Differences in X-Chromosome Transcriptional Activity and Cholesterol Metabolism Between Placentae from Swine Breeds from Asian and Western Origins Steve R
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Rabbit Anti-Human ECH1 Polyclonal Antibody (DPABH-07145) This Product Is for Research Use Only and Is Not Intended for Diagnostic Use
Rabbit Anti-Human ECH1 Polyclonal Antibody (DPABH-07145) This product is for research use only and is not intended for diagnostic use. PRODUCT INFORMATION Immunogen Recombinant Protein, antigen sequence: ISLRLTGSSAQEEASGVALGEAPDHSYESLRVTSAQKHVLHVQLNRPNKRNAMNKVFWREMVE CFNKISRDADCRAVVISGAGKMFTAGIDLMDMASDILQPKGDDVARISWYLRDIITRYQETFNVIE RCPK Isotype IgG Source/Host Rabbit Species Reactivity Human Purification Antigen affinity purified Conjugate Unconjugated Applications IHC, WB Format Liquid Size 100 μL Buffer 40% glycerol and PBS (pH 7.2). Preservative 0.02% Sodium Azide Storage Store at +4°C for short term storage. Long time storage is recommended at -20°C. Gently mix before use. Optimal concentrations and conditions for each application should be determined by the user. BACKGROUND Introduction This gene encodes a member of the hydratase/isomerase superfamily. The gene product shows high sequence similarity to enoyl-coenzyme A (CoA) hydratases of several species, particularly within a conserved domain characteristic of these proteins. The encoded protein, which contains a C-terminal peroxisomal targeting sequence, localizes to the peroxisome. The rat ortholog, 45-1 Ramsey Road, Shirley, NY 11967, USA Email: [email protected] Tel: 1-631-624-4882 Fax: 1-631-938-8221 1 © Creative Diagnostics All Rights Reserved which localizes to the matrix of both the peroxisome and mitochondria, can isomerize 3-trans,5- cis-dienoyl-CoA to 2-trans,4-trans-dienoyl-CoA, indicating that it is a delta3,5-delta2,4-dienoyl- CoA isomerase. This enzyme -
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. -
Dynamics of Gene Silencing During X Inactivation Using Allele-Specific RNA-Seq Hendrik Marks1*, Hindrik H
Marks et al. Genome Biology (2015) 16:149 DOI 10.1186/s13059-015-0698-x RESEARCH Open Access Dynamics of gene silencing during X inactivation using allele-specific RNA-seq Hendrik Marks1*, Hindrik H. D. Kerstens1, Tahsin Stefan Barakat3, Erik Splinter4, René A. M. Dirks1, Guido van Mierlo1, Onkar Joshi1, Shuang-Yin Wang1, Tomas Babak5, Cornelis A. Albers2, Tüzer Kalkan6, Austin Smith6, Alice Jouneau7, Wouter de Laat4, Joost Gribnau3 and Hendrik G. Stunnenberg1* Abstract Background: During early embryonic development, one of the two X chromosomes in mammalian female cells is inactivated to compensate for a potential imbalance in transcript levels with male cells, which contain a single X chromosome. Here, we use mouse female embryonic stem cells (ESCs) with non-random X chromosome inactivation (XCI) and polymorphic X chromosomes to study the dynamics of gene silencing over the inactive X chromosome by high-resolution allele-specific RNA-seq. Results: Induction of XCI by differentiation of female ESCs shows that genes proximal to the X-inactivation center are silenced earlier than distal genes, while lowly expressed genes show faster XCI dynamics than highly expressed genes. The active X chromosome shows a minor but significant increase in gene activity during differentiation, resulting in complete dosage compensation in differentiated cell types. Genes escaping XCI show little or no silencing during early propagation of XCI. Allele-specific RNA-seq of neural progenitor cells generated from the female ESCs identifies three regions distal to the X-inactivation center that escape XCI. These regions, which stably escape during propagation and maintenance of XCI, coincide with topologically associating domains (TADs) as present in the female ESCs. -
The Expression of the Human Apolipoprotein Genes and Their Regulation by Ppars
