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Genome-Wide Characterization of PRE-1 Reveals a Hidden Evolutionary Relationship Between Suidae and Primates
bioRxiv preprint doi: https://doi.org/10.1101/025791; this version posted August 31, 2015. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.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 4.0 International license. Genome-wide characterization of PRE-1 reveals a hidden evolutionary relationship between suidae and primates Hao Yu1,, Qingyan Wu1, Jing Zhag1, Ying zhang1, Chao Lu1, Yunyun Cheng1, Zhihui Zhao1, Andreas Windemuth3, Di Liu2,, Linlin Hao1 1 College of Animal Science, Jilin University, Changchun 130062, China 2 Heilongjiang Academy of Agricultural Sciences, Harbin 150086, China 3 Abcam, Firefly BioWorks Inc, United States Corresponding author: Linlin Hao ([email protected]); Di liu ([email protected]); Andreas Windemuth ([email protected]) Abstract We identified and characterized a free PRE-1 element inserted into the promoter region of the porcine IGFBP7 gene whose integration mechanisms into the genome, including copy number, distribution preferences, capacity to exonize and phyloclustering pattern are similar to that of the primate Alu element. 98% of these PRE-1 elements also contain two conserved internal AluI restriction enzyme recognition sites, and the RNA structure of PRE1 can be folded into a two arms model like the Alu RNA structure. It is more surprising that the length of the PRE-1 fragments is nearly the same in 20 chromosomes and positively correlated to its fracture site frequency. All of these fracture sites are close to the mutation hot spots of PRE-1 families, and most of these hot spots are located in the non-complementary fragile regions of the PRE-1 RNA structure. -
The Title of the Article
Mechanism-Anchored Profiling Derived from Epigenetic Networks Predicts Outcome in Acute Lymphoblastic Leukemia Xinan Yang, PhD1, Yong Huang, MD1, James L Chen, MD1, Jianming Xie, MSc2, Xiao Sun, PhD2, Yves A Lussier, MD1,3,4§ 1Center for Biomedical Informatics and Section of Genetic Medicine, Department of Medicine, The University of Chicago, Chicago, IL 60637 USA 2State Key Laboratory of Bioelectronics, Southeast University, 210096 Nanjing, P.R.China 3The University of Chicago Cancer Research Center, and The Ludwig Center for Metastasis Research, The University of Chicago, Chicago, IL 60637 USA 4The Institute for Genomics and Systems Biology, and the Computational Institute, The University of Chicago, Chicago, IL 60637 USA §Corresponding author Email addresses: XY: [email protected] YH: [email protected] JC: [email protected] JX: [email protected] XS: [email protected] YL: [email protected] - 1 - Abstract Background Current outcome predictors based on “molecular profiling” rely on gene lists selected without consideration for their molecular mechanisms. This study was designed to demonstrate that we could learn about genes related to a specific mechanism and further use this knowledge to predict outcome in patients – a paradigm shift towards accurate “mechanism-anchored profiling”. We propose a novel algorithm, PGnet, which predicts a tripartite mechanism-anchored network associated to epigenetic regulation consisting of phenotypes, genes and mechanisms. Genes termed as GEMs in this network meet all of the following criteria: (i) they are co-expressed with genes known to be involved in the biological mechanism of interest, (ii) they are also differentially expressed between distinct phenotypes relevant to the study, and (iii) as a biomodule, genes correlate with both the mechanism and the phenotype. -
