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Primate Specific Retrotransposons, Svas, in the Evolution of Networks That Alter Brain Function
Title: Primate specific retrotransposons, SVAs, in the evolution of networks that alter brain function. Olga Vasieva1*, Sultan Cetiner1, Abigail Savage2, Gerald G. Schumann3, Vivien J Bubb2, John P Quinn2*, 1 Institute of Integrative Biology, University of Liverpool, Liverpool, L69 7ZB, U.K 2 Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, The University of Liverpool, Liverpool L69 3BX, UK 3 Division of Medical Biotechnology, Paul-Ehrlich-Institut, Langen, D-63225 Germany *. Corresponding author Olga Vasieva: Institute of Integrative Biology, Department of Comparative genomics, University of Liverpool, Liverpool, L69 7ZB, [email protected] ; Tel: (+44) 151 795 4456; FAX:(+44) 151 795 4406 John Quinn: Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, The University of Liverpool, Liverpool L69 3BX, UK, [email protected]; Tel: (+44) 151 794 5498. Key words: SVA, trans-mobilisation, behaviour, brain, evolution, psychiatric disorders 1 Abstract The hominid-specific non-LTR retrotransposon termed SINE–VNTR–Alu (SVA) is the youngest of the transposable elements in the human genome. The propagation of the most ancient SVA type A took place about 13.5 Myrs ago, and the youngest SVA types appeared in the human genome after the chimpanzee divergence. Functional enrichment analysis of genes associated with SVA insertions demonstrated their strong link to multiple ontological categories attributed to brain function and the disorders. SVA types that expanded their presence in the human genome at different stages of hominoid life history were also associated with progressively evolving behavioural features that indicated a potential impact of SVA propagation on a cognitive ability of a modern human. -
A Multi-Omics Interpretable Machine Learning Model Reveals Modes of Action of Small Molecules Natasha L
www.nature.com/scientificreports OPEN A Multi-Omics Interpretable Machine Learning Model Reveals Modes of Action of Small Molecules Natasha L. Patel-Murray1, Miriam Adam2, Nhan Huynh2, Brook T. Wassie2, Pamela Milani2 & Ernest Fraenkel 2,3* High-throughput screening and gene signature analyses frequently identify lead therapeutic compounds with unknown modes of action (MoAs), and the resulting uncertainties can lead to the failure of clinical trials. We developed an approach for uncovering MoAs through an interpretable machine learning model of transcriptomics, epigenomics, metabolomics, and proteomics. Examining compounds with benefcial efects in models of Huntington’s Disease, we found common MoAs for compounds with unrelated structures, connectivity scores, and binding targets. The approach also predicted highly divergent MoAs for two FDA-approved antihistamines. We experimentally validated these efects, demonstrating that one antihistamine activates autophagy, while the other targets bioenergetics. The use of multiple omics was essential, as some MoAs were virtually undetectable in specifc assays. Our approach does not require reference compounds or large databases of experimental data in related systems and thus can be applied to the study of agents with uncharacterized MoAs and to rare or understudied diseases. Unknown modes of action of drug candidates can lead to unpredicted consequences on efectiveness and safety. Computational methods, such as the analysis of gene signatures, and high-throughput experimental methods have accelerated the discovery of lead compounds that afect a specifc target or phenotype1–3. However, these advances have not dramatically changed the rate of drug approvals. Between 2000 and 2015, 86% of drug can- didates failed to earn FDA approval, with toxicity or a lack of efcacy being common reasons for their clinical trial termination4,5. -
