A Bayesian Approach for Learning Gene Networks Underlying Disease Severity in COPD
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Analysis of Trans Esnps Infers Regulatory Network Architecture
Analysis of trans eSNPs infers regulatory network architecture Anat Kreimer Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Graduate School of Arts and Sciences COLUMBIA UNIVERSITY 2014 © 2014 Anat Kreimer All rights reserved ABSTRACT Analysis of trans eSNPs infers regulatory network architecture Anat Kreimer eSNPs are genetic variants associated with transcript expression levels. The characteristics of such variants highlight their importance and present a unique opportunity for studying gene regulation. eSNPs affect most genes and their cell type specificity can shed light on different processes that are activated in each cell. They can identify functional variants by connecting SNPs that are implicated in disease to a molecular mechanism. Examining eSNPs that are associated with distal genes can provide insights regarding the inference of regulatory networks but also presents challenges due to the high statistical burden of multiple testing. Such association studies allow: simultaneous investigation of many gene expression phenotypes without assuming any prior knowledge and identification of unknown regulators of gene expression while uncovering directionality. This thesis will focus on such distal eSNPs to map regulatory interactions between different loci and expose the architecture of the regulatory network defined by such interactions. We develop novel computational approaches and apply them to genetics-genomics data in human. We go beyond pairwise interactions to define network motifs, including regulatory modules and bi-fan structures, showing them to be prevalent in real data and exposing distinct attributes of such arrangements. We project eSNP associations onto a protein-protein interaction network to expose topological properties of eSNPs and their targets and highlight different modes of distal regulation. -
The Genomic Structure and Expression of MJD, the Machado-Joseph Disease Gene
J Hum Genet (2001) 46:413–422 © Jpn Soc Hum Genet and Springer-Verlag 2001 ORIGINAL ARTICLE Yaeko Ichikawa · Jun Goto · Masahira Hattori Atsushi Toyoda · Kazuo Ishii · Seon-Yong Jeong Hideji Hashida · Naoki Masuda · Katsuhisa Ogata Fumio Kasai · Momoki Hirai · Patrícia Maciel Guy A. Rouleau · Yoshiyuki Sakaki · Ichiro Kanazawa The genomic structure and expression of MJD, the Machado-Joseph disease gene Received: March 7, 2001 / Accepted: April 17, 2001 Abstract Machado-Joseph disease (MJD) is an autosomal relative to the MJD gene in B445M7 indicate that there are dominant neurodegenerative disorder that is clinically char- three alternative splicing sites and eight polyadenylation acterized by cerebellar ataxia and various associated symp- signals in MJD that are used to generate the differently toms. The disease is caused by an unstable expansion of the sized transcripts. CAG repeat in the MJD gene. This gene is mapped to chromosome 14q32.1. To determine its genomic structure, Key words Machado-Joseph disease (MJD) · 14q32.1 · we constructed a contig composed of six cosmid clones and CAG repeat · Genome structure · Alternative splicing · eight bacterial artificial chromosome (BAC) clones. It spans mRNA expression approximately 300kb and includes MJD. We also deter- mined the complete sequence (175,330bp) of B445M7, a human BAC clone that contains MJD. The MJD gene was found to span 48,240bp and to contain 11 exons. Northern Introduction blot analysis showed that MJD mRNA is ubiquitously expressed in human tissues, and in at least four different Machado-Joseph disease (MJD) is an autosomal dominant sizes; namely, 1.4, 1.8, 4.5, and 7.5kb. -
Long Noncoding Intronic Rnas Are Differentially Expressed in Primary
