Identification of Differentially Expressed Genes and Pathways for Intramuscular Fat Deposition in Pectoralis Major Tissues of Fa
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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. -
Genome Analysis and Knowledge
Dahary et al. BMC Medical Genomics (2019) 12:200 https://doi.org/10.1186/s12920-019-0647-8 SOFTWARE Open Access Genome analysis and knowledge-driven variant interpretation with TGex Dvir Dahary1*, Yaron Golan1, Yaron Mazor1, Ofer Zelig1, Ruth Barshir2, Michal Twik2, Tsippi Iny Stein2, Guy Rosner3,4, Revital Kariv3,4, Fei Chen5, Qiang Zhang5, Yiping Shen5,6,7, Marilyn Safran2, Doron Lancet2* and Simon Fishilevich2* Abstract Background: The clinical genetics revolution ushers in great opportunities, accompanied by significant challenges. The fundamental mission in clinical genetics is to analyze genomes, and to identify the most relevant genetic variations underlying a patient’s phenotypes and symptoms. The adoption of Whole Genome Sequencing requires novel capacities for interpretation of non-coding variants. Results: We present TGex, the Translational Genomics expert, a novel genome variation analysis and interpretation platform, with remarkable exome analysis capacities and a pioneering approach of non-coding variants interpretation. TGex’s main strength is combining state-of-the-art variant filtering with knowledge-driven analysis made possible by VarElect, our highly effective gene-phenotype interpretation tool. VarElect leverages the widely used GeneCards knowledgebase, which integrates information from > 150 automatically-mined data sources. Access to such a comprehensive data compendium also facilitates TGex’s broad variant annotation, supporting evidence exploration, and decision making. TGex has an interactive, user-friendly, and easy adaptive interface, ACMG compliance, and an automated reporting system. Beyond comprehensive whole exome sequence capabilities, TGex encompasses innovative non-coding variants interpretation, towards the goal of maximal exploitation of whole genome sequence analyses in the clinical genetics practice. This is enabled by GeneCards’ recently developed GeneHancer, a novel integrative and fully annotated database of human enhancers and promoters. -
Sarcomeric Deficits Underlie MYBPC1-Associated Myopathy with Myogenic Tremor
Sarcomeric deficits underlie MYBPC1-associated myopathy with myogenic tremor Janelle Geist Hauserman, … , Christopher Ward, Aikaterini Kontrogianni- Konstantopoulos JCI Insight. 2021. https://doi.org/10.1172/jci.insight.147612. Research In-Press Preview Cell biology Muscle biology Myosin Binding Protein-C slow (sMyBP-C) comprises a subfamily of cytoskeletal proteins encoded byM YBPC1 that is expressed in skeletal muscles where it contributes to myosin thick filament stabilization and actomyosin cross-bridge regulation. Recently, our group described the causal association of dominant missense pathogenic variants in MYBPC1 with an early-onset myopathy characterized by generalized muscle weakness, hypotonia, dysmorphia, skeletal deformities, and myogenic tremor occurring in the absence of neuropathy. To mechanistically interrogate the etiologies of this MYBPC1-associated myopathy in vivo, we generated a knock-in mouse model carrying the E248K pathogenic variant. Using a battery of phenotypic, behavioral, and physiological measurements spanning neonatal to young adult life, we find that heterozygous E248K mice faithfully recapitulate the onset and progression of generalized myopathy, tremor occurrence, and skeletal deformities seen in human carriers. Moreover, using a combination of biochemical, ultrastructural, and contractile assessments at the level of the tissue, cell, and myofilaments, we show that the loss-of- function phenotype observed in mutant muscles is primarily driven by disordered and misaligned sarcomeres containing fragmented -
Deciphering the Gene Expression Profile of Peroxisome Proliferator
