DOCSLIB.ORG

Supplementary Tables

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text

Load more

Supplementary material J Med Genet Supplementary tables Supplementary Table 1. List of 522 genes in the heart gene panel ABCC6 C5orf42 CUL3 FHL1 IGFBP7 MAT2A NR5A1 PTCH1 SKI TMEM43 ABCC9 CACNA1C CUL4B FIG4 IL10 MATR3 NRAS PTCH2 SLC19A2 TMEM67 ACE CACNA1D DAPK3 FKBP14 INVS MCTP2 NRXN1 PTEN SLC29A3 TNNC1 ACTA2 CACNA2D1 DCHS1 FKTN IRF6 MED12 NSD1 PTF1A SLC2A10 TNNI3 ACTB CACNB2 DDX11 FLNA IRX4 MED13L NSDHL PTH1R SLC35B2 TNNT2 ACTC1 CALM1 DDX3X FLNB JAG1 MEGF8 NUB1 PTPN11 SLCO2A1 TNS1 ACTG1 CALM2 DDX59 FOXC1 JPH2 MEOX1 OFD1 RAB10 SLMAP TP63 ACTN2 CALM3 DES FOXC2 JUP MESP1 ORC1 RAB23 SMAD2 TPM1 ACVR1 CALR3 DHCR24 FOXE3 KANSL1 MFAP5 ORC4 RAF1 SMAD3 TRDN ACVR2B CASQ2 DHCR7 FOXF1 KAT6B MGAT2 ORC6 RAI1 SMAD6 TRIM32 ADNP CAV3 DIS3L2 FOXH1 KCNA5 MGP PACS1 RANGRF SMARCA2 TRPM4 AGT CBL DLL3 FRAS1 KCND3 MIB1 PAFAH1B1 RARB SMARCA4 TRPV4 AKAP9 CCBE1 DLX5 FREM2 KCNE1 MID1 PAX1 RBM10 SMARCB1 TSR2 AKT3 CCDC103 DNAAF3 FTO KCNE1L MIR17HG PAX3 RBM20 SMARCE1 TTC37 ALDH18A1 CCDC114 DNAH11 G6PC3 KCNE2 MKKS PAX6 RBM8A SMC1A TTC8 ALDH1A2 CCDC151 DNAH5 GALNS KCNE3 MKS1 PCNT RECQL4 SNAI3 TTN ALG8 CCDC39 DNAI1 GATA3 KCNH2 MMP2 PDGFRB RELN SNRPB TTR ALPK3 CCDC40 DNMT3A GATA4 KCNJ2 MMP21 PDHA1 REN SNTA1 TUBA1A AMER1 CD96 DNMT3B GATA5 KCNJ5 MMP23A PDX1 RFX6 SOS1 TWIST1 ANK2 CDK13 DOCK6 GATA6 KCNJ8 MPDZ PEX1 RIT1 SOX10 TWIST2 ANKRD1 CDKN1C DSC2 GBA KCNQ1 MPLKIP PEX10 RMRP SOX2 UBE2B ANKRD11 CENPJ DSG1 GDF1 KDM5A MSX1 PEX2 RNF135 SOX9 UBR1 ARID1A CEP290 DSG2 GDF6 KDM5B MTCH1 PHF21A RNF20 SPRED1 USP34 ARID1B CEP57 DSP GEMIN2 KDM5C MYBPC3 PHGDH RNU4ATAC SRCAP USP44 ARL6 CFC1 DYNC2H1 GGCX KDM6A MYCN PIEZO2 ROR2 SRD5A3 VCL ASPH CHD4 DYRK1A GJA1 KIAA0196 MYH11 PIGF RPL35A STAMBP VEGFA ASXL1 CHD7 DYX1C1 GJA5 KIAA1279 MYH6 PIGL RPS11 STRA6 VEGFB ATIC CHRNA1 EBP GLA KIF11 MYH7 PIGN RPS17 SUPT5H VEGFC ATP7A CHRNB1 ECE1 GLB1 KIF7 MYH9 PIGT RPS19 SUV420H1 VIPAS39 ATR CHRNG EDN3 GLI3 KMT2A MYL2 PIGV RPS24 TAB2 VPS13B ATRX CHST3 EDNRB GLMN KMT2D MYL3 PIK3CA RPS5 TAF2 VPS33B AXIN1 CHUK EFEMP2 GPC3 KRAS MYLK PIK3R2 RPS7 TALDO1 WDR35 AXIN2 CITED2 EFTUD2 GPC6 KRT1 MYOZ2 PITX1 RRAS TAZ WDR5 B3GALT6 CNTNAP2 EHMT1 GPD1L LAMA4 MYPN PITX2 RUNX1 TBC1D24 WDR60 B3GALTL COG4 ELN GPX4 LAMP2 NAA15 PKD1 RYR2 TBC1D32 WNT4 B3GAT3 COG8 EMD GRHL3 LBR NEK1 PKD2 SALL1 TBX1 WNT5A BAG3 COL18A1 EMG1 HAND1 LDB3 NEXN PKP2 SALL4 TBX2 WNT7A BBS1 COL2A1 EOGT HAND2 LEFTY2 NFATC1 PLD1 SATB2 TBX20 WT1 BBS10 COL3A1 EP300 HCCS LIFR NFIX PLN SCLT1 TBX3 YAP1 BBS12 COLEC11 ESCO2 HCN4 LIG4 NIPBL PLXND1 SCN10A TBX5 ZBTB24 BBS2 COX7B EVC HES7 LMBR1 NKX2 PMM2 SCN1B TCAP ZEB2 BBS4 CREBBP EVC2 HEY2 LMCD1 NKX2-5 POLR1D SCN2B TCOF1 ZFPM2 BBS5 CRELD1 EZH2 HGD LMNA NKX2-6 PORCN SCN3B TCTN3 ZIC3 BBS9 CRELD2 FAM20C HGSNAT LMX1B NODAL PPA2 SCN4B TDGF1 ZMPSTE24 BCL9 CRKL FAM58A HOXA1 LRP2 NOS1 PPP3CA SCN5A TFAP2B ZNF236 BCOR CRYAA FBLN5 