CORE Metadata, citation and similar papers at core.ac.uk Provided by UEF Electronic Publications The expression of the human apolipoprotein genes and their regulation by PPARs Juuso Uski M.Sc. Thesis Biochemistry Department of Biosciences University of Kuopio June 2008 Abstract The expression of the human apolipoprotein genes and their regulation by PPARs. UNIVERSITY OF KUOPIO, the Faculty of Natural and Environmental Sciences, Curriculum of Biochemistry USKI Juuso Oskari Thesis for Master of Science degree Supervisors Prof. Carsten Carlberg, Ph.D. Merja Heinäniemi, Ph.D. June 2008 Keywords: nuclear receptors; peroxisome proliferator-activated receptor; PPAR response element; apolipoprotein; lipid metabolism; high density lipoprotein; low density lipoprotein. Lipids are any fat-soluble, naturally-occurring molecules and one of their main biological functions is energy storage. Lipoproteins carry hydrophobic lipids in the water and salt-based blood environment for processing and energy supply in liver and other organs. In this study, the genomic area around the apolipoprotein genes was scanned in silico for PPAR response elements (PPREs) using the in vitro data-based computer program. Several new putative REs were found in surroundings of multiple lipoprotein genes. The responsiveness of those apolipoprotein genes to the PPAR ligands GW501516, rosiglitazone and GW7647 in the HepG2, HEK293 and THP-1 cell lines were tested with real-time PCR. The APOA1, APOA2, APOB, APOD, APOE, APOF, APOL1, APOL3, APOL5 and APOL6 genes were found to be regulated by PPARs in direct or secondary manners. Those results provide new insights in the understanding of lipid metabolism and so many lifestyle diseases like atherosclerosis, type 2 diabetes, heart disease and stroke. -
The Role of High Density Lipoprotein Compositional and Functional Heterogeneity in Metabolic Disease
The role of high density lipoprotein compositional and functional heterogeneity in metabolic disease By Scott M. Gordon B.S. State University of New York College at Brockport October, 2012 A Dissertation Presented to the Faculty of The University of Cincinnati College of Medicine in partial fulfillment of the requirements for the Degree of Doctor of Philosophy from the Pathobiology and Molecular Medicine graduate program W. Sean Davidson Ph.D. (Chair) David Askew Ph.D. Professor and Thesis Chair Professor Department of Pathology Department of Pathology University of Cincinnati University of Cincinnati Francis McCormack M.D. Gangani Silva Ph.D. Professor Assistant Professor Department of Pathology Department of Pathology University of Cincinnati University of Cincinnati Jason Lu Ph.D. Assistant Professor Division of Bioinformatics Cincinnati Children’s Hospital i Abstract High density lipoproteins (HDL) are complexes of phospholipid, cholesterol and protein that circulate in the blood. Epidemiological studies have demonstrated a strong inverse correlation between plasma levels of HDL associated cholesterol (HDL-C) and the incidence of cardiovascular disease (CVD). Clinically, HDL-C is often measured and used in combination with low density lipoprotein cholesterol (LDL-C) to assess overall cardiovascular health. HDL have been shown to possess a wide variety of functional attributes which likely contribute to this protection including anti-inflammatory and anti- oxidative properties and the ability to remove excess cholesterol from peripheral tissues and deliver it to the liver for excretion, a process known as reverse cholesterol transport. This functional diversity might be explained by the complexity of HDL composition. Recent studies have taken advantage of advances in mass spectrometry technologies to characterize the proteome of total HDL finding that over 50 different proteins can associate with these particles. -
1 Supporting Information for a Microrna Network Regulates
