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Table SI. Differential Target Genes Between GSE105503 and GSE105291 Datasets

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Table SI. Differential target genes between GSE105503 and GSE105291 datasets. Gene ELF1 CSDE1 Fold change P‑value AATF 298.5087938 83.25382874 0.278899083 0.005998215 ABHD11 115.0217371 36.1496888 0.314285714 0.016921537 AC006486.1 501.1661401 52.58136552 0.104918033 4.96E‑06 AC007773.3 30.12474066 7.668115805 0.254545455 0.027561387 AC016586.1 58.42373947 16.43167673 0.28125 0.016439347 AC073528.1 2.738612788 15.33623161 5.6 0.035200688 AC091948.1 4.564354646 24.09979253 5.28 0.014571871 AC092291.2 1.825741858 18.62256696 10.2 0.005871816 AC092384.1 0.912870929 13.14534138 14.4 0.011364226 AC097381.1 28.2989988 6.57267069 0.232258065 0.022941492 AC110084.1 3.651483717 19.71801207 5.4 0.021715996 AC115618.1 139.6692522 10.95445115 0.078431373 3.75E‑06 ACAP3 245.5622799 75.58571294 0.307806691 0.011289432 ACD 154.275187 61.34492644 0.397633136 0.048875511 ACO2 138.7563812 50.39047529 0.363157895 0.032410205 ACOT4 186.2256696 60.24948133 0.323529412 0.016217042 ACTB 279.3385043 90.92194455 0.325490196 0.0150048 ACTL10 74.85541619 24.09979253 0.32195122 0.024725724 ACTR6 374.277081 144.5987552 0.386341463 0.036984508 ADAMTSL4‑AS1 78.50689991 25.19523765 0.320930233 0.023602102 ADAMTSL5 100.4158022 37.24513391 0.370909091 0.040636034 ADAP1 178.0098312 67.91759713 0.381538462 0.038639115 ADPGK 692.8690352 202.6573463 0.292490119 0.007834152 ADPRHL1 385.2315321 25.19523765 0.065402844 1.44E‑07 ADPRHL2 125.9761882 39.43602414 0.313043478 0.015827238 ADRM1 255.6038602 93.11283478 0.364285714 0.028154805 AF165138.7 12.78019301 84.34927386 6.6 0.000373367 AGPAT2 90.37422199 28.48157299 0.315151515 0.019780324 AIP 238.2593125 53.67681064 0.225287356 0.001725477 AK3 171.6197347 61.34492644 0.357446809 0.028088554 AKT1S1 278.4256334 95.30372501 0.342295082 0.019847132 AKT3 99.50293128 260.7159374 2.620183486 0.035161815 AL121761.2 57.51086854 14.2407865 0.247619048 0.009438085 AL138847.1 12.78019301 52.58136552 4.114285714 0.008611941 AL365202.1 2.738612788 15.33623161 5.6 0.035200688 AL590708.2 40.16632088 8.76356092 0.218181818 0.009576099 AL807752.1 41.99206274 12.04989627 0.286956522 0.026019956 ALAD 379.7543065 128.1670785 0.3375 0.017830926 ALDOA 564.1542342 211.4209072 0.374757282 0.03168705 AMDHD2 64.81383597 19.71801207 0.304225352 0.021252876 ANGPTL5 20.99603137 71.20393248 3.391304348 0.015775963 ANKRD13D 340.5008566 128.1670785 0.376407507 0.032328876 ANKRD37 93.11283478 25.19523765 0.270588235 0.00902156 AP1M1 434.5265623 95.30372501 0.219327731 0.001213631 AP2S1 178.0098312 62.44037156 0.350769231 0.025231473 AP5Z1 467.3899157 133.644304 0.2859375 0.006727076 APC2 158.8395417 63.53581667 0.4 0.049929391 APEH 200.8316044 51.48592041 0.256363636 0.00416681 APRT 500.2532692 49.29503018 0.098540146 3.02E‑06 ARF4 303.9860194 43.8178046 0.144144144 7.04E‑05 ARF6 125.9761882 48.19958506 0.382608696 0.04306704 ARHGAP1 413.5305309 151.1714259 0.365562914 0.027624698 ARHGAP20 52.03364296 134.7397491 2.589473684 0.042943545 ARHGAP4 220.0018939 64.63126179 0.293775934 0.008949955 ARHGDIA 335.9365019 60.24948133 0.179347826 0.000316086 ARHGEF18 119.5860917 23.00434742 0.192366412 0.001087007 ARL14EPL 14.60593487 42.72235949 2.925 0.046795738 