HPGD LRP5 NOTCH1 PQBP1 SDCCAG8 TGFB2 BHLHA9 CRYAB FBN1 HRAS LTBP4 NOTCH2 PRDM16 SETBP1 TGFB3 BMP4 CRYBB1 FBN2 HSPG2 LZTR1 NOTCH3 PRKAG2 SF3B4 TGFBR1 BMPR2 CRYGD FGD1 HUWE1 MAFB NPHP1 PRKD1 SH3PXD2B TGFBR2 BMS1 CSRP3 FGF16 IDH1 MAP2K1 NPHP3 PRKG1 SHANK3 TGIF1 BRAF CTCF FGF8 IDS MAP2K2 NPHP4 PRPS1 SHH TLL1 BUB1 CTNNA3 FGFR2 IFT122 MAP3K7 NPPA PSAT1 SHOC2 TMCO1 C12orf57 CTSA FGFR3 IFT80 MASP1 NR2F2 PSPH SHROOM3 TMEM216 van Wijngaarden AL, et al. J Med Genet 2020;0:1–8. doi: 10.1136/jmedgenet-2019-106715 Supplementary material J Med Genet Supplementary Table 2. List of variants of uncertain significance found in 95 probands with mitral valve prolapse based on the heart gene panel ID Gene Exon Allele Nucleotide Amino acid change % HGMD ClinVar change GnomAD 49 ACTN2 10 Htz c.883G>T p.(Glu295*) - - - 56 COL18A1 39 Htz c.4931A>C p.(Asn1644Thr) - - - 93 DSP 2 Htz c.273+5G>A p.(?) 0.029 Class 5 Class 3 123 DSP 2 Htz c.273+5G>A p.(?) 0.029 Class 5 Class 3 32 FBN1 59 Htz c.7412C>G p.(Pro2471Arg) 0.003 Class 4? Class 3 63 FBN1 35 Htz c.4447G>A p.(Gly1483Arg) - - Class 4 75 FBN2 13 Htz c.1826C>G p.(Thr609Ser) - - - 86 FBN2 13 Htz c.1826C>G p.(Thr609Ser) - - - 87 FBN2 13 Htz c.1826C>G p.(Thr609Ser) - - - 99 FBN2 41 Htz c.5225G>A p.(Arg1742Gln) 0.002 - - 8 FLNA 25 Htz c.4288G>C p.(Gly1430Arg) 0.001 - - 69 FLNA 25 Htz c.4150G>A p.(Gly1384Ser) - - - 81 LZTR1 19 Htz c.2263C>T p.(Arg755Trp) 0.001 - - 13 MYH6 22 Htz c.2928+5G>A p.(?) 0.175 Class 5 Class 2 and class 3 29 MYH6 29 Htz c.4136C>T p.(Thr1379Met) 0.056 Class 5 Class 2 and class 3 44 MYH6 24 Htz c.3154C>T p.(Arg1052*) 0.001 - Class 3 114 MYH6 22 Htz c.2842G>A p.(Glu948Lys) 0.002 - - 28 NKX2-5 2c Htz c.545T>A p.(Val182Asp) - - - 92 NKX2-5 2c Htz c.413G>T p.(Arg138Leu) - - - 103 NOTCH1 24 Htz c.3905G>A p.(Arg1302His) 0.004 - - 3 NOTCH3 4 Htz c.625G>A p.(Gly209Arg) 0.002 - - 39 NOTCH3 33 Htz c.6097C>A p.(Pro2033Thr) 0.004 - - 63 NPM3 4 Htz c.343C>T p.(Gln115*) 0.000 - - 3 PRDM16 11 Htz c.2855C>A p.(Thr952Lys) 0.001 - Class 3 37 RYR2 103 Htz c.14757-7_14757- p.(?) - Class 5 - 6delTCinsAT 21 SMAD6 2 Htz c.841C>G p.(Arg281Gly) 0.014 - Class 2 21 SNAI3 3 Htz c.795C>A p.(Tyr265*) 0.003 - - 35 TCOF1 21 Htz c.3283C>T p.(Gln1095*) - - - 64 TNS1 24 Htz c.4223A>G p.(Asn1408Ser) 0.001 - - 69 TPM1 5 Htz c.549_563+10del p.(Glu184_Gly188del) - - - 4 TTN 327 Htz c.80414A>C p.(Glu26805Ala) 0.003 - Class 3 37 TTN 327 Htz c.80717G>A p.(Arg26906Gln) 0.003 - Class 3 77 TTN 327 Htz c.80717G>A p.(Arg26906Gln) 0.003 - Class 3 118 TTN 141 Htz c.33580G>A p.(Val1119Met) 0.001 - Class 3 46 VEGFA 1 Htz c.405_408del p.(Asp135Glufs*38) - - - * Class 2 = likely benign, Class 3 = variant of uncertain significance, Class 4 = likely pathogenic, Class 5 = pathogenic, and Htz = heterozygous 2 van Wijngaarden AL, et al. J Med Genet 2020;0:1–8. doi: 10.1136/jmedgenet-2019-106715.
Recommended publications
  • Educational Paper Ciliopathies

