Large-Scale Genome-Wide Association Analysis of Bipolar Disorder Identifies a New Susceptibility Locus Near ODZ4
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University of Copenhagen, Copenhagen, Denmark, Citation: Pereira J, Johnson WE, O’Brien SJ, 8
Evolutionary genomics and adaptive evolution of the hedgehog gene family (Shh, Ihh and Dhh) in vertebrates Pereira, Joana; Johnson, Warren E.; O'Brien, Stephen J.; Jarvis, Erich D; Zhang, Guojie; Gilbert, M. Thomas P.; Vasconcelos, Vitor; Antunes, Agostinho Published in: PloS one DOI: 10.1371/journal.pone.0074132 Publication date: 2014 Document version Publisher's PDF, also known as Version of record Document license: CC BY Citation for published version (APA): Pereira, J., Johnson, W. E., O'Brien, S. J., Jarvis, E. D., Zhang, G., Gilbert, M. T. P., Vasconcelos, V., & Antunes, A. (2014). Evolutionary genomics and adaptive evolution of the hedgehog gene family (Shh, Ihh and Dhh) in vertebrates. PloS one, 9(12), [e74132]. https://doi.org/10.1371/journal.pone.0074132 Download date: 24. sep.. 2021 RESEARCH ARTICLE Evolutionary Genomics and Adaptive Evolution of the Hedgehog Gene Family (Shh, Ihh and Dhh) in Vertebrates Joana Pereira1¤, Warren E. Johnson2, Stephen J. O’Brien3,4, Erich D. Jarvis5, Guojie Zhang6, M. Thomas P. Gilbert7, Vitor Vasconcelos1,8, Agostinho Antunes1,8* 1. CIIMAR/CIMAR, Interdisciplinary Centre of Marine and Environmental Research, University of Porto, Porto, Portugal, 2. Smithsonian Conservation Biology Institute, National Zoological Park, Front Royal, Virginia, United States of America, 3. Theodosius Dobzhansky Center for Genome Bioinformatics, St. Petersburg State University, St. Petersburg, Russia, 4. Oceanographic Center, N. Ocean Drive, Nova Southeastern University, Ft. Lauderdale, Florida, United States of America, 5. Howard Hughes Medical Institute, Department of Neurobiology, Duke University Medical Center, Durham, North Carolina, United States of America, 6. BGI-Shenzhen, Beishan Industrial Zoon, Yantian District, Shenzhen, China, 7. -
Molecular and Physiological Basis for Hair Loss in Near Naked Hairless and Oak Ridge Rhino-Like Mouse Models: Tracking the Role of the Hairless Gene
University of Tennessee, Knoxville TRACE: Tennessee Research and Creative Exchange Doctoral Dissertations Graduate School 5-2006 Molecular and Physiological Basis for Hair Loss in Near Naked Hairless and Oak Ridge Rhino-like Mouse Models: Tracking the Role of the Hairless Gene Yutao Liu University of Tennessee - Knoxville Follow this and additional works at: https://trace.tennessee.edu/utk_graddiss Part of the Life Sciences Commons Recommended Citation Liu, Yutao, "Molecular and Physiological Basis for Hair Loss in Near Naked Hairless and Oak Ridge Rhino- like Mouse Models: Tracking the Role of the Hairless Gene. " PhD diss., University of Tennessee, 2006. https://trace.tennessee.edu/utk_graddiss/1824 This Dissertation is brought to you for free and open access by the Graduate School at TRACE: Tennessee Research and Creative Exchange. It has been accepted for inclusion in Doctoral Dissertations by an authorized administrator of TRACE: Tennessee Research and Creative Exchange. For more information, please contact [email protected]. To the Graduate Council: I am submitting herewith a dissertation written by Yutao Liu entitled "Molecular and Physiological Basis for Hair Loss in Near Naked Hairless and Oak Ridge Rhino-like Mouse Models: Tracking the Role of the Hairless Gene." I have examined the final electronic copy of this dissertation for form and content and recommend that it be accepted in partial fulfillment of the requirements for the degree of Doctor of Philosophy, with a major in Life Sciences. Brynn H. Voy, Major Professor We have read this dissertation and recommend its acceptance: Naima Moustaid-Moussa, Yisong Wang, Rogert Hettich Accepted for the Council: Carolyn R. -
