Supplementary Table 1. Hypermethylated Loci in Estrogen-Pre-Exposed Stem/Progenitor-Derived Epithelial Cells

Total Page:16

File Type:pdf, Size:1020Kb

Supplementary Table 1. Hypermethylated Loci in Estrogen-Pre-Exposed Stem/Progenitor-Derived Epithelial Cells Supplementary Table 1. Hypermethylated loci in estrogen-pre-exposed stem/progenitor-derived epithelial cells. Entrez Gene Probe genomic location* Control# Pre-exposed# Description Gene ID name chr5:134392762-134392807 5307 PITX1 -0.112183718 6.077605311 paired-like homeodomain transcription factor 1 chr12:006600331-006600378 171017 ZNF384 -0.450661784 6.034362758 zinc finger protein 384 57121 GPR92 G protein-coupled receptor 92 chr3:015115848-015115900 64145 ZFYVE20 -1.38491748 5.544950925 zinc finger, FYVE domain containing 20 chr7:156312210-156312270 -2.026450994 5.430611412 chr4:009794114-009794159 9948 WDR1 0.335617144 5.352264173 WD repeat domain 1 chr17:007280631-007280676 284114 TMEM102 -2.427266294 5.060047786 transmembrane protein 102 chr20:055274561-055274606 655 BMP7 0.764898513 5.023260524 bone morphogenetic protein 7 chr10:088461669-088461729 11155 LDB3 0 4.817869864 LIM domain binding 3 chr7:005314259-005314304 80028 FBXL18 0.921361233 4.779265347 F-box and leucine-rich repeat protein 18 chr9:130571259-130571313 59335 PRDM12 1.123111331 4.740306098 PR domain containing 12 chr2:054768043-054768088 6711 SPTBN1 -0.089623066 4.691756995 spectrin, beta, non-erythrocytic 1 chr10:070330822-070330882 79009 DDX50 -2.848748309 4.691491169 DEAD (Asp-Glu-Ala-Asp) box polypeptide 50 chr1:162469807-162469854 54499 TMCO1 1.495802762 4.655023656 transmembrane and coiled-coil domains 1 chr2:080442234-080442279 1496 CTNNA2 1.296310425 4.507269831 catenin (cadherin-associated protein), alpha 2 347730 LRRTM1 leucine rich repeat transmembrane neuronal 1 chr1:042816934-042816987 4904 YBX1 0.088776519 4.495984562 Y box binding protein 1 chr20:044751602-044751647 112858 TP53RK -0.891062327 4.436484463 TP53 regulating kinase chr19:042261146-042261191 147923 ZNF420 -1.7979144 4.321177101 zinc finger protein 420 chr3:061521967-061522014 5793 PTPRG 1.2291677 4.237829771 protein tyrosine phosphatase, receptor type, G chr22:048600733-048600778 9889 ZBED4 0.34776545 4.183370855 zinc finger, BED-type containing 4 chr1:063497644-063497703 0 4.165474705 chr4:142411142-142411187 57484 RNF150 0.107319494 4.141458153 ring finger protein 150 chr17:002539774-002539819 23277 KIAA0664 0.68755446 4.137010647 KIAA0664 chr20:054638489-054638535 7022 TFAP2C 0.562945412 4.133648881 transcription factor AP-2 gamma chr11:075833207-075833258 56946 C11orf30 0.204044031 4.104957159 chromosome 11 open reading frame 30 chr22:048330412-048330459 0.720341093 4.014749777 chr16:025030484-025030529 51451 LCMT1 0.068896005 3.852987637 leucine carboxyl methyltransferase 1 chr3:053855140-053855185 55540 IL17RB -0.33802645 3.698757049 interleukin 17 receptor B 55349 CHDH choline dehydrogenase chr13:047789025-047789070 5925 RB1 -0.085901601 3.664953161 retinoblastoma 1 (including osteosarcoma) chr3:010251208-010251253 3656 IRAK2 -0.562734894 3.604471701 interleukin-1 receptor-associated kinase 2 chr15:041000713-041000770 146057 TTBK2 -1.017021165 3.592982758 tau tubulin kinase 2 chr4:013225054-013225099 0.248316279 3.58191584 chr1:090903244-090903289 0.658844243 3.574661326 chr10:111959093-111959143 4601 MXI1 0.267636537 3.566586884 MAX interactor 1 chr2:104919065-104919114 -1.19768317 3.502613025 Entrez Gene Probe genomic location* Control# Pre-exposed# Description Gene ID name chr3:036961783-036961828 -1.450582421 3.486571582 chr3:141884566-141884617 287015 TRIM42 -0.404862117 3.470429413 tripartite motif-containing 42 chr20:054400955-054401010 1477 CSTF1 0.541746739 3.463611647 cleavage stimulation factor subunit 1 6790 STK6 aurora kinase A chr12:113303987-113304047 6910 TBX5 1.419170558 3.460274721 T-box 5 chrX:152589739-152589787 57595 PDZD4 -1.040754735 3.427331954 PDZ domain containing 4 chr16:074239053-074239104 54386 TERF2IP 1.037943338 3.397449609 telomeric repeat binding factor 2, interacting protein 3735 KARS lysyl-tRNA synthetase chr7:090541197-090541242 8321 FZD1 -1.593529038 3.378354909 frizzled homolog 1 (Drosophila) wingless-type MMTV integration site family, member chr3:055496465-055496525 7474 WNT5A 0.875195991 3.355084023 5A chr7:148908004-148908049 168544 ZNF467 -0.718466725 3.312450877 zinc finger protein 467 chrX:048532866-048532926 11040 PIM2 0.081525699 3.240311988 pim-2 oncogene chr4:175579652-175579706 80817 KIAA1712 -0.496953992 3.221143024 KIAA1712 26269 FBXO8 F-box protein 8 chr12:102861897-102861942 6996 TDG 0.98608753 3.154607896 thymine-DNA glycosylase chr3:187561710-187561765 1608 DGKG 0.84407774 3.123007724 diacylglycerol kinase, gamma 90kDa chr7:026907480-026907525 3198 HOXA1 -0.495953406 3.095005637 homeobox A1 chr1:148067326-148067373 57592 ZNF687 -0.448548466 3.086631773 zinc finger protein 687 chr14:021049339-021049390 56339 METTL3 0.395823627 3.032608072 methyltransferase like 3 chr1:025003391-025003441 864 RUNX3 -1.016189553 3.01869822 runt-related transcription factor 3 chr19:063553325-063553371 503538 FLJ23569 1.116803981 3.012681196 BC040926 1 A1BG alpha-1-B glycoprotein chr15:039015828-039015873 54567 DLL4 -0.580946517 2.997730441 delta-like 4 (Drosophila) chr13:098650617-098650662 337867 PHGDHL1 -1.28948333 2.967636564 UBA domain containing 2 chrX:039762972-039763017 -0.309681229 2.942323886 chr9:137449365-137449410 54863 FLJ20245 -0.101451753 2.930690215 chromosome 9 open reading frame 167 chr19:003551280-003551325 6915 TBXA2R 0.250492144 2.900512725 thromboxane A2 receptor chrX:150014320-150014369 9248 GPR50 -0.250756805 2.83080234 G protein-coupled receptor 50 chr4:084077214-084077259 79966 SCD5 1.089023862 2.829490987 stearoyl-CoA desaturase 5 chr3:024512242-024512287 7068 THRB 1.291285855 2.788746329 thyroid hormone receptor, beta chr15:080122616-080122661 84206 RKHD3 1.288657655 2.76269307 ring finger and KH domain containing 3 chr2:122123682-122123729 23332 CLASP1 -0.0757216352.712523967 cytoplasmic linker associated protein 1 chr1:243790687-243790737 84838 ZNF496 -0.2842422 2.685882382 zinc finger protein 496 chr21:042979357-042979408 5152 PDE9A 0.123685317 2.624271817 phosphodiesterase 9A chr1:225090221-225090268 200107 FLJ31401 0.232666922 2.621164503 hypothetical protein FLJ31401 574029 DUSP5P dual specificity phosphatase 5 pseudogene chr5:000104307-000104359 -0.362033729 2.614971988 chr12:056374074-056374133 10956 OS9 -1.59401999 2.578938713 amplified in osteosarcoma chr6:167283818-167283870 0.172932602 2.550975145 Entrez Gene Probe genomic location* Control# Pre-exposed# Description Gene ID name chr7:016339679-016339728 25928 SOSTDC1 -0.410989559 2.544224252 sclerostin domain containing 1 chr17:001901955-001902000 -0.747702291 2.529820947 chr14:049135324-049135369 122769 PPIL5 -0.392227131 2.522634792 