ARMC5 755.8571294 90.92194455 0.120289855 1.40E‑05 ARMC7 130.5405429 47.10413995 0.360839161 0.032057642 Table SI. Continued. Gene ELF1 CSDE1 Fold change P‑value ARPC1A 615.2750063 142.407865 0.231454006 0.001740585 ARPC3 264.7325695 62.44037156 0.235862069 0.002200475 ARPC5L 293.0315683 82.15838363 0.280373832 0.006220771 ARRDC1 398.0117251 96.39917012 0.242201835 0.002359676 ARRDC2 243.7365381 59.15403621 0.242696629 0.002730491 ARX 62.07522318 15.33623161 0.247058824 0.00850848 ASB3 0.912870929 10.95445115 12 0.025290099 ASB6 154.275187 47.10413995 0.305325444 0.012666223 ASCL2 45.64354646 10.95445115 0.24 0.011339597 ASCL5 248.3008927 60.24948133 0.242647059 0.002704971 ASF1B 145.1464777 54.77225575 0.377358491 0.038593585 ASPSCR1 653.6155853 178.5575537 0.273184358 0.005119649 ATF4 104.9801569 32.86335345 0.313043478 0.017468547 ATG4D 77.59402898 23.00434742 0.296470588 0.016337607 ATP13A1 357.8454042 136.9306394 0.382653061 0.035200461 ATP6V0C 18.25741858 1.095445115 0.06 0.003987369 ATP6V0D1 745.8155491 144.5987552 0.193880049 0.000517964 AURKAIP1 208.1345719 23.00434742 0.110526316 1.60E‑05 AVPI1 82.15838363 27.38612788 0.333333333 0.027396287 B3GALT6 65.7267069 17.52712184 0.266666667 0.01142317 B3GAT3 295.7701811 59.15403621 0.2 0.000709501 BAD 68.46531969 16.43167673 0.24 0.006613086 BANF1 173.4454765 47.10413995 0.271578947 0.006248831 BCAP31 186.2256696 59.15403621 0.317647059 0.014676226 BCAT2 188.0514114 72.29937759 0.384466019 0.039618178 BCL10 186.2256696 50.39047529 0.270588235 0.005929087 BCL2L1 280.2513753 108.4490664 0.386970684 0.037937814 BHLHA15 25.56038602 6.57267069 0.257142857 0.037502224 BHLHE23 38.34057903 12.04989627 0.314285714 0.04090216 BIN3 196.2672498 52.58136552 0.267906977 0.005468476 BLOC1S3 216.3504102 52.58136552 0.243037975 0.002910062 BLOC1S4 125.9761882 24.09979253 0.191304348 0.000993829 BOP1 53.85938482 15.33623161 0.284745763 0.018904148 BRI3 167.05538 36.1496888 0.216393443 0.001645825 BRMS1 382.4929193 66.82215202 0.174701671 0.000250991 BSCL2 140.5821231 44.91324972 0.319480519 0.016765486 C10orf68 81.2455127 271.6703885 3.343820225 0.009036741 C10orf95 99.50293128 25.19523765 0.253211009 0.006042517 C11orf31 68.46531969 16.43167673 0.24 0.006613086 C11orf35 86.72273827 28.48157299 0.328421053 0.024736235 C12orf10 254.6909892 83.25382874 0.32688172 0.015685513 C12orf61 243.7365381 76.68115805 0.314606742 0.012805164 C12orf66 725.7323887 176.3666635 0.243018868 0.002434456 C14orf2 303.9860194 107.3536213 0.353153153 0.02321312 C14orf39 75.76828712 215.8026877 2.848192771 0.02352538 C14orf80 256.5167311 101.8763957 0.397153025 0.043793329 C16orf13 103.154415 35.05424368 0.339823009 0.02646983 C16orf58 188.0514114 58.0585911 0.308737864 0.012508944 C16orf91 230.0434742 37.24513391 0.161904762 0.000198532 C17orf50 44.73067553 15.33623161 0.342857143 0.04849718 C17orf59 187.1385405 30.67246322 0.163902439 0.000257068 C17orf62 622.5779737 88.73105432 0.142521994 5.25E‑05 C18orf32 91.28709292 8.76356092 0.096 3.50E‑05 C19orf24 173.4454765 16.43167673 0.094736842 7.59E‑06 C19orf25 120.4989627 32.86335345 0.272727273 0.007788001 C19orf26 56.59799761 19.71801207 0.348387097 0.042617227 C19orf40 223.6533776 51.48592041 0.230204082 0.002042779 C19orf52 100.4158022 35.05424368 0.349090909 0.030548916 C19orf53 210.8731846 26.29068276 0.124675325 3.61E‑05 Table SI. Continued. Gene