Binnenwerk Cindy Postma.Indd
CHAPTER 6 Multiple putative oncogenes at the chromosome 20q amplicon contribute to colorectal adenoma to carcinoma progression Gut 2009, 58: 79-89 Beatriz Carvalho Cindy Postma Sandra Mongera Erik Hopmans Sharon Diskin Mark A. van de Wiel Wim van Criekinge Olivier Thas Anja Matthäi Miguel A. Cuesta Jochim S. Terhaar sive Droste Mike Craanen Evelin Schröck Bauke Ylstra Gerrit A. Meijer 104 | Chapter 6 Abstract Objective: This study aimed to identify the oncogenes at 20q involved in colorectal adenoma to carcinoma progression by measuring the effect of 20q gain on mRNA expression of genes in this amplicon. Methods: Segmentation of DNA copy number changes on 20q was performed by array CGH in 34 non-progressed colorectal adenomas, 41 progressed adenomas (i.e. adenomas that present a focus of cancer) and 33 adenocarcinomas. Moreover, a robust analysis of altered expression of genes in these segments was performed by microarray analysis in 37 adenomas and 31 adenocarcinomas. Protein expression was evaluated by immunohistochemistry on tissue microarrays. Results: The genes C20orf24, AURKA, RNPC1, TH1L, ADRM1, C20orf20 and TCFL5, mapping at 20q were signifi cantly overexpressed in carcinomas compared to adenomas as consequence of copy number gain of 20q. Conclusion: This approach revealed C20orf24, AURKA, RNPC1, TH1L, ADRM1, C20orf20 and TCFL5 genes to be important in chromosomal instability-related adenoma to carcinoma progression. These genes therefore may serve as highly specifi c biomarkers for colorectal cancer with potential clinical applications. Putative oncogenes at chromosome 20q in colorectal carcinogenesis | 105 Introduction The majority of cancers are epithelial in origin and arise through a stepwise progression from normal cells, through dysplasia, into malignant cells that invade surrounding tissues and have metastatic potential. -
An Order Estimation Based Approach to Identify Response Genes
AN ORDER ESTIMATION BASED APPROACH TO IDENTIFY RESPONSE GENES FOR MICRO ARRAY TIME COURSE DATA A Thesis Presented to The Faculty of Graduate Studies of The University of Guelph by ZHIHENG LU In partial fulfilment of requirements for the degree of Doctor of Philosophy September, 2008 © Zhiheng Lu, 2008 Library and Bibliotheque et 1*1 Archives Canada Archives Canada Published Heritage Direction du Branch Patrimoine de I'edition 395 Wellington Street 395, rue Wellington Ottawa ON K1A0N4 Ottawa ON K1A0N4 Canada Canada Your file Votre reference ISBN: 978-0-494-47605-5 Our file Notre reference ISBN: 978-0-494-47605-5 NOTICE: AVIS: The author has granted a non L'auteur a accorde une licence non exclusive exclusive license allowing Library permettant a la Bibliotheque et Archives and Archives Canada to reproduce, Canada de reproduire, publier, archiver, publish, archive, preserve, conserve, sauvegarder, conserver, transmettre au public communicate to the public by par telecommunication ou par Plntemet, prefer, telecommunication or on the Internet, distribuer et vendre des theses partout dans loan, distribute