    Educational Paper Ciliopathies

    Eur J Pediatr (2012) 171:1285–1300 DOI 10.1007/s00431-011-1553-z REVIEW Educational paper Ciliopathies Carsten Bergmann Received: 11 June 2011 /Accepted: 3 August 2011 /Published online: 7 September 2011 # The Author(s) 2011. This article is published with open access at Springerlink.com Abstract Cilia are antenna-like organelles found on the (NPHP) . Ivemark syndrome . Meckel syndrome (MKS) . surface of most cells. They transduce molecular signals Joubert syndrome (JBTS) . Bardet–Biedl syndrome (BBS) . and facilitate interactions between cells and their Alstrom syndrome . Short-rib polydactyly syndromes . environment. Ciliary dysfunction has been shown to Jeune syndrome (ATD) . Ellis-van Crefeld syndrome (EVC) . underlie a broad range of overlapping, clinically and Sensenbrenner syndrome . Primary ciliary dyskinesia genetically heterogeneous phenotypes, collectively (Kartagener syndrome) . von Hippel-Lindau (VHL) . termed ciliopathies. Literally, all organs can be affected. Tuberous sclerosis (TSC) . Oligogenic inheritance . Modifier. Frequent cilia-related manifestations are (poly)cystic Mutational load kidney disease, retinal degeneration, situs inversus, cardiac defects, polydactyly, other skeletal abnormalities, and defects of the central and peripheral nervous Introduction system, occurring either isolated or as part of syn- dromes. Characterization of ciliopathies and the decisive Defective cellular organelles such as mitochondria, perox- role of primary cilia in signal transduction and cell isomes, and lysosomes are well-known
  • Transcriptomic Analysis of Human Brain Microvascular Endothelial

