Neuron-Enriched Gene Expression Patterns Are Regionally Anti-Correlated with Oligodendrocyte-Enriched Patterns in the Adult Mouse and Human Brain
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PARSANA-DISSERTATION-2020.Pdf
DECIPHERING TRANSCRIPTIONAL PATTERNS OF GENE REGULATION: A COMPUTATIONAL APPROACH by Princy Parsana A dissertation submitted to The Johns Hopkins University in conformity with the requirements for the degree of Doctor of Philosophy Baltimore, Maryland July, 2020 © 2020 Princy Parsana All rights reserved Abstract With rapid advancements in sequencing technology, we now have the ability to sequence the entire human genome, and to quantify expression of tens of thousands of genes from hundreds of individuals. This provides an extraordinary opportunity to learn phenotype relevant genomic patterns that can improve our understanding of molecular and cellular processes underlying a trait. The high dimensional nature of genomic data presents a range of computational and statistical challenges. This dissertation presents a compilation of projects that were driven by the motivation to efficiently capture gene regulatory patterns in the human transcriptome, while addressing statistical and computational challenges that accompany this data. We attempt to address two major difficulties in this domain: a) artifacts and noise in transcriptomic data, andb) limited statistical power. First, we present our work on investigating the effect of artifactual variation in gene expression data and its impact on trans-eQTL discovery. Here we performed an in-depth analysis of diverse pre-recorded covariates and latent confounders to understand their contribution to heterogeneity in gene expression measurements. Next, we discovered 673 trans-eQTLs across 16 human tissues using v6 data from the Genotype Tissue Expression (GTEx) project. Finally, we characterized two trait-associated trans-eQTLs; one in Skeletal Muscle and another in Thyroid. Second, we present a principal component based residualization method to correct gene expression measurements prior to reconstruction of co-expression networks. -
Mouse Spock1 Knockout Project (CRISPR/Cas9)
https://www.alphaknockout.com Mouse Spock1 Knockout Project (CRISPR/Cas9) Objective: To create a Spock1 knockout Mouse model (C57BL/6J) by CRISPR/Cas-mediated genome engineering. Strategy summary: The Spock1 gene (NCBI Reference Sequence: NM_009262 ; Ensembl: ENSMUSG00000056222 ) is located on Mouse chromosome 13. 12 exons are identified, with the ATG start codon in exon 2 and the TAG stop codon in exon 12 (Transcript: ENSMUST00000185502). Exon 5 will be selected as target site. Cas9 and gRNA will be co-injected into fertilized eggs for KO Mouse production. The pups will be genotyped by PCR followed by sequencing analysis. Note: Mice homozygous for a targeted null mutation display no obvious morphological or behavioral abnormalities, are fertile, and have normal life spans. Adult homozygotes exhibit normal brain morphology and EEG recordings. Exon 5 starts from about 18.25% of the coding region. Exon 5 covers 8.67% of the coding region. The size of effective KO region: ~115 bp. The KO region does not have any other known gene. Page 1 of 8 https://www.alphaknockout.com Overview of the Targeting Strategy Wildtype allele gRNA region 5' gRNA region 3' 1 5 12 Legends Exon of mouse Spock1 Knockout region Page 2 of 8 https://www.alphaknockout.com Overview of the Dot Plot (up) Window size: 15 bp Forward Reverse Complement Sequence 12 Note: The 2000 bp section upstream of Exon 5 is aligned with itself to determine if there are tandem repeats. Tandem repeats are found in the dot plot matrix. The gRNA site is selected outside of these tandem repeats. -
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. -
Molecular Classification Reveals the Diverse Genetic Features and Prognosis
bioRxiv preprint doi: https://doi.org/10.1101/2021.06.07.447364; this version posted June 7, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Molecular classification reveals the diverse genetic features and prognosis of gastric cancer: a multi-omics consensus ensemble clustering 1 Xianyu Hu1#, Zhenglin Wang1#, Qing Wang2#, Ke Chen1, Qijun Han1, Suwen Bai3, 2 Juan Du3,4*, Wei Chen1* 3 1 Department of General Surgery, The First Affiliated Hospital of Anhui Medical 4 University Hefei, Anhui Province 230022, P.R. China 5 2 Department of Biliary-Pancreatic Minimally Invasive Surgery, The First Affiliated 6 Hospital of Shantou University Medical College, Shantou, Guangdong Province 515000, 7 P.R. China 8 3 Longgang District People’s Hospital of Shenzhen & The Third Affiliated Hospital 9 (Provisional) of The Chinese University of Hong Kong, Shenzhen, Shenzhen, 10 Guangdong Province 518172, P.R. China 11 4 School of Medicine, The Chinese University of Hong Kong, Shenzhen, Shenzhen, 12 Guangdong Province 518172, P.R. China 13 14 # These authors contributed equally to the study. 