peptidylprolyl isomerase (cyclophilin)-like 5 chr10:035969628-035969673 8325 FZD8 0.175766627 2.517275693 frizzled homolog 8 (Drosophila) reprimo, TP53 dependent G2 arrest mediator chr2:154160400-154160445 56475 RPRM -0.120005751 2.510801325 candidate chr6:044351420-044351465 -0.004412416 2.459431619 chrX:131816623-131816668 90161 HS6ST2 1.328888425 2.449591193 heparan sulfate 6-O-sulfotransferase 2 chr12:021545932-021545984 51026 GOLT1B 1.448123641 2.441327786 golgi transport 1 homolog B (S. cerevisiae) 5965 RECQL RecQ protein-like (DNA helicase Q1-like) chr2:063192875-063192920 5013 OTX1 0.303037171 2.423589591 orthodenticle homeobox 1 chr9:037026850-037026895 -0.736277206 2.2761096 chr9:135617752-135617797 51116 MRPS2 0.775981707 2.270528942 mitochondrial ribosomal protein S2 chr11:022603583-022603628 2188 FANCF -0.38266565 2.247927513 Fanconi anemia, complementation group F chr19:046763214-046763259 -0.305677715 2.197088301 chr19:004075078-004075123 5605 MAP2K2 0.059248882 2.15796136 mitogen-activated protein kinase kinase 2 chr19:044032796-044032841 3191 HNRPL -1.033266259 2.140860395 heterogeneous nuclear ribonucleoprotein L early growth response 2 (Krox-20 homolog, chr10:064246532-064246582 1959 EGR2 -0.931111704 2.133348048 Drosophila) chr3:035655553-035655598 10777 ARPP-21 -0.734235565 2.100946198 cyclic AMP-regulated phosphoprotein, 21 kD chr16:066828069-066828114 80004 RBM35B 0.292766965 2.053111336 RNA binding motif protein 35B chr19:045596393-045596438 57716 PRX 0.286967596 2.049716456 periaxin chr19:004742518-004742563 55527 FEM1A -0.390849153 2.044394119 fem-1 homolog a (C. elegans) chr8:100095032-100095077 157680 VPS13B 0.209194091 1.98951254 vacuolar protein sorting 13 homolog B (yeast) chr22:036674101-036674146 5435 POLR2F 1.119372056 1.973992205 polymerase (RNA) II (DNA directed) polypeptide F 84645 C22orf23 chromosome 22 open reading frame 23 chr6:127838400-127838445 9729 KIAA0408 0.077406463 1.939520326 KIAA0408 387104 C6orf174 chromosome 6 open reading frame 174 chr2:236869638-236869693 -0.363379146 1.926191613 chr5:065256618-065256666 55914 ERBB2IP 0.179710481 1.907775975 erbb2 interacting protein chr17:070797324-070797369 60386 SLC25A19 0.481796529 1.898505189 solute carrier family 25, member 19 chr14:037138040-037138085 -0.03955225 1.871924304 chr14:068330532-068330577 677 ZFP36L1 0.001197193 1.861835952 zinc finger protein 36, C3H type-like 1 chr14:094304647-094304692 145258 GSC 0.333210027 1.856492354 goosecoid chr12:055918310-055918355 56901 LOC56901 0.455616401 1.826414967 NADH dehydrogenase 1 alpha subcomplex, 4-like 2 chr19:018867391-018867436 2657 GDF1 0.116565674 1.820215719 growth differentiation factor 1 10715 LASS1 LAG1 homolog, ceramide synthase 1 (S. cerevisiae) chr7:022826983-022827028 84668 FAM126A -0.592585118 1.710967304 family with sequence similarity 126, member A chr2:011836925-011836970 23175 LPIN1 -0.984281646 1.693560454 lipin 1 chr18:009465013-009465058 10928 RALBP1
Recommended publications
  • Supplementary Data