ELF1 CSDE1 Fold change P‑value C19orf73 71.20393248 12.04989627 0.169230769 0.00110821 C19orf81 91.28709292 31.76790834 0.348 0.031606396 C1QTNF4 25.56038602 6.57267069 0.257142857 0.037502224 C1orf122 46.55641739 9.859006035 0.211764706 0.006533725 C1orf172 123.2375754 26.29068276 0.213333333 0.001923661 C1orf227 0.912870929 16.43167673 18 0.00367025 C1orf229 87.6356092 29.57701811 0.3375 0.027976145 C1orf74 38.34057903 12.04989627 0.314285714 0.04090216 C20orf24 55.68512668 17.52712184 0.314754098 0.028142284 C21orf119 97.67718942 25.19523765 0.257943925 0.006767594 C21orf2 1068.058987 142.407865 0.133333333 2.77E‑05 C21orf59 177.0969603 42.72235949 0.241237113 0.003076096 C2orf42 342.3265984 93.11283478 0.272 0.005009274 C2orf43 342.3265984 134.7397491 0.3936 0.040737709 C3orf80 60.24948133 19.71801207 0.327272727 0.031157943 C4orf27 130.5405429 50.39047529 0.386013986 0.044415698 C4orf40 52.94651389 146.7896454 2.772413793 0.029878694 C6orf1 93.11283478 24.09979253 0.258823529 0.00716767 C6orf211 321.3305671 94.20827989 0.293181818 0.007979844 C6orf226 132.3662847 26.29068276 0.19862069 0.00118118 C7orf43 189.8771533 67.91759713 0.357692308 0.027432024 C8orf44‑SGK3 18.25741858 3.286335345 0.18 0.02888742 C8orf82 160.6652835 63.53581667 0.395454545 0.047147326 C9orf142 77.59402898 24.09979253 0.310588235 0.020389666 C9orf37 92.19996385 35.05424368 0.38019802 0.047280981 C9orf69 310.3761159 42.72235949 0.137647059 4.96E‑05 CAP1 293.0315683 90.92194455 0.310280374 0.011317369 CATSPERG 533.1166226 211.4209072 0.396575342 0.042433396 CBWD1 125.0633173 310.0109675 2.478832117 0.045825518 CCBL1 336.8493729 132.5488589 0.393495935 0.040700399 CCDC102B 38.34057903 115.0217371 3 0.021820736 CCDC130 285.7286008 62.44037156 0.218530351 0.001300397 CCDC137 142.407865 40.53146926 0.284615385 0.008939117 CCDC173 44.73067553 138.0260845 3.085714286 0.017474759 CCDC28A 213.6117974 62.44037156 0.292307692 0.008786538 CCDC61 440.9166588 71.20393248 0.161490683 0.000138315 CCDC71 70.29106155 10.95445115 0.155844156 0.000751648 CCDC85B 101.3286731 27.38612788 0.27027027 0.008402946 CCDC9 282.989988 75.58571294 0.267096774 0.004675199 CCDC94 241.9107962 52.58136552 0.217358491 0.001360604 CCND3 265.6454404 96.39917012 0.362886598 0.027396976 CCNDBP1 189.8771533 63.53581667 0.334615385 0.019324437 CCNO 108.6316406 37.24513391 0.342857143 0.026925837 CCZ1B 394.3602414 161.0304319 0.408333333 0.049000666 CD1C 23.73464416 66.82215202 2.815384615 0.03927396 CD200R1 53.85938482 147.8850905 2.745762712 0.031311506 CD2BP2 981.3362489 77.77660317 0.079255814 4.36E‑07 CD69 27.38612788 83.25382874 3.04 0.024176623 CDC45 331.3721473 78.87204828 0.238016529 0.002161582 CDIPT 187.1385405 49.29503018 0.263414634 0.005054287 CDK2AP2 191.7028951 59.15403621 0.308571429 0.012389881 CDK9 315.8533415 53.67681064 0.169942197 0.000222691 CEBPA 67.55244876 17.52712184 0.259459459 0.009758076 CEBPD 162.4910254 28.48157299 0.175280899 0.000451076 CELF5 83.98412548 31.76790834 0.37826087 0.04821733 CENPB 122.3247045 31.76790834 0.259701493 0.005896981 CFD 33.77622438 9.859006035 0.291891892 0.03678151 CHCHD2 107.7187696 31.76790834 0.294915254 0.012680586 CHCHD5 630.7938121 81.06293851 0.128509407 2.36E‑05 Table SI.
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  • 1 Human Cells Contain Myriad Excised Linear Intron Rnas with Potential

