DOCSLIB.ORG

A Genetic Screening Identifies a Component of the SWI/SNF Complex, Arid1b As a Senescence Regulator

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text

Load more

A genetic screening identifies a component of the SWI/SNF complex, Arid1b as a senescence regulator

Sadaf Khan
A thesis submitted to Imperial College London for the degree of Doctor in Philosophy

MRC Clinical Sciences Centre
Imperial College London, School of Medicine

July 2013

Statement of originality

All experiments included in this thesis were performed by myself unless otherwise stated.

Copyright Declaration

The copyright of this thesis rests with the author and is made available under a Creative Commons Attribution Non-Commercial No Derivatives license. Researchers are free to copy, distribute or transmit the thesis on the condition that they attribute it, that they do not use it for commercial purposes and that they do not alter, transform or build upon it. For any reuse or redistribution, researchers must make clear to others the license terms of this work.

2

Abstract

Senescence is an important tumour suppressor mechanism, which prevents the proliferation of stressed or damaged cells. The use of RNA interference to identify genes with a role in senescence is an important tool in the discovery of novel cancer genes. In this work, a protocol was established for conducting bypass of senescence screenings, using shRNA libraries together with next-generation sequencing. Using this approach, the SWI/SNF subunit Arid1b was identified as a regulator of cellular lifespan in MEFs. SWI/SNF is a large multi-subunit complex that remodels chromatin. Mutations in SWI/SNF proteins are frequently associated with cancer, suggesting that SWI/SNF components are tumour suppressors.
Here the role of ARID1B during senescence was investigated. Depletion of ARID1B extends the proliferative capacity of primary mouse and human fibroblasts. Furthermore, in cells expressing mutant RASG12V and PIK3CAH1047R, ARID1B is necessary for the maintenance of oncogene-induced senescence (OIS). Knockdown of ARID1B during OIS results in reduced expression of the CKIs p21Cip1 and p16INK4a. Many SWI/SNF proteins are post-transcriptionally induced during both replicative senescence and OIS, suggesting a broader role for the SWI/SNF complex in senescence.
Ectopic expression of components of the SWI/SNF complex induced premature senescence associated with an increase in p21Cip1 and p16INK4a protein levels. SILAC analysis of global changes in protein levels identified enrichment of mitochondrial proteins and depletion of mitotic proteins upon ARID1B expression. Mitochondrial dysfunction and ROS production are important in ARID1B expressing cells as growth arrest was rescued using antioxidant N-acetyl-cysteine. Finally, analysis of cancer genome sequencing data has identified ARID1B as a mutational-driver gene in some cancers. In these tumours, ARID1B mutations are often associated with mutations in TP53 and PTEN. Altogether the present evidence suggests that regulation of senescence by different mechanisms contributes to explain the tumour suppressive properties of the SWI/SNF complex.

3

Acknowledgements

All thanks is for God and Jesus. I am truly grateful for the opportunity to do what I love every day. Throughout my life I have been blessed with amazing teachers who are very important to me. Thank you to Ana, for always going the extra mile to help me. Thank you for always being there for me ♥. You are “the buzz lightyear to my woody”.

Thank you to Juan Carlos and to Selina for the continual encouragement and help over the last few years, and for advising me with your experience every step of the way!! Much of the work wouldn’t have been possible without ‘the horrids’. Marta, thank you for being my inspiration, thank you for all that you did for me, I will never forget it. The day the two big slaves left the little slave was very Meireles, but Nik, YNWA! Thanks Migi for bringing me into your group of “kids” and for being a great friend.

I would like to thank ALL the cool people in the CSC for making my time here so fun. Thank you my partner in distraction, Ines for teaching me ChIP sukhi para me :D. Where were you when Aguero scored 94th minute vs QPR? I was in Bram’s office destroying his ear drums :’), thanks for SO many things, not least the MS, and Vesela thanks for your 5% input ;). Thanks Tom for introducing me to Ronald ‘The Don’ Fisher and the Genomics lab for the NGS optimisation. Thanks also to Angeles, Nuria, Joao and Rita for fun times  and everyone in CP.

Thank you to Mike, for always checking up on me in the night, and Curtis for bringing my 20 boxes with a huge smile. You guys were “The Constant” when I was “unstuck in time”. To all the footie boys thanks for making Mondays worth it: thanks to my “favourite” Fico for filling a huge gap (fatass!) when Ana left. Jorge + Vlad your feedback on my work was absolutely priceless thank you! Fede, Ben, Olivier, Peter thank you for holding back the shots, you’re all true gentlemen . Francesco, I hope I finally convinced you fate exists, after you gave me ‘The Fall’ 4 days before I was that girl…thank you for giving me a break :oP!

For Ken. Thank you for encouraging me to apply for studentships. If it wasn’t for your kind words and confidence in me, I never would have thought to take this path. Thank you for instilling in me your passion for science.

Thank you to my friends who stood by me through all the late dinners, birthdays and engagement parties! Thank you to my big nurturing family for your unconditional love and prayers, especially to my Mummy. Thanks Chibbies for the room cleaning and Sally for ‘praying that I get a life one day’. Thank you for letting me follow my dreams.

All praise for any good in this work belongs to God. Our helper when all doors are closed and our shelter when all solutions fail. Thank you for your guidance.

4

Table of Contents

Statement of originality Copyright declaration Abstract
223
Acknowledgments Table of contents List of Figures and Tables Abbreviations
4510 13