Supplemental Information
Supplemental information Dissection of the genomic structure of the miR-183/96/182 gene. Previously, we showed that the miR-183/96/182 cluster is an intergenic miRNA cluster, located in a ~60-kb interval between the genes encoding nuclear respiratory factor-1 (Nrf1) and ubiquitin-conjugating enzyme E2H (Ube2h) on mouse chr6qA3.3 (1). To start to uncover the genomic structure of the miR- 183/96/182 gene, we first studied genomic features around miR-183/96/182 in the UCSC genome browser (http://genome.UCSC.edu/), and identified two CpG islands 3.4-6.5 kb 5’ of pre-miR-183, the most 5’ miRNA of the cluster (Fig. 1A; Fig. S1 and Seq. S1). A cDNA clone, AK044220, located at 3.2-4.6 kb 5’ to pre-miR-183, encompasses the second CpG island (Fig. 1A; Fig. S1). We hypothesized that this cDNA clone was derived from 5’ exon(s) of the primary transcript of the miR-183/96/182 gene, as CpG islands are often associated with promoters (2). Supporting this hypothesis, multiple expressed sequences detected by gene-trap clones, including clone D016D06 (3, 4), were co-localized with the cDNA clone AK044220 (Fig. 1A; Fig. S1). Clone D016D06, deposited by the German GeneTrap Consortium (GGTC) (http://tikus.gsf.de) (3, 4), was derived from insertion of a retroviral construct, rFlpROSAβgeo in 129S2 ES cells (Fig. 1A and C). The rFlpROSAβgeo construct carries a promoterless reporter gene, the β−geo cassette - an in-frame fusion of the β-galactosidase and neomycin resistance (Neor) gene (5), with a splicing acceptor (SA) immediately upstream, and a polyA signal downstream of the β−geo cassette (Fig. -
Supplementary Table S2
1-high in cerebrotropic Gene P-value patients Definition BCHE 2.00E-04 1 Butyrylcholinesterase PLCB2 2.00E-04 -1 Phospholipase C, beta 2 SF3B1 2.00E-04 -1 Splicing factor 3b, subunit 1 BCHE 0.00022 1 Butyrylcholinesterase ZNF721 0.00028 -1 Zinc finger protein 721 GNAI1 0.00044 1 Guanine nucleotide binding protein (G protein), alpha inhibiting activity polypeptide 1 GNAI1 0.00049 1 Guanine nucleotide binding protein (G protein), alpha inhibiting activity polypeptide 1 PDE1B 0.00069 -1 Phosphodiesterase 1B, calmodulin-dependent MCOLN2 0.00085 -1 Mucolipin 2 PGCP 0.00116 1 Plasma glutamate carboxypeptidase TMX4 0.00116 1 Thioredoxin-related transmembrane protein 4 C10orf11 0.00142 1 Chromosome 10 open reading frame 11 TRIM14 0.00156 -1 Tripartite motif-containing 14 APOBEC3D 0.00173 -1 Apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like 3D ANXA6 0.00185 -1 Annexin A6 NOS3 0.00209 -1 Nitric oxide synthase 3 SELI 0.00209 -1 Selenoprotein I NYNRIN 0.0023 -1 NYN domain and retroviral integrase containing ANKFY1 0.00253 -1 Ankyrin repeat and FYVE domain containing 1 APOBEC3F 0.00278 -1 Apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like 3F EBI2 0.00278 -1 Epstein-Barr virus induced gene 2 ETHE1 0.00278 1 Ethylmalonic encephalopathy 1 PDE7A 0.00278 -1 Phosphodiesterase 7A HLA-DOA 0.00305 -1 Major histocompatibility complex, class II, DO alpha SOX13 0.00305 1 SRY (sex determining region Y)-box 13 ABHD2 3.34E-03 1 Abhydrolase domain containing 2 MOCS2 0.00334 1 Molybdenum cofactor synthesis 2 TTLL6 0.00365 -1 Tubulin tyrosine ligase-like family, member 6 SHANK3 0.00394 -1 SH3 and multiple ankyrin repeat domains 3 ADCY4 0.004 -1 Adenylate cyclase 4 CD3D 0.004 -1 CD3d molecule, delta (CD3-TCR complex) (CD3D), transcript variant 1, mRNA. -
