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Association Analyses of Known Genetic Variants with Gene
ASSOCIATION ANALYSES OF KNOWN GENETIC VARIANTS WITH GENE EXPRESSION IN BRAIN by Viktoriya Strumba A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Bioinformatics) in The University of Michigan 2009 Doctoral Committee: Professor Margit Burmeister, Chair Professor Huda Akil Professor Brian D. Athey Assistant Professor Zhaohui S. Qin Research Statistician Thomas Blackwell To Sam and Valentina Dmitriy and Elizabeth ii ACKNOWLEDGEMENTS I would like to thank my advisor Professor Margit Burmeister, who tirelessly guided me though seemingly impassable corridors of graduate work. Throughout my thesis writing period she provided sound advice, encouragement and inspiration. Leading by example, her enthusiasm and dedication have been instrumental in my path to becoming a better scientist. I also would like to thank my co-advisor Tom Blackwell. His careful prodding always kept me on my toes and looking for answers, which taught me the depth of careful statistical analysis. His diligence and dedication have been irreplaceable in most difficult of projects. I also would like to thank my other committee members: Huda Akil, Brian Athey and Steve Qin as well as David States. You did not make it easy for me, but I thank you for believing and not giving up. Huda’s eloquence in every subject matter she explained have been particularly inspiring, while both Huda’s and Brian’s valuable advice made the completion of this dissertation possible. I would also like to thank all the members of the Burmeister lab, both past and present: Sandra Villafuerte, Kristine Ito, Cindy Schoen, Karen Majczenko, Ellen Schmidt, Randi Burns, Gang Su, Nan Xiang and Ana Progovac. -
Sorbonne Université/China Scholarship Council Program 2021
Sorbonne Université/China Scholarship Council program 2021 Thesis proposal Title of the research project: Hnf1b regulation during kidney development and regeneration Joint supervision: no Joint PhD (cotutelle): no Thesis supervisor: … Muriel Umbhauer. Email address of the thesis supervisor: [email protected] Institution: …… Sorbonne Université …. Doctoral school (N°+name): ED …. …… ED 515 Complexité du Vivant Research laboratory: UMR7622 CNRS Laboratory of developmental biology Name of the laboratory director: … Sylvie Schneider-Maunoury Email address of the laboratory director: [email protected] Subject description (2 pages max): 1) Study context The POU homeodomain transcription factor hepatocyte nuclear factor 1β (Hnf1b) plays an essential role in vertebrate kidney development. Heterozygous mutations in human HNF1B cause the complex multisystem syndrome known as Renal Cysts And Diabetes (RCAD). The most prominent clinical features of this autosomal dominant disorder are non-diabetic renal disease resulting from abnormal renal development and diabetes mellitus (reviewed by Clissold RL et al., 2015). During early mouse kidney development, Hnf1b has been shown to be required for ureteric bud branching and initiation of nephrogenesis (Lokmane et al., 2010). Hnf1b conditional inactivation in murine nephron progenitors has revealed an additional role in segment fate Xenopus is a well established and attractive model to study kidney development (Krneta-Stankic V. et al, 2017). Renal function at larval stages relies on two pronephroi located on both sides of the body, each consisting on one giant nephron displaying the same structural and functional organisation than the mammalian nephron. Moreover, pronephric and metanephric differentiation and morphogenesis share most of the signalling cascades and gene regulatory networks. -
Responses of Bats to White-Nose Syndrome and Implications for Conservation