and sell theses le monde, a des fins commerciales ou autres, worldwide, for commercial or non sur support microforme, papier, electronique commercial purposes, in microform, et/ou autres formats. paper, electronic and/or any other formats. The author retains copyright L'auteur conserve la propriete du droit d'auteur ownership and moral rights in et des droits moraux qui protege cette these. this thesis. Neither the thesis Ni la these ni des extraits substantiels de nor substantial extracts from it celle-ci ne doivent etre imprimes ou autrement may be printed or otherwise reproduits sans son autorisation. -
Identification and Diagnostic Performance of a Small RNA Within the PCA3 and BMCC1 Gene Locus That Potentially Targets Mrna
Published OnlineFirst November 12, 2014; DOI: 10.1158/1055-9965.EPI-14-0377 Research Article Cancer Epidemiology, Biomarkers Identification and Diagnostic Performance of a & Prevention Small RNA within the PCA3 and BMCC1 Gene Locus That Potentially Targets mRNA Ross M. Drayton1, Ishtiaq Rehman1, Raymond Clarke2, Zhongming Zhao3,4, Karl Pang1, Saiful Miah1, Robert Stoehr5, Arndt Hartmann5, Sheila Blizard1, Martin Lavin2, Helen E. Bryant1, Elena S. Martens-Uzunova6, Guido Jenster6, Freddie C. Hamdy7, Robert A. Gardiner2, and James W.F. Catto1 Abstract Background: PCA3 is a long noncoding RNA (lncRNA) with malignant prostatic tissues, exfoliated urinary cells from men unknown function, upregulated in prostate cancer. LncRNAs may with prostate cancer (13–273 fold change; t test P < 0.003), and be processed into smaller active species. We hypothesized this for closely correlated to PCA3 expression (r ¼ 0.84–0.93; P < 0.001). PCA3. Urinary PCA3-shRNA2 (C-index, 0.75–0.81) and PCA3 (C-index, Methods: We computed feasible RNA hairpins within the 0.78) could predict the presence of cancer in most men. PCA3- BMCC1 gene (encompassing PCA3) and searched a prostate shRNA2 knockup altered the expression of predicted target transcriptome for these. We measured expression using qRT- mRNAs, including COPS2, SOX11, WDR48, TEAD1, and Noggin. PCR in three cohorts of prostate cancer tissues (n ¼ 60), PCA3-shRNA2 expression was negatively correlated with COPS2 exfoliated urinary cells (n ¼ 484 with cancer and n ¼ 166 in patient samples (r ¼0.32; P < 0.001). controls), and in cell lines (n ¼ 22). We used in silico predictions Conclusion: We identified a short RNA within PCA3, whose and RNA knockup to identify potential mRNA targets of short expression is correlated to PCA3, which may target mRNAs transcribed RNAs. -
Supplementary Material for “Characterization of the Opossum Immune Genome Provides Insights Into the Evolution of the Mammalian Immune System”
Supplementary material for “Characterization of the opossum immune genome provides insights into the evolution of the mammalian immune system” Katherine Belov1*, Claire E. Sanderson1, Janine E. Deakin2, Emily S.W. Wong1, Daniel Assange3, Kaighin A. McColl3, Alex Gout3,4, Bernard de Bono5, Terence P. Speed3, John Trowsdale5, Anthony T. Papenfuss3 1. Faculty of Veterinary Science, University of Sydney, Sydney, Australia 2. ARC Centre for Kangaroo Genomics, Research School of Biological Sciences, The Australian National University, Canberra, Australia 3. Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Australia 4. Department of Medical Biology, The University of Melbourne, Parkville, Australia 5. Immunology Division, University of Cambridge, Cambridge, UK *Corresponding author: K. Belov, Faculty of Veterinary Science, University of Sydney, NSW 2006, Australia ph 61 2 9351 3454, fx 61 2 9351 3957, email [email protected] MHC paralogous regions Only 36 of the 114 genes in the opossum MHC have paralogs in one of the three paralogous regions (Supplementary Table 1). Genes represented in at least three of the four paralogous regions (13 genes) were used to compare gene order, revealing rearrangements between the four regions in opossum. Table 1: MHC genes with paralogs on opossum chromosomes 1, 2 and 3, corresponding to MHC paralogous regions on human chromosomes 9, 1 and 19 respectively. MHC Chromosome 1 Chromosome 2 Chromosome 3 (Human Chr 9) (Human Chr 1) (Human Chr 19) AGPAT1 AGPAT2 AIF1 C9orf58 ATP6V1G2 ATP6V1G1 ATP6V1G3 B3GALT4 B3GALT2 BAT1 DDX39 BAT2 KIAA0515 BAT2D1 BRD2 BRD3 BRDT BRD4 C4 C5 C3 SLC44A4 SLC44A5 SLC44A2 CLIC1 CLIC3 CLIC4 COL11A2 COL5A1 COL11A1 COL5A3 CREBL1 ATF6 DDAH2 DDAH1 DDR1 DDR2 EGFL8 EGFL7 EHMT2 EHMT1 GPX5 GPX4 MHC Class I CD1 HSPA1A HSPA5 MDC1 PRG4 NOTCH4 NOTCH1 NOTCH2 NOTCH3 PBX2 PBX3 PBX1 PBX4 PHF1 MTF2 PRSS16 DPP7 PSMB9 PSMB7 RGL2 RALGDS RGL1 RGL3 RING1 RNF2 RXRB RXRA RXRG SYNGAP1 RASAL2 TAP ABCA2 TNF/LTA/LTB TNFSF8/TNFSF15 TNFSF4 CD70/TNFSF9/ TNFSF14/ TNXB TNC TNR Table 2. -
Association of Gene Ontology Categories with Decay Rate for Hepg2 Experiments These Tables Show Details for All Gene Ontology Categories
Supplementary Table 1: Association of Gene Ontology Categories with Decay Rate for HepG2 Experiments These tables show details for all Gene Ontology categories. Inferences for manual classification scheme shown at the bottom. Those categories used in Figure 1A are highlighted in bold. Standard Deviations are shown in parentheses. P-values less than 1E-20 are indicated with a "0". Rate r (hour^-1) Half-life < 2hr. Decay % GO Number Category Name Probe Sets Group Non-Group Distribution p-value In-Group Non-Group Representation p-value GO:0006350 transcription 1523 0.221 (0.009) 0.127 (0.002) FASTER 0 13.1 (0.4) 4.5 (0.1) OVER 0 GO:0006351 transcription, DNA-dependent 1498 0.220 (0.009) 0.127 (0.002) FASTER 0 13.0 (0.4) 4.5 (0.1) OVER 0 GO:0006355 regulation of transcription, DNA-dependent 1163 0.230 (0.011) 0.128 (0.002) FASTER 5.00E-21 14.2 (0.5) 4.6 (0.1) OVER 0 GO:0006366 transcription from Pol II promoter 845 0.225 (0.012) 0.130 (0.002) FASTER 1.88E-14 13.0 (0.5) 4.8 (0.1) OVER 0 GO:0006139 nucleobase, nucleoside, nucleotide and nucleic acid metabolism3004 0.173 (0.006) 0.127 (0.002) FASTER 1.28E-12 8.4 (0.2) 4.5 (0.1) OVER 0 GO:0006357 regulation of transcription from Pol II promoter 487 0.231 (0.016) 0.132 (0.002) FASTER 6.05E-10 13.5 (0.6) 4.9 (0.1) OVER 0 GO:0008283 cell proliferation 625 0.189 (0.014) 0.132 (0.002) FASTER 1.95E-05 10.1 (0.6) 5.0 (0.1) OVER 1.50E-20 GO:0006513 monoubiquitination 36 0.305 (0.049) 0.134 (0.002) FASTER 2.69E-04 25.4 (4.4) 5.1 (0.1) OVER 2.04E-06 GO:0007050 cell cycle arrest 57 0.311 (0.054) 0.133 (0.002) -
Examination of the Role of the Hu Proteins, Hur and Hud, in Prostate Cancer Cells