Tahira et al. Molecular Cancer 2011, 10:141 http://www.molecular-cancer.com/content/10/1/141 RESEARCH Open Access Long noncoding intronic RNAs are differentially expressed in primary and metastatic pancreatic cancer Ana C Tahira1, Márcia S Kubrusly2, Michele F Faria1, Bianca Dazzani1, Rogério S Fonseca1, Vinicius Maracaja-Coutinho1, Sergio Verjovski-Almeida1, Marcel CC Machado2 and Eduardo M Reis1* Abstract Background: Pancreatic ductal adenocarcinoma (PDAC) is known by its aggressiveness and lack of effective therapeutic options. Thus, improvement in current knowledge of molecular changes associated with pancreatic cancer is urgently needed to explore novel venues of diagnostics and treatment of this dismal disease. While there is mounting evidence that long noncoding RNAs (lncRNAs) transcribed from intronic and intergenic regions of the human genome may play different roles in the regulation of gene expression in normal and cancer cells, their expression pattern and biological relevance in pancreatic cancer is currently unknown. In the present work we investigated the relative abundance of a collection of lncRNAs in patients’ pancreatic tissue samples aiming at identifying gene expression profiles correlated to pancreatic cancer and metastasis. Methods: Custom 3,355-element spotted cDNA microarray interrogating protein-coding genes and putative lncRNA were used to obtain expression profiles from 38 clinical samples of tumor and non-tumor pancreatic tissues. Bioinformatics analyses were performed to characterize structure and conservation of lncRNAs expressed in pancreatic tissues, as well as to identify expression signatures correlated to tissue histology. Strand-specific reverse transcription followed by PCR and qRT-PCR were employed to determine strandedness of lncRNAs and to validate microarray results, respectively. -
Cdipt Mouse Shrna Plasmid (Locus ID 52858) – TL502924 | Origene
OriGene Technologies, Inc. 9620 Medical Center Drive, Ste 200 Rockville, MD 20850, US Phone: +1-888-267-4436 [email protected] EU: [email protected] CN: [email protected] Product datasheet for TL502924 Cdipt Mouse shRNA Plasmid (Locus ID 52858) Product data: Product Type: shRNA Plasmids Product Name: Cdipt Mouse shRNA Plasmid (Locus ID 52858) Locus ID: 52858 Synonyms: 9530042F15Rik; D7Bwg0575e; Pis; Pis1 Vector: pGFP-C-shLenti (TR30023) Format: Lentiviral plasmids Components: Cdipt - Mouse, 4 unique 29mer shRNA constructs in lentiviral GFP vector(Gene ID = 52858). 5µg purified plasmid DNA per construct Non-effective 29-mer scrambled shRNA cassette in pGFP-C-shLenti Vector, TR30021, included for free. RefSeq: BC021473, BC024413, BC032182, NM_001347656, NM_026638, NM_138754, NM_026638.1, NM_026638.2, NM_026638.3, NM_026638.4 Summary: Catalyzes the biosynthesis of phosphatidylinositol (PtdIns) as well as PtdIns:inositol exchange reaction. May thus act to reduce an excessive cellular PtdIns content. The exchange activity is due to the reverse reaction of PtdIns synthase and is dependent on CMP, which is tightly bound to the enzyme (By similarity).[UniProtKB/Swiss-Prot Function] shRNA Design: These shRNA constructs were designed against multiple splice variants at this gene locus. To be certain that your variant of interest is targeted, please contact [email protected]. If you need a special design or shRNA sequence, please utilize our custom shRNA service. This product is to be used for laboratory only. Not for diagnostic or therapeutic use. View online » ©2021 OriGene Technologies, Inc., 9620 Medical Center Drive, Ste 200, Rockville, MD 20850, US 1 / 2 Cdipt Mouse shRNA Plasmid (Locus ID 52858) – TL502924 Performance OriGene guarantees that the sequences in the shRNA expression cassettes are verified to Guaranteed: correspond to the target gene with 100% identity. -
Supplementary Information Integrative Analyses of Splicing in the Aging Brain: Role in Susceptibility to Alzheimer’S Disease