University of New Hampshire University of New Hampshire Scholars' Repository Doctoral Dissertations Student Scholarship Spring 2020 Responses of Bats to White-Nose Syndrome and Implications for Conservation Meghan Stark University of New Hampshire, Durham Follow this and additional works at: https://scholars.unh.edu/dissertation Recommended Citation Stark, Meghan, "Responses of Bats to White-Nose Syndrome and Implications for Conservation" (2020). Doctoral Dissertations. 2518. https://scholars.unh.edu/dissertation/2518 This Dissertation is brought to you for free and open access by the Student Scholarship at University of New Hampshire Scholars' Repository. It has been accepted for inclusion in Doctoral Dissertations by an authorized administrator of University of New Hampshire Scholars' Repository. For more information, please contact [email protected]. RESPONSES OF BATS TO WHITE-NOSE SYNDROME AND IMPLICATIONS FOR CONSERVATION BY MEGHAN A. STARK B.S., University of Alabama at Birmingham, 2013 DISSERTATION Submitted to the University of New Hampshire in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy In Genetics May 2020 i This dissertation was examined and approved in partial fulfillment of the requirements for the degree of Ph.D. in Genetics by: Dissertation Director, Matthew MacManes, Assoc. Prof. UNH MCBS Jeffrey T. Foster, Associate Professor, NAU PMI W. Kelley Thomas, Professor, UNH MCBS Rebecca Rowe, Associate Professor, UNH NREN Thomas Lee, Associate Professor Emeritus, UNH NREN On April 6, 2020 Approval signatures are on file with the University of New Hampshire Graduate School. ii DEDICATION I dedicate this work to all of the strong women in my life: Myra Michele Ange Heather Michelle Coons Kaitlyn Danielle Cagle Brindlee Michelle Coons Patricia Gail Miller Sarah Jean Lane “Here’s to strong women. -
Efficacy and Mechanistic Evaluation of Tic10, a Novel Antitumor Agent
University of Pennsylvania ScholarlyCommons Publicly Accessible Penn Dissertations 2012 Efficacy and Mechanisticv E aluation of Tic10, A Novel Antitumor Agent Joshua Edward Allen University of Pennsylvania, [email protected] Follow this and additional works at: https://repository.upenn.edu/edissertations Part of the Oncology Commons Recommended Citation Allen, Joshua Edward, "Efficacy and Mechanisticv E aluation of Tic10, A Novel Antitumor Agent" (2012). Publicly Accessible Penn Dissertations. 488. https://repository.upenn.edu/edissertations/488 This paper is posted at ScholarlyCommons. https://repository.upenn.edu/edissertations/488 For more information, please contact [email protected]. Efficacy and Mechanisticv E aluation of Tic10, A Novel Antitumor Agent Abstract TNF-related apoptosis-inducing ligand (TRAIL; Apo2L) is an endogenous protein that selectively induces apoptosis in cancer cells and is a critical effector in the immune surveillance of cancer. Recombinant TRAIL and TRAIL-agonist antibodies are in clinical trials for the treatment of solid malignancies due to the cancer-specific cytotoxicity of TRAIL. Recombinant TRAIL has a short serum half-life and both recombinant TRAIL and TRAIL receptor agonist antibodies have a limited capacity to perfuse to tissue compartments such as the brain, limiting their efficacy in certain malignancies. To overcome such limitations, we searched for small molecules capable of inducing the TRAIL gene using a high throughput luciferase reporter gene assay. We selected TRAIL-inducing compound 10 (TIC10) for further study based on its induction of TRAIL at the cell surface and its promising therapeutic index. TIC10 is a potent, stable, and orally active antitumor agent that crosses the blood-brain barrier and transcriptionally induces TRAIL and TRAIL-mediated cell death in a p53-independent manner. -
Overlap of Vitamin a and Vitamin D Target Genes with CAKUT- Related Processes [Version 1; Peer Review: 1 Approved with Reservations]
