences in Human Tumors Christine A. Iacobuzio-Donahue,1 Jason Song,5 Introduction Giovanni Parmiagiani,4 Charles J. Yeo,2,3 Human pancreatic ductal adenocarcinomas inactivate the Ralph H. Hruban,1,2 and Scott E. Kern2 tumor suppressor gene MADH4 (DPC4, SMAD4) with a high frequency (1). This inactivation occurs most commonly by Departments of 1Pathology, 2Oncology, 3Surgery, and 4Public Health, The Johns Hopkins Medical Institutions, Baltimore, Maryland, and homozygous deletion (HD), but some tumors may also inacti- 5Temple University School of Medicine, Philadelphia, Pennsylvania vate the gene by loss of heterozygosity (LOH) coupled with a mutation in the remaining allele. Inactivation by nonsense mu- tation may cause the loss of protein expression by enhanced Abstract proteosomal degradation (2, 3). Even when expressed as protein, Purpose and Experimental Design: The mutational spec- missense mutations may result in loss of a specific function of trum of MADH4 (DPC4/SMAD4) opens valuable insights the Madh4 protein such as DNA binding or Smad protein into the functions of this protein that confer its tumor- interactions (2–9). Thus, the location of these mutations can suppressive nature in human tumors. We present the provide clues to key structural features that mediate the tumor- MADH4 genetic status determined on a new set of pancre- suppressive function of MADH4. atic, biliary, and duodenal cancers with comparison to the Members of the Smad protein family, including Madh4, mutational data reported for various tumor types. -
4-6 Weeks Old Female C57BL/6 Mice Obtained from Jackson Labs Were Used for Cell Isolation
Methods Mice: 4-6 weeks old female C57BL/6 mice obtained from Jackson labs were used for cell isolation. Female Foxp3-IRES-GFP reporter mice (1), backcrossed to B6/C57 background for 10 generations, were used for the isolation of naïve CD4 and naïve CD8 cells for the RNAseq experiments. The mice were housed in pathogen-free animal facility in the La Jolla Institute for Allergy and Immunology and were used according to protocols approved by the Institutional Animal Care and use Committee. Preparation of cells: Subsets of thymocytes were isolated by cell sorting as previously described (2), after cell surface staining using CD4 (GK1.5), CD8 (53-6.7), CD3ε (145- 2C11), CD24 (M1/69) (all from Biolegend). DP cells: CD4+CD8 int/hi; CD4 SP cells: CD4CD3 hi, CD24 int/lo; CD8 SP cells: CD8 int/hi CD4 CD3 hi, CD24 int/lo (Fig S2). Peripheral subsets were isolated after pooling spleen and lymph nodes. T cells were enriched by negative isolation using Dynabeads (Dynabeads untouched mouse T cells, 11413D, Invitrogen). After surface staining for CD4 (GK1.5), CD8 (53-6.7), CD62L (MEL-14), CD25 (PC61) and CD44 (IM7), naïve CD4+CD62L hiCD25-CD44lo and naïve CD8+CD62L hiCD25-CD44lo were obtained by sorting (BD FACS Aria). Additionally, for the RNAseq experiments, CD4 and CD8 naïve cells were isolated by sorting T cells from the Foxp3- IRES-GFP mice: CD4+CD62LhiCD25–CD44lo GFP(FOXP3)– and CD8+CD62LhiCD25– CD44lo GFP(FOXP3)– (antibodies were from Biolegend). In some cases, naïve CD4 cells were cultured in vitro under Th1 or Th2 polarizing conditions (3, 4). -
Bio 102 Practice Problems Genetic Code and Mutation
Bio 102 Practice Problems Genetic Code and Mutation Multiple choice: Unless otherwise directed, circle the one best answer: 1. Choose the one best answer: Beadle and Tatum mutagenized Neurospora to find strains that required arginine to live. Based on the classification of their mutants, they concluded that: A. one gene corresponds to one protein. B. DNA is the genetic material. C. "inborn errors of metabolism" were responsible for many diseases. D. DNA replication is semi-conservative. E. protein cannot be the genetic material. 2. Choose the one best answer. Which one of the following is NOT part of the definition of a gene? A. A physical unit of heredity B. Encodes a protein C. Segement of a chromosome D. Responsible for an inherited characteristic E. May be linked to other genes 3. A mutation converts an AGA codon to a TGA codon (in DNA). This mutation is a: A. Termination mutation B. Missense mutation C. Frameshift mutation D. Nonsense mutation E. Non-coding mutation 4. Beadle and Tatum performed a series of complex experiments that led to the idea that one gene encodes one enzyme. Which one of the following statements does not describe their experiments? A. They deduced the metabolic pathway for the synthesis of an amino acid. B. Many different auxotrophic mutants of Neurospora were isolated. C. Cells unable to make arginine cannot survive on minimal media. D. Some mutant cells could survive on minimal media if they were provided with citrulline or ornithine. E. Homogentisic acid accumulates and is excreted in the urine of diseased individuals. 5. -