Supplementary Information Integrative analyses of splicing in the aging brain: role in susceptibility to Alzheimer’s Disease Contents 1. Supplementary Notes 1.1. Religious Orders Study and Memory and Aging Project 1.2. Mount Sinai Brain Bank Alzheimer’s Disease 1.3. CommonMind Consortium 1.4. Data Availability 2. Supplementary Tables 3. Supplementary Figures Note: Supplementary Tables are provided as separate Excel files. 1. Supplementary Notes 1.1. Religious Orders Study and Memory and Aging Project Gene expression data1. Gene expression data were generated using RNA- sequencing from Dorsolateral Prefrontal Cortex (DLPFC) of 540 individuals, at an average sequence depth of 90M reads. Detailed description of data generation and processing was previously described2 (Mostafavi, Gaiteri et al., under review). Samples were submitted to the Broad Institute’s Genomics Platform for transcriptome analysis following the dUTP protocol with Poly(A) selection developed by Levin and colleagues3. All samples were chosen to pass two initial quality filters: RNA integrity (RIN) score >5 and quantity threshold of 5 ug (and were selected from a larger set of 724 samples). Sequencing was performed on the Illumina HiSeq with 101bp paired-end reads and achieved coverage of 150M reads of the first 12 samples. These 12 samples will serve as a deep coverage reference and included 2 males and 2 females of nonimpaired, mild cognitive impaired, and Alzheimer's cases. The remaining samples were sequenced with target coverage of 50M reads; the mean coverage for the samples passing QC is 95 million reads (median 90 million reads). The libraries were constructed and pooled according to the RIN scores such that similar RIN scores would be pooled together. -
Dual Proteome-Scale Networks Reveal Cell-Specific Remodeling of the Human Interactome
bioRxiv preprint doi: https://doi.org/10.1101/2020.01.19.905109; this version posted January 19, 2020. 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. Dual Proteome-scale Networks Reveal Cell-specific Remodeling of the Human Interactome Edward L. Huttlin1*, Raphael J. Bruckner1,3, Jose Navarrete-Perea1, Joe R. Cannon1,4, Kurt Baltier1,5, Fana Gebreab1, Melanie P. Gygi1, Alexandra Thornock1, Gabriela Zarraga1,6, Stanley Tam1,7, John Szpyt1, Alexandra Panov1, Hannah Parzen1,8, Sipei Fu1, Arvene Golbazi1, Eila Maenpaa1, Keegan Stricker1, Sanjukta Guha Thakurta1, Ramin Rad1, Joshua Pan2, David P. Nusinow1, Joao A. Paulo1, Devin K. Schweppe1, Laura Pontano Vaites1, J. Wade Harper1*, Steven P. Gygi1*# 1Department of Cell Biology, Harvard Medical School, Boston, MA, 02115, USA. 2Broad Institute, Cambridge, MA, 02142, USA. 3Present address: ICCB-Longwood Screening Facility, Harvard Medical School, Boston, MA, 02115, USA. 4Present address: Merck, West Point, PA, 19486, USA. 5Present address: IQ Proteomics, Cambridge, MA, 02139, USA. 6Present address: Vor Biopharma, Cambridge, MA, 02142, USA. 7Present address: Rubius Therapeutics, Cambridge, MA, 02139, USA. 8Present address: RPS North America, South Kingstown, RI, 02879, USA. *Correspondence: [email protected] (E.L.H.), [email protected] (J.W.H.), [email protected] (S.P.G.) #Lead Contact: [email protected] bioRxiv preprint doi: https://doi.org/10.1101/2020.01.19.905109; this version posted January 19, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. -
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. -
Novel Insights Into Autophagy from Multicellular Model Systems
Feature Review Eaten alive: novel insights into autophagy from multicellular model systems 1 2 Hong Zhang and Eric H. Baehrecke 1 Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China 2 Department of Molecular, Cell, and Cancer Biology, University of Massachusetts Medical School, Worcester, MA 01605, USA Autophagy delivers cytoplasmic material to lysosomes are essential for autophagosome formation [7,8]. Remark- for degradation. First identified in yeast, the core genes ably, the core autophagy machinery that is encoded by that control this process are conserved in higher organ- these genes is conserved between yeast and humans isms. Studies of mammalian cell cultures have expanded [6]. Many studies of immortalized mammalian cell lines our understanding of the core autophagy pathway, but indicate that, as in yeast, nutrient-limiting conditions cannot reveal the unique animal-specific mechanisms induce autophagy that is dependent on ATG genes. How- for the regulation and function of autophagy. Multicel- ever, several aspects of the autophagy pathway in