Examination of the Role of the Hu Proteins, HuR and HuD, in Prostate Cancer Cells. Christin Florence Down This thesis is presented for the degree of Doctor of Philosophy to the School of Medicine and Pharmacology, University of Western Australia. January 2007 i Declaration. This thesis contains published work and/or work prepared for publication, some of which has been co-authored . The bibliographic details of the works and where they appear in the thesis are set out below. (The candidate must attach to this declaration a statement detailing the percentage contribution of each author to the work. This must been signed by all authors. Where this is not possible, the statement detailing the percentage contribution of authors should be signed by the candidate’s Coordinating Supervisor). This thesis contains experimental data from the following co-authored work: Hu Proteins are Expressed and Regulate Androgen Receptor Expression and Cell Proliferation in Prostate Cancer. Christin F Down , Dianne J Beveridge, Michael R Epis, Ricky Lareu, Lisa M Stuart, Britt Granath, Dominic C Voon, Henry Furneaux, Cecily Metcalf, Jacqueline Bentel and Peter J Leedman. Submitted to Cancer Research . The relative contribution of authors is as follows: Christin Down (the Candidate): 55% Dianne J Beveridge 6 % Michael R Epis 6 % Ricky Lareu 3 % Lisa M Stuart 3 % Britt Granath 3 % Dominic Voon 3 % Henry Furneaux 3 % Cecily Metcalf 3 % Jacqueline Bentel 5 % Peter J Leedman 10 % Data from the manuscript described above are presented in this thesis in the following figures, and were performed by the investigator indicated: Figure 3.1A : Dr Cecily Metcalfe, Department of Pathology, Royal Perth Hospital. -
Supplementary Table S4. FGA Co-Expressed Gene List in LUAD
Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase -
(12) United States Patent (10) Patent No.: US 8.440,393 B2 Birrer Et Al
USOO8440393B2 (12) United States Patent (10) Patent No.: US 8.440,393 B2 Birrer et al. (45) Date of Patent: May 14, 2013 (54) PRO-ANGIOGENIC GENES IN OVARIAN OTHER PUBLICATIONS TUMORENDOTHELIAL CELL, SOLATES Boyd (The Basic Science of Oncology, 1992, McGraw-Hill, Inc., p. (75) Inventors: Michael J. Birrer, Mt. Airy, MD (US); 379). Tomas A. Bonome, Washington, DC Tockman et al. (Cancer Res., 1992, 52:2711s-2718s).* (US); Anil Sood, Pearland, TX (US); Pritzker (Clinical Chemistry, 2002, 48: 1147-1150).* Chunhua Lu, Missouri City, TX (US) Benedict et al. (J. Exp. Medicine, 2001, 193(1) 89-99).* Jiang et al. (J. Biol. Chem., 2003, 278(7) 4763-4769).* (73) Assignees: The United States of America as Matsushita et al. (FEBS Letters, 1999, vol. 443, pp. 348-352).* Represented by the Secretary of the Singh et al. (Glycobiology, 2001, vol. 11, pp. 587-592).* Department of Health and Human Abbosh et al. (Cancer Res. Jun. 1, 2006 66:5582-55.91 and Supple Services, Washington, DC (US); The mental Figs. S1-S7).* University of MD Anderson Cancer Zhai et al. (Chinese General Practice Aug. 2008, 11(8A): 1366 Center, Houston, TX (US) 1367).* Lu et al. (Cancer Res. Feb. 15, 2007, 64(4): 1757-1768).* (*) Notice: Subject to any disclaimer, the term of this Bagnato et al., “Activation of Mitogenic Signaling by Endothelin 1 in patent is extended or adjusted under 35 Ovarian Carcinoma Cells', Cancer Research, vol. 57, pp. 1306-1311, U.S.C. 154(b) by 194 days. 1997. Bouras et al., “Stanniocalcin 2 is an Estrogen-responsive Gene (21) Appl. -
Supplemental Figure S1 Differentially Methylated Regions (Dmrs