Supp Table 1.Pdf
Upregulated genes in Hdac8 null cranial neural crest cells fold change Gene Symbol Gene Title 134.39 Stmn4 stathmin-like 4 46.05 Lhx1 LIM homeobox protein 1 31.45 Lect2 leukocyte cell-derived chemotaxin 2 31.09 Zfp108 zinc finger protein 108 27.74 0710007G10Rik RIKEN cDNA 0710007G10 gene 26.31 1700019O17Rik RIKEN cDNA 1700019O17 gene 25.72 Cyb561 Cytochrome b-561 25.35 Tsc22d1 TSC22 domain family, member 1 25.27 4921513I08Rik RIKEN cDNA 4921513I08 gene 24.58 Ofa oncofetal antigen 24.47 B230112I24Rik RIKEN cDNA B230112I24 gene 23.86 Uty ubiquitously transcribed tetratricopeptide repeat gene, Y chromosome 22.84 D8Ertd268e DNA segment, Chr 8, ERATO Doi 268, expressed 19.78 Dag1 Dystroglycan 1 19.74 Pkn1 protein kinase N1 18.64 Cts8 cathepsin 8 18.23 1500012D20Rik RIKEN cDNA 1500012D20 gene 18.09 Slc43a2 solute carrier family 43, member 2 17.17 Pcm1 Pericentriolar material 1 17.17 Prg2 proteoglycan 2, bone marrow 17.11 LOC671579 hypothetical protein LOC671579 17.11 Slco1a5 solute carrier organic anion transporter family, member 1a5 17.02 Fbxl7 F-box and leucine-rich repeat protein 7 17.02 Kcns2 K+ voltage-gated channel, subfamily S, 2 16.93 AW493845 Expressed sequence AW493845 16.12 1600014K23Rik RIKEN cDNA 1600014K23 gene 15.71 Cst8 cystatin 8 (cystatin-related epididymal spermatogenic) 15.68 4922502D21Rik RIKEN cDNA 4922502D21 gene 15.32 2810011L19Rik RIKEN cDNA 2810011L19 gene 15.08 Btbd9 BTB (POZ) domain containing 9 14.77 Hoxa11os homeo box A11, opposite strand transcript 14.74 Obp1a odorant binding protein Ia 14.72 ORF28 open reading -
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. -
Supplementary Table S4. FGA Co-Expressed Gene List in LUAD
Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase -
Novel Mutations in HSF4 Cause Congenital Cataracts in Chinese
Cao et al. BMC Medical Genetics (2018) 19:150 https://doi.org/10.1186/s12881-018-0636-3 RESEARCH ARTICLE Open Access Novel mutations in HSF4 cause congenital cataracts in Chinese families Zongfu Cao2,3,4†, Yihua Zhu5†, Lijuan Liu6†, Shuangqing Wu7, Bing Liu5, Jianfu Zhuang8, Yi Tong5, Xiaole Chen1, Yongqing Xie1, Kaimei Nie1, Cailing Lu2,4,XuMa2,3,4* and Juhua Yang1* Abstract Background: Congenital cataract, a kind of cataract presenting at birth or during early childhood, is a leading cause of childhood blindness. To date, more than 30 genes on different chromosomes are known to cause this disorder. This study aimed to identify the HSF4 mutations in a cohort from Chinese families affected with congenital cataracts. Methods: Forty-two unrelated non-syndromic congenital cataract families and 112 ethnically matched controls from southeast China were recruited from the southeast of China. We employed Sanger sequencing method to discover the variants. To confirm the novel mutations, STR haplotypes were constructed to check the co- segregation with congenital cataract. The pathogenic potential of the novel mutations were assessed using bioinformatics tools including SIFT, Polyphen2, and Human Splicing Finder. The pathogenicity of all the mutations was evaluated by the guidelines of American College of Medical Genetics and InterVar software. Results: No previously reported HSF4 mutations were found in all the congenital cataract families. Five novel HSF4 mutations including c.187 T > C (p.Phe63Leu), c.218G > T (p.Arg73Leu), c.233A > G (p.Tyr78Cys), IVS5 c.233-1G > A and c.314G > C (p.Ser105Thr) were identified in five unrelated families with congenital cataracts, respectively. -
Nonsense and Missense Mutations in Hemophilia A: Estimate of the Relative Mutation Rate at CG Dinucleotides Hagop Youssoufian,* Stylianos E