Chen et al. J Transl Med (2016) 14:157 DOI 10.1186/s12967-016-0871-3 Journal of Translational Medicine RESEARCH Open Access Deciphering the gene expression profile of peroxisome proliferator‑activated receptor signaling pathway in the left atria of patients with mitral regurgitation Mien‑Cheng Chen1*, Jen‑Ping Chang2, Yu‑Sheng Lin3, Kuo‑Li Pan3, Wan‑Chun Ho1, Wen‑Hao Liu1, Tzu‑Hao Chang4, Yao‑Kuang Huang5, Chih‑Yuan Fang1 and Chien‑Jen Chen1 Abstract Background: Differentially expressed genes in the left atria of mitral regurgitation (MR) pigs have been linked to peroxisome proliferator-activated receptor (PPAR) signaling pathway in the KEGG pathway. However, specific genes of the PPAR signaling pathway in the left atria of MR patients have never been explored. Methods: This study enrolled 15 MR patients with heart failure, 7 patients with aortic valve disease and heart failure, and 6 normal controls. We used PCR assay (84 genes) for PPAR pathway and quantitative RT-PCR to study specific genes of the PPAR pathway in the left atria. Results: Gene expression profiling analysis through PCR assay identified 23 genes to be differentially expressed in the left atria of MR patients compared to normal controls. The expressions of APOA1, ACADM, FABP3, ETFDH, ECH1, CPT1B, CPT2, SLC27A6, ACAA2, SMARCD3, SORBS1, EHHADH, SLC27A1, PPARGC1B, PPARA and CPT1A were significantly up-regulated, whereas the expression of PLTP was significantly down-regulated in the MR patients compared to normal controls. The expressions of HMGCS2, ACADM, FABP3, MLYCD, ECH1, ACAA2, EHHADH, CPT1A and PLTP were significantly up-regulated in the MR patients compared to patients with aortic valve disease. -
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. -
Supplementary Table S4. FGA Co-Expressed Gene List in LUAD
Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase -
Multiple Acyl-Coa Dehydrogenase Deficiency with Variable
G C A T T A C G G C A T genes Article Multiple Acyl-CoA Dehydrogenase Deficiency with Variable Presentation Due to a Homozygous Mutation in a Bedouin Tribe Orna Staretz-Chacham 1,2,* , Shirly Amar 3, Shlomo Almashanu 4, Ben Pode-Shakked 5,6, Ann Saada 7,8 , Ohad Wormser 9 and Eli Hershkovitz 2,10 1 Metabolic Clinic, Pediatric Division, Soroka University Medical Center, Beer Sheva 84101, Israel 2 Faculty of Health Sciences, Ben-Gurion University, Beer Sheva 84101, Israel; [email protected] 3 Genetic Lab, Soroka University Medical Center, Beer Sheva 84101, Israel; [email protected] 4 National Newborn Screening Program, Ministry of Health, Tel-HaShomer, Ramat Gan 52621, Israel; [email protected] 5 Metabolic Disease Unit, Edmond and Lily Safra Children’s Hospital, Sheba Medical Center, Tel-Hashomer, Ramat Gan 52621, Israel; [email protected] 6 Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv 39040, Israel 7 Hadassah Medical Center, Department of Genetics, Jerusalem 911201, Israel; [email protected] 8 Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem 911201, Israel 9 The Morris Kahn Laboratory of Human Genetics, National Institute for Biotechnology in the Negev and Faculty of Health Sciences, Ben Gurion University of the Negev, Beer Sheva 84101, Israel; [email protected] 10 Department of Pediatrics D, Soroka Medical Center, Beer Sheva 84101, Israel * Correspondence: [email protected]; Tel.: +972-545-713-191 Abstract: Multiple acyl-CoA dehydrogenase deficiency (MADD) is a fatty acid and amino acid Citation: Staretz-Chacham, O.; Amar, oxidation defect caused by a deficiency of the electron-transfer flavoprotein (ETF) or the electron- S.; Almashanu, S.; Pode-Shakked, B.; transfer flavoprotein dehydrogenase (ETFDH). -
Resveratrol Regulates Mitochondrial Reactive Oxygen Species Homeostasis Through Sirt3 Signaling Pathway in Human Vascular Endothelial Cells
Citation: Cell Death and Disease (2014) 5, e1576; doi:10.1038/cddis.2014.530 OPEN & 2014 Macmillan Publishers Limited All rights reserved 2041-4889/14 www.nature.com/cddis Resveratrol regulates mitochondrial reactive oxygen species homeostasis through Sirt3 signaling pathway in human vascular endothelial cells X Zhou1, M Chen1, X Zeng1, J Yang1, H Deng1, L Yi*,1 and M-t Mi*,1 Mitochondrial reactive oxygen species (mtROS) homeostasis plays an essential role in preventing oxidative injury in endothelial cells, an initial step in atherogenesis. Resveratrol (RSV) possesses a variety of cardioprotective activities, however, little is known regarding the effects of RSV on mtROS homeostasis in endothelial cells. Sirt3 is a mitochondrial deacetylase, which plays a key role in mitochondrial bioenergetics and is closely associated with oxidative stress. The goal of the study