higher lular organisms have different types of cells that possess eukaryotes are distinct from that in yeast. In yeast, all distinct composition, morphology, and organization of autophagosomes arise from the single perivacuolar preau- intracellular organelles. In addition, the autophagic ma- tophagosomal structure (PAS). In higher eukaryotes, there chinery integrates signals from other cells and environ- is no evidence for a PAS and isolation membranes can be mental conditions to maintain cell, tissue and organism generated simultaneously at multiple sites, implicating homeostasis. Here, we highlight how studies of autop- more complex sources for autophagosomal membranes. hagy in flies and worms have identified novel core Indeed, the endoplasmic reticulum (ER), mitochondria, autophagy genes and mechanisms, and provided insight plasma membrane, and recycling endosomes have been into the context-specific regulation and function of shown to contribute to autophagosomal membranes autophagy. -
COX17 (NM 005694) Human Tagged ORF Clone Product Data
OriGene Technologies, Inc. 9620 Medical Center Drive, Ste 200 Rockville, MD 20850, US Phone: +1-888-267-4436 [email protected] EU: [email protected] CN: [email protected] Product datasheet for RC210756 COX17 (NM_005694) Human Tagged ORF Clone Product data: Product Type: Expression Plasmids Product Name: COX17 (NM_005694) Human Tagged ORF Clone Tag: Myc-DDK Symbol: COX17 Vector: pCMV6-Entry (PS100001) E. coli Selection: Kanamycin (25 ug/mL) Cell Selection: Neomycin ORF Nucleotide >RC210756 representing NM_005694 Sequence: Red=Cloning site Blue=ORF Green=Tags(s) TTTTGTAATACGACTCACTATAGGGCGGCCGGGAATTCGTCGACTGGATCCGGTACCGAGGAGATCTGCC GCCGCGATCGCC ATGCCGGGTCTGGTTGACTCAAACCCTGCCCCGCCTGAGTCTCAGGAGAAGAAGCCGCTGAAGCCCTGCT GCGCTTGCCCGGAGACCAAGAAGGCGCGCGATGCGTGTATCATCGAGAAAGGAGAAGAACACTGTGGACA TCTAATTGAGGCCCACAAGGAATGCATGAGAGCCCTAGGATTTAAAATA ACGCGTACGCGGCCGCTCGAGCAGAAACTCATCTCAGAAGAGGATCTGGCAGCAAATGATATCCTGGATT ACAAGGATGACGACGATAAGGTTTAA Protein Sequence: >RC210756 representing NM_005694 Red=Cloning site Green=Tags(s) MPGLVDSNPAPPESQEKKPLKPCCACPETKKARDACIIEKGEEHCGHLIEAHKECMRALGFKI TRTRPLEQKLISEEDLAANDILDYKDDDDKV Chromatograms: https://cdn.origene.com/chromatograms/mk8114_f02.zip Restriction Sites: SgfI-MluI This product is to be used for laboratory only. Not for diagnostic or therapeutic use. View online » ©2021 OriGene Technologies, Inc., 9620 Medical Center Drive, Ste 200, Rockville, MD 20850, US 1 / 4 COX17 (NM_005694) Human Tagged ORF Clone – RC210756 Cloning Scheme: Plasmid Map: ACCN: NM_005694 ORF Size: 189 bp This product is -
Advancing a Clinically Relevant Perspective of the Clonal Nature of Cancer
Advancing a clinically relevant perspective of the clonal nature of cancer Christian Ruiza,b, Elizabeth Lenkiewicza, Lisa Eversa, Tara Holleya, Alex Robesona, Jeffrey Kieferc, Michael J. Demeurea,d, Michael A. Hollingsworthe, Michael Shenf, Donna Prunkardf, Peter S. Rabinovitchf, Tobias Zellwegerg, Spyro Moussesc, Jeffrey M. Trenta,h, John D. Carpteni, Lukas Bubendorfb, Daniel Von Hoffa,d, and Michael T. Barretta,1 aClinical Translational Research Division, Translational Genomics Research Institute, Scottsdale, AZ 85259; bInstitute for Pathology, University Hospital Basel, University of Basel, 4031 Basel, Switzerland; cGenetic Basis of Human Disease, Translational Genomics Research Institute, Phoenix, AZ 85004; dVirginia G. Piper Cancer Center, Scottsdale Healthcare, Scottsdale, AZ 85258; eEppley Institute for Research in Cancer and Allied Diseases, Nebraska Medical Center, Omaha, NE 68198; fDepartment of Pathology, University of Washington, Seattle, WA 98105; gDivision of Urology, St. Claraspital and University of Basel, 4058 Basel, Switzerland; hVan Andel Research Institute, Grand Rapids, MI 49503; and iIntegrated Cancer Genomics Division, Translational Genomics Research Institute, Phoenix, AZ 85004 Edited* by George F. Vande Woude, Van Andel Research Institute, Grand Rapids, MI, and approved June 10, 2011 (received for review March 11, 2011) Cancers frequently arise as a result of an acquired genomic insta- on the basis of morphology alone (8). Thus, the application of bility and the subsequent clonal evolution of neoplastic cells with purification methods such as laser capture microdissection does variable patterns of genetic aberrations. Thus, the presence and not resolve the complexities of many samples. A second approach behaviors of distinct clonal populations in each patient’s tumor is to passage tumor biopsies in tissue culture or in xenografts (4, 9– may underlie multiple clinical phenotypes in cancers. -