    Figure 2S 4 7 A - C 080125 CSCs 080418 CSCs - + IFN-a 48 h + IFN-a 48 h + IFN-a 72 h 6 + IFN-a 72 h 3 5 MRFI 4 2 3 2 1 1 0 0 MHC I MHC II MICA MICB ULBP-1 ULBP-2 ULBP-3 ULBP-4 MHC I MHC II MICA MICB ULBP-1 ULBP-2 ULBP-3 ULBP-4 7 B 13 080125 FBS - D 080418 FBS - + IFN-a 48 h 12 + IFN-a 48 h + IFN-a 72 h + IFN-a 72 h 6 080125 FBS 11 10 5 9 8 4 7 6 3 MRFI 5 4 2 3 2 1 1 0 0 MHC I MHC II MICA MICB ULBP-1 ULBP-2 ULBP-3 ULBP-4 MHC I MHC II MICA MICB ULBP-1 ULBP-2 ULBP-3 ULBP-4 Molecule Molecule FIGURE 4S FIGURE 5S Panel A Panel B FIGURE 6S A B C D Supplemental Results Table 1S. Modulation by IFN-α of APM in GBM CSC and FBS tumor cell lines. Molecule * Cell line IFN-α‡ HLA β2-m# HLA LMP TAP1 TAP2 class II A A HC§ 2 7 10 080125 CSCs - 1∞ (1) 3 (65) 2 (91) 1 (2) 6 (47) 2 (61) 1 (3) 1 (2) 1 (3) + 2 (81) 11 (80) 13 (99) 1 (3) 8 (88) 4 (91) 1 (2) 1 (3) 2 (68) 080125 FBS - 2 (81) 4 (63) 4 (83) 1 (3) 6 (80) 3 (67) 2 (86) 1 (3) 2 (75) + 2 (99) 14 (90) 7 (97) 5 (75) 7 (100) 6 (98) 2 (90) 1 (4) 3 (87) 080418 CSCs - 2 (51) 1 (1) 1 (3) 2 (47) 2 (83) 2 (54) 1 (4) 1 (2) 1 (3) + 2 (81) 3 (76) 5 (75) 2 (50) 2 (83) 3 (71) 1 (3) 2 (87) 1 (2) 080418 FBS - 1 (3) 3 (70) 2 (88) 1 (4) 3 (87) 2 (76) 1 (3) 1 (3) 1 (2) + 2 (78) 7 (98) 5 (99) 2 (94) 5 (100) 3 (100) 1 (4) 2 (100) 1 (2) 070104 CSCs - 1 (2) 1 (3) 1 (3) 2 (78) 1 (3) 1 (2) 1 (3) 1 (3) 1 (2) + 2 (98) 8 (100) 10 (88) 4 (89) 3 (98) 3 (94) 1 (4) 2 (86) 2 (79) * expression of APM molecules was evaluated by intracellular staining and cytofluorimetric analysis; ‡ cells were treatead or not (+/-) for 72 h with 1000 IU/ml of IFN-α; # β-2 microglobulin; § β-2 microglobulin-free HLA-A heavy chain; ∞ values are indicated as ratio between the mean of fluorescence intensity of cells stained with the selected mAb and that of the negative control; bold values indicate significant MRFI (≥ 2).
    [Show full text]
  • Identification of the Binding Partners for Hspb2 and Cryab Reveals
    Brigham Young University BYU ScholarsArchive Theses and Dissertations 2013-12-12 Identification of the Binding arP tners for HspB2 and CryAB Reveals Myofibril and Mitochondrial Protein Interactions and Non- Redundant Roles for Small Heat Shock Proteins Kelsey Murphey Langston Brigham Young University - Provo Follow this and additional works at: https://scholarsarchive.byu.edu/etd Part of the Microbiology Commons BYU ScholarsArchive Citation Langston, Kelsey Murphey, "Identification of the Binding Partners for HspB2 and CryAB Reveals Myofibril and Mitochondrial Protein Interactions and Non-Redundant Roles for Small Heat Shock Proteins" (2013). Theses and Dissertations. 3822. https://scholarsarchive.byu.edu/etd/3822 This Thesis is brought to you for free and open access by BYU ScholarsArchive. It has been accepted for inclusion in Theses and Dissertations by an authorized administrator of BYU ScholarsArchive. For more information, please contact [email protected], [email protected]. Identification of the Binding Partners for HspB2 and CryAB Reveals Myofibril and Mitochondrial Protein Interactions and Non-Redundant Roles for Small Heat Shock Proteins Kelsey Langston A thesis submitted to the faculty of Brigham Young University in partial fulfillment of the requirements for the degree of Master of Science Julianne H. Grose, Chair William R. McCleary Brian Poole Department of Microbiology and Molecular Biology Brigham Young University December 2013 Copyright © 2013 Kelsey Langston All Rights Reserved ABSTRACT Identification of the Binding Partners for HspB2 and CryAB Reveals Myofibril and Mitochondrial Protein Interactors and Non-Redundant Roles for Small Heat Shock Proteins Kelsey Langston Department of Microbiology and Molecular Biology, BYU Master of Science Small Heat Shock Proteins (sHSP) are molecular chaperones that play protective roles in cell survival and have been shown to possess chaperone activity.