    1 Human Cells Contain Myriad Excised Linear Intron Rnas with Potential

    Human cells contain myriad excised linear intron RNAs with potential functions in gene regulation and as disease biomarkers Jun Yao,1 Hengyi Xu,1 Shelby Winans,1 Douglas C. Wu,1,3 Manuel Ares, Jr.,2 and Alan M. Lambowitz1,4 1Institute for Cellular and Molecular Biology and Departments of Molecular Biosciences and Oncology University of Texas at Austin Austin TX 78712 2Department of Molecular, Cell, and Developmental Biology University of California, Santa Cruz Santa Cruz, California 95064 Running Title: Structured excised linear intron RNAs 3Present address: Invitae Corporation 4To whom correspondence should be addressed. E-mail: [email protected] 1 Abstract We used thermostable group II intron reverse transcriptase sequencing (TGIRT-seq), which gives full-length end-to-end sequence reads of structured RNAs, to identify > 8,500 short full- length excised linear intron (FLEXI) RNAs originating from > 3,500 different genes in human cells and tissues. Most FLEXI RNAs have stable predicted secondary structures, making them difficult to detect by other methods. Some FLEXI RNAs corresponded to annotated mirtron pre- miRNAs (introns that are processed by DICER into functional miRNAs) or agotrons (introns that bind AGO2 and function in a miRNA-like manner) and a few encode snoRNAs. However, the vast majority had not been characterized previously. FLEXI RNA profiles were cell-type specific, reflecting differences in host gene transcription, alternative splicing, and intron RNA turnover, and comparisons of matched tumor and healthy tissues from breast cancer patients and cell lines revealed hundreds of differences in FLEXI RNA expression. About half of the FLEXI RNAs contained an experimentally identified binding site for one or more proteins in published CLIP-seq datasets.

  • European Patent Office of Opposition to That Patent, in Accordance with the Implementing Regulations

    (19) TZZ Z_T (11) EP 2 884 280 B1 (12) EUROPEAN PATENT SPECIFICATION (45) Date of publication and mention (51) Int Cl.: of the grant of the patent: G01N 33/566 (2006.01) 09.05.2018 Bulletin 2018/19 (21) Application number: 13197310.9 (22) Date of filing: 15.12.2013 (54) Method for evaluating the scent performance of perfumes and perfume mixtures Verfahren zur Bewertung des Duftverhaltens von Duftstoffen und Duftstoffmischungen Procédé d’evaluation de senteur performance du parfums et mixtures de parfums (84) Designated Contracting States: (56) References cited: AL AT BE BG CH CY CZ DE DK EE ES FI FR GB WO-A2-03/091388 GR HR HU IE IS IT LI LT LU LV MC MK MT NL NO PL PT RO RS SE SI SK SM TR • BAGHAEI KAVEH A: "Deorphanization of human olfactory receptors by luciferase and Ca-imaging (43) Date of publication of application: methods.",METHODS IN MOLECULAR BIOLOGY 17.06.2015 Bulletin 2015/25 (CLIFTON, N.J.) 2013, vol. 1003, 19 June 2013 (2013-06-19), pages229-238, XP008168583, ISSN: (73) Proprietor: Symrise AG 1940-6029 37603 Holzminden (DE) • KAVEH BAGHAEI ET AL: "Olfactory receptors coded by segregating pseudo genes and (72) Inventors: odorants with known specific anosmia.", 33RD • Hatt, Hanns ANNUAL MEETING OF THE ASSOCIATION FOR 44789 Bochum (DE) CHEMORECEPTION, 1 April 2011 (2011-04-01), • Gisselmann, Günter XP055111507, 58456 Witten (DE) • TOUHARA ET AL: "Deorphanizing vertebrate • Ashtibaghaei, Kaveh olfactory receptors: Recent advances in 44801 Bochum (DE) odorant-response assays", NEUROCHEMISTRY • Panten, Johannes INTERNATIONAL, PERGAMON PRESS, 37671 Höxter (DE) OXFORD, GB, vol.
  • Pathogenetic Subgroups of Multiple Myeloma Patients