Supporting Information for A microRNA Network Regulates Expression and Biosynthesis of CFTR and CFTR-ΔF508 Shyam Ramachandrana,b, Philip H. Karpc, Peng Jiangc, Lynda S. Ostedgaardc, Amy E. Walza, John T. Fishere, Shaf Keshavjeeh, Kim A. Lennoxi, Ashley M. Jacobii, Scott D. Rosei, Mark A. Behlkei, Michael J. Welshb,c,d,g, Yi Xingb,c,f, Paul B. McCray Jr.a,b,c Author Affiliations: Department of Pediatricsa, Interdisciplinary Program in Geneticsb, Departments of Internal Medicinec, Molecular Physiology and Biophysicsd, Anatomy and Cell Biologye, Biomedical Engineeringf, Howard Hughes Medical Instituteg, Carver College of Medicine, University of Iowa, Iowa City, IA-52242 Division of Thoracic Surgeryh, Toronto General Hospital, University Health Network, University of Toronto, Toronto, Canada-M5G 2C4 Integrated DNA Technologiesi, Coralville, IA-52241 To whom correspondence should be addressed: Email: [email protected] (M.J.W.); yi- [email protected] (Y.X.); Email: [email protected] (P.B.M.) This PDF file includes: Materials and Methods References Fig. S1. miR-138 regulates SIN3A in a dose-dependent and site-specific manner. Fig. S2. miR-138 regulates endogenous SIN3A protein expression. Fig. S3. miR-138 regulates endogenous CFTR protein expression in Calu-3 cells. Fig. S4. miR-138 regulates endogenous CFTR protein expression in primary human airway epithelia. Fig. S5. miR-138 regulates CFTR expression in HeLa cells. Fig. S6. miR-138 regulates CFTR expression in HEK293T cells. Fig. S7. HeLa cells exhibit CFTR channel activity. Fig. S8. miR-138 improves CFTR processing. Fig. S9. miR-138 improves CFTR-ΔF508 processing. Fig. S10. SIN3A inhibition yields partial rescue of Cl- transport in CF epithelia. -
S1 Supplemental Materials Supplemental Methods Supplemental Figure 1. Immune Phenotype of Mcd19 Targeted CAR T and Dose Titratio
Supplemental Materials Supplemental Methods Supplemental Figure 1. Immune phenotype of mCD19 targeted CAR T and dose titration of in vivo efficacy. Supplemental Figure 2. Gene expression of fluorescent-protein tagged CAR T cells. Supplemental Figure 3. Fluorescent protein tagged CAR T cells function similarly to non-tagged counterparts. Supplemental Figure 4. Transduction efficiency and immune phenotype of mCD19 targeted CAR T cells for survival study (Figure 2D). Supplemental Figure 5. Transduction efficiency and immune phenotype of CAR T cells used in irradiated CAR T study (Fig. 3B-C). Supplemental Figure 6. Differential gene expression of CD4+ m19-humBBz CAR T cells. Supplemental Figure 7. CAR expression and CD4/CD8 subsets of human CD19 targeted CAR T cells for Figure 5E-G. Supplemental Figure 8. Transduction efficiency and immune phenotype of mCD19 targeted wild type (WT) and TRAF1-/- CAR T cells used for in vivo study (Figure 6D). Supplemental Figure 9. Mutated m19-musBBz CAR T cells have increased NF-κB signaling, improved cytokine production, anti-apoptosis, and in vivo function. Supplemental Figure 10. TRAF and CAR co-expression in human CD19-targeted CAR T cells. Supplemental Figure 11. TRAF2 over-expressed h19BBz CAR T cells show similar in vivo efficacy to h19BBz CAR T cells in an aggressive leukemia model. S1 Supplemental Table 1. Probesets increased in m19z and m1928z vs m19-musBBz CAR T cells. Supplemental Table 2. Probesets increased in m19-musBBz vs m19z and m1928z CAR T cells. Supplemental Table 3. Probesets differentially expressed in m19z vs m19-musBBz CAR T cells. Supplemental Table 4. Probesets differentially expressed in m1928z vs m19-musBBz CAR T cells. -
Polychlorinated Biphenyl Ligands of the Aryl Hydrocarbon Receptor Promote Adipocyte-Mediated Diabetes