is to investigate whether RSV could attenuate oxidative injury in endothelial cells via mtROS homeostasis regulation through Sirt3 signaling pathway. We found that pretreatment with RSV suppressed tert-butyl hydroperoxide (t-BHP)-induced oxidative damage in human umbilical vein endothelial cells (HUVECs) by increasing cell viability, inhibiting cell apoptosis, repressing collapse of mitochondrial membrane potential and decreasing mtROS generation. Moreover, the enzymatic activities of isocitrate dehydrogenase 2 (IDH2), glutathione peroxidase (GSH-Px) and manganese superoxide dismutase (SOD2) as well as deacetylation of SOD2 were increased by RSV pretreatment, suggesting RSV notably enhanced mtROS scavenging in t-BHP-induced endothelial cells. Meanwhile, RSV remarkably reduced mtROS generation by promoting Sirt3 enrichment within the mitochondria and subsequent upregulation of forkhead box O3A (FoxO3A)-mediated mitochondria-encoded gene expression of ATP6, CO1, Cytb, ND2 and ND5, thereby leading to increased complex I activity and ATP synthesis. -
Whole Genome Sequencing of Familial Non-Medullary Thyroid Cancer Identifies Germline Alterations in MAPK/ERK and PI3K/AKT Signaling Pathways
biomolecules Article Whole Genome Sequencing of Familial Non-Medullary Thyroid Cancer Identifies Germline Alterations in MAPK/ERK and PI3K/AKT Signaling Pathways Aayushi Srivastava 1,2,3,4 , Abhishek Kumar 1,5,6 , Sara Giangiobbe 1, Elena Bonora 7, Kari Hemminki 1, Asta Försti 1,2,3 and Obul Reddy Bandapalli 1,2,3,* 1 Division of Molecular Genetic Epidemiology, German Cancer Research Center (DKFZ), D-69120 Heidelberg, Germany; [email protected] (A.S.); [email protected] (A.K.); [email protected] (S.G.); [email protected] (K.H.); [email protected] (A.F.) 2 Hopp Children’s Cancer Center (KiTZ), D-69120 Heidelberg, Germany 3 Division of Pediatric Neurooncology, German Cancer Research Center (DKFZ), German Cancer Consortium (DKTK), D-69120 Heidelberg, Germany 4 Medical Faculty, Heidelberg University, D-69120 Heidelberg, Germany 5 Institute of Bioinformatics, International Technology Park, Bangalore 560066, India 6 Manipal Academy of Higher Education (MAHE), Manipal, Karnataka 576104, India 7 S.Orsola-Malphigi Hospital, Unit of Medical Genetics, 40138 Bologna, Italy; [email protected] * Correspondence: [email protected]; Tel.: +49-6221-42-1709 Received: 29 August 2019; Accepted: 10 October 2019; Published: 13 October 2019 Abstract: Evidence of familial inheritance in non-medullary thyroid cancer (NMTC) has accumulated over the last few decades. However, known variants account for a very small percentage of the genetic burden. Here, we focused on the identification of common pathways and networks enriched in NMTC families to better understand its pathogenesis with the final aim of identifying one novel high/moderate-penetrance germline predisposition variant segregating with the disease in each studied family. -
Metabolic Targets of Coenzyme Q10 in Mitochondria
antioxidants Review Metabolic Targets of Coenzyme Q10 in Mitochondria Agustín Hidalgo-Gutiérrez 1,2,*, Pilar González-García 1,2, María Elena Díaz-Casado 1,2, Eliana Barriocanal-Casado 1,2, Sergio López-Herrador 1,2, Catarina M. Quinzii 3 and Luis C. López 1,2,* 1 Departamento de Fisiología, Facultad de Medicina, Universidad de Granada, 18016 Granada, Spain; [email protected] (P.G.-G.); [email protected] (M.E.D.-C.); [email protected] (E.B.-C.); [email protected] (S.L.-H.) 2 Centro de Investigación Biomédica, Instituto de Biotecnología, Universidad de Granada, 18016 Granada, Spain 3 Department of Neurology, Columbia University Medical Center, New York, NY 10032, USA; [email protected] * Correspondence: [email protected] (A.H.-G.); [email protected] (L.C.L.); Tel.: +34-958-241-000 (ext. 20197) (L.C.L.) Abstract: Coenzyme Q10 (CoQ10) is classically viewed as an important endogenous antioxidant and key component of the mitochondrial respiratory chain. For this second function, CoQ molecules seem to be dynamically segmented in a pool attached and engulfed by the super-complexes I + III, and a free pool available for complex II or any other mitochondrial enzyme that uses CoQ as a cofactor. This CoQ-free pool is, therefore, used by enzymes that link the mitochondrial respiratory chain to other pathways, such as the pyrimidine de novo biosynthesis, fatty acid β-oxidation and amino acid catabolism, glycine metabolism, proline, glyoxylate and arginine metabolism, and sulfide oxidation Citation: Hidalgo-Gutiérrez, A.; metabolism. Some of these mitochondrial pathways are also connected to metabolic pathways González-García, P.; Díaz-Casado, in other compartments of the cell and, consequently, CoQ could indirectly modulate metabolic M.E.; Barriocanal-Casado, E.; López-Herrador, S.; Quinzii, C.M.; pathways located outside the mitochondria. -