F1000Research 2021, 10:395 Last updated: 21 JUL 2021 BRIEF REPORT Overlap of vitamin A and vitamin D target genes with CAKUT- related processes [version 1; peer review: 1 approved with reservations] Ozan Ozisik1, Friederike Ehrhart 2,3, Chris T Evelo 2, Alberto Mantovani4, Anaı̈s Baudot 1,5 1Aix Marseille University, Inserm, MMG, Marseille, 13385, France 2Department of Bioinformatics - BiGCaT, Maastricht University, Maastricht, 6200 MD, The Netherlands 3Department of Bioinformatics, NUTRIM/MHeNs, Maastricht University, Maastricht, 6200 MD, The Netherlands 4Istituto Superiore di Sanità, Rome, 00161, Italy 5Barcelona Supercomputing Center (BSC), Barcelona, 08034, Spain v1 First published: 18 May 2021, 10:395 Open Peer Review https://doi.org/10.12688/f1000research.51018.1 Latest published: 18 May 2021, 10:395 https://doi.org/10.12688/f1000research.51018.1 Reviewer Status Invited Reviewers Abstract Congenital Anomalies of the Kidney and Urinary Tract (CAKUT) are a 1 group of abnormalities affecting the kidneys and their outflow tracts, which include the ureters, the bladder, and the urethra. CAKUT version 1 patients display a large clinical variability as well as a complex 18 May 2021 report aetiology, as only 5% to 20% of the cases have a monogenic origin. It is thereby suspected that interactions of both genetic and 1. Elena Menegola, Università degli Studi di environmental factors contribute to the disease. Vitamins are among the environmental factors that are considered for CAKUT aetiology. In Milano, Milan, Italy this study, we collected vitamin A and vitamin D target genes and Any reports and responses or comments on the computed their overlap with CAKUT-related gene sets. -
Gene Knockdown of CENPA Reduces Sphere Forming Ability and Stemness of Glioblastoma Initiating Cells
Neuroepigenetics 7 (2016) 6–18 Contents lists available at ScienceDirect Neuroepigenetics journal homepage: www.elsevier.com/locate/nepig Gene knockdown of CENPA reduces sphere forming ability and stemness of glioblastoma initiating cells Jinan Behnan a,1, Zanina Grieg b,c,1, Mrinal Joel b,c, Ingunn Ramsness c, Biljana Stangeland a,b,⁎ a Department of Molecular Medicine, Institute of Basic Medical Sciences, The Medical Faculty, University of Oslo, Oslo, Norway b Norwegian Center for Stem Cell Research, Department of Immunology and Transfusion Medicine, Oslo University Hospital, Oslo, Norway c Vilhelm Magnus Laboratory for Neurosurgical Research, Institute for Surgical Research and Department of Neurosurgery, Oslo University Hospital, Oslo, Norway article info abstract Article history: CENPA is a centromere-associated variant of histone H3 implicated in numerous malignancies. However, the Received 20 May 2016 role of this protein in glioblastoma (GBM) has not been demonstrated. GBM is one of the most aggressive Received in revised form 23 July 2016 human cancers. GBM initiating cells (GICs), contained within these tumors are deemed to convey Accepted 2 August 2016 characteristics such as invasiveness and resistance to therapy. Therefore, there is a strong rationale for targeting these cells. We investigated the expression of CENPA and other centromeric proteins (CENPs) in Keywords: fi CENPA GICs, GBM and variety of other cell types and tissues. Bioinformatics analysis identi ed the gene signature: fi Centromeric proteins high_CENP(AEFNM)/low_CENP(BCTQ) whose expression correlated with signi cantly worse GBM patient Glioblastoma survival. GBM Knockdown of CENPA reduced sphere forming ability, proliferation and cell viability of GICs. We also Brain tumor detected significant reduction in the expression of stemness marker SOX2 and the proliferation marker Glioblastoma initiating cells and therapeutic Ki67. -
Mediator of DNA Damage Checkpoint 1 (MDC1) Is a Novel Estrogen Receptor Co-Regulator in Invasive 6 Lobular Carcinoma of the Breast 7 8 Evelyn K