Screening and Association Testing of Common Coding Variation in Steroid
BMC Cancer BioMed Central Research article Open Access Screening and association testing of common coding variation in steroid hormone receptor co-activator and co-repressor genes in relation to breast cancer risk: the Multiethnic Cohort Christopher A Haiman*1, Rachel R Garcia1, Chris Hsu1, Lucy Xia1, Helen Ha2, Xin Sheng1, Loic Le Marchand3, Laurence N Kolonel3, Brian E Henderson1, Michael R Stallcup4, Geoffrey L Greene5 and Michael F Press6 Address: 1Department of Preventive Medicine, Keck School of Medicine, University of Southern California/Norris Comprehensive Cancer Center, Los Angeles, California, USA, 2Department of Pharmacology and Pharmaceutical Sciences, School of Pharmacy, University of Southern California, Los Angeles, California, USA, 3Epidemiology Program, Cancer Research Center, University of Hawaii, Honolulu, Hawaii, USA, 4Department of Biochemistry and Molecular Biology, Keck School of Medicine, University of Southern California/Norris Comprehensive Cancer Center, Los Angeles, California, USA, 5The Ben May Department for Cancer Research, The University of Chicago, Chicago Illinois, USA and 6Department of Pathology, Keck School of Medicine, University of Southern California/Norris Comprehensive Cancer Center, Los Angeles, California, USA Email: Christopher A Haiman* - [email protected]; Rachel R Garcia - [email protected]; Chris Hsu - [email protected]; Lucy Xia - [email protected]; Helen Ha - [email protected]; Xin Sheng - [email protected]; Loic Le Marchand - [email protected]; Laurence N Kolonel - [email protected]; Brian E Henderson - [email protected]; Michael R Stallcup - [email protected]; Geoffrey L Greene - [email protected]; Michael F Press - [email protected] * Corresponding author Published: 30 January 2009 Received: 26 November 2008 Accepted: 30 January 2009 BMC Cancer 2009, 9:43 doi:10.1186/1471-2407-9-43 This article is available from: http://www.biomedcentral.com/1471-2407/9/43 © 2009 Haiman et al; licensee BioMed Central Ltd. -
Using Mrna Deep Sequencing to Analyze Differentially Expressed Genes During Panax Notoginseng Saponin Treatment of Ischemic Stroke
MOLECULAR MEDICINE REPORTS 22: 4743-4753, 2020 Using mRNA deep sequencing to analyze differentially expressed genes during Panax notoginseng saponin treatment of ischemic stroke JUN LIN, PING LIANG, QING HUANG, CHONGDONG JIAN, JIANMIN HUANG, XIONGLIN TANG, XUEBIN LI, YANLING LIAO, XIAOHUA HUANG, WENHUA HUANG, LI SU And LANQING MENG Department of Neurology, Affiliated Hospital of Youjiang Medical College for Nationalities, Baise, Guangxi Zhuang Autonomous Region 533000, P.R. China Received October 30, 2019; Accepted August 10, 2020 DOI: 10.3892/mmr.2020.11550 Abstract. Treatment with Panax notoginseng saponin (PNS) growth factor receptor 2. In conclusion, these genes may be can prevent neurological damage in middle cerebral artery important in the underlying mechanism of PNS treatment occlusion model rats to promote recovery after a stroke. in ischemic stroke. Additionally, the present data provided However, the exact molecular mechanisms are unknown and novel insight into the pathogenesis of ischemic stroke. require further study. In the present study, mRNA sequencing was employed to investigate differential gene expression Introduction between model and sham groups, and between model and PNS-treated groups. Enrichment of gene data was performed Stroke is the second leading cause of death and disability using Gene Ontology analysis and the Kyoto Encyclopedia worldwide (1). Ischemic stroke, which accounts for 80% of all of Genes and Genomes database. Hub genes were identi- strokes, usually causes severe neuronal damage and secondary fied and networks were constructed using Cytoscape that neuronal death (2). Cerebral ischemia and reperfusion injury were further verified by reverse transcription‑quantitative are complex pathological processes that involve inflamma- PCR. -