Am. J. Hum. Genet. 42:718-725, 1988 Nonsense and Missense Mutations in Hemophilia A: Estimate of the Relative Mutation Rate at CG Dinucleotides Hagop Youssoufian,* Stylianos E. Antonarakis,* William Bell,t Anne M. Griffin,4 and Haig H. Kazazian, Jr.* *Genetics Unit, Department of Pediatrics, and tDivision of Hematology, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore; and tDivision of Hematology, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill Summary Hemophilia A is an X-linked disease of coagulation caused by deficiency of factor VIII. Using cloned cDNA and synthetic oligonucleotide probes, we have now screened 240 patients and found CG-to-TG transitions in an exon in nine. We have previously reported four of these patients; and here we report the remaining five, all of whom were severely affected. In one patient a TaqI site was lost in exon 23, and in the other four it was lost in exon 24. The novel exon 23 mutation is a CG-to-TG substitution at the codon for amino acid residue 2166, producing a nonsense codon in place of the normal codon for arginine. Simi- larly, the exon 24 mutations are also generated by CG-to-TG transitions, either on the sense strand produc- ing nonsense mutations or on the antisense strand producing missense mutations (Arg to Gln) at position 2228. The novel missense mutations are the first such mutations observed in association with severe hemo- philia A. These results provide further evidence that recurrent mutations are not uncommon in hemophilia A, and they also allow us to estimate that the extent of hypermutability of CG dinucleotides is 10-20 times greater than the average mutation rate for hemophilia A. -
The Genomics Era: the Future of Genetics in Medicine - Glossary
The Genomics Era: the Future of Genetics in Medicine - Glossary The glossary below provides a list of key terms used throughout the course. You do not need to read them all now; we’ll be linking back to the main glossary step wherever these terms appear, so you may refer back to this list if you are unsure of the terminology being used. Term Definition The process of matching reads back to their original Alignment position in the reference genome. An allele is one of a number of alternative forms of the same gene or genetic locus. We inherit one copy Allele of our genetic code from our mother and one copy of our genetic code from our father. Each copy is known as an allele. Microarray based genomic comparative hybridisation. This is a technique used to detect chromosome imbalances by comparing patient and control DNA and comparing differences between the two sets. It is Array CGH a useful technique for detecting small chromosome deletions and duplications which would not have been detected with more traditional karyotyping techniques. A unit of DNA. There are four bases which form the Base cross links (or rungs) of the DNA double helix: adenine (A), thymine (T), guanine (G) and cytosine (C). Capture see Target enrichment. The process by which a cell becomes specialized in Cell differentiation order to perform a specific function. Centromere The point at which the sister chromatids are joined. #1 FutureLearn A structure located in the nucleus all living cells, comprised of DNA bound around proteins called histones. The normal number of chromosomes in each Chromosome human cell nucleus is 46 and is composed of 22 pairs of autosomes and a pair of sex chromosomes which determine gender: males have an X and a Y chromosome whilst females have two X chromosomes. -
What Your Genome Doesn't Tell
UC San Diego UC San Diego Electronic Theses and Dissertations Title Multi-layered epigenetic control of T cell fate decisions Permalink https://escholarship.org/uc/item/8rs7c7b3 Author Yu, Bingfei Publication Date 2018 Peer reviewed|Thesis/dissertation eScholarship.org Powered by the California Digital Library University of California UNIVERSITY OF CALIFORNIA SAN DIEGO Multi-layered epigenetic control of T cell fate decisions A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Biology by Bingfei Yu Committee in charge: Professor Ananda Goldrath, Chair Professor John Chang Professor Stephen Hedrick Professor Cornelis Murre Professor Wei Wang 2018 Copyright Bingfei Yu, 2018 All rights reserved. The dissertation of Bingfei Yu is approved, and it is ac- ceptable in quality and form for publication on microfilm and electronically: Chair University of California San Diego 2018 iii DEDICATION To my parents who have been giving me countless love, trust and support to make me who I am. iv EPIGRAPH Stay hungary. Stay foolish. | Steve Jobs quoted from the back cover of the 1974 edition of the Whole Earth Catalog v TABLE OF CONTENTS Signature Page.................................. iii Dedication..................................... iv Epigraph.....................................v Table of Contents................................. vi List of Figures.................................. ix Acknowledgements................................x Vita........................................ xii Abstract of -