  • Chapter 1. Introduction
  • 20

  • 1.1. Senescence
  • 20

1.1.1. The senescence signature 1.1.2. Replicative senescence 1.1.3. Stress-induced senescence
21 24 25 28 31 31 32 34 36 38 39 44 44 45 47 50
1.1.4. Molecular mechanisms regulating senescence 1.1.5. Epigenetic regulation of senescence
1.1.5.1. Epigenetic regulation of the INK4b-ARF-INK4a locus 1.1.5.2. Chromosomal architecture during senescence
1.1.6. Senescence and ageing in vivo
1.2. Loss-of-function screenings using RNA interference (RNAi)
1.2.1. Systems for pooled shRNA screenings 1.2.2. Genetic screenings to identify novel senescence regulators
1.3. The SWI/SNF complex in senescence and cancer
1.3.1. The SWI/SNF complex of chromatin remodellers
1.3.1.1. A multi-subunit complex 1.3.1.2. ATP-dependent nucleosome remodelling 1.3.1.3. Regulation of transcription
5
1.3.1.4. Specialised domains and exchangeable isoforms
1.3.2. Role of the SWI/SNF complex in senescence and cancer
1.3.2.1. SWI/SNF subunits are frequently mutated in cancer 1.3.2.2. Relationship between the SWI/SNF complex and senescence
1.3.2.2.1. SNF5
50 51 52 57 57 58 60 61 62
1.3.2.2.2. BRG1/BRM 1.3.2.2.3. ARID1A/ARID1B 1.3.2.2.4. PBRM1/BRD7 1.3.2.2.5. Role of SWI/SNF in SAHF formation

  • Chapter 2. Materials and Methods
  • 64

  • 2.1. Libraries
  • 64

  • 2.1.1. HCC deletion library
  • 64

64 65 65 66 67 67 67 68 68 68 69 69 72
2.1.2. pGIPZ genome-wide library
2.2. Cell lines and tissue culture methods 2.3. Retrovirus production and transduction of target cells 2.4. Lentivirus production and transduction of target cells 2.5. Generation of custom Solexa libraries
2.5.1. Genomic DNA isolation 2.5.2. Solexa PCR 2.5.3. DNA purification and quantification
2.6. Next-generation sequencing
2.6.1. Solexa library quality control 2.6.2. High-throughput sequencing 2.6.3. Bioinformatics
2.7. Growth assays

6
2.7. 1. Growth curves and colony formation assays 2.7.2. BrdU (5-Bromo-2’-deoxyuridine) incorporation assay 2.7.3. Senescence-associated β-galactosidase (SA-β-gal) assay
2.7.3.1. Cytochemical staining
72 73 73 73 74 74 74 75 75 75 76 76 76 76 77 77 78 78 78 78 81 81 81 82
2.7.3.2. Fluorescence visualisation
2.8. Generation of shRNA expressing retroviral vectors
2.8.1. shRNA constructs 2.8.2. Plasmid DNA purification 2.8.3. Agarose gel electrophoresis and DNA purification 2.8.4. DNA sequencing
2.9. RNA expression analysis
2.9.1. Total RNA purification 2.9.2. Gene expression profiling
2.9.2.1. RNA quality control 2.9.2.2. Microarray analysis
2.9.3. Quantitative RT-PCR (RT-qPCR) analysis
2.10. Protein expression analysis
2.10.1. Immunofluorescence
2.10.1.2. High throughput microscopy (HTM) 2.10.1.3. High content analysis (HCA) 2.10.1.4. Confocal microscopy
2.10.2. SILAC to identify changes in protein expression
2.10.2.1. Whole cell protein extraction 2.10.2.2. Protein quantification 2.10.2.3. Sodium-dodecyl-sulphate polyacrylamide

  • gel electrophoresis (SDS-PAGE)
  • 82

7
2.10.2.4. Co-immunoprecipitation of nuclear protein complexes 2.10.2.5. Identification of proteins by LC–MS/MS
83 83

Chapter 3. Screening for regulators of lifespan extension in MEFs using NGS

3.1. Optimisation of the bypass of senescence screening

85

85 86 87 91 93 93 96 96 97
3.2. Proof of concept experiment verifies feasibility of the screening 3.3. NGS used to identify shRNAs from bypass of replicative senescence screen in MEFs 3.4. ARID1B is a candidate regulator of replicative senescence in MEFs 3.5. Depletion of Arid1b extends cellular lifespan in MEFs 3.6. ARID1B regulates cell proliferation and replicative senescence in IMR-90 3.7. Conclusions and perspectives
3.7.1. Screening for regulators of replicative senescence in MEFs 3.7.2 Advances in pooled shRNA screenings using NGS

Chapter 4. ARID1B a component of the SWI/SNF complex regulates senescence100

  • 4.1. Knockdown of ARID1B attenuates OIS
  • 100

4.2. ARID1B regulates p21CIP1, p16INK4a and p53 expression during OIS 4.3. Gene expression profiling identifies multiple senescence effectors regulated by ARID1B
100 103 105 106 110
4.4. Expression of oncogenic PIK3CAH1047R induces senescence 4.5. Knockdown of ARID1B attenuates PIK3CAH1047R mediated senescence 4.6. ARID1B regulates p16INK4a and p21CIP1 expression during
PIK3CA-induced senescence
4.7. High expression of SWI/SNF complex components during replicative senescence 4.8. Expression of SWI/SNF complex components increases during OIS 4.9. Post-translational stabilisation of the SWI/SNF complex during senescence
110 113 113

8
4.10. SILAC based quantitative proteomics identifies changes in the levels of

  • ARID1B binding proteins during OIS
  • 116

119 121 121 126 129 132 132 132 134 139 141
4.11. ARID1B is excluded from regions of repressed chromatin 4.12. Retroviral constructs overexpressing ARID1A and ARID1B 4.13. Ectopic expression of SWI/SNF subunits induces premature senescence 4.14. Premature senescence induced by ARID1B is mainly p53 dependent 4.15. Global changes in protein expression associated with ARID1B 4.16. ARID1B is deleted in cancer 4.17. Conclusions and perspectives
4.17.1. ARID1B depletion can bypass senescence through multiple mechanisms 4.17.2. SWI/SNF proteins are induced during senescence 4.17.3. Growth arrest induced by SWI/SNF is exerted through different mechanisms 4.17.4. ARID1B exhibits tumour-suppressive functions in cancer

  • Chapter 5. Discussion & Future work
  • 144

5.1. Genetic screens are useful tools for identifying novel genes and

  • pathways involved in senescence
  • 144

144 145 146 146 150 152 15X 154
5.1.1. Genome-wide screening for regulators of OIS in IMR-90 5.1.2. Library bias not detected from sequencing pGIPZ library pools 5.1.3. Set up of infection conditions for pGIPZ lentiviral screening 5.1.4. pGIPZ shp53-1 can be used as a control hairpin that bypasses OIS
5.2. ARID1B is an important senescence regulator 5.3. The SWI/SNF complex is implicated in cancer and ageing 5.4. The clinical utility of targeting the SWI/SNF complex in cancer detection and therapy 5.5. Concluding remark