Supplementary Table 1. List of Genes Up-Regulated in Abiraterone-Resistant Vcap Xenograft Samples PIK3IP1 Phosphoinositide-3-Kin
Supplementary Table 1. List of genes up-regulated in abiraterone-resistant VCaP xenograft samples PIK3IP1 phosphoinositide-3-kinase interacting protein 1 TMEM45A transmembrane protein 45A THBS1 thrombospondin 1 C7orf63 chromosome 7 open reading frame 63 OPTN optineurin FAM49A family with sequence similarity 49, member A APOL4 apolipoprotein L, 4 C17orf108|LOC201229 chromosome 17 open reading frame 108 | hypothetical protein LOC201229 SNORD94 small nucleolar RNA, C/D box 94 PCDHB11 protocadherin beta 11 RBM11 RNA binding motif protein 11 C6orf225 chromosome 6 open reading frame 225 KIAA1984|C9orf86|TMEM14 1 KIAA1984 | chromosome 9 open reading frame 86 | transmembrane protein 141 KIAA1107 TLR3 toll-like receptor 3 LPAR6 lysophosphatidic acid receptor 6 KIAA1683 GRB10 growth factor receptor-bound protein 10 TIMP2 TIMP metallopeptidase inhibitor 2 CCDC28A coiled-coil domain containing 28A FBXL2 F-box and leucine-rich repeat protein 2 NOV nephroblastoma overexpressed gene TSPAN31 tetraspanin 31 NR3C2 nuclear receptor subfamily 3, group C, member 2 DYNC2LI1 dynein, cytoplasmic 2, light intermediate chain 1 C15orf51 dynamin 1 pseudogene SAMD13 sterile alpha motif domain containing 13 RASSF6 Ras association (RalGDS/AF-6) domain family member 6 ZNF167 zinc finger protein 167 GATA2 GATA binding protein 2 NUDT7 nudix (nucleoside diphosphate linked moiety X)-type motif 7 DNAJC18 DnaJ (Hsp40) homolog, subfamily C, member 18 SNORA57 small nucleolar RNA, H/ACA box 57 CALCOCO1 calcium binding and coiled-coil domain 1 RLN2 relaxin 2 ING4 inhibitor of -
PRC1 and PRC2 Are Not Required for Targeting of H2A.Z to Developmental Genes in Embryonic Stem Cells
PRC1 and PRC2 Are Not Required for Targeting of H2A.Z to Developmental Genes in Embryonic Stem Cells Robert S. Illingworth1, Catherine H. Botting2, Graeme R. Grimes1, Wendy A. Bickmore1*, Ragnhild Eskeland1*¤ 1 MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine at the University of Edinburgh, Edinburgh, United Kingdom, 2 BMS Mass Spectrometry and Proteomics Facility, Biomedical Sciences Research Complex, University of St. Andrews, St. Andrews, Fife, United Kingdom Abstract The essential histone variant H2A.Z localises to both active and silent chromatin sites. In embryonic stem cells (ESCs), H2A.Z is also reported to co-localise with polycomb repressive complex 2 (PRC2) at developmentally silenced genes. The mechanism of H2A.Z targeting is not clear, but a role for the PRC2 component Suz12 has been suggested. Given this association, we wished to determine if polycomb functionally directs H2A.Z incorporation in ESCs. We demonstrate that the PRC1 component Ring1B interacts with multiple complexes in ESCs. Moreover, we show that although the genomic distribution of H2A.Z co-localises with PRC2, Ring1B and with the presence of CpG islands, H2A.Z still blankets polycomb target loci in the absence of Suz12, Eed (PRC2) or Ring1B (PRC1). Therefore we conclude that H2A.Z accumulates at developmentally silenced genes in ESCs in a polycomb independent manner. Citation: Illingworth RS, Botting CH, Grimes GR, Bickmore WA, Eskeland R (2012) PRC1 and PRC2 Are Not Required for Targeting of H2A.Z to Developmental Genes in Embryonic Stem Cells. PLoS ONE 7(4): e34848. doi:10.1371/journal.pone.0034848 Editor: Robert Feil, CNRS, France Received October 8, 2011; Accepted March 9, 2012; Published April 9, 2012 Copyright: ß 2012 Illingworth et al. -