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. -
Distinguishing Pleiotropy from Linked QTL Between Milk Production Traits
Cai et al. Genet Sel Evol (2020) 52:19 https://doi.org/10.1186/s12711-020-00538-6 Genetics Selection Evolution RESEARCH ARTICLE Open Access Distinguishing pleiotropy from linked QTL between milk production traits and mastitis resistance in Nordic Holstein cattle Zexi Cai1*†, Magdalena Dusza2†, Bernt Guldbrandtsen1, Mogens Sandø Lund1 and Goutam Sahana1 Abstract Background: Production and health traits are central in cattle breeding. Advances in next-generation sequencing technologies and genotype imputation have increased the resolution of gene mapping based on genome-wide association studies (GWAS). Thus, numerous candidate genes that afect milk yield, milk composition, and mastitis resistance in dairy cattle are reported in the literature. Efect-bearing variants often afect multiple traits. Because the detection of overlapping quantitative trait loci (QTL) regions from single-trait GWAS is too inaccurate and subjective, multi-trait analysis is a better approach to detect pleiotropic efects of variants in candidate genes. However, large sample sizes are required to achieve sufcient power. Multi-trait meta-analysis is one approach to deal with this prob- lem. Thus, we performed two multi-trait meta-analyses, one for three milk production traits (milk yield, protein yield and fat yield), and one for milk yield and mastitis resistance. Results: For highly correlated traits, the power to detect pleiotropy was increased by multi-trait meta-analysis com- pared with the subjective assessment of overlapping of single-trait QTL confdence intervals. Pleiotropic efects of lead single nucleotide polymorphisms (SNPs) that were detected from the multi-trait meta-analysis were confrmed by bivariate association analysis. The previously reported pleiotropic efects of variants within the DGAT1 and MGST1 genes on three milk production traits, and pleiotropic efects of variants in GHR on milk yield and fat yield were con- frmed. -
Protein Identities in Evs Isolated from U87-MG GBM Cells As Determined by NG LC-MS/MS
Protein identities in EVs isolated from U87-MG GBM cells as determined by NG LC-MS/MS. No. Accession Description Σ Coverage Σ# Proteins Σ# Unique Peptides Σ# Peptides Σ# PSMs # AAs MW [kDa] calc. pI 1 A8MS94 Putative golgin subfamily A member 2-like protein 5 OS=Homo sapiens PE=5 SV=2 - [GG2L5_HUMAN] 100 1 1 7 88 110 12,03704523 5,681152344 2 P60660 Myosin light polypeptide 6 OS=Homo sapiens GN=MYL6 PE=1 SV=2 - [MYL6_HUMAN] 100 3 5 17 173 151 16,91913397 4,652832031 3 Q6ZYL4 General transcription factor IIH subunit 5 OS=Homo sapiens GN=GTF2H5 PE=1 SV=1 - [TF2H5_HUMAN] 98,59 1 1 4 13 71 8,048185945 4,652832031 4 P60709 Actin, cytoplasmic 1 OS=Homo sapiens GN=ACTB PE=1 SV=1 - [ACTB_HUMAN] 97,6 5 5 35 917 375 41,70973209 5,478027344 5 P13489 Ribonuclease inhibitor OS=Homo sapiens GN=RNH1 PE=1 SV=2 - [RINI_HUMAN] 96,75 1 12 37 173 461 49,94108966 4,817871094 6 P09382 Galectin-1 OS=Homo sapiens GN=LGALS1 PE=1 SV=2 - [LEG1_HUMAN] 96,3 1 7 14 283 135 14,70620005 5,503417969 7 P60174 Triosephosphate isomerase OS=Homo sapiens GN=TPI1 PE=1 SV=3 - [TPIS_HUMAN] 95,1 3 16 25 375 286 30,77169764 5,922363281 8 P04406 Glyceraldehyde-3-phosphate dehydrogenase OS=Homo sapiens GN=GAPDH PE=1 SV=3 - [G3P_HUMAN] 94,63 2 13 31 509 335 36,03039959 8,455566406 9 Q15185 Prostaglandin E synthase 3 OS=Homo sapiens GN=PTGES3 PE=1 SV=1 - [TEBP_HUMAN] 93,13 1 5 12 74 160 18,68541938 4,538574219 10 P09417 Dihydropteridine reductase OS=Homo sapiens GN=QDPR PE=1 SV=2 - [DHPR_HUMAN] 93,03 1 1 17 69 244 25,77302971 7,371582031 11 P01911 HLA class II histocompatibility antigen, -