Mapping Mammalian Cell-Type-Specific Transcriptional
ORIGINAL RESEARCH published: 18 November 2015 doi: 10.3389/fgene.2015.00331 Mapping Mammalian Cell-type-specific Transcriptional Regulatory Networks Using KD-CAGE and ChIP-seq Data in the TC-YIK Cell Line Marina Lizio 1, 2, Yuri Ishizu 1, 2, Masayoshi Itoh 1, 2, 3, Timo Lassmann 1, 2, 4, Akira Hasegawa 1, 2, Atsutaka Kubosaki 1, Jessica Severin 1, 2, Hideya Kawaji 1, 2, 3, Yukio Nakamura 5, the FANTOM consortium 1, Harukazu Suzuki 1, 2, Yoshihide Hayashizaki 1, 3, Piero Carninci 1, 2 and Alistair R. R. Forrest 1, 2, 6* 1 RIKEN Center for Life Science Technologies, Yokohama, Japan, 2 Division of Genomic Technologies, RIKEN Center for Life Science Technologies, Yokohama, Japan, 3 RIKEN Preventive Medicine and Diagnosis Innovation Program, Yokohama, Edited by: Japan, 4 Telethon Kids Institute, The University of Western Australia, Subiaco, WA, Australia, 5 Cell Engineering Division, Edgar Wingender, RIKEN BioResource Center, Ibaraki, Japan, 6 QEII Medical Centre and Centre for Medical Research, Harry Perkins Institute of The University Medical Center Medical Research, The University of Western Australia, Nedlands, WA, Australia Göttingen, Germany Reviewed by: Mikael Boden, Mammals are composed of hundreds of different cell types with specialized functions. The University of Queensland, Each of these cellular phenotypes are controlled by different combinations of Australia transcription factors. Using a human non islet cell insulinoma cell line (TC-YIK) which Ka-Chun Wong, City University of Hong Kong, China expresses insulin and the majority of known pancreatic beta cell specific genes *Correspondence: as an example, we describe a general approach to identify key cell-type-specific Alistair R. -
Transcription Factor and Lncrna Regulatory Networks Identify Key Elements in Lung Adenocarcinoma
G C A T T A C G G C A T genes Article Transcription Factor and lncRNA Regulatory Networks Identify Key Elements in Lung Adenocarcinoma Dan Li 1, William Yang 2, Jialing Zhang 3, Jack Y. Yang 1, Renchu Guan 1 and Mary Qu Yang 1,* 1 Joint Bioinformatics Graduate Program, Department of Information Science, George W. Donaghey College of Engineering and Information Technology, University of Arkansas at Little Rock and University of Arkansas for Medical Sciences, 2801 S. University Ave, Little Rock, AR 72204, USA; [email protected] (D.L.); [email protected] (J.Y.Y.); [email protected] (R.G.) 2 School of Computer Science, Carnegie Mellon University, 5000 Forbes Ave, Pittsburgh, PA 15213, USA; [email protected] 3 Department of Genetics, Yale University, New Haven, CT 06520, USA; [email protected] * Correspondence: [email protected]; Tel.: +1-501-683-2035 Received: 19 September 2017; Accepted: 21 December 2017; Published: 5 January 2018 Abstract: Lung cancer is the second most commonly diagnosed carcinoma and is the leading cause of cancer death. Although significant progress has been made towards its understanding and treatment, unraveling the complexities of lung cancer is still hampered by a lack of comprehensive knowledge on the mechanisms underlying the disease. High-throughput and multidimensional genomic data have shed new light on cancer biology. In this study, we developed a network-based approach integrating somatic mutations, the transcriptome, DNA methylation, and protein-DNA interactions to reveal the key regulators in lung adenocarcinoma (LUAD). By combining Bayesian network analysis with tissue-specific transcription factor (TF) and targeted gene interactions, we inferred 15 disease-related core regulatory networks in co-expression gene modules associated with LUAD.