9

References Appendix
159 213

List of Figures and Tables

Figure 1.1. Senescence is an intrinsic cellular response to multiple stresses. Figure 1.2. The senescence signature.
21 24 26 27 30 34 38 40 42 49
Table 1.1. Senescent cells are found in pre-malignant lesions in vivo. Figure 1.3. Senescence is a barrier to tumourigenesis in vivo. Figure 1.4. Key senescence pathways and effectors. Figure 1.5. Epigenetic regulation of senescence. Figure 1.6. Screenings using pooled shRNA libraries. Figure 1.7. Genetic screens for the bypass of replicative senescence. Figure 1.8. Workflow of shRNA identification using different methods. Figure 1.9. The SWI/SNF complex of nucleosome remodellers. Figure 1.10. The SWI/SNF complex interacts with proteins involved in many

  • cancer-related pathways.
  • 52

55 56 69 71 77 80 86
Figure 1.11. Mutations in SWI/SNF genes are predominantly deleterious. Table 1.2. SWI/SNF mutations occur frequently in human cancers. Figure 2.1. Bioanalyser profile of acceptable custom Solexa library for NGS. Figure 2.2. Solexa sequencing schematic. Figure 2.3. Bioanalyser profile of acceptable RNA profile for gene expression profiling. Figure 2.4. Workflow of establishing filters for High Content Analysis. Figure 3.1. An shRNA library targeting genes frequently deleted in human HCC. Figure 3.2. Proof of concept to establish the feasibility of an shRNA lifespan extension

  • screen in MEFs.
  • 87

Figure 3.3. Strategy for the genetic screening for bypass of replicative senescence

10

  • in MEFs.
  • 90

Figure 3.4. Lifespan extension screen in MEFs identifies Arid1b as a candidate

  • senescence regulator.
  • 92

Figure 3.5. Depletion of Arid1b extends cellular lifespan in MEFs. Figure 3.6. Depletion of ARID1B extends cellular lifespan in IMR-90. Figure 4.1. Knockdown of ARID1B attenuates OIS.
94 95 101

  • 102
  • Figure 4.2. ARID1B regulates different senescence effectors.

Figure 4.3. Validation of gene expression changes associated with ARID1B knockdown

  • during OIS.
  • 104

107 108
Figure 4.4.1. Expression of oncogenic PIK3CAH1047R induces senescence. Figure 4.4.2. Characterisation of the senescence response induced upon
PIK3CAH1047R expression.
Figure 4.5. Knockdown of ARID1B attenuates PIK3CAH1047R mediated senescence. Figure 4.6. ARID1B regulates p16INK4a and p21CIP1 during PIK3CA-induced senescence. Figure 4.7. Expression of SWI/SNF complex increases during replicative senescence. Figure 4.8. Expression of SWI/SNF complex increases during OIS. Figure 4.9. Increase in expression of SWI/SNF subunits is not transcriptionally regulated. Figure 4.10. SILAC based quantitative proteomics identifies SWI/SNF interactor exchange during OIS.
109 111 112 114 115

118 120 122 123 125
Figure 4.11. ARID1B is excluded from regions of repressed chromatin. Figure 4.12. Retroviral constructs overexpressing ARID1A and ARID1B. Figure 4.13.1. Overexpression of SWI/SNF subunits induces premature senescence. Figure 4.13.2. Molecular analysis of senescence induced by SWI/SNF subunits. Figure 4.14.1. Knockdown of important senescence regulators alleviates ARID1B

  • mediated senescence.
  • 127

Figure 4.14.2. Co-expression of Human papillomavirus (HPV) oncoproteins alleviates

11
ARID1B-mediated senescence.
Figure 4.15.1. Global changes in protein levels upon ARID1B overexpression analysed by SILAC.
128 130 131 145 148
Figure 4.15.2. Production of oxidative stress may contribute to ARID1B mediated senescence. Figure 5.1. pGIPZ library set up and pool coverage determined by HTS. Figure 5.2. Optimising infection conditions with pGIPZ lentiviral vectors. Figure 5.3. Validation of pGIPZ controls for proof of principle experiment for bypass

  • of OIS screening.
  • 149

213 214 215 215 216 216 217 217 217 219 219 220
Table A1. Inferences from test NGS run at CSC. Table A2. Differential gene expression of ARID1B knockdown cells during OIS. Table A3. pGIPZ pool coverage determined by HTS. Table A4. Copy number deletions in ARID1B is significant across cancers. Table A5. cDNA constructs. Table A6. shRNA target sequences. Table A7. Solexa PCR primers. Table A8. Sequencing primers. Table A9. RT-qPCR primers. Table A10. Primers for cloning. Table A11. Antibodies. Figure A1. Validation of ARID1B antibody for immunoprecipitation

12

Abbreviations

  • 4-OHT
  • 4-hydroxy tamoxifen

  • A
  • Adenine

  • Ac
  • Acetylated

AKT ARF ARID ASF ATCC ATM ATP ATR v-akt murine thymoma viral oncogene homologue Alternative reading frame AT-rich interactive domain Anti-silencing function American Type Culture Collection Ataxia telangiectasia mutated Adenosine tri-phosphate Ataxia telangiectasia and Rad3 related

  • BAF
  • BRG1/BRM associated factors

BMP and activin membrane-bound inhibitor homologue B-cell CLL/lymphoma
BAMBI BCL

  • BH
  • Benjamini-Hochberg

BMP bp
Bone morphogenetic protein Base pair
BRAF BRCA BRD BrdU BRG1 BRM BSA v-raf murine sarcoma viral oncogene homologue B1 Breast cancer susceptibility gene Bromodomain containing 5-bromo-2-deoxyuridine Brahma related gene 1 Brahma Bovine serum albumin

  • C
  • Cytosine

c-FOS C. elegans

C(T)
Cellular-FBJ osteosarcoma oncogene

Caenorhabditis elegans

Threshold cycle
C/EBP C12FDG CASAVA cBAF
CCAAT/enhancer binding protein Fluorescein-di-β-d-galactopyranoside Consensus assessment of sequence and variation Cardiac BAF