Supplemental Figure S1 '$$#0#,2'**7+#2&7*2#"0#%'-,11 #25##,"'1#1#122#1 '!2-0'*"#.'!2'-,-$122,1'2'-,$0-+2- !"Q !"2-$%," $ 31',% 25-$-*" !&,%# ," ' 0RTRW 1 !32V-$$ !0'2#0'T - #.0#1#,22'-, -$ "'$$#0#,2'**7+#2&7*2#"%#,#11',.0#,2#1,"2&#'0 #&4'-022,1'2'-, #25##,"'$$#0#,2"'1#1#122#1T-*!)00-51',"'!2#&7.#0+#2&7*2#"%#,#1Q%0700-51 &7.-+#2&7*2#"%#,#1Q31',%25-$-*"!&,%#,"'0RTRW1!32V-$$!0'2#0'T-%#,#1 +#22&# -4#!0'2#0'22,1'2'-,$0-+$%2-$Q5#2�#$-0#*1-',!*3"#" %#,#15'2&V4*3#0RTRWT$$#!2#"%#,10#&'%&*'%&2#" 712#0'1)1#T Supplemental Figure S2 Validation of results from the HELP assay using Epityper MassarrayT #13*21 $0-+ 2&# 1$ 117 5#0# !-00#*2#" 5'2& /3,2'22'4# +#2&7*2'-, ,*78#" 7 '13*$'2#11007$-04V-,"6U-%#,#.0-+-2#00#%'-,1T11007 51.#0$-0+#"31',%**4'* *#1+.*#1T S Supplemental Fig. S1 A unique hypermethylated genes (methylation sites) 454 (481) 5693 (6747) 120 (122) NLMGUS NEWMM REL 2963 (3207) 1338 (1560) 5 (5) unique hypomethylated genes (methylation sites) B NEWMM 0 (0) MGUS 454 (481) 0 (0) NEWMM REL NL 3* (2) 2472 (3066) NEWMM 2963 REL (3207) 2* (2) MGUS 0 (0) REL 2 (2) NEWMM 0 (0) REL Supplemental Fig. S2 A B ARID4B DNMT3A Methylation by MassArray Methylation by MassArray 0 0.2 0.4 0.6 0.8 1 1.2 0.5 0.6 0.7 0.8 0.9 1 2 0 NL PC MGUS 1.5 -0.5 NEW MM 1 REL MM -1 0.5 -1.5 0 -2 -0.5 -1 -2.5 -1.5 -3 Methylation by HELP Assay Methylation by HELP Methylation by HELP Assay Methylation by HELP -2 -3.5 -2.5 -4 Supplemental tables "3..*#+#,2*6 *#"SS 9*','!*!&0!2#0'12'!1-$.2'#,21+.*#1 DZ_STAGE Age Gender Ethnicity MM isotype PCLI Cytogenetics -
Supplemental Table 3 Site ID Intron Poly(A) Site Type NM/KG Inum
Supplemental Table 3 Site ID Intron Poly(A) site Type NM/KG Inum Region Gene ID Gene Symbol Gene Annotation Hs.120277.1.10 chr3:170997234:170996860 170996950 b NM_153353 7 CDS 151827 LRRC34 leucine rich repeat containing 34 Hs.134470.1.27 chr17:53059664:53084458 53065543 b NM_138962 10 CDS 124540 MSI2 musashi homolog 2 (Drosophila) Hs.162889.1.18 chr14:80367239:80329208 80366262 b NM_152446 12 CDS 145508 C14orf145 chromosome 14 open reading frame 145 Hs.187898.1.27 chr22:28403623:28415294 28404458 b NM_181832 16 3UTR 4771 NF2 neurofibromin 2 (bilateral acoustic neuroma) Hs.228320.1.6 chr10:115527009:115530350 115527470 b BC036365 5 CDS 79949 C10orf81 chromosome 10 open reading frame 81 Hs.266308.1.2 chr11:117279579:117278191 117278967 b NM_032046 12 CDS 84000 TMPRSS13 transmembrane protease, serine 13 Hs.266308.1.4 chr11:117284536:117281662 117283722 b NM_032046 9 CDS 84000 TMPRSS13 transmembrane protease, serine 13 Hs.2689.1.4 chr10:53492398:53563605 53492622 b NM_006258 7 CDS 5592 PRKG1 protein kinase, cGMP-dependent, type I Hs.280781.1.6 chr18:64715646:64829150 64715837 b NM_024781 4 CDS 79839 C18orf14 chromosome 18 open reading frame 14 Hs.305985.2.25 chr12:8983686:8984438 8983942 b BX640639 17 3UTR NA NA NA Hs.312098.1.36 chr1:151843991:151844258 151844232 b NM_003815 15 CDS 8751 ADAM15 a disintegrin and metalloproteinase domain 15 (metargidin) Hs.314338.1.11 chr21:39490293:39481214 39487623 b NM_018963 41 CDS 54014 BRWD1 bromodomain and WD repeat domain containing 1 Hs.33368.1.3 chr15:92685158:92689361 92688314 b NM_018349 6 CDS 55784 MCTP2 multiple C2-domains with two transmembrane regions 2 Hs.346736.1.21 chr2:99270738:99281614 99272414 b AK126402 10 3UTR 51263 MRPL30 mitochondrial ribosomal protein L30 Hs.445061.1.19 chr16:69322898:69290216 69322712 b NM_018052 14 CDS 55697 VAC14 Vac14 homolog (S.