University of Kentucky UKnowledge Theses and Dissertations--Nutritional Sciences Nutritional Sciences 2013 POLYCHLORINATED BIPHENYL LIGANDS OF THE ARYL HYDROCARBON RECEPTOR PROMOTE ADIPOCYTE-MEDIATED DIABETES Nicki A. Baker University of Kentucky, [email protected] Right click to open a feedback form in a new tab to let us know how this document benefits ou.y Recommended Citation Baker, Nicki A., "POLYCHLORINATED BIPHENYL LIGANDS OF THE ARYL HYDROCARBON RECEPTOR PROMOTE ADIPOCYTE-MEDIATED DIABETES" (2013). Theses and Dissertations--Nutritional Sciences. 7. https://uknowledge.uky.edu/nutrisci_etds/7 This Doctoral Dissertation is brought to you for free and open access by the Nutritional Sciences at UKnowledge. It has been accepted for inclusion in Theses and Dissertations--Nutritional Sciences by an authorized administrator of UKnowledge. For more information, please contact [email protected]. STUDENT AGREEMENT: I represent that my thesis or dissertation and abstract are my original work. Proper attribution has been given to all outside sources. I understand that I am solely responsible for obtaining any needed copyright permissions. I have obtained and attached hereto needed written permission statements(s) from the owner(s) of each third-party copyrighted matter to be included in my work, allowing electronic distribution (if such use is not permitted by the fair use doctrine). I hereby grant to The University of Kentucky and its agents the non-exclusive license to archive and make accessible my work in whole or in part in all forms of media, now or hereafter known. I agree that the document mentioned above may be made available immediately for worldwide access unless a preapproved embargo applies. -
Variation in Protein Coding Genes Identifies Information
bioRxiv preprint doi: https://doi.org/10.1101/679456; this version posted June 21, 2019. 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-NC-ND 4.0 International license. Animal complexity and information flow 1 1 2 3 4 5 Variation in protein coding genes identifies information flow as a contributor to 6 animal complexity 7 8 Jack Dean, Daniela Lopes Cardoso and Colin Sharpe* 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Institute of Biological and Biomedical Sciences 25 School of Biological Science 26 University of Portsmouth, 27 Portsmouth, UK 28 PO16 7YH 29 30 * Author for correspondence 31 [email protected] 32 33 Orcid numbers: 34 DLC: 0000-0003-2683-1745 35 CS: 0000-0002-5022-0840 36 37 38 39 40 41 42 43 44 45 46 47 48 49 Abstract bioRxiv preprint doi: https://doi.org/10.1101/679456; this version posted June 21, 2019. 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-NC-ND 4.0 International license. Animal complexity and information flow 2 1 Across the metazoans there is a trend towards greater organismal complexity. How 2 complexity is generated, however, is uncertain. Since C.elegans and humans have 3 approximately the same number of genes, the explanation will depend on how genes are 4 used, rather than their absolute number. -
SLIC-CAGE: High-Resolution Transcription Start Site Mapping Using Nanogram-Levels of Total RNA
bioRxiv preprint doi: https://doi.org/10.1101/368795; this version posted July 19, 2018. 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-NC 4.0 International license. SLIC-CAGE: high-resolution transcription start site mapping using nanogram-levels of total RNA Nevena Cvetesic1, 2*, Harry G. Leitch1,2, Malgorzata Borkowska1,2, Ferenc Müller3, Piero Carninci4,5, Petra Hajkova1,2 and Boris Lenhard1,2,6* 1Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, London W12 0NN, UK 2MRC London Institute of Medical Sciences, London W12 0NN, UK 3Institute of Cancer and Genomic Sciences, University of Birmingham, Edgbaston B15 2TT, UK 4RIKEN Center for Life Science Technologies, Division of Genomic Technologies, Yokohama City, Kanagawa 230-0045, Japan 5RIKEN Omics Science Center, Yokohama City, Kanagawa 230-0045, Japan 6Sars International Centre for Marine Molecular Biology, University of Bergen, N-5008 Bergen, Norway *Correspondence to: Nevena Cvetesic Institute of Clinical Sciences, Faculty of Medicine, Imperial College London and MRC London Institute of Medical Sciences, London, W12 0NN, UK e-mail: [email protected] Boris Lenhard Institute of Clinical Sciences, Faculty of Medicine, Imperial College London and MRC London Institute of Medical Sciences, London, W12 0NN, UK e-mail: [email protected] Running title: TSS discovery using Super-Low Input Carrier-CAGE Keywords: cap analysis of gene expression; low input material; degradable nucleic acid carrier; promoters; gene expression profiling 1 bioRxiv preprint doi: https://doi.org/10.1101/368795; this version posted July 19, 2018. -