Supplementary Table 1 Double Treatment Vs Single Treatment
Supplementary table 1 Double treatment vs single treatment Probe ID Symbol Gene name P value Fold change TC0500007292.hg.1 NIM1K NIM1 serine/threonine protein kinase 1.05E-04 5.02 HTA2-neg-47424007_st NA NA 3.44E-03 4.11 HTA2-pos-3475282_st NA NA 3.30E-03 3.24 TC0X00007013.hg.1 MPC1L mitochondrial pyruvate carrier 1-like 5.22E-03 3.21 TC0200010447.hg.1 CASP8 caspase 8, apoptosis-related cysteine peptidase 3.54E-03 2.46 TC0400008390.hg.1 LRIT3 leucine-rich repeat, immunoglobulin-like and transmembrane domains 3 1.86E-03 2.41 TC1700011905.hg.1 DNAH17 dynein, axonemal, heavy chain 17 1.81E-04 2.40 TC0600012064.hg.1 GCM1 glial cells missing homolog 1 (Drosophila) 2.81E-03 2.39 TC0100015789.hg.1 POGZ Transcript Identified by AceView, Entrez Gene ID(s) 23126 3.64E-04 2.38 TC1300010039.hg.1 NEK5 NIMA-related kinase 5 3.39E-03 2.36 TC0900008222.hg.1 STX17 syntaxin 17 1.08E-03 2.29 TC1700012355.hg.1 KRBA2 KRAB-A domain containing 2 5.98E-03 2.28 HTA2-neg-47424044_st NA NA 5.94E-03 2.24 HTA2-neg-47424360_st NA NA 2.12E-03 2.22 TC0800010802.hg.1 C8orf89 chromosome 8 open reading frame 89 6.51E-04 2.20 TC1500010745.hg.1 POLR2M polymerase (RNA) II (DNA directed) polypeptide M 5.19E-03 2.20 TC1500007409.hg.1 GCNT3 glucosaminyl (N-acetyl) transferase 3, mucin type 6.48E-03 2.17 TC2200007132.hg.1 RFPL3 ret finger protein-like 3 5.91E-05 2.17 HTA2-neg-47424024_st NA NA 2.45E-03 2.16 TC0200010474.hg.1 KIAA2012 KIAA2012 5.20E-03 2.16 TC1100007216.hg.1 PRRG4 proline rich Gla (G-carboxyglutamic acid) 4 (transmembrane) 7.43E-03 2.15 TC0400012977.hg.1 SH3D19 -
Genome Wide Study of Tardive Dyskinesia in Schizophrenia
Lim et al. Translational Psychiatry (2021) 11:351 https://doi.org/10.1038/s41398-021-01471-y Translational Psychiatry ARTICLE Open Access Genome wide study of tardive dyskinesia in schizophrenia Keane Lim 1, Max Lam 1,2,3, Clement Zai4,JennyTay1, Nina Karlsson5,SmitaN.Deshpande6,B.K.Thelma7, Norio Ozaki 8,ToshiyaInada 9,KangSim 1,10, Siow-Ann Chong1,11,ToddLencz 2,3,12,JianjunLiu 5,13 and Jimmy Lee 1,11,14 Abstract Tardive dyskinesia (TD) is a severe condition characterized by repetitive involuntary movement of orofacial regions and extremities. Patients treated with antipsychotics typically present with TD symptomatology. Here, we conducted the largest GWAS of TD to date, by meta-analyzing samples of East-Asian, European, and African American ancestry, followed by analyses of biological pathways and polygenic risk with related phenotypes. We identified a novel locus and three suggestive loci, implicating immune-related pathways. Through integrating trans-ethnic fine mapping, we identified putative credible causal variants for three of the loci. Post-hoc analysis revealed that SNPs harbored in TNFRSF1B and CALCOCO1 independently conferred three-fold increase in TD risk, beyond clinical risk factors like Age of onset and Duration of illness to schizophrenia. Further work is necessary to replicate loci that are reported in the study and evaluate the polygenic architecture underlying TD. 1234567890():,; 1234567890():,; 1234567890():,; 1234567890():,; Introduction more severe schizophrenia illness, cognitive impairments, – Tardive Dyskinesia (TD) is a persistent and potentially lowered quality of life and increased mortality7 10. debilitating involuntary movement disorder characterized The pathophysiology of TD is currently unknown. by choreiform, athetoid, and or dystonic movements1,2. -