    Transcriptomic Analysis of Human Brain Microvascular Endothelial

    www.nature.com/scientificreports OPEN Transcriptomic analysis of human brain microvascular endothelial cells exposed to laminin binding protein (adhesion lipoprotein) and Streptococcus pneumoniae Irene Jiménez‑Munguía1, Zuzana Tomečková1, Evelína Mochnáčová1, Katarína Bhide1, Petra Majerová2 & Mangesh Bhide1,2* Streptococcus pneumoniae invades the CNS and triggers a strong cellular response. To date, signaling events that occur in the human brain microvascular endothelial cells (hBMECs), in response to pneumococci or its surface adhesins are not mapped comprehensively. We evaluated the response of hBMECs to the adhesion lipoprotein (a laminin binding protein—Lbp) or live pneumococci. Lbp is a surface adhesin recently identifed as a potential ligand, which binds to the hBMECs. Transcriptomic analysis was performed by RNA‑seq of three independent biological replicates and validated with qRT‑PCR using 11 genes. In total 350 diferentially expressed genes (DEGs) were identifed after infection with S. pneumoniae, whereas 443 DEGs when challenged with Lbp. Total 231 DEGs were common in both treatments. Integrative functional analysis revealed participation of DEGs in cytokine, chemokine, TNF signaling pathways and phagosome formation. Moreover, Lbp induced cell senescence and breakdown, and remodeling of ECM. This is the frst report which maps complete picture of cell signaling events in the hBMECs triggered against S. pneumoniae and Lbp. The data obtained here could contribute in a better understanding of the invasion of pneumococci across BBB and underscores role of Lbp adhesin in evoking the gene expression in neurovascular unit. Streptococcus pneumoniae (also known as pneumococcus) is a life-threatening pathogen responsible for high morbidity and mortality rates worldwide1. It can cross the blood–brain barrier (BBB) and cause meningitis, commonly known as pneumococcal meningitis, a rare but life-threatening medical emergency.
  • Ciliopathiesneuromuscularciliopathies Disorders Disorders Ciliopathiesciliopathies

    Ciliopathiesneuromuscularciliopathies Disorders Disorders Ciliopathiesciliopathies

    NeuromuscularCiliopathiesNeuromuscularCiliopathies Disorders Disorders CiliopathiesCiliopathies AboutAbout EGL EGL Genet Geneticsics EGLEGL Genetics Genetics specializes specializes in ingenetic genetic diagnostic diagnostic testing, testing, with with ne nearlyarly 50 50 years years of of clinical clinical experience experience and and board-certified board-certified labor laboratoryatory directorsdirectors and and genetic genetic counselors counselors reporting reporting out out cases. cases. EGL EGL Genet Geneticsics offers offers a combineda combined 1000 1000 molecular molecular genetics, genetics, biochemical biochemical genetics,genetics, and and cytogenetics cytogenetics tests tests under under one one roof roof and and custom custom test testinging for for all all medically medically relevant relevant genes, genes, for for domestic domestic andand international international clients. clients. EquallyEqually important important to to improving improving patient patient care care through through quality quality genetic genetic testing testing is is the the contribution contribution EGL EGL Genetics Genetics makes makes back back to to thethe scientific scientific and and medical medical communities. communities. EGL EGL Genetics Genetics is is one one of of only only a afew few clinical clinical diagnostic diagnostic laboratories laboratories to to openly openly share share data data withwith the the NCBI NCBI freely freely available available public public database database ClinVar ClinVar (>35,000 (>35,000 variants variants on on >1700 >1700 genes) genes) and and is isalso also the the only only laboratory laboratory with with a a frefree oen olinnlein dea dtabtaabsaes (eE m(EVmCVlaCslas)s,s f)e, afetuatruinrgin ag vaa vraiarniatn ctl acslasisfiscifiactiaotino sne saercahrc ahn adn rde rpeoprot rrte rqeuqeuset sint tinetrefarcfaec, ew, hwichhic fha cfailcitialiteatse rsa praidp id interactiveinteractive curation curation and and reporting reporting of of variants.
  • KAT6A Syndrome: Genotype-Phenotype Correlation in 76 Patients with Pathogenic KAT6A Variants

    KAT6A Syndrome: Genotype-Phenotype Correlation in 76 Patients with Pathogenic KAT6A Variants