    Pathogenetic Subgroups of Multiple Myeloma Patients

    View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector ARTICLE High-resolution genomic profiles define distinct clinico- pathogenetic subgroups of multiple myeloma patients Daniel R. Carrasco,1,2,8 Giovanni Tonon,1,8 Yongsheng Huang,3,8 Yunyu Zhang,1 Raktim Sinha,1 Bin Feng,1 James P. Stewart,3 Fenghuang Zhan,3 Deepak Khatry,1 Marina Protopopova,5 Alexei Protopopov,5 Kumar Sukhdeo,1 Ichiro Hanamura,3 Owen Stephens,3 Bart Barlogie,3 Kenneth C. Anderson,1,4 Lynda Chin,1,7 John D. Shaughnessy, Jr.,3,9 Cameron Brennan,6,9 and Ronald A. DePinho1,5,9,* 1 Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts 02115 2 Department of Pathology, Brigham and Women’s Hospital, Boston, Massachusetts 02115 3 The Donna and Donald Lambert Laboratory of Myeloma Genetics, Myeloma Institute for Research and Therapy, University of Arkansas for Medical Sciences, Little Rock, Arkansas 72205 4 The Jerome Lipper Multiple Myeloma Center, Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts 02115 5 Center for Applied Cancer Science, Belfer Institute for Innovative Cancer Science, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts 6 Neurosurgery Service, Memorial Sloan-Kettering Cancer Center, Department of Neurosurgery, Weill Cornell Medical College, New York, New York 10021 7 Department of Dermatology, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, 02115 8 These authors contributed equally to this work. 9 Cocorresponding authors: [email protected] (C.B.); [email protected] (J.D.S.); [email protected] (R.A.D.) *Correspondence: [email protected] Summary To identify genetic events underlying the genesis and progression of multiple myeloma (MM), we conducted a high-resolu- tion analysis of recurrent copy number alterations (CNAs) and expression profiles in a collection of MM cell lines and out- come-annotated clinical specimens.
  • Apoptotic Cells Inflammasome Activity During the Uptake of Macrophage

    Apoptotic Cells Inflammasome Activity During the Uptake of Macrophage

    Downloaded from http://www.jimmunol.org/ by guest on September 29, 2021 is online at: average * The Journal of Immunology , 26 of which you can access for free at: 2012; 188:5682-5693; Prepublished online 20 from submission to initial decision 4 weeks from acceptance to publication April 2012; doi: 10.4049/jimmunol.1103760 http://www.jimmunol.org/content/188/11/5682 Complement Protein C1q Directs Macrophage Polarization and Limits Inflammasome Activity during the Uptake of Apoptotic Cells Marie E. Benoit, Elizabeth V. Clarke, Pedro Morgado, Deborah A. Fraser and Andrea J. Tenner J Immunol cites 56 articles Submit online. Every submission reviewed by practicing scientists ? is published twice each month by Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts http://jimmunol.org/subscription http://www.jimmunol.org/content/suppl/2012/04/20/jimmunol.110376 0.DC1 This article http://www.jimmunol.org/content/188/11/5682.full#ref-list-1 Information about subscribing to The JI No Triage! Fast Publication! Rapid Reviews! 30 days* Why • • • Material References Permissions Email Alerts Subscription Supplementary The Journal of Immunology The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2012 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. This information is current as of September 29, 2021. The Journal of Immunology Complement Protein C1q Directs Macrophage Polarization and Limits Inflammasome Activity during the Uptake of Apoptotic Cells Marie E.
  • Supplementary Material Contents

    Supplementary Material Contents

    Supplementary Material Contents Immune modulating proteins identified from exosomal samples.....................................................................2 Figure S1: Overlap between exosomal and soluble proteomes.................................................................................... 4 Bacterial strains:..............................................................................................................................................4 Figure S2: Variability between subjects of effects of exosomes on BL21-lux growth.................................................... 5 Figure S3: Early effects of exosomes on growth of BL21 E. coli .................................................................................... 5 Figure S4: Exosomal Lysis............................................................................................................................................ 6 Figure S5: Effect of pH on exosomal action.................................................................................................................. 7 Figure S6: Effect of exosomes on growth of UPEC (pH = 6.5) suspended in exosome-depleted urine supernatant ....... 8 Effective exosomal concentration....................................................................................................................8 Figure S7: Sample constitution for luminometry experiments..................................................................................... 8 Figure S8: Determining effective concentration .........................................................................................................