15 Correspondence should be addressed to Wei Chen ([email protected]) 16 17 18 bioRxiv preprint doi: https://doi.org/10.1101/2021.06.07.447364; this version posted June 7, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. 19 *Correspondence to: 20 Prof. Juan Du 21 Longgang District People’s Hospital of Shenzhen & The Third Affiliated Hospital 22 (Provisional) of The Chinese University of Hong Kong, Shenzhen, Shenzhen, 23 Guangdong Province 518172, P.R. -
Broad Poster Vivek
A novel computational method for finding regions with copy number abnormalities in cancer cells Vivek, Manuel Garber, and Mike Zody Broad Institute of MIT and Harvard, Cambridge, MA, USA Introduction Results Cancer can result from the over expression of oncogenes, genes which control and regulate cell growth. Sometimes oncogenes increase in 1 2 3 activity due to a specific genetic mutation called a translocation (Fig 1). SMAD4 – a gene known to be deleted in pancreatic COX10 – a gene deleted in cytochrome c oxidase AK001392 – a hereditary prostate cancer protein This translocation allows the oncogene to remain as active as its paired carcinoma deficiency, known to be related to cell proliferation gene. Amplification of this mutation can occur, thereby creating the proper conditions for uncontrolled cell growth; consequently, each Results from Analysis Program Results from Analysis Program Results from Analysis Program component of the translocation will amplify in similar quantities. In this mutation, the chromosomal region containing the oncogene displaces to Region 1 Region 2 R2 Region 1 Region 2 R2 Region 1 Region 2 R2 a region on another chromosome containing a gene that is expressed Chr18:47044749-47311978 Chr17:13930739-14654741 0.499070821478475 Chr17:13930739-14654741 Chr18:26861790-27072166 0.47355172850856 Chr17:12542326-13930738 Chr8:1789292-1801984 0.406208680312004 frequently. Actual region containing gene Actual region containing gene Actual region containing gene chr18: 45,842,214 - 48,514,513 chr17: 13,966,862 - 14,068,461 chr17: 12,542,326 - 13,930,738 Fig 1. Two chromosomal regions (abcdef and ghijk) are translocating to create two new regions (abckl and ghijedf). -
Experimental Validation of the Regulated Expression of Large Numbers of Non-Coding Rnas from the Mouse Genome
Downloaded from genome.cshlp.org on September 30, 2021 - Published by Cold Spring Harbor Laboratory Press Article Experimental validation of the regulated expression of large numbers of non-coding RNAs from the mouse genome Timothy Ravasi,1,4,5 Harukazu Suzuki,2,4 Ken C. Pang,1,3,4 Shintaro Katayama,2,4 Masaaki Furuno,2,4,6 Rie Okunishi,2 Shiro Fukuda,2 Kelin Ru,1 Martin C. Frith,1,2 M. Milena Gongora,1 Sean M. Grimmond,1 David A. Hume,1 Yoshihide Hayashizaki,2 and John S. Mattick1,7 1ARC Special Research Centre for Functional and Applied Genomics, Institute for Molecular Bioscience, University of Queensland, Brisbane QLD 4072, Australia; 2Laboratory for Genome Exploration Research Group, RIKEN Genomic Science Center, RIKEN Yokohama Institute, Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan; 3T Cell Laboratory, Ludwig Institute for Cancer Research, Austin & Repatriation Medical Centre, Heidelberg VIC 3084, Australia Recent large-scale analyses of mainly full-length cDNA libraries generated from a variety of mouse tissues indicated that almost half of all representative cloned sequences did not contain an apparent protein-coding sequence, and were putatively derived from non-protein-coding RNA (ncRNA) genes. However, many of these clones were singletons and the majority were unspliced, raising the possibility that they may be derived from genomic DNA or unprocessed pre-mRNA contamination during library construction, or alternatively represent nonspecific “transcriptional noise.” Here we show, using reverse transcriptase-dependent PCR, microarray, and Northern blot analyses, that many of these clones were derived from genuine transcripts of unknown function whose expression appears to be regulated. -
Differential Patterns of Allelic Loss in Estrogen Receptor-Positive Infiltrating Lobular and Ductal Breast Cancer