    KAT6A Syndrome: genotype-phenotype correlation in 76 patients with pathogenic KAT6A variants. Item Type Article Authors Kennedy, Joanna;Goudie, David;Blair, Edward;Chandler, Kate;Joss, Shelagh;McKay, Victoria;Green, Andrew;Armstrong, Ruth;Lees, Melissa;Kamien, Benjamin;Hopper, Bruce;Tan, Tiong Yang;Yap, Patrick;Stark, Zornitza;Okamoto, Nobuhiko;Miyake, Noriko;Matsumoto, Naomichi;Macnamara, Ellen;Murphy, Jennifer L;McCormick, Elizabeth;Hakonarson, Hakon;Falk, Marni J;Li, Dong;Blackburn, Patrick;Klee, Eric;Babovic- Vuksanovic, Dusica;Schelley, Susan;Hudgins, Louanne;Kant, Sarina;Isidor, Bertrand;Cogne, Benjamin;Bradbury, Kimberley;Williams, Mark;Patel, Chirag;Heussler, Helen;Duff- Farrier, Celia;Lakeman, Phillis;Scurr, Ingrid;Kini, Usha;Elting, Mariet;Reijnders, Margot;Schuurs-Hoeijmakers, Janneke;Wafik, Mohamed;Blomhoff, Anne;Ruivenkamp, Claudia A L;Nibbeling, Esther;Dingemans, Alexander J M;Douine, Emilie D;Nelson, Stanley F;Arboleda, Valerie A;Newbury-Ecob, Ruth DOI 10.1038/s41436-018-0259-2 Journal Genetics in medicine : official journal of the American College of Medical Genetics Download date 30/09/2021 21:53:13 Link to Item http://hdl.handle.net/10147/627191 Find this and similar works at - http://www.lenus.ie/hse HHS Public Access Author manuscript Author ManuscriptAuthor Manuscript Author Genet Med Manuscript Author . Author manuscript; Manuscript Author available in PMC 2019 October 01. Published in final edited form as: Genet Med. 2019 April ; 21(4): 850–860. doi:10.1038/s41436-018-0259-2. KAT6A Syndrome: Genotype-phenotype correlation in 76 patients with pathogenic KAT6A variants A full list of authors and affiliations appears at the end of the article. Abstract Purpose: Mutations in KAT6A have recently been identified as a cause of syndromic developmental delay.
  • Supplemental Figure 1. Vimentin

    Supplemental Figure 1. Vimentin

    Double mutant specific genes Transcript gene_assignment Gene Symbol RefSeq FDR Fold- FDR Fold- FDR Fold- ID (single vs. Change (double Change (double Change wt) (single vs. wt) (double vs. single) (double vs. wt) vs. wt) vs. single) 10485013 BC085239 // 1110051M20Rik // RIKEN cDNA 1110051M20 gene // 2 E1 // 228356 /// NM 1110051M20Ri BC085239 0.164013 -1.38517 0.0345128 -2.24228 0.154535 -1.61877 k 10358717 NM_197990 // 1700025G04Rik // RIKEN cDNA 1700025G04 gene // 1 G2 // 69399 /// BC 1700025G04Rik NM_197990 0.142593 -1.37878 0.0212926 -3.13385 0.093068 -2.27291 10358713 NM_197990 // 1700025G04Rik // RIKEN cDNA 1700025G04 gene // 1 G2 // 69399 1700025G04Rik NM_197990 0.0655213 -1.71563 0.0222468 -2.32498 0.166843 -1.35517 10481312 NM_027283 // 1700026L06Rik // RIKEN cDNA 1700026L06 gene // 2 A3 // 69987 /// EN 1700026L06Rik NM_027283 0.0503754 -1.46385 0.0140999 -2.19537 0.0825609 -1.49972 10351465 BC150846 // 1700084C01Rik // RIKEN cDNA 1700084C01 gene // 1 H3 // 78465 /// NM_ 1700084C01Rik BC150846 0.107391 -1.5916 0.0385418 -2.05801 0.295457 -1.29305 10569654 AK007416 // 1810010D01Rik // RIKEN cDNA 1810010D01 gene // 7 F5 // 381935 /// XR 1810010D01Rik AK007416 0.145576 1.69432 0.0476957 2.51662 0.288571 1.48533 10508883 NM_001083916 // 1810019J16Rik // RIKEN cDNA 1810019J16 gene // 4 D2.3 // 69073 / 1810019J16Rik NM_001083916 0.0533206 1.57139 0.0145433 2.56417 0.0836674 1.63179 10585282 ENSMUST00000050829 // 2010007H06Rik // RIKEN cDNA 2010007H06 gene // --- // 6984 2010007H06Rik ENSMUST00000050829 0.129914 -1.71998 0.0434862 -2.51672
  • The Extracellular Matrix Phenome Across Species