    [Show full text]
  • Implication of a Chromosome 15Q15.2 Locus in Regulating UBR1 and Predisposing Smokers to MGMT Methylation in Lung Shuguang Leng1, Guodong Wu1, Leonard B
    Published OnlineFirst July 16, 2015; DOI: 10.1158/0008-5472.CAN-15-0243 Cancer Prevention and Epidemiology Research Implication of a Chromosome 15q15.2 Locus in Regulating UBR1 and Predisposing Smokers to MGMT Methylation in Lung Shuguang Leng1, Guodong Wu1, Leonard B. Collins2, Cynthia L.Thomas1, Carmen S.Tellez1, Andrew R. Jauregui3, Maria A. Picchi1, Xiequn Zhang1, Daniel E. Juri1, Dhimant Desai4, Shantu G. Amin4, Richard E. Crowell5, Christine A. Stidley5,Yushi Liu1, James A. Swenberg2, Yong Lin1, Marc G. Wathelet3, Frank D. Gilliland6, and Steven A. Belinsky1 Abstract O6-Methylguanine-DNA methyltransferase (MGMT) is a risk prediction for MGMT methylation. We found that the DNA repair enzyme that protects cells from carcinogenic effects predisposition to MGMT methylation arising from the of alkylating agents; however, MGMT is silenced by promoter 15q15.2 locus involved regulation of the ubiquitin protein hypermethylation during carcinogenesis. A single-nucleotide ligase E3 component UBR1. UBR1 attenuation reduced turn- polymorphism (SNP) in an enhancer in the MGMT promoter over of MGMT protein and increased repair of O6-methylgua- was previously identified to be highly significantly associated nine in nitrosomethylurea-treated human bronchial epithelial with risk for MGMT methylation in lung cancer and sputum cells, while also reducing MGMT promoter activity and abol- from smokers. To further genetic investigations, a genome-wide ishing MGMT induction. Overall, our results substantiate association and replication study was conducted in two smoker reduced gene transcription as a major mechanism for predis- cohorts to identify novel loci for MGMT methylation in sputum position to MGMT methylation in the lungs of smokers, and that were independent of the MGMT enhancer polymorphism.
    [Show full text]
  • Genome Sequence of the Progenitor of the Wheat D Genome Aegilops Tauschii Ming-Cheng Luo1*, Yong Q
    OPEN LETTER doi:10.1038/nature24486 Genome sequence of the progenitor of the wheat D genome Aegilops tauschii Ming-Cheng Luo1*, Yong Q. Gu2*, Daniela Puiu3*, Hao Wang4,5,6*, Sven O. Twardziok7*, Karin R. Deal1, Naxin Huo1,2, Tingting Zhu1, Le Wang1, Yi Wang1,2, Patrick E. McGuire1, Shuyang Liu1, Hai Long1, Ramesh K. Ramasamy1, Juan C. Rodriguez1, Sonny L. Van1, Luxia Yuan1, Zhenzhong Wang1,8, Zhiqiang Xia1, Lichan Xiao1, Olin D. Anderson2, Shuhong Ouyang2,8, Yong Liang2,8, Aleksey V. Zimin3, Geo Pertea3, Peng Qi4,5, Jeffrey L. Bennetzen6, Xiongtao Dai9, Matthew W. Dawson9, Hans-Georg Müller9, Karl Kugler7, Lorena Rivarola-Duarte7, Manuel Spannagl7, Klaus F. X. Mayer7,10, Fu-Hao Lu11, Michael W. Bevan11, Philippe Leroy12, Pingchuan Li13, Frank M. You13, Qixin Sun8, Zhiyong Liu8, Eric Lyons14, Thomas Wicker15, Steven L. Salzberg3,16, Katrien M. Devos4,5 & Jan Dvořák1 Aegilops tauschii is the diploid progenitor of the D genome of We conclude therefore that the size of the Ae. tauschii genome is about hexaploid wheat1 (Triticum aestivum, genomes AABBDD) and 4.3 Gb. an important genetic resource for wheat2–4. The large size and To assess the accuracy of our assembly, sequences of 195 inde- highly repetitive nature of the Ae. tauschii genome has until now pendently sequenced and assembled AL8/78 BAC clones8, which precluded the development of a reference-quality genome sequence5. contained 25,540,177 bp in 2,405 unordered contigs, were aligned to Here we use an array of advanced technologies, including ordered- Aet v3.0. Five contigs failed to align and six extended partly into gaps, clone genome sequencing, whole-genome shotgun sequencing, accounting for 0.25% of the total length of the contigs.