Mouse Mybpc1 Conditional Knockout Project (CRISPR/Cas9)
https://www.alphaknockout.com Mouse Mybpc1 Conditional Knockout Project (CRISPR/Cas9) Objective: To create a Mybpc1 conditional knockout Mouse model (C57BL/6J) by CRISPR/Cas-mediated genome engineering. Strategy summary: The Mybpc1 gene (NCBI Reference Sequence: NM_001252372 ; Ensembl: ENSMUSG00000020061 ) is located on Mouse chromosome 10. 29 exons are identified, with the ATG start codon in exon 1 and the TAG stop codon in exon 28 (Transcript: ENSMUST00000119185). Exon 3~4 will be selected as conditional knockout region (cKO region). Deletion of this region should result in the loss of function of the Mouse Mybpc1 gene. To engineer the targeting vector, homologous arms and cKO region will be generated by PCR using BAC clone RP23-408J20 as template. Cas9, gRNA and targeting vector will be co-injected into fertilized eggs for cKO Mouse production. The pups will be genotyped by PCR followed by sequencing analysis. Note: Exon 3 starts from about 1.83% of the coding region. The knockout of Exon 3~4 will result in frameshift of the gene. The size of intron 2 for 5'-loxP site insertion: 12130 bp, and the size of intron 4 for 3'-loxP site insertion: 863 bp. The size of effective cKO region: ~2510 bp. The cKO region does not have any other known gene. Page 1 of 8 https://www.alphaknockout.com Overview of the Targeting Strategy Wildtype allele 5' gRNA region gRNA region 3' 1 3 4 5 29 Targeting vector Targeted allele Constitutive KO allele (After Cre recombination) Legends Exon of mouse Mybpc1 Homology arm cKO region loxP site Page 2 of 8 https://www.alphaknockout.com Overview of the Dot Plot Window size: 10 bp Forward Reverse Complement Sequence 12 Note: The sequence of homologous arms and cKO region is aligned with itself to determine if there are tandem repeats. -
Genomic Evidence of Reactive Oxygen Species Elevation in Papillary Thyroid Carcinoma with Hashimoto Thyroiditis
Endocrine Journal 2015, 62 (10), 857-877 Original Genomic evidence of reactive oxygen species elevation in papillary thyroid carcinoma with Hashimoto thyroiditis Jin Wook Yi1), 2), Ji Yeon Park1), Ji-Youn Sung1), 3), Sang Hyuk Kwak1), 4), Jihan Yu1), 5), Ji Hyun Chang1), 6), Jo-Heon Kim1), 7), Sang Yun Ha1), 8), Eun Kyung Paik1), 9), Woo Seung Lee1), Su-Jin Kim2), Kyu Eun Lee2)* and Ju Han Kim1)* 1) Division of Biomedical Informatics, Seoul National University College of Medicine, Seoul, Korea 2) Department of Surgery, Seoul National University Hospital and College of Medicine, Seoul, Korea 3) Department of Pathology, Kyung Hee University Hospital, Kyung Hee University School of Medicine, Seoul, Korea 4) Kwak Clinic, Okcheon-gun, Chungbuk, Korea 5) Department of Internal Medicine, Uijeongbu St. Mary’s Hospital, Uijeongbu, Korea 6) Department of Radiation Oncology, Seoul St. Mary’s Hospital, Seoul, Korea 7) Department of Pathology, Chonnam National University Hospital, Kwang-Ju, Korea 8) Department of Pathology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea 9) Department of Radiation Oncology, Korea Cancer Center Hospital, Korea Institute of Radiological and Medical Sciences, Seoul, Korea Abstract. Elevated levels of reactive oxygen species (ROS) have been proposed as a risk factor for the development of papillary thyroid carcinoma (PTC) in patients with Hashimoto thyroiditis (HT). However, it has yet to be proven that the total levels of ROS are sufficiently increased to contribute to carcinogenesis. We hypothesized that if the ROS levels were increased in HT, ROS-related genes would also be differently expressed in PTC with HT. To find differentially expressed genes (DEGs) we analyzed data from the Cancer Genomic Atlas, gene expression data from RNA sequencing: 33 from normal thyroid tissue, 232 from PTC without HT, and 60 from PTC with HT.