4-6 Weeks Old Female C57BL/6 Mice Obtained from Jackson Labs Were Used for Cell Isolation
Methods Mice: 4-6 weeks old female C57BL/6 mice obtained from Jackson labs were used for cell isolation. Female Foxp3-IRES-GFP reporter mice (1), backcrossed to B6/C57 background for 10 generations, were used for the isolation of naïve CD4 and naïve CD8 cells for the RNAseq experiments. The mice were housed in pathogen-free animal facility in the La Jolla Institute for Allergy and Immunology and were used according to protocols approved by the Institutional Animal Care and use Committee. Preparation of cells: Subsets of thymocytes were isolated by cell sorting as previously described (2), after cell surface staining using CD4 (GK1.5), CD8 (53-6.7), CD3ε (145- 2C11), CD24 (M1/69) (all from Biolegend). DP cells: CD4+CD8 int/hi; CD4 SP cells: CD4CD3 hi, CD24 int/lo; CD8 SP cells: CD8 int/hi CD4 CD3 hi, CD24 int/lo (Fig S2). Peripheral subsets were isolated after pooling spleen and lymph nodes. T cells were enriched by negative isolation using Dynabeads (Dynabeads untouched mouse T cells, 11413D, Invitrogen). After surface staining for CD4 (GK1.5), CD8 (53-6.7), CD62L (MEL-14), CD25 (PC61) and CD44 (IM7), naïve CD4+CD62L hiCD25-CD44lo and naïve CD8+CD62L hiCD25-CD44lo were obtained by sorting (BD FACS Aria). Additionally, for the RNAseq experiments, CD4 and CD8 naïve cells were isolated by sorting T cells from the Foxp3- IRES-GFP mice: CD4+CD62LhiCD25–CD44lo GFP(FOXP3)– and CD8+CD62LhiCD25– CD44lo GFP(FOXP3)– (antibodies were from Biolegend). In some cases, naïve CD4 cells were cultured in vitro under Th1 or Th2 polarizing conditions (3, 4). -
Investigation of Candidate Genes and Mechanisms Underlying Obesity
Prashanth et al. BMC Endocrine Disorders (2021) 21:80 https://doi.org/10.1186/s12902-021-00718-5 RESEARCH ARTICLE Open Access Investigation of candidate genes and mechanisms underlying obesity associated type 2 diabetes mellitus using bioinformatics analysis and screening of small drug molecules G. Prashanth1 , Basavaraj Vastrad2 , Anandkumar Tengli3 , Chanabasayya Vastrad4* and Iranna Kotturshetti5 Abstract Background: Obesity associated type 2 diabetes mellitus is a metabolic disorder ; however, the etiology of obesity associated type 2 diabetes mellitus remains largely unknown. There is an urgent need to further broaden the understanding of the molecular mechanism associated in obesity associated type 2 diabetes mellitus. Methods: To screen the differentially expressed genes (DEGs) that might play essential roles in obesity associated type 2 diabetes mellitus, the publicly available expression profiling by high throughput sequencing data (GSE143319) was downloaded and screened for DEGs. Then, Gene Ontology (GO) and REACTOME pathway enrichment analysis were performed. The protein - protein interaction network, miRNA - target genes regulatory network and TF-target gene regulatory network were constructed and analyzed for identification of hub and target genes. The hub genes were validated by receiver operating characteristic (ROC) curve analysis and RT- PCR analysis. Finally, a molecular docking study was performed on over expressed proteins to predict the target small drug molecules. Results: A total of 820 DEGs were identified between -