    The Extracellular Matrix Phenome Across Species

    bioRxiv preprint doi: https://doi.org/10.1101/2020.03.06.980169; this version posted March 6, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license. The extracellular matrix phenome across species Cyril Statzer1 and Collin Y. Ewald1* 1 Eidgenössische Technische Hochschule Zürich, Department of Health Sciences and Technology, Institute of Translational Medicine, Schwerzenbach-Zürich CH-8603, Switzerland *Corresponding authors: [email protected] (CYE) Keywords: Phenome, genotype-to-phenotype, matrisome, extracellular matrix, collagen, data mining. Highlights • 7.6% of the human phenome originates from variations in matrisome genes • 11’671 phenotypes are linked to matrisome genes of humans, mice, zebrafish, Drosophila, and C. elegans • Expected top ECM phenotypes are developmental, morphological and structural phenotypes • Nonobvious top ECM phenotypes include immune system, stress resilience, and age-related phenotypes 1 bioRxiv preprint doi: https://doi.org/10.1101/2020.03.06.980169; this version posted March 6, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license. 1 Abstract 2 Extracellular matrices are essential for cellular and organismal function. Recent 3 genome-wide and phenome-wide association studies started to reveal a broad 4 spectrum of phenotypes associated with genetic variants. However, the phenome or 5 spectrum of all phenotypes associated with genetic variants in extracellular matrix 6 genes is unknown.
  • ONCOPANEL (Popv3)

    ONCOPANEL (Popv3)

    ONCOPANEL (POPv3) TEST INFORMATION BACKGROUND: Somatic genetic alterations in oncogenes and tumor-suppressor genes contribute to the pathogenesis and evolution of human cancers. These alterations can provide prognostic and predictive information and stratify cancers for targeted therapeutic information. We classify these alterations into five tiers using the following guidelines: Tier 1: The alteration has well-established published evidence confirming clinical utility in this tumor type, in at least one of the following contexts: predicting response to treatment with an FDA-approved therapy; assessing prognosis; establishing a definitive diagnosis; or conferring an inherited increased risk of cancer to this patient and family. Tier 2: The alteration may have clinical utility in at least one of the following contexts: selection of an investigational therapy in clinical trials for this cancer type; limited evidence of prognostic association; supportive of a specific diagnosis; proven association of response to treatment with an FDA-approved therapy in a different type of cancer; or similar to a different mutation with a proven association with response to treatment with an FDA-approved therapyin this type of cancer. Tier 3: The alteration is of uncertain clinical utility, but may have a role as suggested by at least one of the following: demonstration of association with response to treatment in this cancer type in preclinical studies (e.g., in vitro studies or animal models); alteration in a biochemical pathway that has other known, therapeutically-targetable alterations; alteration in a highly conserved region of the protein predicted, in silico, to alter protein function; or selection of an investigational therapy for a different cancer type.
  • Synergistic Genetic Interactions Between Pkhd1 and Pkd1 Result in an ARPKD-Like Phenotype in Murine Models

    Synergistic Genetic Interactions Between Pkhd1 and Pkd1 Result in an ARPKD-Like Phenotype in Murine Models

    BASIC RESEARCH www.jasn.org Synergistic Genetic Interactions between Pkhd1 and Pkd1 Result in an ARPKD-Like Phenotype in Murine Models Rory J. Olson,1 Katharina Hopp ,2 Harrison Wells,3 Jessica M. Smith,3 Jessica Furtado,1,4 Megan M. Constans,3 Diana L. Escobar,3 Aron M. Geurts,5 Vicente E. Torres,3 and Peter C. Harris 1,3 Due to the number of contributing authors, the affiliations are listed at the end of this article. ABSTRACT Background Autosomal recessive polycystic kidney disease (ARPKD) and autosomal dominant polycystic kidney disease (ADPKD) are genetically distinct, with ADPKD usually caused by the genes PKD1 or PKD2 (encoding polycystin-1 and polycystin-2, respectively) and ARPKD caused by PKHD1 (encoding fibrocys- tin/polyductin [FPC]). Primary cilia have been considered central to PKD pathogenesis due to protein localization and common cystic phenotypes in syndromic ciliopathies, but their relevance is questioned in the simple PKDs. ARPKD’s mild phenotype in murine models versus in humans has hampered investi- gating its pathogenesis. Methods To study the interaction between Pkhd1 and Pkd1, including dosage effects on the phenotype, we generated digenic mouse and rat models and characterized and compared digenic, monogenic, and wild-type phenotypes. Results The genetic interaction was synergistic in both species, with digenic animals exhibiting pheno- types of rapidly progressive PKD and early lethality resembling classic ARPKD. Genetic interaction be- tween Pkhd1 and Pkd1 depended on dosage in the digenic murine models, with no significant enhancement of the monogenic phenotype until a threshold of reduced expression at the second locus was breached.
  • 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