13
CBX7 CDC
Chromobox protein homologue 7 Cell division cycle

  • CDK
  • Cyclin dependent kinase

  • CKI
  • Cyclin dependent kinase inhibitor

cyclin-dependent kinase inhibitor 1A

cyclin-dependent kinase inhibitor 2A

Complementary DNA
CDKN1 CDKN2 cDNA CGH ChIP CML
Comparative genomic hybridisation Chromatin immunoprecipitation Chronic myeloid leukaemia

  • Clinical Sciences Centre
  • CSC

  • CSC
  • Cancer stem cell

  • CSF
  • Colony-stimulating factor

CTGF CXCL CXCR
Connective tissue growth factor CXC chemokine ligand CXC chemokine receptor

DAPI DDR DMEM DMSO DNA
4,6-diamidino-2-phenylindole DNA damage response Dulbecco’s modified Eagle’s medium Dimethyl sulfoxide Deoxyribonucleic acid DNA methyltransferase Deoxyribonucleotide triphosphate Double strand
DNMT dNTP ds

  • DTT
  • Dithiothreitol

E.coli

EDTA EIF

Escherichia coli

Ethylenediaminetetraacetic acid Translation initiation factor
ELAND EMBL ER
Efficient large-scale alignment of nucleotide databases European Molecular Biology Laboratory Oestrogen receptor esBAF ETS
Embryonic stem cell BAF E26 oncogene homologue

  • EZH2
  • Enhancer of zeste homologue 2

FBS FGF
Foetal bovine serum Fibroblast growth factors

14

  • FOXO
  • Forkhead box, sub-group O

Phosphorylated histone 2, variant X Gram γH2AX g

  • G
  • Guanine

GDF GFP GLB1 GM
Growth differentiation factor Green fluorescent protein Galactosidase, beta 1 granulocyte-macrophage

  • Gene ontology
  • GO

  • GR
  • Glucocorticoid receptor

Gene Set Enrichment Analysis glycogen synthase kinase 3 β-glucuronidase
GSEA GSK3 GUS-B

  • H
  • Histone

  • HAT
  • Histone acetyl-transferase

  • High content analysis
  • HCA

HCC HDAC HEK
Hepatocellular carcinoma Histone deacetylase Human embryonic kidney 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid Hutchinson–Gilford progeria syndrome Hypoxia inducible factor 1 Histone repressor A
HEPES HGPS HIF HIRA HMG HMT HP
High mobility group Histone methyltransferase Heterochromatic protein Human pancreatic duct epithelial Human papilloma virus 16 Hour
HPDE HPV16 hHRAS HSCs hTERT HTM HUGO HZI
Harvey rat sarcoma gene Hematopoietic stem cells Human telomerase reverse transcriptase High throughput microscopy Human genome organisation Helmholtz Centre for Infection

Recommended publications
  • Identification of the Genes Up- and Down-Regulated by the High Mobility Group A1 (HMGA1) Proteins: Tissue Specificity of the HMGA1-Dependent Gene Regulation

    Identification of the Genes Up- and Down-Regulated by the High Mobility Group A1 (HMGA1) Proteins: Tissue Specificity of the HMGA1-Dependent Gene Regulation

    [CANCER RESEARCH 64, 5728–5735, August 15, 2004] Identification of the Genes Up- and Down-Regulated by the High Mobility Group A1 (HMGA1) Proteins: Tissue Specificity of the HMGA1-Dependent Gene Regulation Josefina Martinez Hoyos,1 Monica Fedele,1 Sabrina Battista,1 Francesca Pentimalli,1,2 Mogens Kruhoffer,3 Claudio Arra,4 Torben F. Orntoft,3 Carlo Maria Croce,2 and Alfredo Fusco1 1Dipartimento di Biologia e Patologia Cellulare e Molecolare e/o Istituto di Endocrinologia ed Oncologia Sperimentale del CNR, Facolta` di Medicina e Chirurgia di Napoli, Universita` degli Studi di Napoli “Federico II,” Naples, Italy; 2Kimmel Cancer Center, Jefferson Medical College, Philadelphia, Pennsylvania; 3Department of Clinical Biochemistry, Aarhus University Hospital, Aarhus, Denmark; and 4Istituto Dei Tumori Di Napoli “Fondazione Pascale,” Naples, Italy. ABSTRACT To identify the differentiation pathways in which HMGA1 is in- volved and to assess the role of the HMGA1 proteins in development, High mobility group A (HMGA) proteins are chromatinic proteins that we generated embryonic stem (ES) cells in which one or both hmga1 do not have transcriptional activity per se, however, by interacting with alleles are disrupted. We reported recently that hmga1Ϫ/Ϫ ES cells the transcription machinery, they regulate, negatively or positively, the expression of several genes. We searched for genes regulated by HMGA1 generate less T-cell precursors than do wild-type ES cells after in proteins using microarray analysis in embryonic stem (ES) cells bearing vitro-specific differentiation. Indeed, they preferentially differentiate one or two disrupted hmga1 alleles. We identified 87 transcripts increased to B cells, probably consequent to decreased IL-2 expression and and 163 transcripts decreased of at least 4-fold in hmga1؊/؊ ES cells.
  • ARID1B Is a Specific Vulnerability in ARID1A-Mutant Cancers The