Cellular and Molecular Signatures in the Disease Tissue of Early
Cellular and Molecular Signatures in the Disease Tissue of Early Rheumatoid Arthritis Stratify Clinical Response to csDMARD-Therapy and Predict Radiographic Progression Frances Humby1,* Myles Lewis1,* Nandhini Ramamoorthi2, Jason Hackney3, Michael Barnes1, Michele Bombardieri1, Francesca Setiadi2, Stephen Kelly1, Fabiola Bene1, Maria di Cicco1, Sudeh Riahi1, Vidalba Rocher-Ros1, Nora Ng1, Ilias Lazorou1, Rebecca E. Hands1, Desiree van der Heijde4, Robert Landewé5, Annette van der Helm-van Mil4, Alberto Cauli6, Iain B. McInnes7, Christopher D. Buckley8, Ernest Choy9, Peter Taylor10, Michael J. Townsend2 & Costantino Pitzalis1 1Centre for Experimental Medicine and Rheumatology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK. Departments of 2Biomarker Discovery OMNI, 3Bioinformatics and Computational Biology, Genentech Research and Early Development, South San Francisco, California 94080 USA 4Department of Rheumatology, Leiden University Medical Center, The Netherlands 5Department of Clinical Immunology & Rheumatology, Amsterdam Rheumatology & Immunology Center, Amsterdam, The Netherlands 6Rheumatology Unit, Department of Medical Sciences, Policlinico of the University of Cagliari, Cagliari, Italy 7Institute of Infection, Immunity and Inflammation, University of Glasgow, Glasgow G12 8TA, UK 8Rheumatology Research Group, Institute of Inflammation and Ageing (IIA), University of Birmingham, Birmingham B15 2WB, UK 9Institute of -
Identification of Transcriptomic Differences Between Lower
International Journal of Molecular Sciences Article Identification of Transcriptomic Differences between Lower Extremities Arterial Disease, Abdominal Aortic Aneurysm and Chronic Venous Disease in Peripheral Blood Mononuclear Cells Specimens Daniel P. Zalewski 1,*,† , Karol P. Ruszel 2,†, Andrzej St˛epniewski 3, Dariusz Gałkowski 4, Jacek Bogucki 5 , Przemysław Kołodziej 6 , Jolanta Szyma ´nska 7 , Bartosz J. Płachno 8 , Tomasz Zubilewicz 9 , Marcin Feldo 9,‡ , Janusz Kocki 2,‡ and Anna Bogucka-Kocka 1,‡ 1 Chair and Department of Biology and Genetics, Medical University of Lublin, 4a Chod´zkiSt., 20-093 Lublin, Poland; [email protected] 2 Chair of Medical Genetics, Department of Clinical Genetics, Medical University of Lublin, 11 Radziwiłłowska St., 20-080 Lublin, Poland; [email protected] (K.P.R.); [email protected] (J.K.) 3 Ecotech Complex Analytical and Programme Centre for Advanced Environmentally Friendly Technologies, University of Marie Curie-Skłodowska, 39 Gł˛ebokaSt., 20-612 Lublin, Poland; [email protected] 4 Department of Pathology and Laboratory Medicine, Rutgers-Robert Wood Johnson Medical School, One Robert Wood Johnson Place, New Brunswick, NJ 08903-0019, USA; [email protected] 5 Chair and Department of Organic Chemistry, Medical University of Lublin, 4a Chod´zkiSt., Citation: Zalewski, D.P.; Ruszel, K.P.; 20-093 Lublin, Poland; [email protected] St˛epniewski,A.; Gałkowski, D.; 6 Laboratory of Diagnostic Parasitology, Chair and Department of Biology and Genetics, Medical University of Bogucki, J.; Kołodziej, P.; Szyma´nska, Lublin, 4a Chod´zkiSt., 20-093 Lublin, Poland; [email protected] J.; Płachno, B.J.; Zubilewicz, T.; Feldo, 7 Department of Integrated Paediatric Dentistry, Chair of Integrated Dentistry, Medical University of Lublin, M.; et al. -
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 -
Identification of DNAH6 Mutations in Infertile Men with Multiple