    [Show full text]
  • Function in Vertebrates Receptor-Containing Adaptor
    Evidence for Evolving Toll-IL-1 Receptor-Containing Adaptor Molecule Function in Vertebrates This information is current as Con Sullivan, John H. Postlethwait, Christopher R. Lage, of September 30, 2021. Paul J. Millard and Carol H. Kim J Immunol 2007; 178:4517-4527; ; doi: 10.4049/jimmunol.178.7.4517 http://www.jimmunol.org/content/178/7/4517 Downloaded from References This article cites 60 articles, 30 of which you can access for free at: http://www.jimmunol.org/content/178/7/4517.full#ref-list-1 http://www.jimmunol.org/ Why The JI? Submit online. • Rapid Reviews! 30 days* from submission to initial decision • No Triage! Every submission reviewed by practicing scientists • Fast Publication! 4 weeks from acceptance to publication by guest on September 30, 2021 *average Subscription Information about subscribing to The Journal of Immunology is online at: http://jimmunol.org/subscription Permissions Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html Email Alerts Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts The Journal of Immunology is published twice each month by The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2007 by The American Association of Immunologists All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. The Journal of Immunology Evidence for Evolving Toll-IL-1 Receptor-Containing Adaptor Molecule Function in Vertebrates1 Con Sullivan,* John H. Postlethwait,† Christopher R. Lage,* Paul J. Millard,‡ and Carol H. Kim2* In mammals, Toll-IL-1R-containing adaptor molecule 1 (TICAM1)-dependent TLR pathways induce NF-␬B and IFN-␤ re- sponses.
    [Show full text]
  • Parallel Molecular Evolution in Pathways, Genes, and Sites in High-Elevation Hummingbirds Revealed by Comparative Transcriptomics
    GBE Parallel Molecular Evolution in Pathways, Genes, and Sites in High-Elevation Hummingbirds Revealed by Comparative Transcriptomics Marisa C.W. Lim1,*, Christopher C. Witt2, Catherine H. Graham1,3,andLilianaM.Davalos 1,4 1Department of Ecology and Evolution, Stony Brook University 2 Museum of Southwestern Biology and Department of Biology, University of New Mexico Downloaded from https://academic.oup.com/gbe/article-abstract/11/6/1552/5494706 by guest on 08 June 2019 3Swiss Federal Research Institute (WSL), Birmensdorf, Switzerland 4Consortium for Inter-Disciplinary Environmental Research, Stony Brook University *Corresponding author: E-mail: [email protected]. Accepted: May 12, 2019 Data deposition: The raw read data have been deposited in the NCBI Sequence Read Archive under BioProject: PRJNA543673, BioSample: SAMN11774663-SAMN11774674, SRA Study: SRP198856. All scripts used for analyses are available on Dryad: doi:10.5061/dryad.v961mb4. Abstract High-elevation organisms experience shared environmental challenges that include low oxygen availability, cold temperatures, and intense ultraviolet radiation. Consequently, repeated evolution of the same genetic mechanisms may occur across high-elevation taxa. To test this prediction, we investigated the extent to which the same biochemical pathways, genes, or sites were subject to parallel molecular evolution for 12 Andean hummingbird species (family: Trochilidae) representing several independent transitions to high elevation across the phylogeny. Across high-elevation species, we discovered parallel evolution for several pathways and genes with evidence of positive selection. In particular, positively selected genes were frequently part of cellular respiration, metabolism, or cell death pathways. To further examine the role of elevation in our analyses, we compared results for low- and high-elevation species and tested different thresholds for defining elevation categories.
    [Show full text]
  • A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
    Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated.