    ARID1B Is a Specific Vulnerability in ARID1A-Mutant Cancers The

    ARID1B is a specific vulnerability in ARID1A-mutant cancers The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters. Citation Helming, K. C., X. Wang, B. G. Wilson, F. Vazquez, J. R. Haswell, H. E. Manchester, Y. Kim, et al. 2014. “ARID1B is a specific vulnerability in ARID1A-mutant cancers.” Nature medicine 20 (3): 251-254. doi:10.1038/nm.3480. http://dx.doi.org/10.1038/nm.3480. Published Version doi:10.1038/nm.3480 Accessed February 16, 2015 10:04:32 PM EST Citable Link http://nrs.harvard.edu/urn-3:HUL.InstRepos:12987227 Terms of Use This article was downloaded from Harvard University's DASH repository, and is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of- use#LAA (Article begins on next page) NIH Public Access Author Manuscript Nat Med. Author manuscript; available in PMC 2014 September 01. NIH-PA Author ManuscriptPublished NIH-PA Author Manuscript in final edited NIH-PA Author Manuscript form as: Nat Med. 2014 March ; 20(3): 251–254. doi:10.1038/nm.3480. ARID1B is a specific vulnerability in ARID1A-mutant cancers Katherine C. Helming1,2,3,4,*, Xiaofeng Wang1,2,3,*, Boris G. Wilson1,2,3, Francisca Vazquez5, Jeffrey R. Haswell1,2,3, Haley E. Manchester1,2,3, Youngha Kim1,2,3, Gregory V. Kryukov5, Mahmoud Ghandi5, Andrew J. Aguirre5,6,7, Zainab Jagani8, Zhong Wang9, Levi A. Garraway6, William C. Hahn6,7, and Charles W.
  • A Preliminary Transcriptome Analysis Suggests a Transitory Effect of Vitamin D on Mitochondrial Function in Obese Young Finnish Subjects

    A Preliminary Transcriptome Analysis Suggests a Transitory Effect of Vitamin D on Mitochondrial Function in Obese Young Finnish Subjects

    ID: 18-0537 8 5 E Einarsdottir et al. Effect of vitamin D on gene 8:5 559–570 expression RESEARCH A preliminary transcriptome analysis suggests a transitory effect of vitamin D on mitochondrial function in obese young Finnish subjects Elisabet Einarsdottir1,2,3,†, Minna Pekkinen1,4, Kaarel Krjutškov2,5, Shintaro Katayama3, Juha Kere1,2,3,6, Outi Mäkitie1,4,7,8 and Heli Viljakainen1,9 1Folkhälsan Institute of Genetics, University of Helsinki, Helsinki, Finland 2Molecular Neurology Research Program, University of Helsinki, Helsinki, Finland 3Department of Biosciences and Nutrition, Karolinska Institutet, Huddinge, Sweden 4Children’s Hospital, University of Helsinki and Helsinki University Hospital, Helsinki, Finland 5Competence Centre on Health Technologies, Tartu, Estonia 6School of Basic and Medical Biosciences, King’s College London, Guy’s Hospital, London, United Kingdom 7Department of Molecular Medicine and Surgery and Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden 8Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden 9Department of Food and Environmental Sciences, University of Helsinki, Helsinki, Finland Correspondence should be addressed to H Viljakainen: [email protected] †(E Einarsdottir is now at Department of Gene Technology, Science for Life Laboratory, KTH-Royal Institute of Technology, Solna, Sweden) Abstract Objective: The effect of vitamin D at the transcriptome level is poorly understood, Key Words and furthermore, it is unclear if it differs between obese and normal-weight subjects. f vitamin D The objective of the study was to explore the transcriptome effects of vitamin D f gene expression supplementation. f obesity Design and methods: We analysed peripheral blood gene expression using GlobinLock f transcriptome oligonucleotides followed by RNA sequencing in individuals participating in a 12-week f mitochondrial function randomised double-blinded placebo-controlled vitamin D intervention study.
  • 1 Supplementary Table S1. Primers Used for RT-Qpcr PROX1

    1 Supplementary Table S1. Primers Used for RT-Qpcr PROX1

    Supplementary Table S1. Primers used for RT-qPCR PROX1 (Prospero Homeobox 1) 5’ – CCAGCTCCAATATGCTGAAGACCTA – 3’ 5’ – CATCGTTGATGGCTTGACGTG – 3‘ MMP-1 (Matrix Metallopeptidase 1) 5' –CTGTCCCTGAACAGCCCAGTACTTA– 3' 5' –CTGGCCACAACTGCCAAATG– 3' FGF2 (Fibroblast Growth Factor 2) 5′ - GGCTTCTTCCTGCGCATCCA – 3′ 5′ – GCTCTTAGCAGACATTGGAAGA – 3′ MMP-3 (Matrix Metallopeptidase 3) GAAATGAGGTACGAGCTGGATACC– 3’ 5’ –ATGGCTGCATCGATTTTCCT– 3’ NUDT6 (Nudix Hydrolase 6) 5’ –GGCGAGCTGGACAGATTC– 3’ 5’ –GCAGCAGGGGCAATAAATCG– 3’ BAIAP2 (BAI1 Associated Protein 2) 5’ –AAGTCCACAGGCAGATCCAG– 3’ 5’ –GCCTTTGCTCCTTTGCTCAG– 3’ VEGFC (Vascular Endothelial Growth 5’ –GCCACGGCTTATGCAAGCAAAGAT– 3’ Factor C) 5’ –AGTTGAGGTTGGCCTGTTCTCTGT– 3’ ANGPT1 (Angiopoietin 1) 5’ –GAAGGGAACCGAGCCTATTC– 3’ 5’ –AGCATCAAACCACCATCCTC– 3’ KDR (Kinase Insert Domain Receptor) 5’ –AGGAGAGCGTGTCTTTGTGG– 3’ 5’ –GCCTGTCTTCAGTTCCCCTC– 3’ VEGFA (Vascular Endothelial Growth 5’ –CTTGCCTTGCTGCTCTACCT– 3’ Factor A) 5’ –AAGATGTCCACCAGGGTCTC– 3’ PLAT (Plasminogen Activator, Tissue 5’ –AGGAGAGCGTGTCTTTGTGG– 3’ Type) 5’ –GCCTGTCTTCAGTTCCCCTC– 3’ MDK (Midkine) 5’ –CCTGCAACTGGAAGAAGGAG– 3’ 5’ -- CTTTCCCTTCCCTTTCTTGG– 3’ ADAMTS9 (ADAM Metallopeptidase 5’ –ACGAAAAACCTGCCGTAATG– 3’ With Thrombospondin Type 1 Motif 9) 5’ –TCAGAGTCTCCATGCACCAG– 3’ TIMP3 (TIMP Metallopeptidase Inhibitor 5’ –CTGACAGGTCGCGTCTATGA– 3’ 3) 5’ –AGTCACAAAGCAAGGCAGGT– 3’ ACTB (Beta Actin) 5’ – GCCGAGGACTTTGATTGC – 3’ 5’– CTGTGTGGACTTGGGAGAG – 3’ 1 Figure S1. Efficient silencing of PROX1 in CGTH-W-1 and FTC-133 cells. Western blotting analysis shows a decrease in PROX1 protein level by targeting with siRNAs purchased from Santa Cruz (SC) and Sigma-Aldrich (SA) in both CGTH-W-1 and FTC-133 cell line. Beta-actin was used as a loading control of protein lysates. Figure S2. The tube formation assay. The silencing of PROX1 in CGTH-W-1 and FTC-133 cells enhances the angiogenesis in vitro of endothelial cells. HUVECs were cultured in 96-well plates coated with a semi-solid Matrigel.
  • Supplemental Materials ZNF281 Enhances Cardiac Reprogramming