Supplementary Materials
Supplementary materials Supplementary Table S1: MGNC compound library Ingredien Molecule Caco- Mol ID MW AlogP OB (%) BBB DL FASA- HL t Name Name 2 shengdi MOL012254 campesterol 400.8 7.63 37.58 1.34 0.98 0.7 0.21 20.2 shengdi MOL000519 coniferin 314.4 3.16 31.11 0.42 -0.2 0.3 0.27 74.6 beta- shengdi MOL000359 414.8 8.08 36.91 1.32 0.99 0.8 0.23 20.2 sitosterol pachymic shengdi MOL000289 528.9 6.54 33.63 0.1 -0.6 0.8 0 9.27 acid Poricoic acid shengdi MOL000291 484.7 5.64 30.52 -0.08 -0.9 0.8 0 8.67 B Chrysanthem shengdi MOL004492 585 8.24 38.72 0.51 -1 0.6 0.3 17.5 axanthin 20- shengdi MOL011455 Hexadecano 418.6 1.91 32.7 -0.24 -0.4 0.7 0.29 104 ylingenol huanglian MOL001454 berberine 336.4 3.45 36.86 1.24 0.57 0.8 0.19 6.57 huanglian MOL013352 Obacunone 454.6 2.68 43.29 0.01 -0.4 0.8 0.31 -13 huanglian MOL002894 berberrubine 322.4 3.2 35.74 1.07 0.17 0.7 0.24 6.46 huanglian MOL002897 epiberberine 336.4 3.45 43.09 1.17 0.4 0.8 0.19 6.1 huanglian MOL002903 (R)-Canadine 339.4 3.4 55.37 1.04 0.57 0.8 0.2 6.41 huanglian MOL002904 Berlambine 351.4 2.49 36.68 0.97 0.17 0.8 0.28 7.33 Corchorosid huanglian MOL002907 404.6 1.34 105 -0.91 -1.3 0.8 0.29 6.68 e A_qt Magnogrand huanglian MOL000622 266.4 1.18 63.71 0.02 -0.2 0.2 0.3 3.17 iolide huanglian MOL000762 Palmidin A 510.5 4.52 35.36 -0.38 -1.5 0.7 0.39 33.2 huanglian MOL000785 palmatine 352.4 3.65 64.6 1.33 0.37 0.7 0.13 2.25 huanglian MOL000098 quercetin 302.3 1.5 46.43 0.05 -0.8 0.3 0.38 14.4 huanglian MOL001458 coptisine 320.3 3.25 30.67 1.21 0.32 0.9 0.26 9.33 huanglian MOL002668 Worenine -
Identification and Prioritization Genes
Original Article 2015, Vol: 3, Issue: 1, Pages: 18-23 Bioinformatics useful tool in study of genes associated with diseases Research in Molecular Medicine DOI: 10.7508/rmm.2015.01.004 Identifying and prioritizing genes related to Familial hypercholesterolemia QTLs using gene ontology and protein interaction networks Ali Kazemi-Pour 1, Bahram Goliaei 2*, Hamid Pezeshk 3, Behjat Kalantari khandani 4 1 PhD student of Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran. 2 Professor of Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran. 3 Professor of statistics, Science College, University of Tehran, Tehran, Iran. 4 Assistant Professor of Internal Medicine, Kerman University of Medical Sciences, Kerman, Iran. Received: 17 Aug 2014 Abstract Revised : 4 Sep 2014 Background: Gene identification represents the first step to a better understanding of the physiological role of the underlying protein and disease Accepted: 10 Sep 2014 pathways, which in turn serves as a starting point for developing therapeutic interventions. Familial hypercholesterolemia is a hereditary metabolic disorder Corresponding Authors: Bahram Goliaei characterized by high low-density lipoprotein cholesterol levels. Institute of Biochemistry and Hypercholesterolemia is a quantitative trait that is controlled by interactions Biophysics, University of Tehran, among several quantitative trait loci. Many biological data is presented in the Tehran, Iran. context of biological networks and evaluation of biological networks is considered Phone: +98-2161113356 E-mail: [email protected] as the essential key to understanding complex biological systems. Materials and Methods: In this research, we used combination of information about quantitative trait loci of hypercholesterolemia with information of gene ontology and protein–protein interaction network for identification of genes associated with hypercholesterolemia.