www.nature.com/scientificreports OPEN Identifcation of DNAH6 mutations in infertile men with multiple morphological abnormalities of the sperm fagella Chaofeng Tu1,2,3,4, Hongchuan Nie1,2,3,4, Lanlan Meng2, Shimin Yuan2, Wenbin He1,2,3, Aixiang Luo1, Haiyu Li1, Wen Li1,2,3, Juan Du1,2,3, Guangxiu Lu1,2,3, Ge Lin1,2,3 & Yue-Qiu Tan1,2,3* Male infertility due to spermatogenesis defects afects millions of men worldwide. However, the genetic etiology of the vast majority remains unclear. Here we describe three men with primary infertility due to multiple morphological abnormalities of the sperm fagella (MMAF) from two unrelated Han Chinese families. We performed whole-exome sequencing (WES) and Sanger sequencing on the proband of family 1, and found that he carried novel compound heterozygous missense mutations in dynein axonemal heavy chain 6 (DNAH6) that resulted in the substitution of a conserved amino acid residue and co-segregated with the MMAF phenotype in this family. Papanicolaou staining and transmission electron microscopy analysis revealed morphological and ultrastructural abnormalities in the sperm fagella in carriers of these genetic variants. Immunostaining experiments showed that DNAH6 was localized in the sperm tail. This is the frst report identifying novel recessive mutations in DNAH6 as a cause of MMAF. These fndings expand the spectrum of known MMAF mutations and phenotypes and provide information that can be useful for genetic and reproductive counseling of MMAF patients. Infertility is a major health concern that afects more than 20 million men worldwide1. Factors contributing to male infertility include genetic disorders, urogenital infections, and immunological or hormonal abnormalities. -
Novel Gene Discovery in Primary Ciliary Dyskinesia
Novel Gene Discovery in Primary Ciliary Dyskinesia Mahmoud Raafat Fassad Genetics and Genomic Medicine Programme Great Ormond Street Institute of Child Health University College London A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy University College London 1 Declaration I, Mahmoud Raafat Fassad, confirm that the work presented in this thesis is my own. Where information has been derived from other sources, I confirm that this has been indicated in the thesis. 2 Abstract Primary Ciliary Dyskinesia (PCD) is one of the ‘ciliopathies’, genetic disorders affecting either cilia structure or function. PCD is a rare recessive disease caused by defective motile cilia. Affected individuals manifest with neonatal respiratory distress, chronic wet cough, upper respiratory tract problems, progressive lung disease resulting in bronchiectasis, laterality problems including heart defects and adult infertility. Early diagnosis and management are essential for better respiratory disease prognosis. PCD is a highly genetically heterogeneous disorder with causal mutations identified in 36 genes that account for the disease in about 70% of PCD cases, suggesting that additional genes remain to be discovered. Targeted next generation sequencing was used for genetic screening of a cohort of patients with confirmed or suggestive PCD diagnosis. The use of multi-gene panel sequencing yielded a high diagnostic output (> 70%) with mutations identified in known PCD genes. Over half of these mutations were novel alleles, expanding the mutation spectrum in PCD genes. The inclusion of patients from various ethnic backgrounds revealed a striking impact of ethnicity on the composition of disease alleles uncovering a significant genetic stratification of PCD in different populations.