    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
  • 1 AGING Supplementary Table 2

    1 AGING Supplementary Table 2

    SUPPLEMENTARY TABLES Supplementary Table 1. Details of the eight domain chains of KIAA0101. Serial IDENTITY MAX IN COMP- INTERFACE ID POSITION RESOLUTION EXPERIMENT TYPE number START STOP SCORE IDENTITY LEX WITH CAVITY A 4D2G_D 52 - 69 52 69 100 100 2.65 Å PCNA X-RAY DIFFRACTION √ B 4D2G_E 52 - 69 52 69 100 100 2.65 Å PCNA X-RAY DIFFRACTION √ C 6EHT_D 52 - 71 52 71 100 100 3.2Å PCNA X-RAY DIFFRACTION √ D 6EHT_E 52 - 71 52 71 100 100 3.2Å PCNA X-RAY DIFFRACTION √ E 6GWS_D 41-72 41 72 100 100 3.2Å PCNA X-RAY DIFFRACTION √ F 6GWS_E 41-72 41 72 100 100 2.9Å PCNA X-RAY DIFFRACTION √ G 6GWS_F 41-72 41 72 100 100 2.9Å PCNA X-RAY DIFFRACTION √ H 6IIW_B 2-11 2 11 100 100 1.699Å UHRF1 X-RAY DIFFRACTION √ www.aging-us.com 1 AGING Supplementary Table 2. Significantly enriched gene ontology (GO) annotations (cellular components) of KIAA0101 in lung adenocarcinoma (LinkedOmics). Leading Description FDR Leading Edge Gene EdgeNum RAD51, SPC25, CCNB1, BIRC5, NCAPG, ZWINT, MAD2L1, SKA3, NUF2, BUB1B, CENPA, SKA1, AURKB, NEK2, CENPW, HJURP, NDC80, CDCA5, NCAPH, BUB1, ZWILCH, CENPK, KIF2C, AURKA, CENPN, TOP2A, CENPM, PLK1, ERCC6L, CDT1, CHEK1, SPAG5, CENPH, condensed 66 0 SPC24, NUP37, BLM, CENPE, BUB3, CDK2, FANCD2, CENPO, CENPF, BRCA1, DSN1, chromosome MKI67, NCAPG2, H2AFX, HMGB2, SUV39H1, CBX3, TUBG1, KNTC1, PPP1CC, SMC2, BANF1, NCAPD2, SKA2, NUP107, BRCA2, NUP85, ITGB3BP, SYCE2, TOPBP1, DMC1, SMC4, INCENP. RAD51, OIP5, CDK1, SPC25, CCNB1, BIRC5, NCAPG, ZWINT, MAD2L1, SKA3, NUF2, BUB1B, CENPA, SKA1, AURKB, NEK2, ESCO2, CENPW, HJURP, TTK, NDC80, CDCA5, BUB1, ZWILCH, CENPK, KIF2C, AURKA, DSCC1, CENPN, CDCA8, CENPM, PLK1, MCM6, ERCC6L, CDT1, HELLS, CHEK1, SPAG5, CENPH, PCNA, SPC24, CENPI, NUP37, FEN1, chromosomal 94 0 CENPL, BLM, KIF18A, CENPE, MCM4, BUB3, SUV39H2, MCM2, CDK2, PIF1, DNA2, region CENPO, CENPF, CHEK2, DSN1, H2AFX, MCM7, SUV39H1, MTBP, CBX3, RECQL4, KNTC1, PPP1CC, CENPP, CENPQ, PTGES3, NCAPD2, DYNLL1, SKA2, HAT1, NUP107, MCM5, MCM3, MSH2, BRCA2, NUP85, SSB, ITGB3BP, DMC1, INCENP, THOC3, XPO1, APEX1, XRCC5, KIF22, DCLRE1A, SEH1L, XRCC3, NSMCE2, RAD21.
  • The Genetic Basis of Hepatosplenic T-Cell Lymphoma

    The Genetic Basis of Hepatosplenic T-Cell Lymphoma

    Published OnlineFirst January 25, 2017; DOI: 10.1158/2159-8290.CD-16-0330 RESEARCH BRIEF The Genetic Basis of Hepatosplenic T-cell Lymphoma Matthew McKinney 1 , Andrea B. Moffi tt 2 , Philippe Gaulard 3 , Marion Travert 3 , Laurence De Leval4 , Alina Nicolae 5 , Mark Raffeld 5 , Elaine S. Jaffe 5 , Stefania Pittaluga 5 , Liqiang Xi 5 , Tayla Heavican 6 , Javeed Iqbal 6 , Karim Belhadj 3 , Marie Helene Delfau-Larue 3 , Virginie Fataccioli 3 , Magdalena B. Czader7 , Izidore S. Lossos 8 , Jennifer R. Chapman-Fredricks 8 , Kristy L. Richards 9 , Yuri Fedoriw 9 , Sarah L. Ondrejka10 , Eric D. Hsi 10 , Lawrence Low 11 , Dennis Weisenburger 11 , Wing C. Chan 11 , Neha Mehta-Shah12 , Steven Horwitz 12 , Leon Bernal-Mizrachi 13 , Christopher R. Flowers 13 , Anne W. Beaven 1 , Mayur Parihar 14 , Lucile Baseggio 15 , Marie Parrens 16 , Anne Moreau 17 , Pierre Sujobert 18 , Monika Pilichowska 19 , Andrew M. Evens 19 , Amy Chadburn 20 , Rex K.H. Au-Yeung 21 , Gopesh Srivastava 21 , William W. L. Choi 21 , John R. Goodlad 22 , Igor Aurer 23 , Sandra Basic-Kinda 23 , Randy D. Gascoyne 24 , Nicholas S. Davis 1 , Guojie Li 1 , Jenny Zhang 1 , Deepthi Rajagopalan 1 , Anupama Reddy 1 , Cassandra Love 1 , Shawn Levy 25 , Yuan Zhuang 1 , Jyotishka Datta 26 , David B. Dunson 26 , and Sandeep S. Davé 1 , 2 ABSTRACT Hepatosplenic T-cell lymphoma (HSTL) is a rare and lethal lymphoma; the genetic drivers of this disease are unknown. Through whole-exome sequencing of 68 HSTLs, we defi ne recurrently mutated driver genes and copy-number alterations in the disease.
  • MECHANISMS in ENDOCRINOLOGY: Novel Genetic Causes of Short Stature