bioRxiv preprint doi: https://doi.org/10.1101/2020.12.16.423142; this version posted December 16, 2020. 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. 1 Running Title: MDC1 co-regulates ER in ILC 2 3 Research article 4 5 Mediator of DNA damage checkpoint 1 (MDC1) is a novel estrogen receptor co-regulator in invasive 6 lobular carcinoma of the breast 7 8 Evelyn K. Bordeaux1+, Joseph L. Sottnik1+, Sanjana Mehrotra1, Sarah E. Ferrara2, Andrew E. Goodspeed2,3, James 9 C. Costello2,3, Matthew J. Sikora1 10 11 +EKB and JLS contributed equally to this project. 12 13 Affiliations 14 1Dept. of Pathology, University of Colorado Anschutz Medical Campus 15 2Biostatistics and Bioinformatics Shared Resource, University of Colorado Comprehensive Cancer Center 16 3Dept. of Pharmacology, University of Colorado Anschutz Medical Campus 17 18 Corresponding author 19 Matthew J. Sikora, PhD.; Mail Stop 8104, Research Complex 1 South, Room 5117, 12801 E. 17th Ave.; Aurora, 20 CO 80045. Tel: (303)724-4301; Fax: (303)724-3712; email: [email protected]. Twitter: 21 @mjsikora 22 23 Authors' contributions 24 MJS conceived of the project. MJS, EKB, and JLS designed and performed experiments. JLS developed models 25 for the project. EKB, JLS, SM, and AEG contributed to data analysis and interpretation. SEF, AEG, and JCC 26 developed and performed informatics analyses. MJS wrote the draft manuscript; all authors read and revised the 27 manuscript and have read and approved of this version of the manuscript. -
Analysis and Characterisation of the Mouse Hic2 Gene
Aus dem Institut für Entwicklungsgenetik des GSF-Forschungszentrums für Umwelt und Gesundheit, GmbH Direktor: Prof. Dr. Wolfgang Wurst Anfertigung unter der Leitung von Prof. Dr. Jochen Graw Vorgelegt über den Lehrstuhl für Molekulare Tierzucht und Biotechnologie Der Tierärztlichen Fakultät der Ludwig-Maximilians-Universität München Vorstand: Prof. Dr. Eckhard Wolf Untersuchung und Charakterisierung des Hic2-Gens der Maus Inaugural-Dissertation Zur Erlangung der tiermedizinischen Doktorwürde der Tierärztlichen Fakultät der Ludwig-Maximilians-Universität München von Aleksandra Terzic aus Sarajevo/Bosnia und Herzegowina München 2004 II Aus dem Institut für Entwicklungsgenetik des GSF-Forschungszentrums für Umwelt und Gesundheit, GmbH Direktor: Prof. Dr. Wolfgang Wurst Anfertigung unter der Leitung von Prof. Dr. Jochen Graw Vorgelegt über den Lehrstuhl für Molekulare Tierzucht und Biotechnologie Der Tierärztlichen Fakultät der Ludwig-Maximilians-Universität München Vorstand: Prof. Dr. Eckhard Wolf Analysis and characterisation of the mouse Hic2 gene Inaugural-Dissertation Zur Erlangung der tiermedizinischen Doktorwürde der Tierärztlichen Fakultät der Ludwig-Maximilians-Universität München von Aleksandra Terzic aus Sarajevo/Bosnia und Herzegowina München 2004 III Gedruckt mit Genehmigung der Tierärztlichen Fakultät der Ludwig-Maximilians-Universität München Dekan: Univ.-Prof. Dr. A.Stolle Referent: Univ.-Prof. Dr. E. Wolf Korreferent: Univ.-Prof. Dr. K. Heinritzi Tag der Promotion: 13. Februar 2004 IV List of contents 1 INTRODUCTION.............................................................................................................1 -
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. -
Supplementary Table 3 Complete List of RNA-Sequencing Analysis of Gene Expression Changed by ≥ Tenfold Between Xenograft and Cells Cultured in 10%O2
Supplementary Table 3 Complete list of RNA-Sequencing analysis of gene expression changed by ≥ tenfold between xenograft and cells cultured in 10%O2 Expr Log2 Ratio Symbol Entrez Gene Name (culture/xenograft) -7.182 PGM5 phosphoglucomutase 5 -6.883 GPBAR1 G protein-coupled bile acid receptor 1 -6.683 CPVL carboxypeptidase, vitellogenic like -6.398 MTMR9LP myotubularin related protein 9-like, pseudogene -6.131 SCN7A sodium voltage-gated channel alpha subunit 7 -6.115 POPDC2 popeye domain containing 2 -6.014 LGI1 leucine rich glioma inactivated 1 -5.86 SCN1A sodium voltage-gated channel alpha subunit 1 -5.713 C6 complement C6 -5.365 ANGPTL1 angiopoietin like 1 -5.327 TNN tenascin N -5.228 DHRS2 dehydrogenase/reductase 2 leucine rich repeat and fibronectin type III domain -5.115 LRFN2 containing 2 -5.076 FOXO6 forkhead box O6 -5.035 ETNPPL ethanolamine-phosphate phospho-lyase -4.993 MYO15A myosin XVA -4.972 IGF1 insulin like growth factor 1 -4.956 DLG2 discs large MAGUK scaffold protein 2 -4.86 SCML4 sex comb on midleg like 4 (Drosophila) Src homology 2 domain containing transforming -4.816 SHD protein D -4.764 PLP1 proteolipid protein 1 -4.764 TSPAN32 tetraspanin 32 -4.713 N4BP3 NEDD4 binding protein 3 -4.705 MYOC myocilin -4.646 CLEC3B C-type lectin domain family 3 member B -4.646 C7 complement C7 -4.62 TGM2 transglutaminase 2 -4.562 COL9A1 collagen type IX alpha 1 chain -4.55 SOSTDC1 sclerostin domain containing 1 -4.55 OGN osteoglycin -4.505 DAPL1 death associated protein like 1 -4.491 C10orf105 chromosome 10 open reading frame 105 -4.491 -