    [Show full text]
  • Downloaded the Rnaseq and Mirnaseq Profiling Taining DAPI (Invitrogen) Following the Manufacturer’S Datasets on 12 OTSCC and Paired Normal Tissue Samples Protocol
    He et al. BMC Cancer (2016) 16:685 DOI 10.1186/s12885-016-2716-0 RESEARCH ARTICLE Open Access MicroRNA-21 regulates prostaglandin E2 signaling pathway by targeting 15- hydroxyprostaglandin dehydrogenase in tongue squamous cell carcinoma Qianting He1,2†, Zujian Chen1†, Qian Dong2, Leitao Zhang1,3, Dan Chen1,2, Aditi Patel1, Ajay Koya1, Xianghong Luan4, Robert J. Cabay5, Yang Dai6,7, Anxun Wang2* and Xiaofeng Zhou1,7,8* Abstract Background: Oral tongue squamous cell carcinoma (OTSCC) is one of the most aggressive forms of head and neck/oral cancer (HNOC), and is a complex disease with extensive genetic and epigenetic defects, including microRNA deregulation. Identifying the deregulation of microRNA-mRNA regulatory modules (MRMs) is crucial for understanding the role of microRNA in OTSCC. Methods: A comprehensive bioinformatics analysis was performed to identify MRMs in HNOC by examining the correlation among differentially expressed microRNA and mRNA profiling datasets and integrating with 12 different sequence-based microRNA target prediction algorithms. Confirmation experiments were performed to further assess the correlation among MRMs using OTSCC patient samples and HNOC cell lines. Functional analyses were performed to validate one of the identified MRMs: miR-21-15-Hydroxyprostaglandin Dehydrogenase (HPGD) regulatory module. Results: Our bioinformatics analysis revealed 53 MRMs that are deregulated in HNOC. Four high confidence MRMs were further defined by confirmation experiments using OTSCC patient samples and HNOC cell lines, including miR-21-HPGD regulatory module. HPGD is a known anti-tumorigenic effecter, and it regulates the tumorigenic actions of Prostaglandin E2 (PGE2) by converts PGE2 to its biologically inactive metabolite. Ectopic transfection of miR-21 reduced the expression of HPGD in OTSCC cell lines, and the direct targeting of the miR-21 to the HPGD mRNA was confirmed using a luciferase reporter gene assay.
    [Show full text]
  • Microrna Pharmacoepigenetics: Posttranscriptional Regulation Mechanisms Behind Variable Drug Disposition and Strategy to Develop More Effective Therapy
    1521-009X/44/3/308–319$25.00 http://dx.doi.org/10.1124/dmd.115.067470 DRUG METABOLISM AND DISPOSITION Drug Metab Dispos 44:308–319, March 2016 Copyright ª 2016 by The American Society for Pharmacology and Experimental Therapeutics Minireview MicroRNA Pharmacoepigenetics: Posttranscriptional Regulation Mechanisms behind Variable Drug Disposition and Strategy to Develop More Effective Therapy Ai-Ming Yu, Ye Tian, Mei-Juan Tu, Pui Yan Ho, and Joseph L. Jilek Department of Biochemistry & Molecular Medicine, University of California Davis School of Medicine, Sacramento, California Received September 30, 2015; accepted November 12, 2015 Downloaded from ABSTRACT Knowledge of drug absorption, distribution, metabolism, and excre- we review the advances in miRNA pharmacoepigenetics including tion (ADME) or pharmacokinetics properties is essential for drug the mechanistic actions of miRNAs in the modulation of Phase I and development and safe use of medicine. Varied or altered ADME may II drug-metabolizing enzymes, efflux and uptake transporters, and lead to a loss of efficacy or adverse drug effects. Understanding the xenobiotic receptors or transcription factors after briefly introducing causes of variations in drug disposition and response has proven the characteristics of miRNA-mediated posttranscriptional gene dmd.aspetjournals.org critical for the practice of personalized or precision medicine. The regulation. Consequently, miRNAs may have significant influence rise of noncoding microRNA (miRNA) pharmacoepigenetics and on drug disposition and response. Therefore, research on miRNA pharmacoepigenomics has come with accumulating evidence sup- pharmacoepigenetics shall not only improve mechanistic under- porting the role of miRNAs in the modulation of ADME gene standing of variations in pharmacotherapy but also provide novel expression and then drug disposition and response.
    [Show full text]
  • Long Non‑Coding Rnas in Small Cell Lung Cancer: a Potential Opening to Combat the Disease (Review)
    ONCOLOGY REPORTS 40: 1831-1842, 2018 Long non‑coding RNAs in small cell lung cancer: A potential opening to combat the disease (Review) TIAN-TIAN LI1, RONG-QUAN HE1, JIE MA1, ZU-YUN LI2, XIAO-HUA HU1 and GANG CHEN2 Departments of 1Medical Oncology and 2Pathology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region 530021, P.R. China Received February 16, 2018; Accepted August 1, 2018 DOI: 10.3892/or.2018.6635 Abstract. Lung cancer is the top cause of cancer-associated 3. Expression of lncRNAs in SCLC mortality in men and women worldwide. Small cell lung cancer 4. Conclusions and future directions (SCLC) is a subtype that constitutes ~15% of all lung cancer cases. Long non-coding RNAs (lncRNAs), possessing no or limited protein-coding ability, have gained extensive attention 1. Introduction as a potentially promising avenue by which to investigate the biological regulation of human cancer. lncRNAs can modulate Lung cancer, recognized as the leading cause of cancer- gene expression at the transcriptional, post-transcriptional and associated mortality worldwide, is classified into small epigenetic levels. The current review highlights the developing cell lung cancer (SCLC) and non-SCLC (NSCLC). SCLC clinical implications and functional roles of lncRNAs in constitutes ~15% of all confirmed cases of lung cancer SCLC, and provides directions for their future utilization in worldwide (1-3). Distinct from NSCLC, SCLC is unique in the diagnosis and treatment of SCLC. its inclination for quick metastasis and sensitivity to initial systemic cytotoxic chemotherapy. Systemic chemotherapy is the solid foundation of treatment for the limited and extensive Contents stages of this disease.