    MECHANISMS in ENDOCRINOLOGY: Novel Genetic Causes of Short Stature

    J M Wit and others Genetics of short stature 174:4 R145–R173 Review MECHANISMS IN ENDOCRINOLOGY Novel genetic causes of short stature 1 1 2 2 Jan M Wit , Wilma Oostdijk , Monique Losekoot , Hermine A van Duyvenvoorde , Correspondence Claudia A L Ruivenkamp2 and Sarina G Kant2 should be addressed to J M Wit Departments of 1Paediatrics and 2Clinical Genetics, Leiden University Medical Center, PO Box 9600, 2300 RC Leiden, Email The Netherlands [email protected] Abstract The fast technological development, particularly single nucleotide polymorphism array, array-comparative genomic hybridization, and whole exome sequencing, has led to the discovery of many novel genetic causes of growth failure. In this review we discuss a selection of these, according to a diagnostic classification centred on the epiphyseal growth plate. We successively discuss disorders in hormone signalling, paracrine factors, matrix molecules, intracellular pathways, and fundamental cellular processes, followed by chromosomal aberrations including copy number variants (CNVs) and imprinting disorders associated with short stature. Many novel causes of GH deficiency (GHD) as part of combined pituitary hormone deficiency have been uncovered. The most frequent genetic causes of isolated GHD are GH1 and GHRHR defects, but several novel causes have recently been found, such as GHSR, RNPC3, and IFT172 mutations. Besides well-defined causes of GH insensitivity (GHR, STAT5B, IGFALS, IGF1 defects), disorders of NFkB signalling, STAT3 and IGF2 have recently been discovered. Heterozygous IGF1R defects are a relatively frequent cause of prenatal and postnatal growth retardation. TRHA mutations cause a syndromic form of short stature with elevated T3/T4 ratio. Disorders of signalling of various paracrine factors (FGFs, BMPs, WNTs, PTHrP/IHH, and CNP/NPR2) or genetic defects affecting cartilage extracellular matrix usually cause disproportionate short stature.
  • 1714 Gene Comprehensive Cancer Panel Enriched for Clinically Actionable Genes with Additional Biologically Relevant Genes 400-500X Average Coverage on Tumor

    1714 Gene Comprehensive Cancer Panel Enriched for Clinically Actionable Genes with Additional Biologically Relevant Genes 400-500X Average Coverage on Tumor

    xO GENE PANEL 1714 gene comprehensive cancer panel enriched for clinically actionable genes with additional biologically relevant genes 400-500x average coverage on tumor Genes A-C Genes D-F Genes G-I Genes J-L AATK ATAD2B BTG1 CDH7 CREM DACH1 EPHA1 FES G6PC3 HGF IL18RAP JADE1 LMO1 ABCA1 ATF1 BTG2 CDK1 CRHR1 DACH2 EPHA2 FEV G6PD HIF1A IL1R1 JAK1 LMO2 ABCB1 ATM BTG3 CDK10 CRK DAXX EPHA3 FGF1 GAB1 HIF1AN IL1R2 JAK2 LMO7 ABCB11 ATR BTK CDK11A CRKL DBH EPHA4 FGF10 GAB2 HIST1H1E IL1RAP JAK3 LMTK2 ABCB4 ATRX BTRC CDK11B CRLF2 DCC EPHA5 FGF11 GABPA HIST1H3B IL20RA JARID2 LMTK3 ABCC1 AURKA BUB1 CDK12 CRTC1 DCUN1D1 EPHA6 FGF12 GALNT12 HIST1H4E IL20RB JAZF1 LPHN2 ABCC2 AURKB BUB1B CDK13 CRTC2 DCUN1D2 EPHA7 FGF13 GATA1 HLA-A IL21R JMJD1C LPHN3 ABCG1 AURKC BUB3 CDK14 CRTC3 DDB2 EPHA8 FGF14 GATA2 HLA-B IL22RA1 JMJD4 LPP ABCG2 AXIN1 C11orf30 CDK15 CSF1 DDIT3 EPHB1 FGF16 GATA3 HLF IL22RA2 JMJD6 LRP1B ABI1 AXIN2 CACNA1C CDK16 CSF1R DDR1 EPHB2 FGF17 GATA5 HLTF IL23R JMJD7 LRP5 ABL1 AXL CACNA1S CDK17 CSF2RA DDR2 EPHB3 FGF18 GATA6 HMGA1 IL2RA JMJD8 LRP6 ABL2 B2M CACNB2 CDK18 CSF2RB DDX3X EPHB4 FGF19 GDNF HMGA2 IL2RB JUN LRRK2 ACE BABAM1 CADM2 CDK19 CSF3R DDX5 EPHB6 FGF2 GFI1 HMGCR IL2RG JUNB LSM1 ACSL6 BACH1 CALR CDK2 CSK DDX6 EPOR FGF20 GFI1B HNF1A IL3 JUND LTK ACTA2 BACH2 CAMTA1 CDK20 CSNK1D DEK ERBB2 FGF21 GFRA4 HNF1B IL3RA JUP LYL1 ACTC1 BAG4 CAPRIN2 CDK3 CSNK1E DHFR ERBB3 FGF22 GGCX HNRNPA3 IL4R KAT2A LYN ACVR1 BAI3 CARD10 CDK4 CTCF DHH ERBB4 FGF23 GHR HOXA10 IL5RA KAT2B LZTR1 ACVR1B BAP1 CARD11 CDK5 CTCFL DIAPH1 ERCC1 FGF3 GID4 HOXA11 IL6R KAT5 ACVR2A
  • Genome-Wide DNA Methylation Analysis Reveals Molecular Subtypes of Pancreatic Cancer