Downloaded from Ensembl
UCSF UC San Francisco Electronic Theses and Dissertations Title Detecting genetic similarity between complex human traits by exploring their common molecular mechanism Permalink https://escholarship.org/uc/item/1k40s443 Author Gu, Jialiang Publication Date 2019 Peer reviewed|Thesis/dissertation eScholarship.org Powered by the California Digital Library University of California by Submitted in partial satisfaction of the requirements for degree of in in the GRADUATE DIVISION of the UNIVERSITY OF CALIFORNIA, SAN FRANCISCO AND UNIVERSITY OF CALIFORNIA, BERKELEY Approved: ______________________________________________________________________________ Chair ______________________________________________________________________________ ______________________________________________________________________________ ______________________________________________________________________________ ______________________________________________________________________________ Committee Members ii Acknowledgement This project would not have been possible without Prof. Dr. Hao Li, Dr. Jiashun Zheng and Dr. Chris Fuller at the University of California, San Francisco (UCSF) and Caribou Bioscience. The Li lab grew into a multi-facet research group consist of both experimentalists and computational biologists covering three research areas including cellular/molecular mechanism of ageing, genetic determinants of complex human traits and structure, function, evolution of gene regulatory network. Labs like these are the pillar of global success and reputation -
A Meta-Analysis of the Effects of High-LET Ionizing Radiations in Human Gene Expression
Supplementary Materials A Meta-Analysis of the Effects of High-LET Ionizing Radiations in Human Gene Expression Table S1. Statistically significant DEGs (Adj. p-value < 0.01) derived from meta-analysis for samples irradiated with high doses of HZE particles, collected 6-24 h post-IR not common with any other meta- analysis group. This meta-analysis group consists of 3 DEG lists obtained from DGEA, using a total of 11 control and 11 irradiated samples [Data Series: E-MTAB-5761 and E-MTAB-5754]. Ensembl ID Gene Symbol Gene Description Up-Regulated Genes ↑ (2425) ENSG00000000938 FGR FGR proto-oncogene, Src family tyrosine kinase ENSG00000001036 FUCA2 alpha-L-fucosidase 2 ENSG00000001084 GCLC glutamate-cysteine ligase catalytic subunit ENSG00000001631 KRIT1 KRIT1 ankyrin repeat containing ENSG00000002079 MYH16 myosin heavy chain 16 pseudogene ENSG00000002587 HS3ST1 heparan sulfate-glucosamine 3-sulfotransferase 1 ENSG00000003056 M6PR mannose-6-phosphate receptor, cation dependent ENSG00000004059 ARF5 ADP ribosylation factor 5 ENSG00000004777 ARHGAP33 Rho GTPase activating protein 33 ENSG00000004799 PDK4 pyruvate dehydrogenase kinase 4 ENSG00000004848 ARX aristaless related homeobox ENSG00000005022 SLC25A5 solute carrier family 25 member 5 ENSG00000005108 THSD7A thrombospondin type 1 domain containing 7A ENSG00000005194 CIAPIN1 cytokine induced apoptosis inhibitor 1 ENSG00000005381 MPO myeloperoxidase ENSG00000005486 RHBDD2 rhomboid domain containing 2 ENSG00000005884 ITGA3 integrin subunit alpha 3 ENSG00000006016 CRLF1 cytokine receptor like