GENES, CHROMOSOMES & CANCER 47:1049–1066 (2008) Differential Patterns of Allelic Loss in Estrogen Receptor-Positive Infiltrating Lobular and Ductal Breast Cancer L. W. M. Loo,1 C. Ton,1,2 Y.-W. Wang,2 D. I. Grove,2 H. Bouzek,1 N. Vartanian,1 M.-G. Lin,1 X. Yuan,1 T. L. Lawton,3 J. R. Daling,2 K. E. Malone,2 C. I. Li,2 L. Hsu,2 and P.L. Porter1,2,3* 1Division of Human Biology,Fred Hutchinson Cancer Research Center,Seattle,WA 2Division of Public Health Sciences,Fred Hutchinson Cancer Research Center,Seattle,WA 3Departmentof Pathology,Universityof Washington,Seattle,WA The two main histological types of infiltrating breast cancer, lobular (ILC) and the more common ductal (IDC) carcinoma are morphologically and clinically distinct. To assess the molecular alterations associated with these breast cancer subtypes, we conducted a whole-genome study of 166 archival estrogen receptor (ER)-positive tumors (89 IDC and 77 ILC) using the Affy- metrix GeneChip® Mapping 10K Array to identify sites of loss of heterozygosity (LOH) that either distinguished, or were shared by, the two phenotypes. We found single nucleotide polymorphisms (SNPs) of high-frequency LOH (>50%) common to both ILC and IDC tumors predominately in 11q, 16q, and 17p. Overall, IDC had a slightly higher frequency of LOH events across the genome than ILC (fractional allelic loss 5 0.186 and 0.156). By comparing the average frequency of LOH by chro- mosomal arm, we found IDC tumors with significantly (P < 0.05) higher frequency of LOH on 3p, 5q, 8p, 9p, 20p, and 20q than ILC tumors. -
Supplementary Table 1: Adhesion Genes Data Set
Supplementary Table 1: Adhesion genes data set PROBE Entrez Gene ID Celera Gene ID Gene_Symbol Gene_Name 160832 1 hCG201364.3 A1BG alpha-1-B glycoprotein 223658 1 hCG201364.3 A1BG alpha-1-B glycoprotein 212988 102 hCG40040.3 ADAM10 ADAM metallopeptidase domain 10 133411 4185 hCG28232.2 ADAM11 ADAM metallopeptidase domain 11 110695 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 195222 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 165344 8751 hCG20021.3 ADAM15 ADAM metallopeptidase domain 15 (metargidin) 189065 6868 null ADAM17 ADAM metallopeptidase domain 17 (tumor necrosis factor, alpha, converting enzyme) 108119 8728 hCG15398.4 ADAM19 ADAM metallopeptidase domain 19 (meltrin beta) 117763 8748 hCG20675.3 ADAM20 ADAM metallopeptidase domain 20 126448 8747 hCG1785634.2 ADAM21 ADAM metallopeptidase domain 21 208981 8747 hCG1785634.2|hCG2042897 ADAM21 ADAM metallopeptidase domain 21 180903 53616 hCG17212.4 ADAM22 ADAM metallopeptidase domain 22 177272 8745 hCG1811623.1 ADAM23 ADAM metallopeptidase domain 23 102384 10863 hCG1818505.1 ADAM28 ADAM metallopeptidase domain 28 119968 11086 hCG1786734.2 ADAM29 ADAM metallopeptidase domain 29 205542 11085 hCG1997196.1 ADAM30 ADAM metallopeptidase domain 30 148417 80332 hCG39255.4 ADAM33 ADAM metallopeptidase domain 33 140492 8756 hCG1789002.2 ADAM7 ADAM metallopeptidase domain 7 122603 101 hCG1816947.1 ADAM8 ADAM metallopeptidase domain 8 183965 8754 hCG1996391 ADAM9 ADAM metallopeptidase domain 9 (meltrin gamma) 129974 27299 hCG15447.3 ADAMDEC1 ADAM-like, -
Transcriptomic Profile of the Subiculum-Projecting VIP Gabaergic Neurons in the Mouse CA1 Hippocampus
Brain Structure and Function (2019) 224:2269–2280 https://doi.org/10.1007/s00429-019-01883-z SHORT COMMUNICATION Transcriptomic profle of the subiculum‑projecting VIP GABAergic neurons in the mouse CA1 hippocampus Xiao Luo1,2 · Einer Muñoz‑Pino1,2 · Ruggiero Francavilla1,2 · Maxime Vallée3,4 · Arnaud Droit3 · Lisa Topolnik1,2 Received: 16 March 2018 / Accepted: 2 May 2019 / Published online: 16 May 2019 © Springer-Verlag GmbH Germany, part of Springer Nature 2019 Abstract In cortical circuits, the vasoactive intestinal peptide (VIP+)-expressing GABAergic cells represent a heterogeneous but unique group of interneurons that is mainly specialized in network disinhibition. While the physiological properties and connectivity patterns have been elucidated in several types of VIP+ interneurons, little is known about the cell type-specifc molecular repertoires important for selective targeting of VIP+ cell types and understanding their functions. Using patch- sequencing approach, we analyzed the transcriptomic profle of anatomically identifed subiculum-projecting VIP+ GABAe- rgic neurons that reside in the mouse hippocampal CA1 area, express muscarinic receptor 2 and coordinate the hippocampo- subicular interactions via selective innervation of interneurons in the CA1 area and of interneurons and pyramidal cells in subiculum. We explored the VIP+ cell gene expression within major gene families including ion channels, neurotransmitter receptors, neuromodulators, cell adhesion and myelination molecules. Among others, a large variety of genes involved in neuromodulatory signaling, including acetylcholine (Chrna4), norepinephrin (Adrb1), dopamine (Drd1), serotonin (Htr1d), cannabinoid (Cnr1), opioid (Oprd1, Oprl1) and neuropeptide Y (Npy1r) receptors was detected in these cells. Many genes that were enriched in other local VIP+ cell types, including the interneuron-selective interneurons and the cholecystokinin- coexpressing basket cells, were detected in VIP+ subiculum-projecting cells. -