    Genome-Wide DNA Methylation Analysis Reveals Molecular Subtypes of Pancreatic Cancer

    www.impactjournals.com/oncotarget/ Oncotarget, 2017, Vol. 8, (No. 17), pp: 28990-29012 Research Paper Genome-wide DNA methylation analysis reveals molecular subtypes of pancreatic cancer Nitish Kumar Mishra1 and Chittibabu Guda1,2,3,4 1Department of Genetics, Cell Biology and Anatomy, University of Nebraska Medical Center, Omaha, NE, 68198, USA 2Bioinformatics and Systems Biology Core, University of Nebraska Medical Center, Omaha, NE, 68198, USA 3Department of Biochemistry and Molecular Biology, University of Nebraska Medical Center, Omaha, NE, 68198, USA 4Fred and Pamela Buffet Cancer Center, University of Nebraska Medical Center, Omaha, NE, 68198, USA Correspondence to: Chittibabu Guda, email: [email protected] Keywords: TCGA, pancreatic cancer, differential methylation, integrative analysis, molecular subtypes Received: October 20, 2016 Accepted: February 12, 2017 Published: March 07, 2017 Copyright: Mishra et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC-BY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. ABSTRACT Pancreatic cancer (PC) is the fourth leading cause of cancer deaths in the United States with a five-year patient survival rate of only 6%. Early detection and treatment of this disease is hampered due to lack of reliable diagnostic and prognostic markers. Recent studies have shown that dynamic changes in the global DNA methylation and gene expression patterns play key roles in the PC development; hence, provide valuable insights for better understanding the initiation and progression of PC. In the current study, we used DNA methylation, gene expression, copy number, mutational and clinical data from pancreatic patients.
  • MDM4 Is Targeted by 1Q Gain and Drives Disease in Burkitt Lymphoma

    MDM4 Is Targeted by 1Q Gain and Drives Disease in Burkitt Lymphoma

    Published OnlineFirst April 18, 2019; DOI: 10.1158/0008-5472.CAN-18-3438 Cancer Translational Science Research MDM4 Is Targeted by 1q Gain and Drives Disease in Burkitt Lymphoma Jennifer Hullein€ 1,2, Mikołaj Słabicki1, Maciej Rosolowski3, Alexander Jethwa1,2, Stefan Habringer4, Katarzyna Tomska1, Roma Kurilov5, Junyan Lu6, Sebastian Scheinost1, Rabea Wagener7,8, Zhiqin Huang9, Marina Lukas1, Olena Yavorska6, Hanne Helfrich10,Rene Scholtysik11, Kyle Bonneau12, Donato Tedesco12,RalfKuppers€ 11, Wolfram Klapper13, Christiane Pott14, Stephan Stilgenbauer10, Birgit Burkhardt15, Markus Lof€ fler3, Lorenz H. Trumper€ 16, Michael Hummel17, Benedikt Brors5, Marc Zapatka9, Reiner Siebert7,8, Markus Kreuz3, Ulrich Keller4,18, Wolfgang Huber6, and Thorsten Zenz1,19 Abstract Oncogenic MYC activation promotes proliferation in growth in a xenograft model in a p53-dependent manner. Burkitt lymphoma, but also induces cell-cycle arrest and Small molecule inhibition of the MDM4–p53 interaction apoptosis mediated by p53, a tumor suppressor that is was effective only in TP53wt Burkitt lymphoma cell lines. mutated in 40% of Burkitt lymphoma cases. To identify Moreover, primary TP53wt Burkitt lymphoma samples fre- molecular dependencies in Burkitt lymphoma, we per- quently acquired gains of chromosome 1q, which includes formed RNAi-based, loss-of-function screening in eight the MDM4 locus, and showed elevated MDM4 mRNA levels. Burkitt lymphoma cell lines and integrated non-Burkitt 1q gain was associated with TP53wt across 789 cancer cell lymphoma RNAi screens and genetic data. We identified lines and MDM4 was essential in the TP53wt-context in 216 76 genes essential to Burkitt lymphoma, including genes cell lines representing 19 cancer entities from the Achilles associated with hematopoietic cell differentiation (FLI1, Project.
  • Blueprint Genetics Comprehensive Growth Disorders / Skeletal

    Blueprint Genetics Comprehensive Growth Disorders / Skeletal

    Comprehensive Growth Disorders / Skeletal Dysplasias and Disorders Panel Test code: MA4301 Is a 374 gene panel that includes assessment of non-coding variants. This panel covers the majority of the genes listed in the Nosology 2015 (PMID: 26394607) and all genes in our Malformation category that cause growth retardation, short stature or skeletal dysplasia and is therefore a powerful diagnostic tool. It is ideal for patients suspected to have a syndromic or an isolated growth disorder or a skeletal dysplasia. About Comprehensive Growth Disorders / Skeletal Dysplasias and Disorders This panel covers a broad spectrum of diseases associated with growth retardation, short stature or skeletal dysplasia. Many of these conditions have overlapping features which can make clinical diagnosis a challenge. Genetic diagnostics is therefore the most efficient way to subtype the diseases and enable individualized treatment and management decisions. Moreover, detection of causative mutations establishes the mode of inheritance in the family which is essential for informed genetic counseling. For additional information regarding the conditions tested on this panel, please refer to the National Organization for Rare Disorders and / or GeneReviews. Availability 4 weeks Gene Set Description Genes in the Comprehensive Growth Disorders / Skeletal Dysplasias and Disorders Panel and their clinical significance Gene Associated phenotypes Inheritance ClinVar HGMD ACAN# Spondyloepimetaphyseal dysplasia, aggrecan type, AD/AR 20 56 Spondyloepiphyseal dysplasia, Kimberley