Guidelines for the Use and Interpretation of Assays for Monitoring Autophagy (3Rd Edition)
AUTOPHAGY 2016, VOL. 12, NO. 1, 1–222 http://dx.doi.org/10.1080/15548627.2015.1100356 EDITORIAL Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition) Daniel J Klionsky1745,1749*, Kotb Abdelmohsen840, Akihisa Abe1237, Md Joynal Abedin1762, Hagai Abeliovich425, Abraham Acevedo Arozena789, Hiroaki Adachi1800, Christopher M Adams1669, Peter D Adams57, Khosrow Adeli1981, Peter J Adhihetty1625, Sharon G Adler700, Galila Agam67, Rajesh Agarwal1587, Manish K Aghi1537, Maria Agnello1826, Patrizia Agostinis664, Patricia V Aguilar1960, Julio Aguirre-Ghiso784,786, Edoardo M Airoldi89,422, Slimane Ait-Si-Ali1376, Takahiko Akematsu2010, Emmanuel T Akporiaye1097, Mohamed Al-Rubeai1394, Guillermo M Albaiceta1294, Chris Albanese363, Diego Albani561, Matthew L Albert517, Jesus Aldudo128, Hana Algul€ 1164, Mehrdad Alirezaei1198, Iraide Alloza642,888, Alexandru Almasan206, Maylin Almonte-Beceril524, Emad S Alnemri1212, Covadonga Alonso544, Nihal Altan-Bonnet848, Dario C Altieri1205, Silvia Alvarez1497, Lydia Alvarez-Erviti1395, Sandro Alves107, Giuseppina Amadoro860, Atsuo Amano930, Consuelo Amantini1554, Santiago Ambrosio1458, Ivano Amelio756, Amal O Amer918, Mohamed Amessou2089, Angelika Amon726, Zhenyi An1538, Frank A Anania291, Stig U Andersen6, Usha P Andley2079, Catherine K Andreadi1690, Nathalie Andrieu-Abadie502, Alberto Anel2027, David K Ann58, Shailendra Anoopkumar-Dukie388, Manuela Antonioli832,858, Hiroshi Aoki1791, Nadezda Apostolova2007, Saveria Aquila1500, Katia Aquilano1876, Koichi Araki292, Eli Arama2098, -
Systematic Data-Querying of Large Pediatric Biorepository Identifies Novel Ehlers-Danlos Syndrome Variant Akshatha Desai1, John J
Desai et al. BMC Musculoskeletal Disorders (2016) 17:80 DOI 10.1186/s12891-016-0936-8 RESEARCH ARTICLE Open Access Systematic data-querying of large pediatric biorepository identifies novel Ehlers-Danlos Syndrome variant Akshatha Desai1, John J. Connolly1, Michael March1, Cuiping Hou1, Rosetta Chiavacci1, Cecilia Kim1, Gholson Lyon1, Dexter Hadley1 and Hakon Hakonarson1,2* Abstract Background: Ehlers Danlos Syndrome is a rare form of inherited connective tissue disorder, which primarily affects skin, joints, muscle, and blood cells. The current study aimed at finding the mutation that causing EDS type VII C also known as “Dermatosparaxis” in this family. Methods: Through systematic data querying of the electronic medical records (EMRs) of over 80,000 individuals, we recently identified an EDS family that indicate an autosomal dominant inheritance. The family was consented for genomic analysis of their de-identified data. After a negative screen for known mutations, we performed whole genome sequencing on the male proband, his affected father, and unaffected mother. We filtered the list of non- synonymous variants that are common between the affected individuals. Results: The analysis of non-synonymous variants lead to identifying a novel mutation in the ADAMTSL2 (p. Gly421Ser) gene in the affected individuals. Sanger sequencing confirmed the mutation. Conclusion: Our work is significant not only because it sheds new light on the pathophysiology of EDS for the affected family and the field at large, but also because it demonstrates the utility of unbiased large-scale clinical recruitment in deciphering the genetic etiology of rare mendelian diseases. With unbiased large-scale clinical recruitment we strive to sequence as many rare mendelian diseases as possible, and this work in EDS serves as a successful proof of concept to that effect.