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) -
Molecular Effects of Isoflavone Supplementation Human Intervention Studies and Quantitative Models for Risk Assessment
Molecular effects of isoflavone supplementation Human intervention studies and quantitative models for risk assessment Vera van der Velpen Thesis committee Promotors Prof. Dr Pieter van ‘t Veer Professor of Nutritional Epidemiology Wageningen University Prof. Dr Evert G. Schouten Emeritus Professor of Epidemiology and Prevention Wageningen University Co-promotors Dr Anouk Geelen Assistant professor, Division of Human Nutrition Wageningen University Dr Lydia A. Afman Assistant professor, Division of Human Nutrition Wageningen University Other members Prof. Dr Jaap Keijer, Wageningen University Dr Hubert P.J.M. Noteborn, Netherlands Food en Consumer Product Safety Authority Prof. Dr Yvonne T. van der Schouw, UMC Utrecht Dr Wendy L. Hall, King’s College London This research was conducted under the auspices of the Graduate School VLAG (Advanced studies in Food Technology, Agrobiotechnology, Nutrition and Health Sciences). Molecular effects of isoflavone supplementation Human intervention studies and quantitative models for risk assessment Vera van der Velpen Thesis submitted in fulfilment of the requirements for the degree of doctor at Wageningen University by the authority of the Rector Magnificus Prof. Dr M.J. Kropff, in the presence of the Thesis Committee appointed by the Academic Board to be defended in public on Friday 20 June 2014 at 13.30 p.m. in the Aula. Vera van der Velpen Molecular effects of isoflavone supplementation: Human intervention studies and quantitative models for risk assessment 154 pages PhD thesis, Wageningen University, Wageningen, NL (2014) With references, with summaries in Dutch and English ISBN: 978-94-6173-952-0 ABSTRact Background: Risk assessment can potentially be improved by closely linked experiments in the disciplines of epidemiology and toxicology. -
Association Weight Matrix for the Genetic Dissection of Puberty in Beef Cattle
Association weight matrix for the genetic dissection of puberty in beef cattle Marina R. S. Fortesa,b,c, Antonio Revertera,b, Yuandan Zhanga,d, Eliza Collisa,b, Shivashankar H. Nagarajb,NickN.Jonssona,c,e, Kishore C. Prayagaa,b,1, Wes Barrisa,b, and Rachel J. Hawkena,b,2 aCooperative Research Centre for Beef Genetic Technologies; bCommonwealth Scientific and Industrial Research Organization, division of Livestock Industries, Queensland Bioscience Precinct, Brisbane QLD 4067, Australia; cThe University of Queensland, School of Veterinary Science, Gatton QLD 4343, Australia; dAnimal Genetics and Breeding Unit, University of New England, Armidale NSW 2351, Australia; and eFaculty of Veterinary Medicine, University of Glasgow, Glasgow G61 1QH, United Kingdom Edited by George Seidel, Colorado State University, Fort Collins, CO, and approved June 21, 2010 (received for review February 23, 2010) We describe a systems biology approach for the genetic dissection tional data on traits related to puberty are available. For example, of complex traits based on applying gene network theory to the re- weight and condition score are often measured on occasions sults from genome-wide associations. The associations of single- throughout an animal’s development. Hence, understanding ge- nucleotide polymorphisms (SNP) that were individually associated netics of cattle puberty and its biology serves two purposes: as with a primary phenotype of interest, age at puberty in our study, a strategy to develop efficient livestock resources and as a model were explored across 22 related traits. Genomic regions were sur- for human biology. veyed for genes harboring the selected SNP. As a result, an asso- The focus of this work is to demonstrate a unique systems ap- ciation weight matrix (AWM) was constructed with as many rows proach, which we call an association weight matrix (AWM), ap- as genes and as many columns as traits.