    [Show full text]
  • (12) Patent Application Publication (10) Pub. No.: US 2010/0159477 A1 Hornbeck Et Al
    US 20100159477A1 (19) United States (12) Patent Application Publication (10) Pub. No.: US 2010/0159477 A1 Hornbeck et al. (43) Pub. Date: Jun. 24, 2010 (54) REAGENTS FOR THE DETECTION OF Publication Classification PROTEIN PHOSPHORYLATION IN (51) Int. Cl. SIGNALNG PATHWAYS GOIN 33/573 (2006.01) GOIN 33/53 (2006.01) (76) Inventors: Peter Hornbeck, Magnolia, MA C07K 6/00 (2006.01) C07K 7/06 (2006.01) (US); Valerie Goss, Seabrook, NH C07K 7/08 (2006.01) (US); Kimberly Lee, Seattle, WA C07K I4/00 (2006.01) (US); Ting-Lei Gu, Woburn, MA CI2N 5/071 (2010.01) (US); Albrecht Moritz, Salem, MA CI2N 5/16 (2006.01) (US) CI2N 5/18 (2006.01) (52) U.S. Cl. ........ 435/7.4; 435/7.1:530/387.1; 530/328; Correspondence Address: 530/327: 530/326; 530/325; 530/324; 435/326 Nancy Chiu Wilker, Ph.D. (57) ABSTRACT Chief Intellectual Property Counsel CELL SIGNALING TECHNOLOGY, INC., 3 The invention discloses novel phosphorylation sites identi Trask Lane fied in signal transduction proteins and pathways, and pro vides phosphorylation-site specific antibodies and heavy-iso Danvers, MA 01923 (US) tope labeled peptides (AQUA peptides) for the selective detection and quantification of these phosphorylated sites/ (21) Appl. No.: 12/309,311 proteins, as well as methods of using the reagents for Such purpose. Among the phosphorylation sites identified are sites occurring in the following protein types: adaptor/scaffold (22) PCT Filed: Jul. 13, 2007 proteins, adhesion/extracellular matrix protein, apoptosis proteins, calcium binding proteins, cell cycle regulation pro (86). PCT No.: PCT/US07f73537 teins, chaperone proteins, chromatin, DNA binding/repair/ replication proteins, cytoskeletal proteins, endoplasmic S371 (c)(1), reticulum or golgi proteins, enzyme proteins, G/regulator (2), (4) Date: Feb.
    [Show full text]
  • Tyson Goldberg Et Al-2015-Development-1267-78
    © 2015. Published by The Company of Biologists Ltd | Development (2015) 142, 1267-1278 doi:10.1242/dev.111526 RESEARCH ARTICLE STEM CELLS AND REGENERATION Duration of culture and sonic hedgehog signaling differentially specify PV versus SST cortical interneuron fates from embryonic stem cells Jennifer A. Tyson1,2, Ethan M. Goldberg3,4, Asif M. Maroof5, Qing Xu6, Timothy J. Petros7 and Stewart A. Anderson1,* ABSTRACT dysfunction is associated with a variety of neurological diseases, Medial ganglionic eminence (MGE)-derived GABAergic cortical including seizure disorders, schizophrenia and autism (Belforte et al., interneurons (cINs) consist of multiple subtypes that are involved in 2010; Chao et al., 2010; Inan et al., 2013). Interneurons are classified many cortical functions. They also have a remarkable capacity to into functionally distinct subgroups based on neurochemical markers, migrate, survive and integrate into cortical circuitry after transplantation connectivity profiles and electrophysiological properties (DeFelipe into postnatal cortex. These features have engendered considerable et al., 2013), with specific subtypes being implicated in different interest in generating distinct subgroups of interneurons from pluripotent disease etiologies (Binaschi et al., 2003; Levitt et al., 2004; Inan et al., stem cells (PSCs) for the study of interneuron fate and function, and for 2013; Jiang et al., 2013; Smith-Hicks, 2013). Genetic fate mapping the development of cell-based therapies. Although advances have been and transplantation studies
    [Show full text]