    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
  • C-Myc Regulates Cell Proliferation During Lens Development

    C-Myc Regulates Cell Proliferation During Lens Development

    c-myc Regulates Cell Proliferation during Lens Development Gabriel R. Cavalheiro., Gabriel E. Matos-Rodrigues., Anielle L. Gomes, Paulo M. G. Rodrigues, Rodrigo A. P. Martins* Programa de Biologia Celular e do Desenvolvimento, Instituto de Cieˆncias Biome´dicas, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Rio de Janeiro, Brazil Abstract Myc protooncogenes play important roles in the regulation of cell proliferation, growth, differentiation and survival during development. In various developing organs, c-myc has been shown to control the expression of cell cycle regulators and its misregulated expression is detected in many human tumors. Here, we show that c-myc gene (Myc) is highly expressed in developing mouse lens. Targeted deletion of c-myc gene from head surface ectoderm dramatically impaired ocular organogenesis, resulting in severe microphtalmia, defective anterior segment development, formation of a lens stalk and/or aphakia. In particular, lenses lacking c-myc presented thinner epithelial cell layer and growth impairment that was detectable soon after its inactivation. Defective development of c-myc-null lens was not caused by increased cell death of lens progenitor cells. Instead, c-myc loss reduced cell proliferation, what was associated with an ectopic expression of Prox1 and p27Kip1 proteins within epithelial cells. Interestingly, a sharp decrease in the expression of the forkhead box transcription factor Foxe3 was also observed following c-myc inactivation. These data represent the first description of the physiological roles played by a Myc family member in mouse lens development. Our findings support the conclusion that c- myc regulates the proliferation of lens epithelial cells in vivo and may, directly or indirectly, modulate the expression of classical cell cycle regulators in developing mouse lens.
  • Supplementary Materials

    Supplementary Materials

    1 Supplementary Materials: Supplemental Figure 1. Gene expression profiles of kidneys in the Fcgr2b-/- and Fcgr2b-/-. Stinggt/gt mice. (A) A heat map of microarray data show the genes that significantly changed up to 2 fold compared between Fcgr2b-/- and Fcgr2b-/-. Stinggt/gt mice (N=4 mice per group; p<0.05). Data show in log2 (sample/wild-type). 2 Supplemental Figure 2. Sting signaling is essential for immuno-phenotypes of the Fcgr2b-/-lupus mice. (A-C) Flow cytometry analysis of splenocytes isolated from wild-type, Fcgr2b-/- and Fcgr2b-/-. Stinggt/gt mice at the age of 6-7 months (N= 13-14 per group). Data shown in the percentage of (A) CD4+ ICOS+ cells, (B) B220+ I-Ab+ cells and (C) CD138+ cells. Data show as mean ± SEM (*p < 0.05, **p<0.01 and ***p<0.001). 3 Supplemental Figure 3. Phenotypes of Sting activated dendritic cells. (A) Representative of western blot analysis from immunoprecipitation with Sting of Fcgr2b-/- mice (N= 4). The band was shown in STING protein of activated BMDC with DMXAA at 0, 3 and 6 hr. and phosphorylation of STING at Ser357. (B) Mass spectra of phosphorylation of STING at Ser357 of activated BMDC from Fcgr2b-/- mice after stimulated with DMXAA for 3 hour and followed by immunoprecipitation with STING. (C) Sting-activated BMDC were co-cultured with LYN inhibitor PP2 and analyzed by flow cytometry, which showed the mean fluorescence intensity (MFI) of IAb expressing DC (N = 3 mice per group). 4 Supplemental Table 1. Lists of up and down of regulated proteins Accession No.
  • 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