Figure S1. Representative Report Generated by the Ion Torrent System Server for Each of the KCC71 Panel Analysis and Pcafusion Analysis
Figure S1. Representative report generated by the Ion Torrent system server for each of the KCC71 panel analysis and PCaFusion analysis. (A) Details of the run summary report followed by the alignment summary report for the KCC71 panel analysis sequencing. (B) Details of the run summary report for the PCaFusion panel analysis. A Figure S1. Continued. Representative report generated by the Ion Torrent system server for each of the KCC71 panel analysis and PCaFusion analysis. (A) Details of the run summary report followed by the alignment summary report for the KCC71 panel analysis sequencing. (B) Details of the run summary report for the PCaFusion panel analysis. B Figure S2. Comparative analysis of the variant frequency found by the KCC71 panel and calculated from publicly available cBioPortal datasets. For each of the 71 genes in the KCC71 panel, the frequency of variants was calculated as the variant number found in the examined cases. Datasets marked with different colors and sample numbers of prostate cancer are presented in the upper right. *Significantly high in the present study. Figure S3. Seven subnetworks extracted from each of seven public prostate cancer gene networks in TCNG (Table SVI). Blue dots represent genes that include initial seed genes (parent nodes), and parent‑child and child‑grandchild genes in the network. Graphical representation of node‑to‑node associations and subnetwork structures that differed among and were unique to each of the seven subnetworks. TCNG, The Cancer Network Galaxy. Figure S4. REVIGO tree map showing the predicted biological processes of prostate cancer in the Japanese. Each rectangle represents a biological function in terms of a Gene Ontology (GO) term, with the size adjusted to represent the P‑value of the GO term in the underlying GO term database. -
PDF Output of CLIC (Clustering by Inferred Co-Expression)
PDF Output of CLIC (clustering by inferred co-expression) Dataset: Num of genes in input gene set: 13 Total number of genes: 16493 CLIC PDF output has three sections: 1) Overview of Co-Expression Modules (CEMs) Heatmap shows pairwise correlations between all genes in the input query gene set. Red lines shows the partition of input genes into CEMs, ordered by CEM strength. Each row shows one gene, and the brightness of squares indicates its correlations with other genes. Gene symbols are shown at left side and on the top of the heatmap. 2) Details of each CEM and its expansion CEM+ Top panel shows the posterior selection probability (dataset weights) for top GEO series datasets. Bottom panel shows the CEM genes (blue rows) as well as expanded CEM+ genes (green rows). Each column is one GEO series dataset, sorted by their posterior probability of being selected. The brightness of squares indicates the gene's correlations with CEM genes in the corresponding dataset. CEM+ includes genes that co-express with CEM genes in high-weight datasets, measured by LLR score. 3) Details of each GEO series dataset and its expression profile: Top panel shows the detailed information (e.g. title, summary) for the GEO series dataset. Bottom panel shows the background distribution and the expression profile for CEM genes in this dataset. Overview of Co-Expression Modules (CEMs) with Dataset Weighting Scale of average Pearson correlations Num of Genes in Query Geneset: 13. Num of CEMs: 1. 0.0 0.2 0.4 0.6 0.8 1.0 Cenpk Cenph Cenpp Cenpu Cenpn Cenpq Cenpl Apitd1